22 two indicators, poverty level of sub districts will be ranked by ORDIT ranking
method.
2.3 Methodology
Poverty Indicators In general, level of poverty is determined by the ability of people to meet the
minimum needs of life. There are several definitions of poverty are raised by the experts. According to Levitan, poverty is defined as a shortage of goods and
services needed to achieve an adequate standard of living. Schiller defines poverty as the inability to obtain adequate goods and services to meet limited social needs.
Salim believes that poverty is the lack of income to meet basic living needs. Therefore we can conclude that poverty involves the possibility of a person poor
families to establish and develop economic activities in an effort to improve the standard of living Soetrisno 2001. Minimum needs of life include health care
access. In overcoming the problem of poverty through a program of direct cash
assistance BLT, BPS has set 14 fourteen criteria of poor families, as has been disseminated by the Ministry of Communications and Information Technology
2005, which the 11th criterion is: unable to pay medical expenses in health centers polyclinics . People that meet 14 fourteen criteria can receive health
insurance for the poor Bajari 2008. Based on this rule and explanation about poverty letters in section 2.2.4, number of HIP and PL can be used as poverty level
indicators of a region. In other words, one of practical perspectives on poverty rate of a sub district is concerned with number of HIP and PL as multiple indicators.
The focus of this chapter is on placing the multiple dimensions of poverty in professional and public perspective to support policy of the district treat for
improvement.
Study Area Java Island is one of the five biggest islands in Indonesia. The Capital city of
Indonesia is located in the west area of Java Island. The percentage of population in this island is about 60 of the total population of Indonesia BPS 2010. But
23 this island has not been free from poverty. This interesting condition is one reason
to choose this island to be studied. Figure 8 is the map of Java Island with 115 districts area.
The study area of this research is Java Island in 2008 by omitting Jakarta, Banten and Yogyakarta provinces due to incomplete data and different typical of
those areas. West Java, Central Java, and East Java has total 1852 sub districts, but ranking method is used for 1679 sub districts because of incomplete data.
Figure 8 The Map of Java Island with district identity Description of the Data
This research focused on two indicators, even though many more indicators are also potentially interesting and the ranking method is applicable for
more than two indicators. HIP and PL are aggregated of a sub district as multiple
indicators in ranking method. Table 2 is six leading lines of dataset: id column is the identity of sub districts, Sub district is the name of sub districts, HIP is number
of health insurance for the poor, and PL is number of poverty letters. Table 3 is the description of indicators HIP and PL.
106 E 108 E
110 E 112 E
114 E 116 E
10 S 8 S
6 S 4 S
1 2
3 4
5 6
7 8
9 10
11 12
13 14
15 16
17 18
19 20
21 22
23 24
25 26
27 28
29 30
31 32
33 34
35 36
37 38
39 40
41 42
43 44
45 46
47 48
49 50
51 52 53
54 55
56 57
58 59
60 61
62 63
64 65
66 67
68 69
70 71
72 73
74 75
76 77
78 79
80 81
82 83
84 85
86 87
88 89
90 91
92 93
94 95
96 97
98 99
100 101
102 103
104 105
106 107108
109 110
111 112
113 114
Created with R
Longitude L
a ti
tu d
e
24 Table 2 Six leading lines of the poverty dataset
id Sub district
Number of health insurances for the poor HIP
Number of poverty letters PL
1 Nanggung
3402 634
2 Leuwiliang
7727 636
3 Leuwisadeng
3131 976
4 Pamijahan
7382 1275
5 Cibungbulang
9919 1423
6 Ciampea
6485 2084
…
Table 3 Description of indicators HIP and PL Statistic
Number of health insurances for the poor HIP
Number of poverty letters PL
Minimum Q1 Quartil1
2481 367
Median 4156
869 Mean
4549 1910
Q3 Quartil2 6046
2766 Maximum
27383 17136
Standard deviation 3159
2325 ORDIT ranking Algorithm
The steps of ORDIT to obtain ranking are as follows, 1. Preparing the data. Indicators of poverty used in this study are number of
health insurances for the poor and poverty letters. Table 2 is six leading lines of the dataset.
2. Exploring the data. Descriptive statistics and analysis of coefficient correlation are needed to obtain the view of the dataset.
3. Ranking every indicator. Indicators ranking is the beginning of ORDIT computation.
4. Building Hasse diagram. Positions of 1679 sub districts entities in Hasse diagram is based on indicators ranking. Hasse diagram with 1679 entities is
not shown.
5. Counting DD = N – 1. DD is the total number of sub districts compared to
every sub district.
25 6. Counting ffss, the number of sub districts as subordinate status with
respect to every sub district. ffaa, the number of sub districts as ascribe advantage over every sub district, and ffii, the number of sub districts as
indefinite to every sub district.
7. Obtaining AA = 100 × ffaaDD, SS = 100 × ffssDD, II = 100 ×
ff
iiDD clearly, AA + SS + II = 100. 8. CCC = 100
– AA and 9. ccc is obtained by rounding CCC to two decimal places and then
multiplying by 100.
10. bbb = SSCCC, and imposing 0.999 as an upper limit. 11. Adding these two values, ccc and bbb as ccc.bbb.
12. Ranking of ccc.bbb values of all individuals is as salient. 13. Precedence plot graphing. Precedence plot is a scatter plot of SS as DD
and AA as DD. Dots represent the position of sub districts at the
ranking. North West part is the position of top level and South East is the bottom level.
Actually there are some other steps to continue, but not written here due to only two indicators in the application.
2.4. Results and Discussion
Kategori