The Application of GAP of Shallot in Bantul Regency | Suharni | Agro Ekonomi 25022 60079 1 PB
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Agro Ekonomi Vol. 28/No. 1, Juni 2017
THE APPLICATION OF GOOD AGRICULTURE PRACTICES (GAP) OF
SHALLOT IN BANTUL REGENCY
Aplikasi Good Agriculture Practices (GAP) Bawang Merah Kecamatan
di Kabupaten Bantul
Suharni, Lestari Rahayu Waluyati, Jamhari
Master of Agribussiness Management, Faculty of Agriculture, Universitas Gadjah Mada
Jl. Flora, Bulaksumur, Kec.Depok, Kabupaten Sleman,
Daerah Istimewa Yogyakarta 55281
[email protected]
Diterima tanggal 16 Mei 2017 ; Disetujui tanggal 10 Juni 2017
ABSTRACT
Bantul Regency is one of the center of shallots in Indonesia, but its productivity is low. In
2015, the productivity of shallots in Bantul Regency was 7.66 tons/ha. The application of Good
Agriculture Practices (GAP) is a form of technology adoption aiming to improve the shallot
productivity.The purposes of this study are to determine the level of application of shallots
GAP in Bantul Regency and to find out the factors influencing the application such as land area,
farmers’ age, farmers’ education, farming experience, availability of farm inputs, and extension
service frequency. Purposive technique was used to determine the research location. Sanden and
Kretek districts were discovered since these areas are the production centers of shallots in Bantul
Regency. The study involved the respondents consisting of sixty shallot farmers, thirty people
from Kretek District and the other thirty people from Sanden District who were determined by
simple random sampling. This research used scoring technique with Likert scale to measure the
application level of GAP. Multiple linear regression analysis was used to understand the factors
affecting the application of GAP of shallots. Result showed that the application of GAP of shallots
in Bantul Regency is low. The factors of land area, farmers’ education, farming experience, and
availability of farm inputs means influence the application level of GAP of shallots significantly.
Keywords: adoption of technology, application of GAP, productivity, shallot
INTISARI
Kabupaten Bantul merupakan salah satu sentra bawang merah di Indonesia, tetapi
produktivitasnya masih rendah. Tahun 2015, produktivitas bawang merah di Kabupaten
Bantul sebesar 7,66 ton/ha. Penerapan Good Agriculture Practices (GAP) merupakan salah
satu bentuk adopsi teknologi yang bertujuan untuk meningkatkan produktivitas bawang
merah. Tujuan penelitian ini adalah untuk mengetahui tingkat penerapan GAP bawang
merah di Kabupaten Bantul dan mengetahui faktor-faktor yang mempengaruhi penerapannya
diantaranya luas lahan, umur petani, pendidikan petani, pengalaman usahatani, ketersediaan
sarana produksi, dan frekuensi penyuluhan. Pemilihan lokasi penelitian dilakukan dengan
teknik purposive. Kecamatan Sanden dan Kretek dipilih karena merupakan sentra produksi
bawang merah di Kabupaten Bantul. Penelitian dilakukan terhadap 60 orang petani sampel
bawang merah, 30 orang dari Kecamatan Kretek dan 30 orang dari Kecamatan Sanden yang
dipilih secara acak sederhana. Penelitian ini menggunakan teknik skoring dengan skala likert
untuk mengukur tingkat penerapan GAP. Analisis regresi linear berganda digunakan untuk
Agro Ekonomi Vol. 28/No. 1, Juni 2017
49
mengetahui faktor-faktor yang mempengaruhi penerapan GAP bawang merah. Dari hasil
penelitian diketahui bahwa tingkat penerapan GAP bawang merah di Kabupaten Bantul
rendah. Faktor luas lahan, pendidikan petani, pengalaman usahatani, dan ketersediaan
sarana produksi berpengaruh signifikan terhadap tingkat penerapan GAP bawang merah.
Kata kunci: adopsi teknologi, bawang merah, penerapan GAP, produktivitas
INTRODUCTION
Horticulture subsector has a strategic
and important position in the agricultural
of good quality shallot seeds (Thamrin et
al., 2003; Winarto et al., 2009; Asaad &
Warda, 2010; Azmi et al., 2011).
sector because it has a high market potential.
Several issues that resulted in
One of the horticultural commodities that
low productivity of shallot in Indonesia
have high economic value is shallot
were: (a) availability of quality seeds, (b)
(Wiguna et al., 2013; Theresia et al., 2016).
limited farm inputs, (c) not yet properly
Shallot is a spice vegetable that has high
implemented location-specific GAP; as a
selling value and developed intensively.
result the cultivation problems were not
In economic terms, shallot business is
solved (Paranata et al., 2015).
quite profitable and has a wide market.
The cultivation of shallots by farmers
Shallot is needed as a spice in almost all
in Indonesia generally has not fully applied
Indonesian dishes everyday. Shallot is also
the correct cultivation rules, yet in the
used in the food industry as a seasoning
current era of global trade, shallot farmers
flavor. The consumption and demand of
are required to improve the competitiveness
shallots will continue to increase in line
of products to produce agricultural products
with the increasing needs of the population
that are safe to consume, good quality, and
due to the growing number of people, the
produced in an environmentally friendly
development of the food industry and
manner. Today people are becoming
market development.
aware that the excessive use of chemical
One of the central area of shallot
fertilizers and pesticides used by farmers
production in Indonesia is Bantul Regency,
are not good for health. To improve the
Yogyakarta. The area of shallot harvest
production, quality and competitiveness of
in Bantul Regency in 2015 reached 585
shallot in meeting the needs of the domestic
hectares with production of 4,478.9 tons
market and for export, the production
and productivity of 7.66 tons/ha. This
process needs to be done well by applying
productivity decreased in the previous year
Good Agriculture Practices (GAP).
which reached 10.07 tons/ha (Ministry of
The efforts to increase the
Agriculture, 2017). It was suppossed to
productivity of shallots are done by
obtain yields of 15-20 tons/ha with the use
introducing new technology, both local
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Agro Ekonomi Vol. 28/No. 1, Juni 2017
technology and technology produced by
standard were land area, access of off-farm
research institutions (Sasongko et al.,
income, access to market information, and
2014). One of the adoption of technology
extension role, while the negative factor
is by applying shallot GAP. The application
was age of farmer.
of fruit and vegetable GAP is regulated
According to Lionberger (1968),
in Minister of Agriculture Regulation
several factors that affect a person’s speed
number 48/ Permentan/ OT.160/10/2009
to adopt innovation are:
on Guidelines for Good Fruit and Vegetable
1. Land area, the wider land area usually
Cultivation. GAP components include land
the faster adopt the innovation because
issues, use of seeds and crop varieties,
it has better economic capability.
planting, fertilizing, crop protection,
2. Income level, the higher the income
irrigation, harvesting, post harvest,
level usually the faster adopt the
agricultural machinery, environmental
innovation.
conservation, workers, worker welfare,
3. Courage to take risks, individuals
landfills, surveillance, recording and
who have the courage to face risks are
traceback,and internal evaluation (Ministry
usually innovative.
of Agriculture, 2009).
4. Age, getting older (above 50 years),
The research on measuring the
usually getting slower to adopt
level of application of GAP for several
commodities has been done. Sriyadi et al
innovation.
5.
Level of participation in groups or
(2015) conducted a study on the Evaluation
organizations outside the environment.
of Implementation of Standard Operating
Someone who likes to join people
Procedure-Good Agriculture Practice
outside of his social system is generally
(SOP-GAP) on Organic Rice Farming in
more innovative.
Bantul District. This study aims to measure
6. Source of information utilized.
the level of application of SOP-GAP
organic rice farming. The results showed
Due to the low shallot productivity
that the level of SOP-GAP application of
in Bantul Regency, it is necessary to do
organic rice farming in Bantul Regency
research on the extent to which shallot
was high (82.31%).
farmers in Bantul Regency apply GAP of
Research on factors influencing the
shallots on the agribusinesssubsystems of
application of GAP has also been done
input provision, cultivation, post-harvest,
by Annor (2016). The results showed
and the factors that affect the level of
that the factors that positively affect the
application of GAP. This study aims to
farmer’s decision to meet GLOBAL GAP
determine the level of application of GAP
Agro Ekonomi Vol. 28/No. 1, Juni 2017
51
of shallots and to determine the factors that
obtained from interviews and observations,
affect the application of GAP of shallot in
while secondary data were obtained from
Bantul Regency.
the literature or references.
The hypothesis used in this research
is that the level of application of GAP of
Analysis of Shallot GAP Application
shallots in Bantul Regency ishigh on input
The application of GAP of shallotswas
provision and cultivation subsystems,
divided into three subsystems, namely the
butstill low on postharvest subsystem.
provision of input, cultivation, and post-
The factors that positively influence the
harvest. The application of GAPshallot was
application of GAPshallot are land area,
measured by scoring technique using Likert
farmer education, farming experience,
scale. With Likert scale, the variables
availability of farm inputs, and frequency
used were described as statements which
of extension service by extension officer,
were the indicators in measurement of the
while the farmers’ age has negative effect.
application of GAP.
The answers to the questions given
METHODS
This research was conducted on
shallot farmers in Bantul Regency,
in this study were given scores that are:
1 for answers of never, 2 for answers of
sometimes, and 3 for answers of always.
Yogyakarta. The location was selected
purposively, related to Kretek and Sanden
as a district which has the larger shallot
farming in Bantul.
Validity and Reliability Test
The way used to determine the
validity of a measuring tool is by correlating
The number offarmer samples used
between the scores obtained by each item
in this study was 60, 30 farmers from
(question or statement) with the total
Kretek District and 30 farmers from
score. Validity test uses product moment
Sanden District, selected by simple random
correlation (pearsons correlation) as
sampling.The number of samples taken
follows:
as many as 60 people has met the general
rule statistically ≥ 30 and able to present
the state of agriculture in that location
because the number of 30 samples has
rxy= coefficient of validity
been normally distributed and can be used
X = item score
to predict the population (Hasan, 2002).
Y = total item score
The type of data used was primary
data and secondary data. Primary data were
N = respondent number
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Agro Ekonomi Vol. 28/No. 1, Juni 2017
To test the reliability of measuring
equipment is calculated by using estimation
where
P = Percentage of GAPapplication level
parameters
of Cronbach’s Alpha model that is processed
with the help of SPSS program.
Po = Percentage of assigned applicationlevel
parameters (0.5)
The GAP application scores achieved
by the respondents on each subsystem are
n = sample number
calculated on average score.Furthermore,
The criterion of determination is:
the level of GAP application is classified
Ho is accepted when Zarithmetic ≤ Ztable and Ho
into 2 categories of classes, namely low
is refused when Zarithmetic > Ztable.
application level and high application
level based on the scores obtained by
Analysis of Factors Affecting the Level
respondents used intervals of the formula
of Apllication of GAP
To determine the factors that
as follows:
influence the level of application of GAP of
shallot in Bantul Regency, multiple linear
Where:
regression analysis was used. Application
I = class interval
of GAP of shallot was dependent variable
J = range between maximum score (3) and
(Y) which was suspected to be influenced
minimum score (1)
K = The number of used class(that was 2).
by independent variables that were land
area (X1), farmers’ age (X2), farmers’
education level (X3), farming experience
The classification of GAP application level
(X4), availability of farm inputs (X5),
is classified based on the following scores:
and extension service frequency (X6)
1. Low application level if score 1 – 2.
which can be expressed by multiple linear
2. High application level if score 2.01–3
regression model as follows:
Y = a + b1X1 + b2X2 + b3X3 + b4X4 +
Hypothesis Test
Hypothesis test was done by testing
the parameter of proportion. Test steps
b5X5 + b6X6
Information:
Y = GAP Apllication (percentage of likert
score)
were determine the hypothesis Ho and Ha
then calculate z arithmetic. The value of z
a
= constants
arithmetic was obtained by the formula:
b1, b2, b3, b4, b5, b6 = regression coefficient
X1 = land area (hectare)
X2 = farmers age (year)
X3 = farmers’ education level (year)
Agro Ekonomi Vol. 28/No. 1, Juni 2017
53
X4 = shallot farming experience(year)
this study included several tests as follows:
X5 = availability of farm inputs (score)
a. D e t e r m i n a t i o n c o e ff i c i e n t t e s t
X6 = extension servicefrequency (times)
To meet statistical test requirements
in multiple linear regression analysis, the
(Adjusted R²)
b. Simultaneous test(F-test)
c. Individual test (t-test)
classical assumption test using EViews
program includes:
RESULTS AND DISCUSSION
a. Normality test using Jarque-Bera (JB)
Age of respondent farmers was
Test, that is comparing JB probability
dominated by productive age between
value with alpha level 5%.
15-64 years (81.67%). A productive age is
b. Multicolinearity test, data is free from
the most appropriate age for carrying out
multicolinearity if all correlation
working activities such as farming because
coefficient between independent
it is physically still good, has high spirits
variables is smaller than 0.8.
and an obligation to support the family
c. Heteroscedasticity test, the data is free
(Aldila et al., 2015).
of heteroscedasticity if the probability
Shallot farmer respondents in Bantul
value of Obs*R-squaredvalue shows
Regency mostly had elementary education
significant or greater result thanalpha
that was equal to 38.33%, while those with
of 1%.
SMA education as much as 35.00%. The
level of education will affect a farmer’s
In addition to using the classical
way of thinking and the level of technology
assumption test, this study also used
and science absorption (Aldila et al., 2015).
hypothesis testing. The hypothesis test in
Table 1. Characteristics of Respondents
Characteristics
Ages (year)
Education
Farming experience
(year)
Groups
≤ 14 years old
15-64 ears old
≥ 65 years old
Elementary school
Junior high school
Senior high school
University
1–7
8 – 14
15 – 21
22 – 28
29 – 35
36 – 42
43 – 49
Source: Analysis of Primary Data (2017)
The number (people)
0
49
11
23
15
21
1
9
8
15
10
12
4
2
Percentage (%)
0,00
81,67
18,33
38,33
25,00
35,00
1,67
15,00
13,33
25,00
16,67
20,00
6,67
3,33
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Agro Ekonomi Vol. 28/No. 1, Juni 2017
The level of shallot farming
alpha in this study used a value of 0.6
experience was mostly between 15-21
assuming the list of questions tested would
years (25.00%). Level of education and
be reliable if the value of cronbach’s alpha
farming experience will affect the way of
≥ 0.6. Reliability test results can be seen
thinking, the higher the level of education,
in Table 3.
the more responsive to new things.
Based on Table 3, it can be seen
that all GAPapplication items for input
Level of Application of GAP of Shallots
provision, cultivation and postharvest
Validity Test
subsystems have a very high reliability
Calculation of validity test with
product moment correlation coefficient
valuebecause cronbach’s alphavalue is
greater than 0.6.
used SPSS program aid. rarithmetic of each
item was compared with value in r Table
Hypothesis Test
of product moment. In this study with
The average score of GAP application
the respondent number of 60 and 5%
on the subsystem of input supply was 2.17
significance level,it resulted in rtable of
(72.18%), on the subsystem of cultivation
0.254. The result of validity test of GAP
of 2.04 (67.96%), on postharvest subsystem
of shallots can be seen in Table 2.
of 1.49 (49.58%), and the average total
GAP application score of 2.04(68.12%).
Table 2. Validity Test Result
No.
Subsystems
1.
2.
3.
Input provision
Cultivation
Post-harvest
The point
Valid
number
47
37
28
12
8
8
Source: Analysis of primary data (2017)
The results of GAP application level
analysis can be seen in Table 4.
From Table 4 it can be seen that
the low level of GAP application on the
input subsystem was the seed component,
the low level of application of GAP in
Reliability Test
the cultivation subsystem was on the
To see the reliability value,we used
fertilization component, while the low level
cronbach’s alpha value that estimated using
of application of GAP in the post-harvest
SPSS program. The value of cronbach’s
subsystem were on sorting and grading,
packaging, and storage.
Table 3. Reliability Test Result
No.
1.
2.
3.
Subsystem
Cronbach’s Alpha Value
Input provision
0,943
Cultivation
0,886
Post-harvest
0,819
Source: Analysis of primary data (2017)
Reliability Standard number
≥ 0,6
≥ 0,6
≥ 0,6
Information
Reliable
Reliable
Reliable
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Table 4. The Level of Application of Shallot GAP in Bantul Regency
Subsystem
Input
Provision
Cultivation
Postharvest
Technology Components
Land
Seed
Fertilizer
Pesticide
Agricultural equipment &
machinery
Workers
Land preparation
Planting
Fertilization
Plant protection
Irrigation
Harvest
Early treatment
Cleaning
Sorting and Grading
Packaging
Storage
Maximum
Score
3
3
3
3
3
Average
Percentage
Score
(%)
2,55
85,00
1,52
50,60
2,75
91,67
2,22
73,83
2,08
69,26
3
3
3
3
3
3
3
3
3
3
3
3
2,07
2,52
2,53
1,59
2,25
2,32
2,34
2,72
2,87
1,03
1,05
1,07
Criteria
High
Low
High
High
High
69,03
83,89
84,44
52,89
75,00
77,22
78,06
90,56
95,56
34,44
35,14
35,56
High
High
High
Low
High
High
High
High
High
Low
Low
Low
Source: Analysis of primary data (2017)
Table 5. Distribution of Farmers Based on The Application Level of GAP
GAP Application level
No.
Subsystem
1. Input provision
2. Cultivation
3. Post-harvest
Total GAP of shallots
Low
Frequency (people)
19
29
58
28
%
31,67
48,33
96,67
46,67
High
Frequency (people)
41
31
2
32
%
68,33
51,67
3,33
53,33
Source: Analysis of Primary Data (2017)
To determine whether the application
is conducted to determine the level of GAP
of shallot GAP is included in low or high
application statistically.Hypothesis test
criteria, then the GAP application level
results can be seen in Table 6.
is classified by score into low and high
Based on the hypothesis test, it can
application level. The distribution of
be determined that:
farmers based on the level of application
1) The level of application of shallot GAP
of GAP can be seen in Table 5.
on the input provision subsystem was
Based on Table 5, it is known that on
high because the farmers had used
the application of GAP as a whole, as many
good planting media, good commercial
as 32 respondents (53.33%) included in
varieties of shallot seeds, registered
the category of high application level and
and permitted fertilizers and pesticides,
28 respondents (46.67%) included in low
and appropriate agricultural machinery
category. Furthermore, hypothesis testing
and tools. All farmers are already using
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Agro Ekonomi Vol. 28/No. 1, Juni 2017
Table 6. Hypothesis Test Result
No. Subsystem
1. Input
Provision
2.
3.
Hypothesis
Zarithmetic
Ho = p ≤ 0.50 had high
2,840
application of GAP
Ha = p > 0.50 had high
application of GAP
Cultivation
Ho = p ≤ 0.50 had high
0,258
application of GAP
Ha = p > 0.50 had high
application of GAP
Post-harvest Ho = p ≤ 0.50 had low application
7,230
of GAP
Ha = p > 0.50 had low application
of GAP
Total GAP of Ho = p ≤ 0.50 had high
0,516
Shallots
application of GAP
Ha = p > 0.50 had high
application of GAP
zTable Conclusion Criteria
1,645 Ho refused High
Ha accepted
1,645 Ho accepted Low
Ha refused
1,645 Ho refused Low
Ha accepted
1,645 Ho accepted Low
Ha refused
Source: Analysis of Primary Data (2017)
commercial varieties of shallot seeds.
recommended dose, while 25%
However, only 25% of respondent
farmers used NPK fertilizer above
farmers use labeled/ certified seed
recommended dose. The average use
from Balai Pengawasan dan Sertifikasi
of NPK fertilizer was 500.78 kg/ha,
Benih (BPSB). Shallot farmers also
while the recommended dose was 650
had sufficient competence for shallot
kg/ha. Utilization of fertilizers that
cultivation because there was training
exceed the dose was the habit of the
from Dinas Pertanian Bantul and from
farmers in general, the reason to the
Balai Pengkajian Teknologi Pertanian
use of fertilizer more would be better
(BPTP) Yogyakarta.
results obtained.On the contrary, the
2) The level of application of GAP of
shallots on the subsystem of cultivation
reason farmers reduce doses aimed at
reducing production costs.
was lowbecause the application of
3) The level of application of shallot GAP
GAP on fertilization is still low.
in postharvest subsystem was low.
Respondent farmers who used organic
This shows that most farmers did not
fertilizer before planting or at the time
do postharvest activities of shallots.
of processing new land reached 54%.
Postharvest activities carried out by
There are still the majority of farmers
farmers were only in the stages of
(83.83%) did not use NPK fertilizer
withering and cleaning. The farmers
in recommended dose. 63.33% of
did not sort and grading the shallots,
farmers used NPK fertilizer under
while the shallot packaging and storage
Agro Ekonomi Vol. 28/No. 1, Juni 2017
57
activities were done at the merchant
labor, the existence of financial institutions
level. The intensity of postharvest
and assistance from the government will
handling of shallot in Bantul Regency
increase the adoption of technological
was included in the low category
innovation.
because farmers sold shallot directly.
Farmers immediately wanted to get
The Factors Affecting the Application of
money quickly used for household
GAP of Shallots
purposes and next farming costs.
Classic assumption test
4) The overall of GAP shallot application
Normality Test
was low. The application of the shallot
GAP was still low on the seeds,
fertilization, sorting and grading,
packaging, and storage component.
Normality test results using the
EViews program in this study showed that
residual values in this study were normally
distributed or met the requirements of
normality. This was indicated by the JB
The results of the analysis of the
application of shallot GAP in Bantul
Regency was in accordance with the
probability value greater than the alpha
of 5% (0.05) was 0.867. The result of
normality test can be seen in Figure 1.
results of research Witjaksono et al. (2012)
indicating that the highest adoption rate
Multicolinearity Test
was found in input selection innovation.
The availability of production input has a
significant effect on the adoption rate of
technological innovation. The increasing
availability of production input such as the
provision of farmland, availability of seeds,
fertilizers, pesticides and plant diseases,
The result of multicolinearity test in
this research showed that the data was free
from multicollinearity, indicated by the
coefficient value between variables smaller
than 0.8. The results of multicolinearity
testing can be seen in Table 7.
8
Series: Residuals
Sample 1 60
Observations 60
7
6
5
4
3
2
1
0
-0.3
-0.2
-0.1
0.0
0.1
0.2
Figure 1. Normality Test Result
Source: Analysis of primary data (2017)
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
1.83e-15
-0.005344
0.223980
-0.321195
0.105660
-0.142256
3.181524
Jarque-Bera
Probability
0.284746
0.867298
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Agro Ekonomi Vol. 28/No. 1, Juni 2017
Table 7. Multicollinearity Test Result
Land
Area
Land area
Farmers’ age
Farmers’ Education
Experience
Provision of farm input
Extension service
frequency
Farmers’ Farmers’
Provision of
Experience
age
Education
farm input
1,0000
-0,1664
0,0954
0,1179
0,1901
-0,0018
-0,1664
1,0000
-0,6698
-0,5243
-0,3078
-0,1860
0,0954
-0,6698
1,0000
-0,3460
0,3317
0,0130
0,1179
0,5243
-0,3460
1,0000
-0,0210
-0,0365
0,1901
-0,3078
0,3317
-0,0210
1,0000
0,2237
Extension
service
Frequency
-0,0018
-0,1860
0,0130
-0,0365
0,2237
1,0000
Source: Analysis of primary data (2017)
Table 8. Heteroscedasticity Test Result
F-statistic
Obs*R-squared
1,200 Prob, F
7,1790 Prob, Chi-Square
0,3206
0,3046
Source: Analysis of primary data (2017)
Heteroscedasticity Test
to explain the application level of GAP of
The results of heteroscedasticity
shallots in Bantul Regency (55.3%), while
testing in this study showed that research
the rest (44.7%) was caused by variable
data was free from heteroscedasticity,
outside model. The results of adjusted R2
indicated by the value of Obs*R-squared
test can be seen in Table 9.
0.305 which was significant or greater than
the alpha of 1% as shown in Table 8.
Based on the output of regression
analysis in Table 9, it can be mathematically
writtenregression model between the
Hypothesis Test
variable levelsof GAPapplication with
Determination Test (Adjusted R2)
variables that influenced it in the following
The results of data processing factors
influencing the application of GAP of
shallots in Bantul Regency showed that
correlation coefficient value (adjusted R2)
was 0.553. The value of adjusted R2 shown
in this study was quite good because the
correlation between the dependent variable
and the independent variable was called
equation:
Y = 1.652 + 0.058 x1 + 0.122 x3 + 0.045
x4 + 0.944 x5
Simultaneous Test
After the simultaneous test of the
factors affecting the level of GAPapplication,
strong if the value of adjusted R2 was above
it can be said that together the factors of land
0.5. The result of adjusted R2 test in this
area, farmers’ age, farmers’ education level,
research stated that the model used was able
farming experience, availability of farm
inputs, and extension service frequency
Agro Ekonomi Vol. 28/No. 1, Juni 2017
59
Table 9. Regression Analysis Test Result
Variable
C
Land area (x1)
Farmers’age (x2)
Farmers’ education (x3)
Farming experience (x4)
Provision of farm input (x5)
Extension service frequency (x6)
R-squared
Adjusted R-squared
F-statistic
Prob(F-statistic)
Expected Sign
+/+
+
+
+
+
Coefficient
1,652**
0,058***
-0,026ns
0,122*
0,045**
0,944***
0,052ns
0,599
0,553
13,174
0,000
Prob.
0,025
0,007
0,770
0,066
0,027
0,000
0,114
* Significant α = 10%
** Significant α = 5%
***Significant α = 1%
significantly affected the application level
< α = 1% (0.007
Agro Ekonomi Vol. 28/No. 1, Juni 2017
THE APPLICATION OF GOOD AGRICULTURE PRACTICES (GAP) OF
SHALLOT IN BANTUL REGENCY
Aplikasi Good Agriculture Practices (GAP) Bawang Merah Kecamatan
di Kabupaten Bantul
Suharni, Lestari Rahayu Waluyati, Jamhari
Master of Agribussiness Management, Faculty of Agriculture, Universitas Gadjah Mada
Jl. Flora, Bulaksumur, Kec.Depok, Kabupaten Sleman,
Daerah Istimewa Yogyakarta 55281
[email protected]
Diterima tanggal 16 Mei 2017 ; Disetujui tanggal 10 Juni 2017
ABSTRACT
Bantul Regency is one of the center of shallots in Indonesia, but its productivity is low. In
2015, the productivity of shallots in Bantul Regency was 7.66 tons/ha. The application of Good
Agriculture Practices (GAP) is a form of technology adoption aiming to improve the shallot
productivity.The purposes of this study are to determine the level of application of shallots
GAP in Bantul Regency and to find out the factors influencing the application such as land area,
farmers’ age, farmers’ education, farming experience, availability of farm inputs, and extension
service frequency. Purposive technique was used to determine the research location. Sanden and
Kretek districts were discovered since these areas are the production centers of shallots in Bantul
Regency. The study involved the respondents consisting of sixty shallot farmers, thirty people
from Kretek District and the other thirty people from Sanden District who were determined by
simple random sampling. This research used scoring technique with Likert scale to measure the
application level of GAP. Multiple linear regression analysis was used to understand the factors
affecting the application of GAP of shallots. Result showed that the application of GAP of shallots
in Bantul Regency is low. The factors of land area, farmers’ education, farming experience, and
availability of farm inputs means influence the application level of GAP of shallots significantly.
Keywords: adoption of technology, application of GAP, productivity, shallot
INTISARI
Kabupaten Bantul merupakan salah satu sentra bawang merah di Indonesia, tetapi
produktivitasnya masih rendah. Tahun 2015, produktivitas bawang merah di Kabupaten
Bantul sebesar 7,66 ton/ha. Penerapan Good Agriculture Practices (GAP) merupakan salah
satu bentuk adopsi teknologi yang bertujuan untuk meningkatkan produktivitas bawang
merah. Tujuan penelitian ini adalah untuk mengetahui tingkat penerapan GAP bawang
merah di Kabupaten Bantul dan mengetahui faktor-faktor yang mempengaruhi penerapannya
diantaranya luas lahan, umur petani, pendidikan petani, pengalaman usahatani, ketersediaan
sarana produksi, dan frekuensi penyuluhan. Pemilihan lokasi penelitian dilakukan dengan
teknik purposive. Kecamatan Sanden dan Kretek dipilih karena merupakan sentra produksi
bawang merah di Kabupaten Bantul. Penelitian dilakukan terhadap 60 orang petani sampel
bawang merah, 30 orang dari Kecamatan Kretek dan 30 orang dari Kecamatan Sanden yang
dipilih secara acak sederhana. Penelitian ini menggunakan teknik skoring dengan skala likert
untuk mengukur tingkat penerapan GAP. Analisis regresi linear berganda digunakan untuk
Agro Ekonomi Vol. 28/No. 1, Juni 2017
49
mengetahui faktor-faktor yang mempengaruhi penerapan GAP bawang merah. Dari hasil
penelitian diketahui bahwa tingkat penerapan GAP bawang merah di Kabupaten Bantul
rendah. Faktor luas lahan, pendidikan petani, pengalaman usahatani, dan ketersediaan
sarana produksi berpengaruh signifikan terhadap tingkat penerapan GAP bawang merah.
Kata kunci: adopsi teknologi, bawang merah, penerapan GAP, produktivitas
INTRODUCTION
Horticulture subsector has a strategic
and important position in the agricultural
of good quality shallot seeds (Thamrin et
al., 2003; Winarto et al., 2009; Asaad &
Warda, 2010; Azmi et al., 2011).
sector because it has a high market potential.
Several issues that resulted in
One of the horticultural commodities that
low productivity of shallot in Indonesia
have high economic value is shallot
were: (a) availability of quality seeds, (b)
(Wiguna et al., 2013; Theresia et al., 2016).
limited farm inputs, (c) not yet properly
Shallot is a spice vegetable that has high
implemented location-specific GAP; as a
selling value and developed intensively.
result the cultivation problems were not
In economic terms, shallot business is
solved (Paranata et al., 2015).
quite profitable and has a wide market.
The cultivation of shallots by farmers
Shallot is needed as a spice in almost all
in Indonesia generally has not fully applied
Indonesian dishes everyday. Shallot is also
the correct cultivation rules, yet in the
used in the food industry as a seasoning
current era of global trade, shallot farmers
flavor. The consumption and demand of
are required to improve the competitiveness
shallots will continue to increase in line
of products to produce agricultural products
with the increasing needs of the population
that are safe to consume, good quality, and
due to the growing number of people, the
produced in an environmentally friendly
development of the food industry and
manner. Today people are becoming
market development.
aware that the excessive use of chemical
One of the central area of shallot
fertilizers and pesticides used by farmers
production in Indonesia is Bantul Regency,
are not good for health. To improve the
Yogyakarta. The area of shallot harvest
production, quality and competitiveness of
in Bantul Regency in 2015 reached 585
shallot in meeting the needs of the domestic
hectares with production of 4,478.9 tons
market and for export, the production
and productivity of 7.66 tons/ha. This
process needs to be done well by applying
productivity decreased in the previous year
Good Agriculture Practices (GAP).
which reached 10.07 tons/ha (Ministry of
The efforts to increase the
Agriculture, 2017). It was suppossed to
productivity of shallots are done by
obtain yields of 15-20 tons/ha with the use
introducing new technology, both local
50
Agro Ekonomi Vol. 28/No. 1, Juni 2017
technology and technology produced by
standard were land area, access of off-farm
research institutions (Sasongko et al.,
income, access to market information, and
2014). One of the adoption of technology
extension role, while the negative factor
is by applying shallot GAP. The application
was age of farmer.
of fruit and vegetable GAP is regulated
According to Lionberger (1968),
in Minister of Agriculture Regulation
several factors that affect a person’s speed
number 48/ Permentan/ OT.160/10/2009
to adopt innovation are:
on Guidelines for Good Fruit and Vegetable
1. Land area, the wider land area usually
Cultivation. GAP components include land
the faster adopt the innovation because
issues, use of seeds and crop varieties,
it has better economic capability.
planting, fertilizing, crop protection,
2. Income level, the higher the income
irrigation, harvesting, post harvest,
level usually the faster adopt the
agricultural machinery, environmental
innovation.
conservation, workers, worker welfare,
3. Courage to take risks, individuals
landfills, surveillance, recording and
who have the courage to face risks are
traceback,and internal evaluation (Ministry
usually innovative.
of Agriculture, 2009).
4. Age, getting older (above 50 years),
The research on measuring the
usually getting slower to adopt
level of application of GAP for several
commodities has been done. Sriyadi et al
innovation.
5.
Level of participation in groups or
(2015) conducted a study on the Evaluation
organizations outside the environment.
of Implementation of Standard Operating
Someone who likes to join people
Procedure-Good Agriculture Practice
outside of his social system is generally
(SOP-GAP) on Organic Rice Farming in
more innovative.
Bantul District. This study aims to measure
6. Source of information utilized.
the level of application of SOP-GAP
organic rice farming. The results showed
Due to the low shallot productivity
that the level of SOP-GAP application of
in Bantul Regency, it is necessary to do
organic rice farming in Bantul Regency
research on the extent to which shallot
was high (82.31%).
farmers in Bantul Regency apply GAP of
Research on factors influencing the
shallots on the agribusinesssubsystems of
application of GAP has also been done
input provision, cultivation, post-harvest,
by Annor (2016). The results showed
and the factors that affect the level of
that the factors that positively affect the
application of GAP. This study aims to
farmer’s decision to meet GLOBAL GAP
determine the level of application of GAP
Agro Ekonomi Vol. 28/No. 1, Juni 2017
51
of shallots and to determine the factors that
obtained from interviews and observations,
affect the application of GAP of shallot in
while secondary data were obtained from
Bantul Regency.
the literature or references.
The hypothesis used in this research
is that the level of application of GAP of
Analysis of Shallot GAP Application
shallots in Bantul Regency ishigh on input
The application of GAP of shallotswas
provision and cultivation subsystems,
divided into three subsystems, namely the
butstill low on postharvest subsystem.
provision of input, cultivation, and post-
The factors that positively influence the
harvest. The application of GAPshallot was
application of GAPshallot are land area,
measured by scoring technique using Likert
farmer education, farming experience,
scale. With Likert scale, the variables
availability of farm inputs, and frequency
used were described as statements which
of extension service by extension officer,
were the indicators in measurement of the
while the farmers’ age has negative effect.
application of GAP.
The answers to the questions given
METHODS
This research was conducted on
shallot farmers in Bantul Regency,
in this study were given scores that are:
1 for answers of never, 2 for answers of
sometimes, and 3 for answers of always.
Yogyakarta. The location was selected
purposively, related to Kretek and Sanden
as a district which has the larger shallot
farming in Bantul.
Validity and Reliability Test
The way used to determine the
validity of a measuring tool is by correlating
The number offarmer samples used
between the scores obtained by each item
in this study was 60, 30 farmers from
(question or statement) with the total
Kretek District and 30 farmers from
score. Validity test uses product moment
Sanden District, selected by simple random
correlation (pearsons correlation) as
sampling.The number of samples taken
follows:
as many as 60 people has met the general
rule statistically ≥ 30 and able to present
the state of agriculture in that location
because the number of 30 samples has
rxy= coefficient of validity
been normally distributed and can be used
X = item score
to predict the population (Hasan, 2002).
Y = total item score
The type of data used was primary
data and secondary data. Primary data were
N = respondent number
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Agro Ekonomi Vol. 28/No. 1, Juni 2017
To test the reliability of measuring
equipment is calculated by using estimation
where
P = Percentage of GAPapplication level
parameters
of Cronbach’s Alpha model that is processed
with the help of SPSS program.
Po = Percentage of assigned applicationlevel
parameters (0.5)
The GAP application scores achieved
by the respondents on each subsystem are
n = sample number
calculated on average score.Furthermore,
The criterion of determination is:
the level of GAP application is classified
Ho is accepted when Zarithmetic ≤ Ztable and Ho
into 2 categories of classes, namely low
is refused when Zarithmetic > Ztable.
application level and high application
level based on the scores obtained by
Analysis of Factors Affecting the Level
respondents used intervals of the formula
of Apllication of GAP
To determine the factors that
as follows:
influence the level of application of GAP of
shallot in Bantul Regency, multiple linear
Where:
regression analysis was used. Application
I = class interval
of GAP of shallot was dependent variable
J = range between maximum score (3) and
(Y) which was suspected to be influenced
minimum score (1)
K = The number of used class(that was 2).
by independent variables that were land
area (X1), farmers’ age (X2), farmers’
education level (X3), farming experience
The classification of GAP application level
(X4), availability of farm inputs (X5),
is classified based on the following scores:
and extension service frequency (X6)
1. Low application level if score 1 – 2.
which can be expressed by multiple linear
2. High application level if score 2.01–3
regression model as follows:
Y = a + b1X1 + b2X2 + b3X3 + b4X4 +
Hypothesis Test
Hypothesis test was done by testing
the parameter of proportion. Test steps
b5X5 + b6X6
Information:
Y = GAP Apllication (percentage of likert
score)
were determine the hypothesis Ho and Ha
then calculate z arithmetic. The value of z
a
= constants
arithmetic was obtained by the formula:
b1, b2, b3, b4, b5, b6 = regression coefficient
X1 = land area (hectare)
X2 = farmers age (year)
X3 = farmers’ education level (year)
Agro Ekonomi Vol. 28/No. 1, Juni 2017
53
X4 = shallot farming experience(year)
this study included several tests as follows:
X5 = availability of farm inputs (score)
a. D e t e r m i n a t i o n c o e ff i c i e n t t e s t
X6 = extension servicefrequency (times)
To meet statistical test requirements
in multiple linear regression analysis, the
(Adjusted R²)
b. Simultaneous test(F-test)
c. Individual test (t-test)
classical assumption test using EViews
program includes:
RESULTS AND DISCUSSION
a. Normality test using Jarque-Bera (JB)
Age of respondent farmers was
Test, that is comparing JB probability
dominated by productive age between
value with alpha level 5%.
15-64 years (81.67%). A productive age is
b. Multicolinearity test, data is free from
the most appropriate age for carrying out
multicolinearity if all correlation
working activities such as farming because
coefficient between independent
it is physically still good, has high spirits
variables is smaller than 0.8.
and an obligation to support the family
c. Heteroscedasticity test, the data is free
(Aldila et al., 2015).
of heteroscedasticity if the probability
Shallot farmer respondents in Bantul
value of Obs*R-squaredvalue shows
Regency mostly had elementary education
significant or greater result thanalpha
that was equal to 38.33%, while those with
of 1%.
SMA education as much as 35.00%. The
level of education will affect a farmer’s
In addition to using the classical
way of thinking and the level of technology
assumption test, this study also used
and science absorption (Aldila et al., 2015).
hypothesis testing. The hypothesis test in
Table 1. Characteristics of Respondents
Characteristics
Ages (year)
Education
Farming experience
(year)
Groups
≤ 14 years old
15-64 ears old
≥ 65 years old
Elementary school
Junior high school
Senior high school
University
1–7
8 – 14
15 – 21
22 – 28
29 – 35
36 – 42
43 – 49
Source: Analysis of Primary Data (2017)
The number (people)
0
49
11
23
15
21
1
9
8
15
10
12
4
2
Percentage (%)
0,00
81,67
18,33
38,33
25,00
35,00
1,67
15,00
13,33
25,00
16,67
20,00
6,67
3,33
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Agro Ekonomi Vol. 28/No. 1, Juni 2017
The level of shallot farming
alpha in this study used a value of 0.6
experience was mostly between 15-21
assuming the list of questions tested would
years (25.00%). Level of education and
be reliable if the value of cronbach’s alpha
farming experience will affect the way of
≥ 0.6. Reliability test results can be seen
thinking, the higher the level of education,
in Table 3.
the more responsive to new things.
Based on Table 3, it can be seen
that all GAPapplication items for input
Level of Application of GAP of Shallots
provision, cultivation and postharvest
Validity Test
subsystems have a very high reliability
Calculation of validity test with
product moment correlation coefficient
valuebecause cronbach’s alphavalue is
greater than 0.6.
used SPSS program aid. rarithmetic of each
item was compared with value in r Table
Hypothesis Test
of product moment. In this study with
The average score of GAP application
the respondent number of 60 and 5%
on the subsystem of input supply was 2.17
significance level,it resulted in rtable of
(72.18%), on the subsystem of cultivation
0.254. The result of validity test of GAP
of 2.04 (67.96%), on postharvest subsystem
of shallots can be seen in Table 2.
of 1.49 (49.58%), and the average total
GAP application score of 2.04(68.12%).
Table 2. Validity Test Result
No.
Subsystems
1.
2.
3.
Input provision
Cultivation
Post-harvest
The point
Valid
number
47
37
28
12
8
8
Source: Analysis of primary data (2017)
The results of GAP application level
analysis can be seen in Table 4.
From Table 4 it can be seen that
the low level of GAP application on the
input subsystem was the seed component,
the low level of application of GAP in
Reliability Test
the cultivation subsystem was on the
To see the reliability value,we used
fertilization component, while the low level
cronbach’s alpha value that estimated using
of application of GAP in the post-harvest
SPSS program. The value of cronbach’s
subsystem were on sorting and grading,
packaging, and storage.
Table 3. Reliability Test Result
No.
1.
2.
3.
Subsystem
Cronbach’s Alpha Value
Input provision
0,943
Cultivation
0,886
Post-harvest
0,819
Source: Analysis of primary data (2017)
Reliability Standard number
≥ 0,6
≥ 0,6
≥ 0,6
Information
Reliable
Reliable
Reliable
Agro Ekonomi Vol. 28/No. 1, Juni 2017
55
Table 4. The Level of Application of Shallot GAP in Bantul Regency
Subsystem
Input
Provision
Cultivation
Postharvest
Technology Components
Land
Seed
Fertilizer
Pesticide
Agricultural equipment &
machinery
Workers
Land preparation
Planting
Fertilization
Plant protection
Irrigation
Harvest
Early treatment
Cleaning
Sorting and Grading
Packaging
Storage
Maximum
Score
3
3
3
3
3
Average
Percentage
Score
(%)
2,55
85,00
1,52
50,60
2,75
91,67
2,22
73,83
2,08
69,26
3
3
3
3
3
3
3
3
3
3
3
3
2,07
2,52
2,53
1,59
2,25
2,32
2,34
2,72
2,87
1,03
1,05
1,07
Criteria
High
Low
High
High
High
69,03
83,89
84,44
52,89
75,00
77,22
78,06
90,56
95,56
34,44
35,14
35,56
High
High
High
Low
High
High
High
High
High
Low
Low
Low
Source: Analysis of primary data (2017)
Table 5. Distribution of Farmers Based on The Application Level of GAP
GAP Application level
No.
Subsystem
1. Input provision
2. Cultivation
3. Post-harvest
Total GAP of shallots
Low
Frequency (people)
19
29
58
28
%
31,67
48,33
96,67
46,67
High
Frequency (people)
41
31
2
32
%
68,33
51,67
3,33
53,33
Source: Analysis of Primary Data (2017)
To determine whether the application
is conducted to determine the level of GAP
of shallot GAP is included in low or high
application statistically.Hypothesis test
criteria, then the GAP application level
results can be seen in Table 6.
is classified by score into low and high
Based on the hypothesis test, it can
application level. The distribution of
be determined that:
farmers based on the level of application
1) The level of application of shallot GAP
of GAP can be seen in Table 5.
on the input provision subsystem was
Based on Table 5, it is known that on
high because the farmers had used
the application of GAP as a whole, as many
good planting media, good commercial
as 32 respondents (53.33%) included in
varieties of shallot seeds, registered
the category of high application level and
and permitted fertilizers and pesticides,
28 respondents (46.67%) included in low
and appropriate agricultural machinery
category. Furthermore, hypothesis testing
and tools. All farmers are already using
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Agro Ekonomi Vol. 28/No. 1, Juni 2017
Table 6. Hypothesis Test Result
No. Subsystem
1. Input
Provision
2.
3.
Hypothesis
Zarithmetic
Ho = p ≤ 0.50 had high
2,840
application of GAP
Ha = p > 0.50 had high
application of GAP
Cultivation
Ho = p ≤ 0.50 had high
0,258
application of GAP
Ha = p > 0.50 had high
application of GAP
Post-harvest Ho = p ≤ 0.50 had low application
7,230
of GAP
Ha = p > 0.50 had low application
of GAP
Total GAP of Ho = p ≤ 0.50 had high
0,516
Shallots
application of GAP
Ha = p > 0.50 had high
application of GAP
zTable Conclusion Criteria
1,645 Ho refused High
Ha accepted
1,645 Ho accepted Low
Ha refused
1,645 Ho refused Low
Ha accepted
1,645 Ho accepted Low
Ha refused
Source: Analysis of Primary Data (2017)
commercial varieties of shallot seeds.
recommended dose, while 25%
However, only 25% of respondent
farmers used NPK fertilizer above
farmers use labeled/ certified seed
recommended dose. The average use
from Balai Pengawasan dan Sertifikasi
of NPK fertilizer was 500.78 kg/ha,
Benih (BPSB). Shallot farmers also
while the recommended dose was 650
had sufficient competence for shallot
kg/ha. Utilization of fertilizers that
cultivation because there was training
exceed the dose was the habit of the
from Dinas Pertanian Bantul and from
farmers in general, the reason to the
Balai Pengkajian Teknologi Pertanian
use of fertilizer more would be better
(BPTP) Yogyakarta.
results obtained.On the contrary, the
2) The level of application of GAP of
shallots on the subsystem of cultivation
reason farmers reduce doses aimed at
reducing production costs.
was lowbecause the application of
3) The level of application of shallot GAP
GAP on fertilization is still low.
in postharvest subsystem was low.
Respondent farmers who used organic
This shows that most farmers did not
fertilizer before planting or at the time
do postharvest activities of shallots.
of processing new land reached 54%.
Postharvest activities carried out by
There are still the majority of farmers
farmers were only in the stages of
(83.83%) did not use NPK fertilizer
withering and cleaning. The farmers
in recommended dose. 63.33% of
did not sort and grading the shallots,
farmers used NPK fertilizer under
while the shallot packaging and storage
Agro Ekonomi Vol. 28/No. 1, Juni 2017
57
activities were done at the merchant
labor, the existence of financial institutions
level. The intensity of postharvest
and assistance from the government will
handling of shallot in Bantul Regency
increase the adoption of technological
was included in the low category
innovation.
because farmers sold shallot directly.
Farmers immediately wanted to get
The Factors Affecting the Application of
money quickly used for household
GAP of Shallots
purposes and next farming costs.
Classic assumption test
4) The overall of GAP shallot application
Normality Test
was low. The application of the shallot
GAP was still low on the seeds,
fertilization, sorting and grading,
packaging, and storage component.
Normality test results using the
EViews program in this study showed that
residual values in this study were normally
distributed or met the requirements of
normality. This was indicated by the JB
The results of the analysis of the
application of shallot GAP in Bantul
Regency was in accordance with the
probability value greater than the alpha
of 5% (0.05) was 0.867. The result of
normality test can be seen in Figure 1.
results of research Witjaksono et al. (2012)
indicating that the highest adoption rate
Multicolinearity Test
was found in input selection innovation.
The availability of production input has a
significant effect on the adoption rate of
technological innovation. The increasing
availability of production input such as the
provision of farmland, availability of seeds,
fertilizers, pesticides and plant diseases,
The result of multicolinearity test in
this research showed that the data was free
from multicollinearity, indicated by the
coefficient value between variables smaller
than 0.8. The results of multicolinearity
testing can be seen in Table 7.
8
Series: Residuals
Sample 1 60
Observations 60
7
6
5
4
3
2
1
0
-0.3
-0.2
-0.1
0.0
0.1
0.2
Figure 1. Normality Test Result
Source: Analysis of primary data (2017)
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
1.83e-15
-0.005344
0.223980
-0.321195
0.105660
-0.142256
3.181524
Jarque-Bera
Probability
0.284746
0.867298
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Agro Ekonomi Vol. 28/No. 1, Juni 2017
Table 7. Multicollinearity Test Result
Land
Area
Land area
Farmers’ age
Farmers’ Education
Experience
Provision of farm input
Extension service
frequency
Farmers’ Farmers’
Provision of
Experience
age
Education
farm input
1,0000
-0,1664
0,0954
0,1179
0,1901
-0,0018
-0,1664
1,0000
-0,6698
-0,5243
-0,3078
-0,1860
0,0954
-0,6698
1,0000
-0,3460
0,3317
0,0130
0,1179
0,5243
-0,3460
1,0000
-0,0210
-0,0365
0,1901
-0,3078
0,3317
-0,0210
1,0000
0,2237
Extension
service
Frequency
-0,0018
-0,1860
0,0130
-0,0365
0,2237
1,0000
Source: Analysis of primary data (2017)
Table 8. Heteroscedasticity Test Result
F-statistic
Obs*R-squared
1,200 Prob, F
7,1790 Prob, Chi-Square
0,3206
0,3046
Source: Analysis of primary data (2017)
Heteroscedasticity Test
to explain the application level of GAP of
The results of heteroscedasticity
shallots in Bantul Regency (55.3%), while
testing in this study showed that research
the rest (44.7%) was caused by variable
data was free from heteroscedasticity,
outside model. The results of adjusted R2
indicated by the value of Obs*R-squared
test can be seen in Table 9.
0.305 which was significant or greater than
the alpha of 1% as shown in Table 8.
Based on the output of regression
analysis in Table 9, it can be mathematically
writtenregression model between the
Hypothesis Test
variable levelsof GAPapplication with
Determination Test (Adjusted R2)
variables that influenced it in the following
The results of data processing factors
influencing the application of GAP of
shallots in Bantul Regency showed that
correlation coefficient value (adjusted R2)
was 0.553. The value of adjusted R2 shown
in this study was quite good because the
correlation between the dependent variable
and the independent variable was called
equation:
Y = 1.652 + 0.058 x1 + 0.122 x3 + 0.045
x4 + 0.944 x5
Simultaneous Test
After the simultaneous test of the
factors affecting the level of GAPapplication,
strong if the value of adjusted R2 was above
it can be said that together the factors of land
0.5. The result of adjusted R2 test in this
area, farmers’ age, farmers’ education level,
research stated that the model used was able
farming experience, availability of farm
inputs, and extension service frequency
Agro Ekonomi Vol. 28/No. 1, Juni 2017
59
Table 9. Regression Analysis Test Result
Variable
C
Land area (x1)
Farmers’age (x2)
Farmers’ education (x3)
Farming experience (x4)
Provision of farm input (x5)
Extension service frequency (x6)
R-squared
Adjusted R-squared
F-statistic
Prob(F-statistic)
Expected Sign
+/+
+
+
+
+
Coefficient
1,652**
0,058***
-0,026ns
0,122*
0,045**
0,944***
0,052ns
0,599
0,553
13,174
0,000
Prob.
0,025
0,007
0,770
0,066
0,027
0,000
0,114
* Significant α = 10%
** Significant α = 5%
***Significant α = 1%
significantly affected the application level
< α = 1% (0.007