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All Journal Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Agrikan: Jurnal Agribisnis Perikanan Jurnal Indonesia Sosial Sains
Purwanto, Moh Yanuar Jarwadi
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Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Energy Environmental Science Immunology & microbiology Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Neuroscience Physics Social Sciences

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Prediction and Simulation for Land Use and Land Cover Change of Paddy Field Influence by Salinization in Coastal Demak Regency Tivianton, Tommy Andryan; Barus, Baba; Purwanto, Moh Yanuar Jarwadi; Anwar, Syaiful; Widiatmaka
Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Vol 14 No 4 (2024): Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (JPSL)
Publisher : Pusat Penelitian Lingkungan Hidup, IPB (PPLH-IPB) dan Program Studi Pengelolaan Sumberdaya Alam dan Lingkungan, IPB (PS. PSL, SPs. IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jpsl.14.4.811

Abstract

Luas lahan pertanian sawah di pesisir rentan terhadap perubahan penggunaan lahan dan tutupan lahan (LULC) menjadi penggunaan non-pertanian akibat degradasi lahan, salah satunya disebabkan oleh salinitas. Studi ini bertujuan untuk mendeteksi dan memproyeksikan perubahan LULC hingga tahun 2031, terutama di daerah sawah pesisir yang terkena salinitas, dengan membandingkan LULC pada tahun 2017, 2019, dan 2021. Citra Sentinel-2 digunakan untuk klasifikasi LULC, dengan rekaman yang dipilih selama fase generatif pertumbuhan padi untuk memperoleh area sawah yang paling optimal. Terdapat enam klasifikasi LULC: air, lahan basah, area vegetasi, dan area terbangun. Untuk memahami dampak salinitas pada tanaman, beberapa indeks vegetasi (VIs) seperti NDVI, SAVI, EVI, dan ARVI digunakan. Perubahan LULC yang diklasifikasikan menurut VIs dibandingkan dengan plugin MOLUSCE berdasarkan jaringan saraf tiruan-perceptron multilapis (ANN-MLP) dan Automata Seluler (CA). Perbandingan hasil VIs menunjukkan bahwa NDVI lebih baik dalam menggambarkan perubahan LULC akibat pengaruh salinitas, dengan nilai kappa sebesar 0.63 dan Correctness sebesar 72.565. Proyeksi LULC menggunakan CA dalam semua VIs menunjukkan bahwa area lahan basah lebih cenderung berubah menjadi badan air, yang menunjukkan bahwa lahan dengan salinitas tinggi cenderung tidak produktif untuk sawah, sehingga rentan terhadap konversi.
Analysis of Waste Processing Reduce Reuse and Recycle to Reduce the Burden of Waste Accumulation in Bekasi City Saleh, Abdul; Purwanto, Moh Yanuar Jarwadi; Pravitasari, Andrea Emma
Agrikan Jurnal Agribisnis Perikanan Vol. 18 No. 1 (2025): Agrikan: Jurnal Agribisnis Perikanan
Publisher : Fakultas Pertanian, Universitas Muhammadiyah Maluku Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52046/agrikan.v18i1.2476

Abstract

Waste management in large cities like Bekasi is a major challenge in achieving sustainable development. The implementation of the 3R concept (Reduce, Reuse, Recycle) through 3R-Based Waste Processing Sites (TPS3R) has become a key solution. This study analyzes five TPS3Rs in Bekasi City: Bina Lindung, Prima Harapan, Sakura Regency, Mustika Sari, and Ciketing Udik. The objective is to assess the amount of waste, observe the processing methods, and formulate waste management strategies using both quantitative and qualitative methods. Samples were collected from varying numbers of households. TPS3R Bina Lindung and Sakura Regency each sampled 80 households, including a mix of permanent, semi-permanent, and non-permanent homes. TPS3R Prima Harapan sampled 28 households, Mustika Sari 160 households, and Ciketing Udik 49 households. The results show varying levels of waste management effectiveness. Mustika Sari achieved the highest effectiveness at 97.58%, followed by Sakura Regency at 92.39%, Prima Harapan at 50%, Ciketing Udik at 5.71%, and Bina Lindung at 2.67%. SWOT analysis reveals that the success of waste management is highly influenced by the reuse of recyclable materials. However, weaknesses include a lack of public awareness and low community participation in environmental initiatives. There is significant potential in community support, particularly in reducing paper, plastic, and bottle waste. On the other hand, challenges include limited training for TPS3R operators and the infrequent processing of organic waste by residents.
Artificial Intelligence-Based Irrigation Monitoring Information System For Enhancing Irrigation Rehabilitation Work Supervision Nurlaelah, Nurlaelah; Saptomo, Satyanto Krido; Purwanto, Moh Yanuar Jarwadi
Jurnal Indonesia Sosial Sains Vol. 7 No. 1 (2026): Jurnal Indonesia Sosial Sains
Publisher : CV. Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jiss.v7i1.2182

Abstract

The rehabilitation of irrigation networks plays a critical role in enhancing agricultural productivity and supporting national food self-sufficiency targets as mandated by Presidential Instruction No. 2 of 2025. Traditional monitoring practices still rely on manual reporting, inconsistent documentation, and non–real-time inspections, leading to data inaccuracies and limited transparency. These challenges highlight the need for a more reliable, timely, and objective monitoring system. SIMORI (Irrigation Monitoring Information System) is introduced as an AI-powered digital solution capable of providing real-time data, detecting anomalies, and generating accountable automated reports. This paper explores the relevance and urgency of SIMORI as a strategic instrument to enhance transparency, accountability, and monitoring quality in irrigation rehabilitation projects, thereby accelerating national food security objectives.
Co-Authors Andrea Emma Pravitasari, Andrea Emma Baba Barus Nurlaelah Nurlaelah, Nurlaelah Saleh, Abdul Satyanto Krido Saptomo Syaiful Anwar Tivianton, Tommy Andryan Widiatmaka