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All Journal Budimas : Jurnal Pengabdian Masyarakat Journal of The Physical Society of Indonesia
Husnul Hamdi, Husnul
Jurusan Fisika Fakultas Matematika dan Ilmu Pengetahuan Alam Institut Teknologi Bandung
Religion Humanities Economics, Econometrics & Finance Physics Social Sciences Other

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Upaya Peningkatan Kesadaran Lingkungan melalui Pembuatan Plang Sampah Terurai dan Tong Sampah di Desa Perkebunan Bukit Lawang Hamdi, Husnul; Ananda Dewi, Suci; Akbar Harahap, Fadilah; Nursakila Ena Anjani; Zein, Achyar
BUDIMAS : JURNAL PENGABDIAN MASYARAKAT Vol. 7 No. 3 (2025): BUDIMAS : Jurnal Pengabdian Masyarakat
Publisher : LPPM ITB AAS Indonesia Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/budimas.v7i3.18180

Abstract

Kuliah Kerja Nyata (KKN) merupakan salah satu bentuk pengabdian mahasiswa kepada masyarakat melalui program kerja yang disusun sesuai kebutuhan desa. Kegiatan KKN UINSU di Desa Perkebunan Bukit Lawang dilaksanakan pada tanggal 30 Juli – 01 September 2025 dengan fokus pada permasalahan lingkungan, khususnya pengelolaan sampah. Program utama yang dijalankan adalah pembuatan dan pemasangan plang sampah terurai sebagai media edukasi masyarakat mengenai lamanya sampah terurai secara alami, serta penyediaan tong sampah organik dan anorganik yang dibuat dari kayu sesuai aturan desa yang melarang penggunaan bahan berbasis kimia. Metode pelaksanaannya dilakukan melalui tahap persiapan berupa observasi, koordinasi, dan sosialisasi, kemudian dilanjutkan dengan tahap pelaksanaan berupa pembuatan serta pemasangan plang dan tong sampah di lokasi strategis. Hasil kegiatan menunjukkan adanya peningkatan kesadaran masyarakat dalam memilah dan membuang sampah pada tempatnya, serta terciptanya lingkungan yang lebih bersih dan sehat. Program ini tidak hanya memberikan solusi praktis terhadap permasalahan sampah, tetapi juga menumbuhkan budaya peduli lingkungan yang berkelanjutan di Desa Perkebunan Bukit Lawang.
Prediction of Rainfall Using a Backpropagation Artificial Neural Network Model over Muaro Jambi Regency Damanik, Irawati; Aminoto, Tugiyo; Hamdi, Husnul
Journal of the Physical Society of Indonesia Vol. 2 No. 1 (2026): April 2026
Publisher : The Physical Society of Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35895/jpsi.2.1.59-71.2026

Abstract

This study aims to predict rainfall in Muaro Jambi Regency using the Backpropagation Artificial Neural Network (ANN) method. The input variables include air humidity, air temperature, air pressure, and wind speed, with data obtained from the BMKG Muaro Jambi Climatology Station. The method is quantitative with a time series approach, involving data collection, normalization, and division into training, validation, and testing, along with the application of Trainlm, Trainrp, and Traindx. The results show that air humidity has the greatest influence on rainfall, while temperature, air pressure, and wind speed show weak negative correlations. Testing variations in the number of neurons in the hidden layer shows that 100 neurons with the Traindx algorithm produce the best performance, with a Mean Square Error (MSE) of 4.95%, categorized as very accurate. The Backpropagation ANN model follows the actual rainfall pattern from BMKG with a conformity level of more than 95% and recognizes seasonal patterns such as peak rainfall in March and a decrease in the middle of the year. Thus, this model is effective for predicting rainfall and supports disaster mitigation planning and water resource management in Muaro Jambi Regency.
Mapping of Potential Flood Prone Areas Using the Scoring Method and Overlay in Batanghari Regency Melka Sintia Siburian; Aminoto, Tugiyo; Hamdi, Husnul
Journal of the Physical Society of Indonesia Vol. 2 No. 1 (2026): April 2026
Publisher : The Physical Society of Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35895/jpsi.2.1.47-58.2026

Abstract

Mapping of potential flood-prone areas using scoring and overlay methods in Batanghari Regency has been carried out. This study aims to determine the level of flood vulnerability and the distribution of flood-prone areas. The parameters used are rainfall parameters, soil type parameters, river distance parameters, slope parameters, land cover parameters, and elevation parameters. The methods used are scoring and overlay methods with the assistance of ArcGIS 10.8 software. The level of flood vulnerability is classified into three categories: not vulnerable, vulnerable, and highly vulnerable. The results obtained in this study show that the majority of Batanghari Regency has a flood vulnerability level in the not vulnerable class, covering an area of 397,158.03 Ha (72%), with areas in the vulnerable category covering 132,119.089 Ha (24.22%), and highly vulnerable areas covering 15,380.96 Ha (2.82%). In contrast, the area that is relatively safe from flooding is the Bajubang District, which covers an area of 102,592.1 hectares (90.17%). This indicates that some areas of Batanghari Regency are prone to flooding, making it very important to take disaster mitigation actions in the Batanghari Regency.
Co-Authors Achyar Zein, Achyar Akbar Harahap, Fadilah Ananda Dewi, Suci Damanik, Irawati Melka Sintia Siburian Nursakila Ena Anjani Tugiyo Aminoto