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All Journal ARRUS Jurnal Pengabdian Kepada Masyarakat Pinisi: Physics Journal
Muhammad Arief Fitrah Istiyanto Aslim
Universitas Negeri Makassar
Humanities Earth & Planetary Sciences Energy Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Physics Public Health Social Sciences Other

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Weather Prediction in Indonesia: A Review of Models, Accuracy, Influencing Variables, and Climate Suitability Muhammad Arief Fitrah Istiyanto Aslim; Nasrul Ihsan; Muhammad Arsyad
Pinisi: Physics Journal Vol 2 No 1 (2026): Pinisi: Physics Journal
Publisher : Physics Department, Faculty of Mathematics and Natural Sciences, Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/ppj.v2i1.12664

Abstract

Indonesia’s complex tropical climate, diverse topography, and strong influence from large-scale climate variability such as ENSO and MJO pose persistent challenges for accurate weather prediction. This study reviews recent developments in weather forecasting research in Indonesia, focusing on model approaches, predictor variables, and performance across different climatic regions. The literature shows a clear transition from conventional statistical methods, such as ARIMA and regression models, toward machine learning, deep learning, hybrid, and ensemble frameworks. Deep learning models (e.g., LSTM, Bi-LSTM, and CNN) generally achieve higher accuracy when sufficient quality data are available, while hybrid and ensemble methods improve robustness under heterogeneous climatic and data conditions. Key predictors include rainfall, temperature, humidity, wind variables, atmospheric pressure, satellite-based products, and climate indices such as Niño3.4 and the Dipole Mode Index. Performance is strongly influenced by regional climate characteristics, data availability, and model configuration. Despite these advances, major limitations remain, including uneven observational coverage, challenges in extreme weather prediction, sensitivity to sparse and noisy data, high computational demands, and limited operational deployment. These findings highlight the need for adaptive, computationally efficient forecasting frameworks and stronger integration between data infrastructure and real-time operational systems.
PKM Analisis Peran e-Nose Berbasis Machine Learning Untuk Mengatasi Kualitas dan Nilai Ekonomi Kopi Sangrai Kelompok Tani Sarro Anging Nasrul Ihsan; Ahmad Dahlan Dahlan; Laode Manarfah; Nurhayati; Muhammad Arief Fitrah Istiyanto Aslim
ARRUS Jurnal Pengabdian Kepada Masyarakat Vol. 5 No. 1 (2026)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.abdiku4900

Abstract

Kelompok Tani Sarroanging di Dusun Botong, Desa Bontomanai, Kabupaten Gowa, memiliki potensi besar dalam budidaya kopi Robusta, namun nilai tambah produk masih rendah karena sebagian besar hasil panen dijual dalam bentuk green bean kepada tengkulak. Selain itu, proses penyangraian yang masih manual menyebabkan mutu produk tidak konsisten, sementara pemasaran yang terbatas menghambat peningkatan pendapatan petani. Program Pengabdian kepada Masyarakat ini bertujuan meningkatkan kualitas, konsistensi mutu, dan nilai ekonomi kopi melalui pelatihan sangrai terstandarisasi berbasis informasi profil aroma electronic nose (e-nose) serta penguatan pemasaran digital dan branding produk. Metode pelaksanaan menggunakan pendekatan partisipatif yang melibatkan 15 anggota kelompok tani dalam kegiatan sosialisasi, pelatihan, praktik langsung, pendampingan, dan evaluasi. Kegiatan meliputi pengadaan mesin roasting semi otomatis, pelatihan teknik roasting, demonstrasi penggunaan e-nose sebagai media pembelajaran kualitas aroma, penerapan manajemen stok berbasis First In First Out (FIFO), serta pelatihan digital marketing dan pengembangan identitas merek Kopi Dusun Botong. Hasil yang diharapkan adalah meningkatnya kemampuan mitra dalam menerapkan proses sangrai yang konsisten, memahami hubungan profil aroma dengan kualitas kopi, serta mengelola produk secara lebih profesional. Di sisi pemasaran, program ditargetkan meningkatkan kapasitas promosi digital, memperluas akses pasar, meningkatkan jumlah pengikut media sosial, dan mendorong kenaikan volume penjualan kopi. Program ini diharapkan mampu menciptakan sistem produksi dan pemasaran kopi yang lebih berkelanjutan sehingga nilai tambah produk dan kesejahteraan petani dapat meningkat.
Co-Authors Ahmad Dahlan Dahlan Laode Manarfah Muhammad Arsyad Nasrul Ihsan Nasrul Ihsan Nurhayati