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All Journal JTSL (Jurnal Tanah dan Sumberdaya Lahan) Jurnal Wilayah dan Lingkungan Journal of Electrical Engineering and Computer (JEECOM) Proceeding ISETH (International Summit on Science, Technology, and Humanity) International Journal for Disaster and Development Interface
Sandy Budi Wibowo
FAKULTAS PERTANIAN UNIVERSITAS BRAWIJAYA
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Medicine & Pharmacology Social Sciences Other

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ANALISIS JENIS BUDIDAYA TEBU MENGGUNAKAN ALGORITMA RANDOM FOREST (STUDI KASUS KECAMATAN TAJINAN, KABUPATEN MALANG) Nurhadi, Muhammad; Widayani, Prima; Wibowo, Sandy Budi
Jurnal Tanah dan Sumberdaya Lahan Vol. 12 No. 2 (2025)
Publisher : Departemen Tanah, Fakultas Pertanian, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jtsl.2025.012.2.6

Abstract

Indonesia's national sugar demand continues to increase, while domestic production is still limited due to the lack of accurate data on the area and type of sugarcane cultivation. To address this issue, this research utilized the Random Forest (RF) algorithm on PlanetScope satellite imagery to classify the types of sugarcane cultivation, i.e. early planted sugarcane and pressed sugarcane. This study offers a more detailed approach than previous studies by dividing sugarcane based on its growth cycle into two main classes: < 3 times and ≥ 3 times. The results showed that the Random Forest (RF) method was able to increase the mapping accuracy to 94.52%, higher than conventional methods which are generally in the range of 85-91%. Of the three classification schemes tested, Scheme 3 produced the best performance with an accuracy of 94.52% and a Kappa coefficient of 43.87%. The mapping results also revealed that sugarcane cultivation of ≥ 3 squeezes dominated the study area with 93.08% coverage of the total sugarcane land, while sugarcane of < 3 squeezes only covered 7.55%. The difference between the classification results and the field data shows that the imbalance in the number of samples and spectral similarity between classes are the main challenges in mapping sugarcane cultivation. This finding proves that the Random Forest algorithm with PlanetScope images can significantly improve the accuracy of sugarcane cultivation type mapping compared to previous methods. The results of this study make an important contribution in providing more accurate spatial data to support sugarcane production estimation, optimization of plantation management, and strategic planning in achieving national sugar self-sufficiency.
Estimasi Ukuran Butir Pasir Menggunakan Citra Sentinel-2 pada Sungai Rejali, Kabupaten Lumajang Fathoni, Mohammad Naufal; Hadmoko, Danang Sri; Wibowo, Sandy Budi
Journal of Electrical Engineering and Computer (JEECOM) Vol 5, No 2 (2023)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v5i2.6568

Abstract

Lahar hujan merupakan suatu fenomena kebencanaan yang mengancam daerah sekitar gunungapi, namun juga memiliki dampak positif berupa potensi pertambangan yang besar. Berdasarkan hal tersebut perlu adanya pengelolaan dan perencanaan, didukung oleh informasi spasial yang memadai salah satunya adalah ukuran butir. Berkembangnya produk penginderaan jauh dan sistem informasi geografi dapat digunakan sebagai penyedia data spasial ukuran butir. Fokus penelitian ini adalah pemanfaatan Citra Sentinel-2 melalui indeks ukuran butir untuk mengestimasi ukuran butir menggunakan pendekatan empiris. Tahap penelitian terdiri dari pra-pemrosesan citra, pengambilan ukuran butir lapangan, analisis laboratorium, pemodelan empiris, dan identifikasi sebaran ukuran butir. Hasil penelitian menunjukkan indeks ukuran butir berkorelasi terhadap ukuran butir dan dapat digunakan sebagai variabel pemodelan. Ukuran butir pada lokasi penelitian berkisar antara -0.050 Φ sampai 11.828 Φ. Nilai validitas tergolong baik dikarenakan model memiliki nilai kesalahan estimasi yang setara dengan satu kelas ukuran butir. Distribusi ukuran butir menunjukkan semakin jauh transportasi material diiringi dengan semakin kecilnya ukuran butir.
Pengembangan Metode Penentuan Kawasan Relokasi Akibat Bencana Awan Panas Guguran. Studi Kasus : Erupsi Semeru 4 Desember 2021 Setiawan, Muhammad Anggri; Rhosadi, Iwan; Kafafa, Utia; Laksana, Agung; Farda, Nur Muhammad; Wibowo, Sandy Budi; Palembang, Muhammad Fikram
Jurnal Wilayah dan Lingkungan Vol 12, No 1 (2024): April 2024
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jwl.12.1.53-70

Abstract

Kawasan permukiman yang terletak di zona rawan bencana gunungapi sudah seharusnya memiliki rencana antisipasi berupa kajian relokasi akibat dampak bencana. Penentuan kawasan relokasi seringkali dilakukan pada situasi pasca tanggap darurat bencana sehingga cenderung tergesa-gesa, rawan konflik kepentingan atau bahkan dapat memunculkan permasalahan baru yang rumit. Penelitian ini bertujuan untuk mengembangkan metode penentuan kawasan relokasi bagi permukiman terdampak berdasarkan pada bencana letusan gunungapi Semeru dengan tipe awan panas guguran tahun 2021.  Pengembangan metode dilakukan dengan menggabungkan tiga skenario model SMCE (Spatial Multi Criteria Evaluation) dan Network Analysis secara berjenjang. Kerangka utama dalam pengembangan metode ini adalah mencari lokasi aman multi-ancaman namun tetap memiliki daya dukung dan daya tampung yang baik, serta tidak terlalu jauh dengan lokasi desa yang menjadi sumber penghidupan mereka. Secara sosiologis dan ketentuan peraturan, masyarakat akan diperbolehkan memanfaatkan kembali lahan milik mereka untuk aktivitas non-permukiman (seperti perkebunan dan pertanian) ketika status ancaman Gunungapi Semeru kembali normal. Wilayah administrasi desa digunakan sebagai satuan analisis kesesuaian lokasi. Setelah muncul beberapa pilihan lokasi desa yang sesuai dengan kriteria-kriteria yang ditentukan dalam skenario SMCE, maka analisis jaringan jalan terdekat dilakukan untuk memilih desa yang paling dekat dengan kawasan yang terdampak. Penelitian ini berhasil mengidentifikasi secara obyektif bahwa Desa Penanggal, Kecamatan Pronojiwo sebagai tempat yang paling sesuai untuk relokasi kawasan permukiman akibat guguran awan panas Gunungapi Semeru. Metode ini perlu dimanfaatkan oleh pemangku kebijakan untuk mempercepat pengambilan keputusan yang tepat dan menjadi investasi yang berkelanjutan dalam pengurangan risiko bencana.
Reducing Greenhouse Gasses Emission from Energy Consumption in Floating Net Cage Aquaculture (FNCA) Nurani, Idea Wening; Sunardi, S; Muta'ali, Lutfi; Mei, Estuning Tyas Wulan; Wibowo, Sandy Budi; Fajarwati, Alia; Ridwan, Briantama Yanuar; Maharani, Nooriza; Pradipta, Aditya
Proceeding ISETH (International Summit on Science, Technology, and Humanity) 2019: Proceeding ISETH (International Summit on Science, Technology, and Humanity)
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/iseth.1521

Abstract

Every sector including aquaculture should be prepared to cope with climate change impacts. Climate change impacts to aquaculture can bring any change to instability of socio-economy and the environment due to its role to support food security, employment and economic growth. Management of aquaculture needs to be modified to face this challenge, not only adaptation efforts but also mitigation efforts. Energy consumption is one of significant source of Green House Gasses (GHG) emission. Therefore, it is necessary to know the detail of energy consumption in aquaculture to find the proper strategy in reducing GHG emission from its operational. This study aimed: (1) to identify sort of energy source used in FNCA; (2) to identify the factors that influences the energy consumption of FNCA. This research was conducted in Cirata Reservoir, West Java Province, Indonesia. This research was conducted in Cirata Reservoir, West Java Province. Quatitative method was applied in this research. The research methodology involved: (1) in depht interview, (2) analysis of existing data through institutional reports and (3) observation. This study showed that: (1) farmers of FNCA in Cirata reservoir consume renewable and non-renewable energy for their daily activities; (2) factors that influence the energy consumption in FNCA are location, operational pattern, number of dwellers, types of boat and electricity sources.
Land Cover Change Dynamics And Potential Acid Sulfate Soil Formation in Segara Anakan Wahyu, Hyundra Zakiya Putri; Widyatmanti, Wirastuti; Wibowo, Sandy Budi
International Journal for Disaster and Development Interface Vol. 5 No. 2 (2025): October 2025
Publisher : Amcolabora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53824/ijddi.v5i2.111

Abstract

Tropical coastal regions are highly susceptible to acid sulfate soi formation due to ecological and hydrological changes driven by land cover dynamics and sedimentation. This study analyzes land cover changes from 1990 to 2025 and their implications for ASS development in Segara Anakan, Indonesia. Landsat imagery (Landsat 5 and Landsat 8/9 OLI) was classified using Random Forest and Gradient Boosting Tree algorithms within Google Earth Engine. Classification accuracy was assessed using overall accuracy and the Kappa coefficient. Land cover classes included mangrove, nipa palm, paddy fields, aquaculture ponds, settlements, bare land, water bodies, and forest. Results reveal substantial conversion of natural vegetation into paddy fields, bare land, and settlements, particularly in low-lying tidal areas. These changes disrupted ecological conditions that previously sustained organic matter accumulation, low-energy environments, and anaerobic waterlogging—three of the five key factors for ASS formation. Field validation confirmed soil pH < 4 in high-risk areas. This research demonstrates the effectiveness of integrating multi-temporal Landsat imagery with machine learning to detect spatio-temporal land cover dynamics and to identify areas prone to ASS formation, offering valuable insights for adaptive coastal management.
Co-Authors Aditya Pradipta, Aditya Alia Fajarwati Danang Sri Hadmoko Estuning Tyas Wulan Mei Fathoni, Mohammad Naufal Kafafa, Utia Laksana, Agung Maharani, Nooriza Muta'ali, Lutfi Nur Muhammad Farda Nurani, Idea Wening Nurhadi, Muhammad Palembang, Muhammad Fikram Prima Widayani Rhosadi, Iwan Ridwan, Briantama Yanuar S Sunardi Setiawan, Muhammad Anggri Wahyu, Hyundra Zakiya Putri Widyatmanti, Wirastuti