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All Journal HAYATI Journal of Biosciences Jurnal Agronomi Indonesia (Indonesian Journal of Agronomy) Teknotan: Jurnal Industri Teknologi Pertanian Jurnal AGROSAINS dan TEKNOLOGI JURNAL PERTANIAN PRESISI (JOURNAL OF PRECISION AGRICULTURE) Jurnal Agrotek Indonesia Kumawula: Jurnal Pengabdian Kepada Masyarakat JURNAL AGRIVIGOR
Miftakhul Bakhrir Rozaq Khamid
Universitas Singaperbangsa Karawang
Agriculture, Biological Sciences & Forestry Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Social Sciences Other

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Respon Fisiologis Varietas Bawang Merah Dataran Rendah Terhadap Intensitas Naungan Agroekosistem Karawang Dini Yuandini; Miftakhul Bakhrir Rozaq Khamid; Devie Rienzani Supriadi
Jurnal Agrosains dan Teknologi Vol 11 No 1 (2026)
Publisher : Fakultas Pertanian - UMJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24853/jat.v11i1.31571

Abstract

Shallot (Allium ascalonicum L.) is a high-value horticultural crop whose productivity is strongly influenced by light intensity, particularly in lowland agroecosystems such as Karawang characterized by high temperature and solar radiation. This study aimed to evaluate the physiological responses of several shallot varieties under different shading levels. The experiment was conducted using a Split Plot Design with two factors: shading intensity (0%, 40%, and 65%) and varieties (Bima Brebes, Bauji, and Tajuk). Observed parameters included leaf color, chlorophyll content (SPAD), leaf area, leaf area index, fresh and dry leaf weight, root length, transpiration rate, and relative water content (RWC). The results showed significant interaction between shading and variety on leaf color and chlorophyll content at several observation stages. Increasing shading intensity significantly reduced SPAD values in Bima Brebes and Tajuk, while Bauji exhibited greater chlorophyll stability under shaded conditions. Shading reduced photosynthetic efficiency due to limited light availability, leading to lower biomass accumulation. In contrast, no shading resulted in the highest chlorophyll content, particularly in the Tajuk variety. This study concludes that physiological responses of shallot are influenced by genotype–environment interaction, with no shading providing the most optimal physiological performance.
Pengembangan Model Prediksi Produksi Padi di Provinsi Jawa Barat Berbasis Integrasi Data Agroklimat Menggunakan Ensemble Machine Learning Fadila, Abil; Syabena, Muhammad Farrel; Khamid, Miftakhul Bakhrir Rozaq; Prastyo, Hadi; Umadi, Sarah Sakinah; Saliha, Ilmiasa
Teknotan: Jurnal Industri Teknologi Pertanian Vol 20, No 2 (2026): TEKNOTAN, Agustus 2026
Publisher : Fakultas Teknologi Industri Pertanian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jt.vol20n2.18

Abstract

Dinamika cuaca yang tidak menentu menjadi faktor utama yang mempengaruhi variabilitas produksi padi di Jawa Barat dan menuntut penerapan teknologi prediksi yang akurat untuk mendukung pengelolaan produksi pertanian secara efisien dan adaptif. Penelitian ini bertujuan mengembangkan sistem prediksi produksi padi berbasis integrasi data agroklimat menggunakan algoritma ensemble machine learning, yaitu Random Forest (RF) dan Extreme Gradient Boosting (XGBoost). Data yang digunakan meliputi variabel agroklimat berupa curah hujan, suhu udara, kelembapan, dan kecepatan angin serta data historis produksi padi di Provinsi Jawa Barat periode 2018–2024. Pengembangan sistem dilakukan melalui tahapan pra-pemrosesan data, transformasi fitur, pelatihan model, dan validasi menggunakan skema 10-fold cross-validation untuk menjamin stabilitas dan reliabilitas model. Kinerja model dievaluasi menggunakan koefisien determinasi (R²), Mean Absolute Error (MAE), dan Root Mean Square Error (RMSE). Hasil penelitian menunjukkan bahwa algoritma Random Forest memberikan performa terbaik dengan nilai R² sebesar 0,9928, MAE sebesar 16.608,92, dan RMSE sebesar 24.796,55. Variabel luas lahan, curah hujan, suhu, dan kelembapan teridentifikasi sebagai faktor utama yang memengaruhi produksi padi. Sistem yang dikembangkan berpotensi diimplementasikan sebagai teknologi pendukung prediksi produksi padi dengan memanfaatkan data agroklimat sebagai variabel prediktor, sehingga dapat mendukung pengambilan keputusan dalam pengelolaan produksi tanaman dan penerapan pertanian presisi berbasis data guna meningkatkan efisiensi serta ketahanan sistem produksi padi.
Co-Authors Abdullah Bin Arif AHMAD JUNAEDI Astuti Kurnianingsih Dermawan, Rahmansyah Devie Rienzani Supriadi Devie Rienzani Supriadi Dini Yuandini Elda Kristiani Paisey Enrico Syaefullah Fadila, Abil Fawzy Muhammad Bayfurqon Indrajit Wicaksana Irpan Badrul Jamal Iskandar Lubis Isna Tustiyani Marlin Sefrila Prastyo, Hadi Rianti, Winda Rika Yayu Agustini Saliha, Ilmiasa Sarah Sakinah Umadi Siti Latifatus Siriyah Suhaeni Suhaeni, Suhaeni Supriadi, Devie Rienzani Syabena, Muhammad Farrel Topik Hidayat Ubad Badrudin Yamamoto, dan Yoshinori Yayu Sri Rahayu, Yayu Sri