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All Journal MANAJEMEN HUTAN TROPIKA Journal of Tropical Forest Management Jurnal Ilmu Pertanian Indonesia Jurnal Silvikultur Tropika (JST) MEDIA KONSERVASI Indonesian Journal of Geography Journal of Tropical Soils TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Teknosains Jurnal Kawistara : Jurnal Ilmiah Sosial dan Humaniora Jurnal Penelitian Hutan dan Konservasi Alam Jurnal Penelitian Hutan Tanaman BioWallacea Journal of Biological Research MAJALAH ILMIAH GLOBE Jurnal Penelitian Sosial dan Ekonomi Kehutanan Jurnal Penelitian Pengelolaan Daerah Aliran Sungai JURNAL METEOROLOGI DAN GEOFISIKA Indonesian Journal of Electrical Engineering and Computer Science Jurnal Sylva Lestari Jurnal Ilmu-Ilmu Kehutanan Aceh International Journal of Science and Technology Jurnal Penelitian Kehutanan Wallacea Jurnal Kawistara

Muhammad Buce Saleh

Departement Of Forest Management, Faculty Of Forestry And Environment, IPB University, Academic Ring Road, Campus IPB Dramaga, Bogor, Indonesia 16680

Author-ID : 369156

Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Physics Social Sciences Veterinary

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Algorithm for detecting deforestation and forest degradation using vegetation indices M. Buce Saleh; I Nengah Surati Jaya; Nitya Ade Santi; Dewayany Sutrisno; Ita Carolita; Zhang Yuxing; Wang Xuenjun; Liu Qian
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 | DOI: 10.12928/telkomnika.v17i5.12585

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.

Biomass estimation model for peat swamp forest ecosystem using light detection and ranging Muhamad Rizal; M. Buce Saleh; Lilik Budi Prasetyo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 3: June 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i3.18152

Peat swamp forest plays a very important role in absorbing and storing large amounts of terrestrial carbon, both above ground and in the soil. There has been a lot of research on the estimation of the amount of biomass above the ground, but a little on peat swamp ecosystems using light detection and ranging (LiDAR) technology, especially in Indonesia. The purpose of this study is to build a biomass estimation model based on LiDAR data. This technology can obtain information about the structure and characteristics of any vegetation in detail and in real time. Data was obtained from the East Kotawaringin Regency, Central Kalimantan. Biomass field was generated from the available allometry, and Point cloud of LiDAR was extracted into canopy cover (CC), and data on tree height, using the FRCI and local maxima (LM) method, respectively. The CC and tree height data were then used as independent variables in building the regression model. The best-fitted model was obtained after the scoring and ranking of several regression forms such as linear, quadratic, power, exponential and logarithmic. This research concluded that the quadratic regression model, with R2 of 72.16 % and root mean square error (RMSE) of 0.0003% is the best-fitted estimation model (BK). Finally, the biomass value from the models was 244.510 tons/ha.

ANALISIS KELEMBAGAAN DAN PERANAN KESATUAN PENGELOLAAN HUTAN PRODUKSI (KPHP) DALAM PENGEMBANGAN WILAYAH KABUPATEN KERINCI Mika Lestaria; Setia Hadi; M. Buce Saleh
Jurnal Kawistara Vol 6, No 1 (2016)
Publisher : Universitas Gadjah Mada

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.

Study of Land Cover Change using Multi Layer Perceptron and Logistic Regression Methods in Gunung Ciremai National Park Agus Rudi Darmawan; Nining Puspaningsih; M. Buce Saleh
Media Konservasi Vol 22 No 3 (2017): Media Konservasi Vol. 22 No. 3 Desember 2017
Publisher : Department of Forest Resources Conservation and Ecotourism - IPB University

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

EVALUASI PENGGUNAAN BEBERAPA METODE PENDUGA BIOMASSA PADA JENIS Acacia mangium Wild Muhammad Abdul Qirom; M. Buce Saleh2; Budi Kuncahyo
Jurnal Penelitian Hutan dan Konservasi Alam Vol 9, No 3 (2012): Jurnal Penelitian Hutan dan Konservasi Alam
Publisher : Pusat Penelitian dan Pengembangan Hutan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20886/jphka.2012.9.3.251-263

Metode pengukuran biomasa sangatlah beragam dengan akurasi dan ketepatan yang berbeda-beda. Keakuratan dan ketepatan metode pengukuran tersebut perlu dibandingkan untuk mendapatkan metode terbaik. Tujuan penelitian ini adalah 1) mendapatkan besarnya alokasi biomasa masing-masing bagian tanaman, 2) mendapatkan nilai Biomass Expansion Factor (BEF) dan Root to Shoot Ratio (R) jenis Acacia mangium Willd., 3) mendapatkan persamaan alometrik biomasa masing-masing bagian tanaman, 4) mendapatkan metode terbaik untuk menduga biomasa di hutan tanaman Acacia mangium Wild. di Kalimantan Selatan. Pengambilan sampel pohon dilakukan secara destructive sebanyak 30 pohon contoh yang mewakili umur satu, dua, tiga, empat, lima, enam, delapan, dan sembilan tahun. Berdasarkan pohon contoh tersebut didapatkan data biomasa, Biomass Expansion Factor dan Root to Shoot Ratio (R). Penyusunan model alometrik menggunakan model linear dan non linear. Hasil penelitian menunjukkan alokasi biomasa terbesar pada bagian batang (> 50%) dan ranting menyimpan biomasa terkecil Pada umur 1-9 tahun, besarnya BEF (Mg.m-3) berkisar antara 0,44-0,71 Mg.m-3 dan nilai BEF (Mg.) jenis Acacia mangiumWild. berkisar antara 1,06-1,80. Rata-rata nilai R yakni 0,16. Pada bagian permukan tanah model alometrik terbaik yakni AGB = - 3.14 + 2.84 lnD dengan koefisien determinasi R2 98,6%. Metode penduga biomase terbaik menggunakan BEF (Mg.Mg) per umur. Penggunaan metode ini membutuhkan persamaan alometrik penduga biomassa batang.

APLIKASI CITRA ALOS PALSAR UNTUK PENDUGAAN SIMPANAN KARBON DI HUTAN TANAMAN AKASIA Muhammad Abdul Qirom; Muhammad Buce Saleh; Budi Kuncahyo
Jurnal Penelitian Hutan Tanaman Vol 9, No 3 (2012): JURNAL PENELITIAN HUTAN TANAMAN
Publisher : Pusat Penelitian dan Pengembangan Hutan

Pendugaan persediaan karbon secara langsung mempunyai keterbatasan terkait dengan kecepatan memperoleh hasil, cakupan luasan yang terbatas dan biaya yang mahal. Penginderaan jarak jauh dapat dimanfaatkan untuk menduga persediaan karbon dengan akurasi yang cukup memadai. Tujuan penelitian ini yakni: 1) mendapatkan potensi simpanan karbon jenis A. mangium, 2) mendapatkan model penduga simpanan karbon berdasarkan citra Radar (nilai backscatter citra Alos Palsar), 3) mendapatkan peta sebaran potensi simpanan karbon jenis A. mangium di PT. Inhutani II, Kalimantan Selatan. Metode yang digunakan dengan melakukan inventarisasi persediaan karbon secara langsung yakni pembuatan plot pengukuran sebanyak 69 plot dengan luas masing-masing plot seluas 0,1 Ha tersebar pada beberapa umur. Hasil inventarisasi tersebut digunakan untuk membentuk hubungan dengan nilai polarisasi dari citra Alos Palsar. Hasil penelitian menunjukkan potensi simpanan karbon permukaan sebesar 32,03 - 46,10 ton/ha dengan rata-rata 39,06 ton/ha. Potensi simpanan karbon total per Ha berkisar antara 35,48 -51,01 ton/ha dengan rata-rata 43,24 ton/ha. Model alometrik terbaik hubungan antara simpanan karbon dan nilai polarisasi HH dan HV dari citra Alos Palsar adalah Simpanan karbon = 292 + 2,00 HH2 + 27,1 HV dengan koefisien determinasi sebesar 40,9%. Potensi sebaran simpanan karbon total terbesar berdasarkan aplikasi citra Alos Palsar yakni berkisar antara 40 - 80 ton/Ha. Penggunaan Alos Palsar untuk menduga simpanan karbon menghasilkan dugaan yang cukup akurat sehingga teknologi ini dapat digunakan untuk mengukur atau monitoring persediaan karbon pada tegakan hutan tanaman.

PENENTUAN JENIS TUMBUHAN LOKAL DALAM UPAYA MITIGASI LONGSOR DAN TEKNIK BUDIDAYANYA PADA AREAL RAWAN LONGSOR DI KPH LAWU DS: Studi Kasus di RPH Cepoko Determination of Local Plants Species in Mitigation Effort at Areas Prone and Cultivation Techniques .... Fibo Adhitya; Omo Rusdiana; Muhammad Buce Saleh
Jurnal Silvikultur Tropika Vol. 8 No. 1 (2017): Jurnal Silvikultur Tropika
Publisher : Departemen Silvikultur, Fakultas Kehutanan dan Lingkungan, Institut Pertanian Bogor (IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j-siltrop.8.1.9-19

Natural disasters that occur in most areas of Indonesia would certainly give rise to a wide range of impacts on the physical, social, and economic life of the society. One of these natural disasters is landslides. KPH Lawu Ds is a owned company Perhutani, which produces pine resin. KPH area Lawu Ds are generally located in areas that have a steep slope has an area prone to landslides are quite extensive. Therefore, in carrying out forest cultivation of plants which are generally homogenous need additional types of vegetation can reduce the level of vulnerability to landslides. Landslides can also be regarded as a form of land use that have little or no attention to soil conservation techniques, but in this study only look from the vegetation in developing soil conservation techniques in homogeneous plantation forests in the forest management unit areas KPH Lawu Ds. Therefore, the purpose of this study was to obtain the right local plant species as the plant are prioritized and appropriate to prevent the occurrence of landslides and obtain the shape and pattern of cultivation. Data analysis using descriptive analysis of qualitative and models that fit the preferences of local preferences of plants grown on land prone to landslides in RPH Cepoko by using the method of AHP (Analytical Hierarchy Process). Alternatives are obtained based on the plants prioritized is clove, coffee, chocolate, calliandra, Leucaena leucocephala, durian, Swietenia macrophylla, Aleuriteus Moluccana, Paraserianthes falcataria, Pangium edule, Anacardium occidentale , and Sterculia foetida and cultivation techniques of forest vegetation on the sides of the plant adjusted based onsolum soil, slope and vegetation cover of pine with dense composition, middle and rare on research plots in the area of KPH Lawu Ds and planting distance is determined by the density of the canopy.Key words: mitigation, native plant species, preference, cultivation techniques.

TIPE KOMUNITAS HUTAN LAHAN KERING DI HUTAN LINDUNG SENTAJO, KABUPATEN KUANTAN SINGINGI, RIAU Community Types of Dryland Forest Within The Sentajo Protected Forest, Kuantan Singingi Regency, Riau Province Pebriandi .; Omo Rusdiana; Muhammad Buce Saleh
Jurnal Silvikultur Tropika Vol. 8 No. 2 (2017): Jurnal Silvikultur Tropika
Publisher : Departemen Silvikultur, Fakultas Kehutanan dan Lingkungan, Institut Pertanian Bogor (IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j-siltrop.8.2.103-109

Sentajo Protected Forest located in Kuantan Singingi Regency, Riau Province. There is no information about vegetation diversity in this location. Therefore this study was conducted. This study aimed to determine the diversity of vegetation, structure, and composition of each community in Sentajo Protected Forest. The study was conducted in April-September 2016. A sampling design was determined using systematic sampling with random start. The sampling intensity used was 5%. The parameters measured in this study were the importance value index, similarity index between communities, species diversity index, evenness index, dominance index, regeneration, as well as horizontal and vertical structures. Based on the type of soil, elevation, and slope, 6 communities were grouped from the dense coverage area (forested). The results showed that the Sentajo Protected Forest had 424 flora consisted of 254 species, and 102 families. Sentajo Protected Forest had similarity index between 18 - 64%, species diversity index of 2.62 - 4.15, evenness index of 0.59 - 0.86, dominance index of 0.02 - 0.08. The larger the diameter of the tree, the smaller the number of individuals. The stratification of the canopy had 5 layers of canopy. Sentajo Protected Forest regeneration was relatively good as the number of seedlings> saplings> mature trees.Key words: community, composition and structure, diversity, Sentajo Protected Forest.

Ecosystem Services Dynamics in Bogor Regency Sri Lestari Munajati; Hariadi Kartodihardjo; Muhammad Buce Saleh; Nurwadjedi Nurwadjedi
Indonesian Journal of Geography Vol 53, No 2 (2021): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijg.64493

The decline in the quality of ecosystem services in Bogor Regency is indicated by the existence of various natural disasters in recent years. Prudent development must be carried out to minimize the impact of a decrease in the ecosystem services index. The purpose of this research is to map ecosystem services for food supply, water supply, water and flood management, and tourism aspects within 2000-2017. The data used were land cover and land facet maps at a scale of 1:25,000 obtained from BIG, accompanied by a reinterpretation process. The data sources were Indonesia's topographic maps (RBI), Citra SPOT 7, DEMNAS, and field surveys. The ecosystem services index (ESI) is calculated based on an analysis of changes in land use and land facets. The value of ESI was weighted using analytic hierarchy process approaches to each of the variables assessed by experts. The results showed that the largest changes in land use occurred in residential and forest areas. The residential area increased by 1.96%, while the forest area decreased by 1.8% in 17 years. Bogor Regency is dominated by forest and rice fields which are spread over four main landforms, namely volcanic, structural, fluvial, and karst. The most significant increase of 5.65% was found in the clean water provisioning function, while the most significant decrease of 38.47% was found in the tourism and ecotourism sector. Accumulatively, the increase in ESI was 23%, while the decrease was 20.64%. Mitigation efforts that can be done are to maintain the availability of green open space by implementing strong regulations.

KAJIAN METODE DETEKSI DEGRADASI HUTAN MENGGUNAKAN CITRA SATELIT LANDSAT DI HUTAN LAHAN KERING TAMAN NASIONAL HALIMUN SALAK Sigit Nugroho; I Nengah Surati Jaya; M. Buce Saleh; Antonius B Wijanarto
Jurnal Teknosains Vol 1, No 1 (2011): December
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/teknosains.3988

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.

Co-Authors . Asisah . HIKMATULLAH . Hikmatullah Afandi Ahmad Afandi Ahmad Agus Rudi Darmawan Ahsana Riska Ahyar Gunawan Andrie Ridzki Prasetyo Antonius B Wijanarto Antonius Bambang Wijanarto Anugrah Andini Natsir Arif Kurnia Wijayanto Asisah, . Bahruni . Beni Iskandar Bramasto Nugroho Budi Kuncahyo Budi Kuncahyo Dahlan Dahlan Dahlan Dahlan Dede Kosasih Deki Zulkarnain Dewayany Sutrisno Dewayany Sutrisno Dwi Noventasari Eva Achmad Faid Abdul Manan Fibo Adhitya Hanifah Ikhsani Hardian, Dwika Hasriani Muis Hendrayanto . Hendri Nurwanto I Gusti Bagus Wiksuana I Nengah Surati Jaya Ibnu Sofian, Ibnu Irlan Ita Carolita Kartodihardjo, Hariadi Kukuh Murtilakono LILIK BUDIPRASETYO Liu Qian Liu Qian M. Akbar AS, M. Akbar M. Ali Sharifi Malta Daerangga Mika Lestaria Muhamad Rizal Muhammad Abdul Qirom Muhammad Abdul Qirom Muzailin Affan Muzailin Affan Nanin Anggraini Nining Puspaningsih Nitya Ade Santi Nitya Ade Santi Nitya Ade Santi Nobuyuki Abe Nunung Parlinah Nunung Parlinah Nurdin, Nurjannah Nurdiyanto Agung Prasetya Nurwadjedi Nurwadjedi Omo Rusdiana Pebriandi, Pebriandi Prasetya, Nurdiyanto Agung Putu Ananta Wijaya Retno Kuswandari Ricca Rohani Hutauruk Rosima Wati Dewi Rudi Ichsan Ismail Sahid Hudjimartsu Setia Hadi Sigit Nugroho Soedomo, Sudarsono Sri Lestari Munajati Suria Darma Tarigan Syamsu Rijal Tatang Tiryana Teddy Rusolono Umara Firman Rizidansyah Uus Saepul Mukarom Wang Xuenjun Wang Xuenjun Yudi Armanda Syahputra Yudi Setiawan Yudi Setiawan Zhang Yuxing Zulkarnain

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