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All Journal SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Journal of Mathematics, Computation and Statistics (JMATHCOS)
Muhammad Ashari
Universitas Negeri Medan
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Optimalisasi pakan untuk meningkatkan efisiensi budidaya lele di Kecamatan Tebing Tinggi Kabupaten Serdang Bedagai Muhammad Aulia Rahman Sembiring; Bakti Dwi Waluyo; Muhammad Ashari; Dian Putra Saragi; Ricky Nelson Tampubolon; Felix Hizkia Simanjuntak
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 9, No 4 (2025): Juli
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v9i4.31974

Abstract

AbstrakBudidaya lele di Kecamatan Tebing Tinggi, Kabupaten Serdang Bedagai, menghadapi tantangan efisiensi penggunaan pakan yang berdampak pada tingginya biaya produksi dan rendahnya hasil panen. Kegiatan pengabdian masyarakat ini bertujuan meningkatkan efisiensi budidaya lele melalui pelatihan manajemen pakan dan penerapan teknologi pencampur pakan otomatis. Sasaran kegiatan adalah Kelompok Tani Lele "Kuta Baru" dengan jumlah peserta 20 orang. Metode pelaksanaan meliputi sosialisasi, pelatihan teknis penggunaan pH Meter dan TDS Meter, aplikasi alat pencampur pakan otomatis berkapasitas 15 kg, serta pendampingan dan evaluasi hasil. Hasil program menunjukkan peningkatan efisiensi penggunaan pakan sebesar 18%, kenaikan rata-rata bobot panen 12%, dan 90% peserta mengadopsi teknologi baru. Kegiatan ini berkontribusi dalam meningkatkan produktivitas, efisiensi biaya, dan pengetahuan petani dalam budidaya lele yang berkelanjutan. Kata kunci: budidaya lele; efisiensi pakan; teknologi tepat guna; pelatihan; serdang bedagai AbstractCatfish farming in Tebing Tinggi Subdistrict, Serdang Bedagai Regency, faces the challenge of feed use efficiency which has an impact on high production costs and low yields. This community service activity aims to improve the efficiency of catfish cultivation through feed management training and the application of automatic feed mixing technology. The target of the activity is the "Kuta Baru" Catfish Farmer Group with a total of 20 participants. The implementation method includes socialization, technical training on the use of pH Meter and TDS Meter, application of automatic feed mixing equipment with a capacity of 15 kg, as well as mentoring and evaluation of results. The program results showed an 18% increase in feed use efficiency, a 12% increase in average harvest weight, and 90% of participants adopted the new technology. This activity contributed to increasing productivity, cost efficiency, and farmers' knowledge in sustainable catfish farming. Keywords: catfish farming; feed efficiency; appropriate technology; training; serdang bedagai
Graph-Theoretic Analysis of Weighted Neighborhood Graphs for Spatial Soil Nutrient Prediction Nurul Maulida Surbakti; Sisti Nadia Amalia; Muhammad Ashari; Riza Pahlwan
Journal of Mathematics, Computations and Statistics Vol. 9 No. 3 (2026): Volume 09 Issue 03 (September 2026)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/fazqcb69

Abstract

Soil nutrient prediction is a spatial modeling problem because nutrient values observed at nearby locations may share common spatial structure. This study develops a graph-theoretic analysis of weighted neighborhood graphs for Graph Convolutional Network (GCN)-based prediction of synthetic nitrogen (N), phosphorus (P), and potassium (K) patterns. Ten independent Monte Carlo realizations of 100 sampling locations were generated from a uniform distribution on the unit square. For each realization, weighted k-nearest-neighbor (kNN) and epsilon-neighborhood graphs were constructed using an exponential distance-decay kernel. Graph structure was quantified using the number of edges, average degree, density, number of connected components, and algebraic connectivity. Separate transductive GCN regressors were trained for N, P, and K using  train-validation-test splits, target standardization based only on the training set, early stopping, and repeated random seeds. Binary GCN, multilayer perceptron (MLP), Random Forest, and inverse-distance weighting (IDW) were included as baselines. Among the tested graph configurations, kNN with  gave the lowest mean test error , whereas kNN with  produced a marginally higher mean . Weighted GCN improved numerically over binary GCN overall , with a significant paired improvement in MAE under a Wilcoxon test , although MLP remained slightly stronger overall . Across graph configurations, density was negatively associated with test  indicating that excessive neighborhood mixing can reduce predictive performance in these controlled settings. Nutrient-specific analysis showed that phosphorus was the most difficult target, while residual Moran’s I values were close to zero. Within the controlled synthetic scenarios, weighted neighborhood graphs provided a useful and interpretable representation for GCN-based spatial nutrient modeling. Future work should evaluate the framework on field measurements using spatial block validation and environmental covariates.
Co-Authors Bakti Dwi Waluyo Felix Hizkia Simanjuntak Muhammad Aulia Rahman Sembiring Nurul Maulida Surbakti Ricky Nelson Tampubolon Riza Pahlwan Saragi, Dian Putra Sisti Nadia Amalia