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All Journal AXIOM : Jurnal Pendidikan dan Matematika Indonesian Journal of Education and Mathematical Science JURNAL SIPISSANGNGI: Jurnal Pengabdian Kepada Masyarakat
Rizki Habibi
Universitas Negeri Medan
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Education Languange, Linguistic, Communication & Media Library & Information Science Mathematics Public Health Other

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Optimization of operational cost planning in integrated farming systems using a mixed-integer linear programming approach Lasker Pangarapan Sinaga; Rizki Habibi; Suvriadi Panggabean
AXIOM : Jurnal Pendidikan dan Matematika Vol 15, No 1 (2026)
Publisher : State Islamic University of North Sumatra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30821/axiom.v15i1.26491

Abstract

This study addresses the challenge of optimizing small-scale integrated farming systems (IFS) by minimizing operational costs while ensuring sustainable land use across agricultural, livestock, and aquaculture components. The main objective is to develop a Mixed-Integer Linear Programming (MILP) model that incorporates deterministic parameters such as land availability, labor allocation, and internal-external input flows. The model integrates multiple interrelated subsystems using production coefficients, resource constraints, and cost structures derived from actual smallholder scenarios. A two-period simulation was conducted to evaluate the model’s effectiveness using fixed input values, reflecting rural farming conditions. The results demonstrate that the system achieved consistent outputs without requiring external purchases of manure, feed, or irrigation water. The total operational cost reached IDR 96,770,000, with optimized land and labor allocation across periods. This research contributes a novel MILP formulation tailored to integrated farming, providing practical insights for policymakers and practitioners. Its implications extend to the development of decision-support systems for rural agricultural planning. However, the model's deterministic assumption limits its adaptability to dynamic environments. Future work should explore stochastic variants and real-time input adjustments to improve model flexibility and realism.
Evaluation of Gaussian Process Regression, Support Vector Regression, and K-Nearest Neighbors for Predicting Concrete Compressive Strength at Various Curing Ages Elmanani Simamora; Abil Mansyur; Muhammad Badzlan Darari; Suvriadi Panggabean; Rizki Habibi
Indonesian Journal of Education and Mathematical Science Vol 7, No 3 (2026)
Publisher : Universitas Muhammadiyah Sumatera Utara (UMSU)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/ijems.v7i3.31258

Abstract

Accurate prediction of concrete compressive strength is critical for quality control, structural evaluation, and mix optimization. However, the connection between mix composition, curing age, and compressive strength is often nonlinear and heterogeneous. This study assesses four prediction models, including Native Gaussian Process Regression, Gaussian Process Regression with Conformal Intervals, Support Vector Regression, and K-Nearest Neighbors, to estimate concrete compressive strength at various curing ages. Predictors are produced from a combination of composition, curing age, and material-important properties. Model performance is evaluated using Leave-One-Age-Out and repeated stratified K-fold by Age, with root mean square error, mean absolute error, coefficient of determination, coverage, and average interval length. The results demonstrate that Native Gaussian Process Regression gives the best steady overall performance in both assessment methodologies. At the same time, Gaussian Process Regression with Conformal Intervals tends to provide higher coverage with the consequence of wider intervals. In general, Native Gaussian Process Regression provides the best balance among point prediction accuracy, interval coverage, and interval efficiency for heterogeneous concrete compressive strength data by curing age.
INOVASI BATIK DIGITAL MENGGUNAKAN APLIKASI AMBATIG UNTUK PELESTARIAN KEARIFAN LOKAL DI NIAS Dinda Kartika; Debi Yandra Niska; Misgiya Misgiya; Ade Andriani; Arnah Ritonga; Rizki Habibi; Didi Febrian
JURNAL SIPISSANGNGI: Jurnal Pengabdian Kepada Masyarakat Vol 6, No 3 (2026): Sipissangngi Volume 6, Nomor 3, September 2026
Publisher : Lembaga Penelitan dan Pengabdian Masyarakat, Universitas Al Asyariah Mandar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35329/jp.v6i3.7439

Abstract

Pengabdian kepada masyarakat ini bertujuan meningkatkan kapasitas perajin dalam mengembangkan motif batik berbasis kearifan lokal Nias melalui aplikasi Ambatig. Kegiatan dilaksanakan dengan pendekatan partisipatif yang meliputi sosialisasi, pelatihan tatap muka, penerapan mandiri, pendampingan teknis, dan evaluasi. Sebanyak 10 penggiat seni binaan Dinas Perindustrian, Koperasi, dan UKM Kota Gunungsitoli dilatih mengembangkan motif dari ikonografi lokal menggunakan pola simetri frieze dan kelompok kristalografi bidang, mulai dari penyusunan bentuk dasar hingga penyimpanan hasil dalam portofolio digital. Evaluasi dilakukan melalui observasi ketuntasan langkah, angket Likert, pencatatan kendala, dan kurasi portofolio. Hasil menunjukkan seluruh peserta mampu menggunakan Ambatig dan menghasilkan motif digital berbasis budaya Nias. Skor kepuasan berada pada rentang 4,30 – 4,90 dari skala 5. Penerapan aplikasi juga mendorong terbentuknya bank motif digital, mempercepat proses desain, meningkatkan latihan mandiri, dan mengurangi kebutuhan bantuan teknis. Fitur pratinjau waktu nyata dan penataan berkas secara sistematis turut memudahkan peserta memperbaiki rancangan, mendokumentasikan karya, serta menyiapkan materi komunikasi produk. Dengan demikian, Ambatig efektif mendukung diversifikasi motif, efisiensi desain, peningkatan kapasitas perajin, serta pelestarian ikonografi lokal Nias. Keberlanjutan program diarahkan pada pengembangan pelatih internal, repositori motif bersama, dan penyempurnaan aplikasi berdasarkan umpan balik pengguna.
Co-Authors Abil Mansyur, Abil Ade Andriani ARNAH RITONGA DIdi Febrian Dinda Kartika Elmanani Simamora Lasker Pangarapan Sinaga Muhammad Badzlan Darari Niska, Debi Yandra Suvriadi Panggabean