Saran KESIMPULAN DAN SARAN
[Kemenkoperekonomian RI]. 2010. Laporan Tim Narasumber Kementerian Koordinator
Bidang Perekonomian
RI. Koordinasi
Kebijakan Pengembangan dan Pengelolaan Sumberdaya Air untuk Ketahanan
Pangan. Jakarta. Khan, Aziz. 2006. Pelatihan Valuasi Ekonomi Sumberdaya Alam Dan
Lingkungan: “Valuasi Ekonomi Sumberdaya Alam Secara Partisipatif Di Taman Nasional Gunung Gede Pangrango
. Modul SEAMEO-BIOTROP. Bogor.
Lembaga Ilmu Pengetahuan Indonesia LIPI dan Departemen Pekerjaan Umum PU. 2006. Laporan Kajian Ekohidrologi Sebagai Dasar Penetapan Pola
Pengelolaan Danau Limboto Secara Terpadu . Gorontalo.
Merryna. 2009. Analisis WTP Masyarakat Terhadap Pembayaran Jasa Lingkungan Mata Air Cirahab, Desa Curug Goong, Kecamatan
Padarincang, Kabupaten Serang, Banten. Skripsi. Institut Pertanian Bogor. Mitchell, Setiawan, Rahmi. 2003. Pengelolaan Sumberdaya dan Lingkungan.
Yogyakarta: Gadjah Mada University Press. Mitchell, R and Carson, R
. 1989. “Using Surveys to Value Public Goods: The Contingent Valuation Method
”. Resources for the Future, Washington, D.C., Number of Pages: 463. Keywords: Contingent Valuation.
Munasinghe, M. 1993. Environmental Economics and Sustainable Development. World Bank Environment Paper Number 2.
O’neill, John et.al. 2008. Routledge Introductions to Environment Series Environmental Values. Simultaneously Published in the USA and Canada.
New York. Pawitan, H dan Daniel M. 1995. Monitoring Dan Evaluasi Komponen Biofisik
DAS. Lokakarya Pembahasan Hasil Penelitian dan Analisis Pengelolaan Daerah Aliran Sungai, Garut, 20-24 November 1995.
Pearce D. 1993. Economic Values and The Natural World. Earthscan Publications Limited, London.
Pearce D. W, Moran D. 1994. The Economic Value of Biodiversity. Journal The World Conservation Union EARTHSCAN Publications Ltd, London.
Pearce D. W, Turner R. K. 1990. Economic of Natural Resources and The Environment
. Harvesters Wheatsheaf. New York. London. [Pemprov Gorontalo]. 2008. Master Plan Penyelamatan Danau Limboto.
Pemerintah Propinsi Gorontalo. Gorontalo.
Rees, Judith. 1990. Natural Resources: Allocation, Economics and Policy, Secon Edition
. Routledge: London. Rumfaker K Maurits. 2010. Analisis Pembayaran Jasa Lingkungan Di Kawasan
Konservasi Laut Daerah Kabupaten Raja Ampat . Tesis. Sekolah
Pascasarjana IPB. Bogor. Simanjuntak, M. H Sahat. 2010. Perkiraan Nilai Ekonomi Sumberdaya Alam
Productivity Method . [Materi Kuliah Productivity Method]. Program
Pascasarjana, Institut Pertanian Bogor. Bogor. Simanjuntak, M. H Sahat. 2010. Perkiraan Nilai Ekonomi Sumberdaya Alam
Water Residual Value . [Materi Kuliah Water Residual Value]. Program
Pascasarjana, Institut Pertanian Bogor. Bogor. Sinukaban, Naik. 2001. Pengelolaan Daerah Aliran Sungai DAS. [Materi Kuliah
Pengelolaan DAS]. Program Studi DAS, Program Pascasarjana, Institut Pertanian Bogor. Bogor.
Sihite, J dan Sinukaban, N. 2004. Economic Valuation of Land Use Cange in Besai Sub Watershed Tulang Bawang Lampung
. Proceed of International Seminar on
“Toward Harmonization between Development and Environmental Conservation in Biological Production” 3 – 5 Dec 2004.
Cilegon, Indonesia. Turner, K. Pearce, D. and Bateman, I. 1994. Environmental Economics: An
Elementary Introduction. Center for Social and Economic Research on the
Global Environment. University of East Anglia and University College London. London.
[UKP4]. 2011. Draft Final Strategi Nasional Reducing Emissions from Deforestation and Forest Degradation in Developing Countries
REDD+. USAID. 2007. Laporan Studi PES untuk Mengembangkan Skema PES di DAS
Deli, Sumatera Utara dan DAS Progo, Jawa Tengah. Widada. 2006. Pelatihan Valuasi Ekonomi Sumberdaya Alam Dan Lingkungan:
“Valuasi Ekonomi Sumberdaya Alam Secara Partisipatif Di Taman Nasional Gunung Halimun
. Modul SEAMEO-BIOTROP. Bogor.
Wijayanti, P dan Hastuti. 2009. Analisis Ekonomi Dan Strategi Pengelolaan Ekowisata: Studi Kasus Kawasan Wisata Gunung Salak Endah kabupaten
Bogor. Jurnal Ekonomi Lingkungan Vol.13No.22009. Hal.39-59. Yulian E. Noor. 2010. Valuasi Ekonomi Sumberdaya Alam Taman Hutan Raya
Bukit Soeharto Di Provinsi Kalimantan Timur . Tesis. Sekolah
Pascasarjana IPB. Bogor.
LAMPIRAN
Lampiran 1. Analisis Regresi Nilai WTP Ekowisata
Regression Analysis: WTP versus Usia, Pendidikan, ...
Swasta is highly correlated with other X variables Swasta has been removed from the equation.
The regression equation is WTP = 0.331 + 0.0001 Usia + 0.0419 Pendidikan - 0.113 PNS + 0.341
Pendapatan + 0.0815 Anggota Keluarga - 0.223 Daerah Asal + 0.00217 Jarak
- 0.315 Fasilitas - 0.252 Keindahan - 0.090 Tata Ruang Predictor Coef SE Coef T P VIF
Constant 0.3306 0.7719 0.43 0.671 Usia 0.00015 0.01271 0.01 0.991 3.084
Pendidikan 0.04187 0.03359 1.25 0.220 1.477 PNS -0.1135 0.2929 -0.39 0.701 2.092
Pendapatan 0.34068 0.06760 5.04 0.000 1.297 Anggota Keluarga 0.08152 0.05699 1.43 0.161 2.516
Daerah Asal -0.2233 0.2011 -1.11 0.274 1.539 Jarak 0.002166 0.003928 0.55 0.585 1.279
Fasilitas -0.3148 0.2606 -1.21 0.234 1.656 Keindahan -0.2516 0.2097 -1.20 0.237 1.162
Tata Ruang -0.0902 0.2258 -0.40 0.692 1.244 S = 0.550091 R-Sq = 49.8 R-Sqadj = 37.0
PRESS = 19.7810 R-Sqpred = 15.90 Analysis of Variance
Source DF SS MS F P Regression 10 11.7186 1.1719 3.87 0.001
Residual Error 39 11.8014 0.3026 Total 49 23.5200
Source DF Seq SS Usia 1 1.0983
Pendidikan 1 0.0715 PNS 1 0.0401
Pendapatan 1 9.1617 Anggota Keluarga 1 0.3600
Daerah Asal 1 0.0735 Jarak 1 0.0263
Fasilitas 1 0.3328 Keindahan 1 0.5062
Tata Ruang 1 0.0483
Unusual Observations Obs Usia WTP Fit SE Fit Residual St Resid
34 36.0 3.0000 1.9568 0.2639 1.0432 2.16R 44 15.0 1.0000 2.0217 0.2427 -1.0217 -2.07R
48 20.0 3.0000 1.8964 0.1527 1.1036 2.09R 50 23.0 3.0000 1.8969 0.1517 1.1031 2.09R
R denotes an observation with a large standardized residual. Durbin-Watson statistic = 2.44918
No evidence of lack of fit P = 0.1.
Lampiran 2. Analisis Regresi Nilai WTP Keberadaan
Regression Analysis: WTP versus Usia, Pendidikan, ...
Swasta is highly correlated with other X variables Swasta has been removed from the equation.
The regression equation is WTP = 0.091 + 0.0019 Usia - 0.0171 Pendidikan + 0.205 Petani + 0.212 PNS
+ 0.338 Pendapatan - 0.0030 Anggota Keluarga - 0.361 Daerah Asal - 0.00729 Jarak + 0.185 Kelestarian Lingkungan
+ 0.775 Pengetahuan Fungsi DAS Predictor Coef SE Coef T P VIF
Constant 0.0909 0.7162 0.13 0.900 Usia 0.00188 0.01053 0.18 0.860 3.877
Pendidikan -0.01713 0.02028 -0.84 0.409 1.425 Petani 0.2052 0.2379 0.86 0.399 1.820
PNS 0.2118 0.1834 1.15 0.263 1.731 Pendapatan 0.3381 0.1017 3.32 0.004 1.234
Anggota Keluarga -0.00304 0.05971 -0.05 0.960 3.452 Daerah Asal -0.3608 0.1794 -2.01 0.059 1.730
Jarak -0.007295 0.004472 -1.63 0.119 1.542 Kelestarian Lingkungan 0.1846 0.1872 0.99 0.336 1.298
Pengetahuan Fungsi DAS 0.7754 0.2407 3.22 0.004 1.208 S = 0.359961 R-Sq = 67.2 R-Sqadj = 49.9
PRESS = 5.86050 R-Sqpred = 21.86 Analysis of Variance
Source DF SS MS F P Regression 10 5.0381 0.5038 3.89 0.005
Residual Error 19 2.4619 0.1296 Total 29 7.5000
Source DF Seq SS Usia 1 0.2706
Pendidikan 1 0.0553 Petani 1 0.3462
PNS 1 0.0698 Pendapatan 1 1.7307
Anggota Keluarga 1 0.0525 Daerah Asal 1 0.6179
Jarak 1 0.4959 Kelestarian Lingkungan 1 0.0547
Pengetahuan Fungsi DAS 1 1.3445 Durbin-Watson statistic = 1.84134
No evidence of lack of fit P = 0.1.
Lampiran 3. Analisis Regresi Nilai WTP Warisan
Regression Analysis: WTP versus Usia, Pendidikan, ...
Swasta is highly correlated with other X variables Swasta has been removed from the equation.
The regression equation is WTP = - 0.499 + 0.00014 Usia + 0.0110 Pendidikan + 0.164 Petani + 0.702
Nelayan + 0.114 PNS + 0.813 Pendapatan - 0.0302 Anggota Keluarga
- 0.182 Daerah Asal - 0.0296 Jarak + 0.130 Kelestarian Lingkungan + 0.250 Pengetahuan Fungsi DAS
Predictor Coef SE Coef T P VIF Constant -0.4988 0.7739 -0.64 0.521
Usia 0.000145 0.008947 0.02 0.987 1.896 Pendidikan 0.01095 0.02530 0.43 0.666 1.726
Petani 0.1641 0.3148 0.52 0.604 2.560 Nelayan 0.7020 0.3422 2.05 0.044 2.701
PNS 0.1143 0.2586 0.44 0.660 2.260 Pendapatan 0.8126 0.1103 7.36 0.000 1.909
Anggota Keluarga -0.03019 0.04950 -0.61 0.544 1.628 Daerah Asal -0.1825 0.2334 -0.78 0.437 1.178
Jarak -0.02960 0.06337 -0.47 0.642 1.772 Kelestarian Lingkungan 0.1300 0.2727 0.48 0.635 1.378
Pengetahuan Fungsi DAS 0.2499 0.2492 1.00 0.319 1.762 S = 0.686969 R-Sq = 57.2 R-Sqadj = 50.3
PRESS = 44.5554 R-Sqpred = 40.58 Analysis of Variance
Source DF SS MS F P Regression 11 42.8965 3.8997 8.26 0.000
Residual Error 68 32.0910 0.4719 Total 79 74.9875
Source DF Seq SS Usia 1 2.6963
Pendidikan 1 0.8808 Petani 1 3.7757
Nelayan 1 2.6780 PNS 1 0.1445
Pendapatan 1 31.3916 Anggota Keluarga 1 0.1826
Daerah Asal 1 0.3751 Jarak 1 0.1021
Kelestarian Lingkungan 1 0.1951 Pengetahuan Fungsi DAS 1 0.4746
Unusual Observations Obs Usia WTP Fit SE Fit Residual St Resid
28 60.0 4.0000 2.6959 0.3182 1.3041 2.14R 50 46.0 4.0000 2.5822 0.2780 1.4178 2.26R
54 49.0 1.0000 2.6956 0.2025 -1.6956 -2.58R 55 49.0 1.0000 2.5880 0.2125 -1.5880 -2.43R
64 63.0 4.0000 2.6026 0.3407 1.3974 2.34R R denotes an observation with a large standardized residual.
Durbin-Watson statistic = 1.70202 No evidence of lack of fit P = 0.1.
Lampiran 4. Net Present Value NPV Sub DAS Biyonga Selama 15, 25 dan
50 Tahun Pada Tingkat Diskon Faktor 5
Thn TEV
Rp NPV
Rp Thn
TEV Rp
NPV Rp
1 1,122,249,073,172.81
1,068,808,641,117 26
1,122,249,073,172.81 315,622,154,136
2 1,122,249,073,172.81
1,017,912,991,540 27
1,122,249,073,172.81 300,592,527,749
3 1,122,249,073,172.81
969,440,944,324 28
1,122,249,073,172.81 286,278,597,856
4 1,122,249,073,172.81
923,277,089,832 29
1,122,249,073,172.81 272,646,283,672
5 1,122,249,073,172.81
879,311,514,126 30
1,122,249,073,172.81 259,663,127,307
6 1,122,249,073,172.81
837,439,537,263 31
1,122,249,073,172.81 247,298,216,483
7 1,122,249,073,172.81
797,561,464,060 32
1,122,249,073,172.81 235,522,110,936
8 1,122,249,073,172.81
759,582,346,724 33
1,122,249,073,172.81 224,306,772,320
9 1,122,249,073,172.81
723,411,758,784 34
1,122,249,073,172.81 213,625,497,448
10 1,122,249,073,172.81
688,963,579,795 35
1,122,249,073,172.81 203,452,854,712
11 1,122,249,073,172.81
656,155,790,281 36
1,122,249,073,172.81 193,764,623,535
12 1,122,249,073,172.81
624,910,276,458 37
1,122,249,073,172.81 184,537,736,700
13 1,122,249,073,172.81
595,152,644,245 38
1,122,249,073,172.81 175,750,225,429
14 1,122,249,073,172.81
566,812,042,139 39
1,122,249,073,172.81 167,381,167,075
15 1,122,249,073,172.81
539,820,992,513 40
1,122,249,073,172.81 159,410,635,310
16 1,122,249,073,172.81
514,115,230,965 41
1,122,249,073,172.81 151,819,652,676
17 1,122,249,073,172.81
489,633,553,300 42
1,122,249,073,172.81 144,590,145,406
18 1,122,249,073,172.81
466,317,669,809 43
1,122,249,073,172.81 137,704,900,386
19 1,122,249,073,172.81
444,112,066,485 44
1,122,249,073,172.81 131,147,524,177
20 1,122,249,073,172.81
422,963,872,843 45
1,122,249,073,172.81 124,902,403,979
21 1,122,249,073,172.81
402,822,736,041 46
1,122,249,073,172.81 118,954,670,456
22 1,122,249,073,172.81
383,640,700,991 47
1,122,249,073,172.81 113,290,162,339
23 1,122,249,073,172.81
365,372,096,182 48
1,122,249,073,172.81 107,895,392,704
24 1,122,249,073,172.81
347,973,424,935 49
1,122,249,073,172.81 102,757,516,861
25 1,122,249,073,172.81
331,403,261,843 50
1,122,249,073,172.81 97,864,301,772
Lampiran 5. Net Present Value NPV Sub DAS Biyonga Selama 15, 25 dan
50 Tahun Pada Tingkat Diskon Faktor 10
Thn TEV
Rp NPV
Rp Thn
TEV Rp
NPV Rp
1 1,122,249,073,172.81 1,020,226,430,157.10
26 1,122,249,073,172.81
94,162,816,737.97 2
1,122,249,073,172.81 927,478,572,870.09
27 1,122,249,073,172.81
85,602,560,670.88 3
1,122,249,073,172.81 843,162,338,972.81
28 1,122,249,073,172.81
77,820,509,700.80 4
1,122,249,073,172.81 766,511,217,248.01
29 1,122,249,073,172.81
70,745,917,909.82 5
1,122,249,073,172.81 696,828,379,316.37
30 1,122,249,073,172.81
64,314,470,827.11 6
1,122,249,073,172.81 633,480,344,833.07
31 1,122,249,073,172.81
58,467,700,751.92 7
1,122,249,073,172.81 575,891,222,575.51
32 1,122,249,073,172.81
53,152,455,229.02 8
1,122,249,073,172.81 523,537,475,068.65
33 1,122,249,073,172.81
48,320,413,844.56 9
1,122,249,073,172.81 475,943,159,153.32
34 1,122,249,073,172.81
43,927,648,949.60 10
1,122,249,073,172.81 432,675,599,230.29
35 1,122,249,073,172.81
39,934,226,317.82 11
1,122,249,073,172.81 393,341,453,845.72
36 1,122,249,073,172.81
36,303,842,107.11 12
1,122,249,073,172.81 357,583,139,859.74
37 1,122,249,073,172.81
33,003,492,824.64 13
1,122,249,073,172.81 325,075,581,690.68
38 1,122,249,073,172.81
30,003,175,295.13 14
1,122,249,073,172.81 295,523,256,082.43
39 1,122,249,073,172.81
27,275,613,904.66 15
1,122,249,073,172.81 268,657,505,529.48
40 1,122,249,073,172.81
24,796,012,640.60 16
1,122,249,073,172.81 244,234,095,935.89
41 1,122,249,073,172.81
22,541,829,673.28 17
1,122,249,073,172.81 222,030,996,305.36
42 1,122,249,073,172.81
20,492,572,430.25 18
1,122,249,073,172.81 201,846,360,277.60
43 1,122,249,073,172.81
18,629,611,300.23 19
1,122,249,073,172.81 183,496,691,161.45
44 1,122,249,073,172.81
16,936,010,272.93 20
1,122,249,073,172.81 166,815,173,783.14
45 1,122,249,073,172.81
15,396,372,975.40 21
1,122,249,073,172.81 151,650,157,984.67
46 1,122,249,073,172.81
13,996,702,704.90 22
1,122,249,073,172.81 137,863,779,986.07
47 1,122,249,073,172.81
12,724,275,186.28 23
1,122,249,073,172.81 125,330,709,078.24
48 1,122,249,073,172.81
11,567,522,896.62 24
1,122,249,073,172.81 113,937,008,252.95
49 1,122,249,073,172.81
10,515,929,906.01 25
1,122,249,073,172.81 103,579,098,411.77
50 1,122,249,073,172.81
9,559,936,278.19
Lampiran 6. Net Present Value NPV Sub DAS Biyonga Selama 15, 25 dan
50 Tahun Pada Tingkat Diskon Faktor 15
Thn TEV
Rp NPV
Rp Thn
TEV Rp
NPV Rp
1 1,122,249,073,172.81
975,868,759,281 26
1,122,249,073,172.81 29,644,587,133
2 1,122,249,073,172.81
848,581,529,809 27
1,122,249,073,172.81 25,777,901,855
3 1,122,249,073,172.81
737,896,982,443 28
1,122,249,073,172.81 22,415,566,831
4 1,122,249,073,172.81
641,649,549,950 29
1,122,249,073,172.81 19,491,797,244
5 1,122,249,073,172.81
557,956,130,392 30
1,122,249,073,172.81 16,949,388,908
6 1,122,249,073,172.81
485,179,243,819 31
1,122,249,073,172.81 14,738,599,050
7 1,122,249,073,172.81
421,894,994,625 32
1,122,249,073,172.81 12,816,173,087
8 1,122,249,073,172.81
366,865,212,717 33
1,122,249,073,172.81 11,144,498,337
9 1,122,249,073,172.81
319,013,228,450 34
1,122,249,073,172.81 9,690,868,119
10 1,122,249,073,172.81
277,402,807,348 35
1,122,249,073,172.81 8,426,841,843
11 1,122,249,073,172.81
241,219,832,476 36
1,122,249,073,172.81 7,327,688,559
12 1,122,249,073,172.81
209,756,376,066 37
1,122,249,073,172.81 6,371,903,095
13 1,122,249,073,172.81
182,396,848,753 38
1,122,249,073,172.81 5,540,785,300
14 1,122,249,073,172.81
158,605,955,438 39
1,122,249,073,172.81 4,818,074,174
15 1,122,249,073,172.81
137,918,222,120 40
1,122,249,073,172.81 4,189,629,716
16 1,122,249,073,172.81
119,928,888,800 41
1,122,249,073,172.81 3,643,156,275
17 1,122,249,073,172.81
104,285,990,261 42
1,122,249,073,172.81 3,167,961,978
18 1,122,249,073,172.81
90,683,469,792 43
1,122,249,073,172.81 2,754,749,546
19 1,122,249,073,172.81
78,855,191,123 44
1,122,249,073,172.81 2,395,434,388
20 1,122,249,073,172.81
68,569,731,412 45
1,122,249,073,172.81 2,082,986,424
21 1,122,249,073,172.81
59,625,853,401 46
1,122,249,073,172.81 1,811,292,543
22 1,122,249,073,172.81
51,848,568,175 47
1,122,249,073,172.81 1,575,036,994
23 1,122,249,073,172.81
45,085,711,457 48
1,122,249,073,172.81 1,369,597,386
24 1,122,249,073,172.81
39,204,966,484 49
1,122,249,073,172.81 1,190,954,249
25 1,122,249,073,172.81
34,091,275,204 50
1,122,249,073,172.81 1,035,612,390
Lampiran 7. Kuesioner Penelitian Mengenai Focus Group Discussion
FL IL PS Tanggal Wawancara
No Pertanyaan
Jawaban
1 Nama
2 JabatanUsaha
3 Lama JabatanUsaha
No Pertanyaan
Jawaban
I Bagaimana kehidupan
masyarakat di daerah anda?
II Bagaimana pendidikan
masyarakat di daerah anda?
III Bagaimana pendapat anda
mengenai DAS Limboto?
IV Bagaimana pendapat anda
mengenai pertanian, perikanan, kehutanan dan industri di Sub
DAS Biyonga?
V Bagaimana usulan anda
mengenai permasalahan tersebut?
Keterangan: FL
: Formal Leader IL
: Informal Leader PS
: Pengusaha
FOCUS GROUP DISCUSSION
FGD
Lampiran 8. Kuesioner Penelitian Mengenai Productivity Method
PROFIL RESPONDEN 1.
a. Nama :
b. Suku :
c. Aslipendatang :
d. Jika pendatang, dari mana :
e. Sejak kapan menetap :
f. Agama :
2. Umur :
3. Pendidikan Terakhir :
4. Pekerjaan :
5. Pendapatan :
6. Status Matrial :
7. Pekerjaan Istri :
8. Pendapatan Istri :
9. Jumlah Anak :
a. Anak I :
Status Matrial :
Umur :
Alamat :
Pendidikan :
Pekerjaan :
b. Anak II :
Status Matrial :
Umur :
Alamat :
Pendidikan :
Pekerjaan :
c. Anak III :
Status Matrial :
Umur :
Alamat :
Pendidikan :
Pekerjaan :
KUESIONER PRODUCTIVITY METHOD
No Responden: Tanggal Wawancara:
Luas Lahan Jumlah
Harga Rp Status
Milik sendiriSewa Milik sendiriSewa
Biaya Input Non-Sumberdaya Alam Jumlah
Harga Rp Total
BenihBibit Pakan
Pupuk Biaya Panen
Bagi Hasil Mesin Pompa Air
RumahPondok Alat Panen
Pajak PBB Perawatan Lahan
Perawatan Alat UpahGaji Buruh
BBM …………………………
………………………… …………………………
………………………… …………………………
Komoditi Jumlah ProduksiHa
Harga RpKg
Lampiran 9. Kuesioner Penelitian Mengenai Contingent Valuation Method
untuk WTP Keberadaan dan WTP Warisan
I. SOSIAL EKONOMI RESPONDEN 1. a. Nama
: b. Suku
: c. Aslipendatang
: d. Jika pendatang, dari mana
: e. Sejak kapan menetap
: f. Agama
: 2. Umur
: 3. Pendidikan Terakhir
: 4. Pekerjaan
: 5. Pendapatan
: 6. Status Matrial
: 7. Pekerjaan Istri
: 8. Pendapatan Istri
: 9. Jumlah Anak
: a. Anak I
: Status Matrial
: Umur
: Alamat
: Pendidikan
: Pekerjaan
: b. Anak II
: Status Matrial
: Umur
: Alamat
: Pendidikan
: Pekerjaan
: c. Anak III
: Status Matrial
: Umur
: Alamat
: Pendidikan
: Pekerjaan
:
KUESIONER CVM
No Responden: Tanggal Wawancara: