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AGGREGATION METHODS FOR ASSESING THE SUSTAINABILITY OF FOREST MANAGEMENT Kuswandari, Retno; Sharifi, M. Ali; Saleh, M. Buce
Jurnal Manajemen Hutan Tropika Vol. 12 No. 2 (2006)
Publisher : Institut Pertanian Bogor (IPB University)

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Abstract

Kelestarian pengelolaan hutan merupakan konsep yang samar dan kompleks, oleh karena itu tidak ada satupun alat ukur yang dapat mengukurnya secara jelas. Sertifikasi hutan digunakan sebagai instrumen untuk mengukur kelestarian pengelolaan hutan yang didasarkan atas kelestarianproduksi, ekologi dan sosial. Kriteria dan Indikator (C & I) untuk kelestarian hutan alam produksi dalam sistem sertifikasi di Indonesia (Lembaga Ekolabel Indonesia) menggunakan Analytical Hierarchy Process (AHP) sebagai alat dalam proses pengambilan keputusannya. AHP telah lama dikritisi, antara lain karena pendekatan kompensatori menggunakan modellinier additive utilitas untuk mengintegrasikan -nilai baku. Riset ini bertujuan untuk menganalisa beberapa metoda aggregasi nilai baku sebagai alternatif untuk menilai kelestarian pengelolaan hutan. Fuzzy AHP dan Rule Base (Fuzzy Reasoning Method) dipelajari sebagai metode untuk mengatasi kekurangmampuan AHP dalam menangani secara tepat peubah-peubah linguistik. Data hasil proses penilaian sertifikasi Unit Pengelolaan Hutan Labanan, Kalimantan Timur,Indonesia digunakan untuk menilai kelestarian pengelolaan hutan dengan tiga metode tersebut. Hasil Fuzzy AHP dibanding dengan Normal AHP menunjukkan hasil yeng lebih jelas dan sudah menampung ketidakpastian justifikasi ekspert yang tidak terdapat dalam Normal AHP. Metode Rule Base, yang sangat tergantung kepada pengetahuan dan pengalaman ekspertnya, memberikan hasil yang lebih berarti dan transparan dalam proses penilaian dibanding kedua metode lainnya, yaitu Normal AHP dan Fuzzy AHP.Keywords:  SFM assessment, forest certification, fuzzy decision making, AHP, Fuzzy AHP, Fuzzy Rule Base
STUDY OF LAND COVER CHANGE USING MULTI LAYER PERCEPTRON AND LOGISTIC REGRESSION METHODS IN GUNUNG CIREMAI NATIONAL PARK Darmawan, Agus Rudi; Puspaningsih, Nining; Saleh, M. Buce
Media Konservasi Vol 22 No 3 (2017): Media Konservasi Vol. 22 No. 3 Desember 2017
Publisher : Deparement of Forest Resources Conservation and Ecotourism - Bogor Agricultural University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (644.283 KB) | DOI: 10.29244/medkon.22.3.252-261

Abstract

The development of land cover change is important to understand, so that the pattern of future land cover changes can be predicted and its negative impacts can be prevented or reduced. Various modeling approaches have been widely used to analyze land cover changes. The common modeling methods used for analyzing land cover changes are Multi-layer Perceptron (MLP) and Logistic Regression (Logit). This research is designed to assess the accuracy of modeling of land cover change with MLP and Logit methods in Gunung Ciremai National Park. The result indicated that the accuracy of both methods was very good with kappa values were 0,8991 and 0,8989 for MLP and Logit respectively. Therefore, the model can be applied to predict land cover change in Gunung Ciremai National Park in the future. Keywords: Gunung Ciremai National Park, land cover change, Logistic Regression, Multi-layer Perceptron
PRACTICAL TECHNIQUE FOR DETECTING MANGROVE VEGETATION USING DIGITAL MOS MESSR AND LANDSAT-5 TM IMAGES: A CASE STUDY IN KARAWANG CAPE, WEST JAVA Jaya, I Nengah Surati; Saleh, M. Buce; Ismail, Rudi Ichsan; Nurwanto, Hendri; Kusmana, Cecep; Abe, Nobuyuki
Jurnal Manajemen Hutan Tropika Vol. 7 No. 1 (2001)
Publisher : Institut Pertanian Bogor (IPB University)

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Abstract

Studi ini menerangkan bagaimana algoritme-algoritme indeks separabilitas dan akurasi klasifikasi seyogyanya diterapkan secara benar untuk mendeteksi obyek-obyek yang dikehendaki secara optimal. Studi ini menemukan bahwa akurasi Kappa dan kriteria Separabilitas (Transformed Divergence) harus digunakan secara simultan. Evaluasi dengan hanya menggunakan akurasi Kappa saja atau separabilitas saja akan memberikan hasil yang keliru. Algoritme-algoritme yang diterapkan diujicobakan pada data dijital MOS MESSR (Marine Observation Satellite Multispectral Self-Scanning Radiometer) dan Landsat TM (Thematic Mapper) untuk mendeteksi distribusi vegetasi mangrove. Studi ini memperlihatkan bahwa algoritme-algoritme yang diujicobakan pada MESSR dan TM berhasil mendeteksi distribusi mangrove secara baik, dengan akurasi pengguna (user accuracy) dan akurasi pembuat (producer?s accuracy) yang cukup tinggi berkisar antara 55% dan 100%.
KAJIAN METODE DETEKSI DEGRADASI HUTAN MENGGUNAKAN CITRA SATELIT LANDSAT DI HUTAN LAHAN KERING TAMAN NASIONAL HALIMUN SALAK Nugroho, Sigit; Jaya, I Nengah Surati; Saleh, M. Buce; Wijanarto, Antonius B
Jurnal Teknosains Vol. 1 No. 1 tahun 2011
Publisher : Sekolah Pascasarjana UGM

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Abstract

The study examined detection method of forest degradation using forest canopy density (FCD), maximum likelihood, fuzzy and belief dempster shafer classification method. Accuracy evaluation of classification and detection were based on overall accuracy which obtained from 51 ground sample plot. Canopy density, LAI, crown indicator, trees density and basal area (Lbds) were conducted   as field indicators. Accuracy of classification among forest density (trees/Ha) with four classification methods were FCD 61%, maximum likelihood 57%, fuzzy 51% and belief dempster shafer 49%. Based on temporal detection accuracy from 2003 until 2008, FCD had overall accuracy 68 %.  The result of research, FCD  is  the best method to detect of forest degradation.    
KAJIAN METODE DETEKSI DEGRADASI HUTAN MENGGUNAKAN CITRA SATELIT LANDSAT DI HUTAN LAHAN KERING TAMAN NASIONAL HALIMUN SALAK Nugroho, Sigit; Jaya, I Nengah Surati; Saleh, M. Buce; Wijanarto, Antonius B
Jurnal Teknosains Vol 1, No 1 (2011): December
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (534.537 KB) | DOI: 10.22146/teknosains.3988

Abstract

The study examined detection method of forest degradation using forest canopy density (FCD), maximum likelihood, fuzzy and belief dempster shafer classification method. Accuracy evaluation of classification and detection were based on overall accuracy which obtained from 51 ground sample plot. Canopy density, LAI, crown indicator, trees density and basal area (Lbds) were conducted   as field indicators. Accuracy of classification among forest density (trees/Ha) with four classification methods were FCD 61%, maximum likelihood 57%, fuzzy 51% and belief dempster shafer 49%. Based on temporal detection accuracy from 2003 until 2008, FCD had overall accuracy 68 %.  The result of research, FCD  is  the best method to detect of forest degradation.    
Algorithm for detecting deforestation and forest degradation using vegetation indices Saleh, M. Buce; Jaya, I Nengah Surati; Santi, Nitya Ade; Sutrisno, Dewayany; Carolita, Ita; Yuxing, Zhang; Xuenjun, Wang; Qian, Liu
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 5: October 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (473.586 KB) | DOI: 10.12928/telkomnika.v17i5.12585

Abstract

In forestry sector, the remote sensing technology hold a key role on forest inventory and monitoring their changes. This paper describes the algorithm for detecting deforestation and forest degradation using high resolution satellite imageries with knowledge-based approach. The main objective of the study is to develop a practical technique for monitoring deforestation and forest degradation occurred within the mangrove and swamp forest ecosystem.  The SPOT 4, 5, and 6 images acquired in 2007, 2012 and 2014 were transformed into three vegetation indices, i.e., Normalized Difference Vegetation Index (NDVI), Green-Normalized Difference Vegetation index (GNDVI) and Normalized Green-Red Vegetation index (NRGI).  The study found that deforestation was well detected and identified using the NDVI and GNDVI, however the forest degradation could be well detected using NRGI, better than NDVI and GNDVI.  The study concludes that the strategy for monitoring deforestation, biomass-based forest degradation as well as forest growth could be done by combining the use of NDVI, GNDVI and NRGI respectively.
ANALISIS KELEMBAGAAN DAN PERANAN KESATUAN PENGELOLAAN HUTAN PRODUKSI (KPHP) DALAM PENGEMBANGAN WILAYAH KABUPATEN KERINCI Lestaria, Mika; Hadi, Setia; Saleh, M. Buce
Jurnal Kawistara Vol 6, No 1 (2016)
Publisher : Sekolah Pascasarjana UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (603.139 KB) | DOI: 10.22146/kawistara.15482

Abstract

Kerinci is one of regency with the large forest, but sub sector of forestry contributes only 0,04% of GDP Kerinci Regency. It’s may possibly by the weakness of forest management and policy of Kerinci Regency Government. Forest production management unit (KPHP) Model Kerinci establishment is one of goverment efforts to achieve sustainable forest management. Therefore, we need research with purpose: (1) to analyze the role of forest production management unit (KPHP) Model Kerinci in the regional development of Kerinci Regency; (2) to analyze the institutional of forest production management unit (KPHP) Model Kerinci; (3) to analyze region’s readiness forest production management unit (KPHP) Model Kerinci development. The study was conducted in Kerinci Regency. Data were analyzed by total economic value (TEV), institutional analysis, and analytical hierarchy process (AHP). The results showed that the total economic value of natural resources of KPHP Model Kerinci is Rp. 337.839.832.400 in a year, it’s mean that sub sector of forestry potentially to contribute about 8,38% of GDP Kerinci Regency. To realize the total economic values of natural resources of KPHP Model Kerinci, it needs strong institutions. Kerinci Regency is ready for KPHP Model Kerinci development, because it’s has the support from stakeholders.