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All Journal Jurnal Belantara SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal Teknologi Informasi, Komputer, dan Aplikasinya (JTIKA ) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Teknik Silitek
Beni Iskandar
Universitas Muhammadiyah Palangkaraya
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Crown closure segmentation on wetland lowland forest using the mean shift algorithm Beni Iskandar; I Nengah Surati Jaya; Muhammad Buce Saleh
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp965-977

Abstract

The availability of high and very high-resolution imagery is helpful for forest inventory, particularly to measure the stand variables such as canopy dimensions, canopy density, and crown closure. This paper describes the examination of mean shift (MS) algorithm on wetland lowland forest. The study objective was to find the optimal parameters for crown closure segmentation Pleiades-1B and SPOT-6 imageries. The study shows that the segmentation of crown closure with the red band of Pleiades-1B image would be well segmented by using the parameter combination of (hs: 6, hr: 5, M: 33) having overall accuracy of 88.93% and Kappa accuracy of 73.76%, while the red, green, blue (RGB) composite of SPOT-6 image, the optimal parameter combination was (hs:2, hr: 8, M: 11), having overall accuracy of 85.72% and kappa accuracy of 68.33%. The Pleiades-1B image with a spatial resolution of (0.5 m) provides better accuracy than SPOT-5 of (1.5 m) spatial resolution. The differences between single spectral, synthetic, and RGB does not significantly affect the accuracy of segmentation. The study concluded that the segmentation of high and very high-resolution images gives promising results on forest inventory.
PEMBERDAYAAN MASYARAKAT DENGAN BUDIDAYA PAKAN LEBAH DAN PEMANENAN MADU KELULUT Pienyani Rosawanti; Nurul Hidayati; Hariyadi Hariyadi; Nanang Hanafi; Beni Iskandar
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 6, No 3 (2022): September
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v6i3.9633

Abstract

ABSTRAKKegiatan penyediaan  pakan lebah kelulut (Trigona sp) mengandalkan tanaman yang ada di sekitarnya dan pemanenan madu dilakukan teknik konvesional, yang memiliki kekurangan tidak efektif dari segi waktu dan kurang higienis. Pengabdian ini bertujuan mengenalkan jenis-jens tanaman sumber pakan lebah kelulut (Trigona sp) dan melatih teknik budidayanya serta pemanenan madu kelulut yang higienis. Lokasi kegiatan ini di Desa Anjir, Kabupaten Pulang Pisau, Kalimantan Tengah. Metode kegiatan ini terdiri dari (1) persiapan pengadaan bahan tanaman dan media tanam, (2) persiapan bahan dan alat pemanenan madu kelulut modifikasi, dan (3) sosialisasi. Tanaman yang dikembangkan adalah tanaman bunga air mata pengantin karena mudah untuk ditanam dan dipelihara. Alat panen yang diperkenalkan merupakan alat panen modifikasi yang direkatkan dengan botol sebagai wadah untuk menampung madu. Hasil kegiatan ini bahwa terdapat peningkatan pengetahuan dan keterampilan masyarakat pembudidaya lebah madu kelulut melakukan budidaya tanaman bunga air mata pengantin sebagai sumber pakan lebah kelulut dan melakukan kegiatan pemanenan madu kelulut  dengan menggunakan alat panen madu modifikasi, sehingga  terjadi peningkatan kuantitas dan kualitas produk karena proses pemanenan madu kelulut lebih cepat dan higienis dengan menggunakan alat panen madu modifikasi. Pengabdian ini menyimpulkan bahwa meningkat pengetahuan dan keahlian masyarakat dalam penyediaan pakan dan proses panen madu kelulut yang higienis. Kata kunci: kelulut; madu; pakan; panen ABSTRACTThe activity of providing kelulut bee feed (Trigona sp) relies on the surrounding plants and harvesting of honey is carried out by conventional techniques, which have the disadvantage of being ineffective in terms of time and hygiene. This service aims to introduce the types of plants that feed the kelulut bee (Trigona sp) and train cultivation techniques and hygienic harvesting of kelulut honey. The location of this activity is in Anjir Village, Pulang Pisau Regency, Central Kalimantan. The method of this activity consists of (1) preparation of procurement of plant materials and planting media, (2) preparation of materials and tools for harvesting modified kelulut honey, (3) socialization. The plant developed is a bridal tear flower plant because it is easy to plant and maintain. The harvesting tool introduced is a modified harvesting tool that is glued to a bottle as a container to hold honey. The result of this activity is that there is an increase in the knowledge and skills of the kelulut honey bee cultivator community in cultivating bridal tear flower plants as a source of kelulut bee feed and harvesting kelulut honey using modified honey harvesting tools, resulting in an increase in product quantity and quality due to the honey harvesting process. kelulut faster and more hygienic by using a modified honey harvester. This service concludes that the knowledge and expertise of the community increases in the provision of feed and the hygienic harvesting process of kelulut honey. Keywords: feed; harvest;honey; kelulut
ALGORITMA MACHINE LEARNING DETEKSI DEFORESTASI HUTAN HUJAN TROPIS DI KABUPATEN KOTAWARINGIN BARAT Beni Iskandar; Nanang Hanafi
JTIKA (Jurnal Teknik Informatika, Komputer dan Aplikasinya) Vol 4 No 2 (2022): September 2022
Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jtika.v4i2.205

Abstract

Deforestasi hutan hujan tropis sangat ekstensif dan permanen menyebabkan degradasi hilangnya keanekaragaman hayati, penuruan kualitas dan kuantitas air, polusi udara dan emisi CO2. Beberapa dekade terakhir telah berkembang signifikan penerapan ektraksi penutupan lahan pada citra secara otomatis dengan teknik Mechine Learning (ML). Penelitian ini bertujuan menguji kehandalan ML algoritma RF, CART dan SVM untuk deteksi perubahan penutupan lahan dan mengukur deforestasi hutan hujan tropis di Kabupaten Kotawaringin Barat. Penelitian ini menggunakan citra Landsat-7 perekaman tahun 2000 dan citra Senintel-2A perekaman tahun 2021, saluran parameter spektral klasifikasi yang digunakan yaitu biru, merah, hijau, infra merah dekat dan gelombang pendek infra merah 1 dan 2, klasifikasi penutupan lahan menggunakan tiga ML algoritma yaitu RF, CART dan SVM. Hasil penelitian ini menunjukan bahwa penutupan hutan alam mengalami penurunan seluas 180.073 ha dan laju deforestasi 24.975 ha/th atau 1.9 %/th yang terjadi antara tahun 2000 hingga 2021. Algoritma RF menunjukan hasil yang terbaik dengan rerata akurasi OA 95% dan Kappa 94%. Keywords: Deforestasi Hutan Hujan Tropis, Penutupan Lahan, Machine Learning, Random Forest, Classification And Regression Trees, Support Vector Machine
KAJIAN PEMANTAUAN PERUBAHAN PENUTUPAN LAHAN BERBASIS PENGINDERAAN JAUH DI KOTAWARINGIN BARAT Beni Iskandar; Nanang Hanafi; Rifqi Anshari
Jurnal Belantara Vol 5 No 2 (2022)
Publisher : Forestry Study Program University Of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jbl.v5i2.866

Abstract

The first step in monitoring deforestation is to measure and identify land cover changes. Our research uses remote sensing technology, because it has advantages such as: cheap, transparent, fast and has measurable accuracy and temporal analysis. This study aims to identify, measure, and analyze trends in land cover change in 1990-2000, 2000-2012, and 2012-2021. The results showed that there were 18 land cover classes with details of 3 forest classes; and 15 non-forest classes; Forest class decreased throughout 1990 to 2021, the trend of changing forest cover was deforestation into plantations, swamp shrubs, dryland agriculture mixed with shrubs, and swamps. The rate of deforestation in 1990-2000 was 3.07%, deforestation in 2000-2012 was 3.02%, and deforestation in 2012-2021 was 1.02%. The accuracy of land cover classification is 91%. 
IDENTIFIKASI PENUTUPAN LAHAN DAERAH ALIRAN SUNGAI KAPUAS MENGGUNAKAN CITRA SENTINEL-2 Sari Marlina; Beni Iskandar; Suhenra Maulana; Saiful Dahtiar
Jurnal Teknik SILITEK Vol. 4 No. 02 (2024)
Publisher : Fakultas Teknik Universitas Pasifik Morotai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51135/jts.v4i02.170

Abstract

Pemantauan hutan dalam ekosistem DAS Kapuas harus dilakukan secara berkelanjutan untuk mendukung tercapainya pengelolaan DAS secara optimal dan lestari. Penelitian ini bertujuan mengidentifikasi penutupan lahan DAS Kapuas menggunakan citra Sentinel-2. Penelitian ini menggunakan algoritma Random Forest (RF) untuk mengklasifikasikan penutupan lahan DAS Kapuas pada citra Sentinel-2 perekaman tahun 2022. Hasil penelitian ini menunjukan bahwa karakteristik reflektan penutupan lahan DAS Kapuas kecenderuangan dengan nilai rerata reflektan sinar tidak tampak lebih tinggi daripada sinar tampak rerata selisih sebesar (0,07%), klasifikasi penutupan lahan DAS Kapuas terdiri dari hutan alam (677.66 ha), hutan tanaman (37.01 ha), semak/belukar (388.04 ha), tanah/lahan terbuka (11.40 ha), pertambangan (23.82 ha), pertanian (294.01 ha), perkebunan (43.28 ha), permukiman (26.12 ha), tubuh air (40.91 ha), dan awan (82.77 ha), serta akurasi klasifikasi penutupan lahan untuk akurasi keseluruhan 93.88% dan akurasi kappa 92.8%, dengan demikian identifikasi penutupan lahan menggunakan citra Sentinel-2 dapat menjadi salah satu informasi dasar untuk mendukung pengelolaan hutan di DAS Kapuas.
Co-Authors Hariyadi Hariyadi I Nengah Surati Jaya Muhammad Buce Saleh Nanang Hanafi Nurul Hidayati Pienyani Rosawanti Rifqi Anshari Saiful Dahtiar Sari Marlina Suhenra Maulana