6.4 Arahan Rencana Pengelolaan Kawasan Konservasi Laut Kepulauan Derawan
7.2.2 Ditujukan pada para peneliti
Analisis kebijakan perlindungan penyu hijau yang merupakan bagian dari penelitian ini mengandung kelemahan karena minimnya data pengelolaan spesies. Untuk menyelamatkan penyu hijau dari kepunahan masih banyak penelitian yang dapat dikembangkan dengan kajian aspek ekologi, ekonomi, sosial dan budaya, antara lain:
1) Pengaruh perubahan iklim global terhadap kondisi populasi penyu.
2) Perubahan karakteristik siklus hidup penyu akibat kerusakan habitat dan eksploitasi secara berlebihan;
3) Tata niaga perdagangan ilegal penyu di seluruh Indonesia.
4) Penegakan hukum dan pengambilan sanksi serta koordinasi pemangku kepentingan baik di tingkat regional, nasional dan lokal.
5) Dukungan masyarakat terhadap upaya konservasi penyu berkaitan dengan persepsi masyarakat dan ketidakpedulian pengambil keputusan terhadap status konservasi penyu.
6) Tekanan masyarakat terhadap populasi penyu akibat peningkatan kemiskinan dan konflik pemanfaatan di wilayah pesisir dan laut.
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Lampiran 1. Analisis CATREG - Regression for Categorical Data
Metoda Categorical Regression (software package SPSS) digunakan untuk menguji pengaruh input pengelolaan UPT/ predictors (7 variabel) terhadap UPT pengelola penyu hijau/ response (ke 50 UPT). Dengan menggunakan prosedur
Optimal Scaling dapat memberi gambaran tentang hubungan antara variabel
response dengan sekelompok predictor. Hubungan tersebut dikuantitatifkan
sehingga nilai response dapat diprediksi dengan mengkombinasian predictors.
Tabel 1.1 Data NAMA VARIABEL LABEL KRITERIA VARIABEL DEPENDEN (RESPONSE)
UPT UPT UPT ( n=1,2,...50 )
TiU Tipe UPT (1)Tipe C (2)Tipe B (3)Tipe A Dana Dana yang
dialokasikan pada th 2004 (1) < 1,4 Milyar Rupiah (2) 2 s/d 2,9 Milyar Rupiah (3) 3 s/d 3,9 Milyar Rupiah (4) > 4 Milyar Rupiah SDM Jumlah SDM pada th 2004 (1) < 99 orang (2) 100 s/d 149 orang (3) 150 s/d 200 orang (4) > 200 orang KK Luas Kawasan Konservasi yang dimiliki UPT (1) < 199 ribu Ha (2) 200 s/d 299 Ha (3) 300 s/d 399 Ha (4) > 400 Ha Wilker Luas Wilayah
Kerja yang merupakan tanggungjawab UPT (1) < 4.9 juta Ha (2) 5 s/d 9.9 juta Ha (3) 10 s/d 14,9 juta Ha (4) > 15 juta Ha VARIABEL INDEPENDEN (PREDICTORS)
PGPan Panjang Garis Pantai Nesting site penyu yang ada di suatu UPT
(1) < 24,9 km (2) 25 s/d 49,9 km (3) 50 s/d 74,9 km (4) > 75 km JNest Jumlah Nesting
Site yang ada di suatu UPT
(1) < 2,9 lokasi (2) 3 s/d 5,9 lokasi (3) 8 s/d 8,9 lokasi (5) > 9 lokasi
Dengan menggunakan prosedur Optimal Scaling hubungan tersebut dikuantitatifkan sehingga nilai response dapat diprediksi dengan mengkombinasikan beberapa predictor.
Tabel 1.2 Case Processing Summary
Valid Active Cases 50
Active Cases with Missing Values 0
Supplementary Cases 0
Total 50
Cases Used in Analysis 50
Tabel 1.3ANOVA
Sum of
Squares df Mean Square F Sig.
Regression 26.052 13 2.004 3.013 .004
Residual 23.948 36 .665
Total 50.000 49
Dependent Variable: UPT
Predictors: Tipe UPT; Luas Kws Konservasi ;Luas Wil.Kerja ;Dana Pengelolaan 2004; Jumlah SDM 2004; Panjang Garis Pantai; Jumlah Nesting site.
Tabel ANOVA adalah hasil pengujian terhadap model yang menerangkan hubungan antara variabel dependen dengan independen, namun tidak secara langsung menjelaskan kekuatan hubungan. Nilai p = 0.04 berarti model regresi dapat menerangkan variabel UPT.
Tabel 1.4Correlations Original Variables
Tipe UPT Luas Kws Konserv asi Luas Wil.Kerja Dana Pengel olaan 2004 Jumlah SDM 2004 Panjang Garis Pantai Jumlah Nesting site Tipe UPT 1.000 -.047 .569 .334 .239 -.088 -.239 Luas Kws Konserv. -.047 1.000 -.161 .108 -.247 .085 .053 Luas Wil.Kerja .569 -.161 1.000 .111 -.013 .056 -.012 Dana Peng. 2004 .334 .108 .111 1.000 .339 .014 -.019 Jumlah SDM 2004 .239 -.247 -.013 .339 1.000 -.118 -.006 Panjang Grs Pantai -.088 .085 .056 .014 -.118 1.000 .257 Jumlah Nesting site -.239 .053 -.012 -.019 -.006 .257 1.000
Dimension 1 2 3 4 5 6 7
Tabel 1.5 Correlations Transformed Variables Tipe UPT Luas Kws Konserva si Luas Wil.Ke rja Dana Pengelola an 2004 Jumlah SDM 2004 Panjang Garis Pantai Jumlah Nesting site Tipe UPT 1.000 .034 .276 .400 .290 -.119 -.119 Luas Kws Konserv. .034 1.000 -.168 .205 -.252 .195 -.086 Luas Wil.Kerja .276 -.168 1.000 .124 .081 -.125 -.125 Dana Peng. 2004 .400 .205 .124 1.000 .483 .071 -.064 Jumlah SDM 2004 .290 -.252 .081 .483 1.000 -.153 .038 Panjang Grs Pantai -.119 .195 -.125 .071 -.153 1.000 -.064 Jumlah Nesting site -.119 -.086 -.125 -.064 .038 -.064 1.000 Dimension 1 2 3 4 5 6 7 Eigenvalue 1.916 1.403 1.122 .855 .799 .575 .330 Korelasi antar predictor digunakan untuk mengidentifikasi adanya
multicollinearity dalam regresi ini. Variabel-variabel yang memiliki korelasi tinggi akan menyebabkan ketidak-stabilan estimasi dari regresi. Jika korelasi antar predictor mendekati 0 maka dapat dikatakan bahwa multicollinearity antar individu tidak perlu diperhatikan.
Tabel 1.6 Model Summary
Multiple R R Square Adjusted R Square
.722 .521 .348
Dependent Variable: UPT
Predictors: Tipe UPT; Luas Kws Konservasi; Luas Wil.Kerja; Dana Pengelolaan 2004; Jumlah SDM 2004; Panjang Garis Pantai ; Jumlah Nesting site
Hubungan antara variabel response dengan sekelompok predictor dapat dijelaskan oleh model Regresi. Dengan koefisien determinasi: R2 = 0, 521 maka perbedaan UPT (response) setelah ditransformasi hanya 52,1 % yang dijelaskan oleh regresi dengan ke 7 predictor yang telah ditransformasi secara optimal. Adapun 47,9 % sisanya di pengaruhi oleh faktor yang tidak diketahui.
Dengan demikian pengelolaan penyu di 50 UPT tidak hanya dipengaruhi oleh input pengelolaan, seperti: Tipe UPT, Dana pengelolaan, Jumlah SDM, Luas Kawasan Konservasi, Luas Wilayah Kerja, Panjang Garis Pantai dan Jumlah
Tabel 1.7 Coefficients Standardized Coefficients df F Sig. Beta Std. Error Tipe UPT .480 .132 2 13.121 .000 Luas Kws Konservasi .425 .133 2 10.210 .000 Luas Wil.Kerja -.172 .124 2 1.912 .162 Dana Pengelolaan 2004 -.304 .152 3 4.006 .015 Jumlah SDM 2004 -.253 .148 2 2.945 .065 Panjang Garis Pantai .114 .121 1 .881 .354 Jumlah Nesting site .090 .118 1 .590 .447
Dependent Variable: UPT
Standardized Coefficients Beta mencerminkan pentingnya setiap predictor. Pada Tabel 2.7 dapat diketahui bahwa secara berurutan variabel predictor yang penting, adalah: Tipe UPT (0,480); Luas Kws Konservasi (0,425); Dana Pengelolaan 2004 (-0,304); Jumlah SDM 2004 (-0,253); Luas Wil.Kerja (-0,172); Panjang Garis Pantai (0,114); Jumlah Nesting site (0,09).
Persamaan Regresi :
Y = 0,48 X1 + 0,425 X2 – 0,304 X3 – 0,253 X4 -0, 172 X5 + 0,114 X6 + 0,09 X7 dimana :
Y = UPT X3 = Dana X6 = Panjang Garis pantai X1 = Tipe UPT X4 = SDM X1 = Jumlah Nesting site
X2 = Luas KK X5 = Luas Wilayah kerja Tabel 1.8 Correlations and Tolerance
Correlations Tolerance
Zero-Order Partial Part
Importance After Transfor mation Before Transfo rmation Tipe UPT .227 .517 .418 .209 .758 .516 Luas Kws Konservasi .486 .470 .369 .397 .752 .846 Luas Wil.Kerja -.194 -.225 -.160 .064 .865 .595 Dana Pengel. 2004 -.166 -.316 -.231 .097 .577 .775 Jumlah SDM 2004 -.396 -.275 -.198 .193 .610 .740 Panjang Garis Pantai .172 .155 .108 .038 .909 .908 Jumlah Nesting site .020 .127 .089 .004 .959 .857
Dari angka korelasi zero-order diketahui bahwa korelasi antara predictors
dengan response setelah ditransformasi. Korelasi tertinggi secara berurutan adalah: Luas Kws Konservasi (0.486); Jumlah SDM 2004 (-0.396); Tipe UPT (0.227); Luas Wil.Kerja (-0.194); Panjang Garis Pantai (0.172); Dana Pengel. 2004 (-0.166); Jumlah Nesting site (0.02).
Korelasi partial merupakan pengaruh linear dari predictors baik antar
predictor maupun tehadap response. Jika korelasi partial dikuadratkan akan memberi petunjuk proporsi dari variance jika pengaruh variabel lain dianggap tidak ada. Pada Tabel 1.8 diketahui bahwa proporsi dari beberapa predictor yakni : Tipe UPT (72%); Luas Kws Konservasi (69%);Dana Pengelolaan 2004 (56%); Jumlah SDM 2004 (52%); Luas Wil.Kerja (47%); Panjang Garis Pantai (39%); Jumlah Nesting site (36%).
Lampiran 2. Analisis Hierarchical Clustering
Penentuan karakteristik pengelolaan dan ancaman terhadap penyu hijau menggunakan analisis Metoda Hierarchical Clustering. Analisis cluster ini mengklasifikasikan data menjasi beberapa kelompok yang memiliki kesamaan (similarity/homogeneous). Pada Tabel 2.1 adalah data pengelolaan penyu dari
qoestionnaires yang berasal dari UPT lingkup Ditjen PHKA
Tabel 2.1 Kriteria data tentang pengelolaan penyu hijau dan ancaman terhadap penyu hijau
VARIABEL LABEL KRITERIA
1. NsKl Nesting & kelola (1) Tidak ada nesting & tidak ada pengelolaan
(2) Ada nesting & tidak ada pengelolaan
(3) Ada nesting & ada pengelolaan 2. Giat Jenis kegiatan
pengelolaan (1) 0 jenis kegiatan (2) 1 jenis kegiatan (3) 2 jenis kegiatan (4) 3 jenis kegiatan (5) 4 jenis kegiatan (6) 5 jenis kegiatan (7) 6 jenis kegiatan PENGELOLAAN
3. TiKe Tipe pengelolaan (1) penyu tidak dikelola (2) penyu dikelola pemerintah (3) penyu dikelola pemerintah &
LSM/Swasta
(4) penyu dikelola LSM & Masyarakat
(5) penyu dikelola Masyarakat
VARIABEL LABEL KRITERIA
1. Induk Penangkapan induk
(1) Ada (2) Tidak 2. Telur Eksploitasi telur (1) Ada
(2) Tidak 3. Daging Konsumsi daging
penyu