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All Journal Teknotan: Jurnal Industri Teknologi Pertanian Jurnal SOLMA JURNAL REKAYASA DAN MANAJEMEN AGROINDUSTRI
Fadila, Abil
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Agriculture, Biological Sciences & Forestry Chemistry Immunology & microbiology Industrial & Manufacturing Engineering Other

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Sosialisasi dan Pelatihan Budidaya Tanaman Unggul untuk Mendukung Program Kampung Buah Mahatmayana, I Ketut Manu; Supriadi, Devie Rienzani; Primajaya, Aji; Syabena, Muhammad Farrel; Fadila, Abil; Prastyo, Hadi
Jurnal SOLMA Vol. 14 No. 3 (2025)
Publisher : Universitas Muhammadiyah Prof. DR. Hamka (UHAMKA Press)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/solma.v14i3.20701

Abstract

Background: Karanganyar Village, Klari Subdistrict, Karawang Regency has vast land and potential for fruit crop development. By utilizing this vast land, a fruit village can be created, thereby increasing the potential to improve the income of the surrounding community. This activity aims to support the creation of a fruit village to improve food quality and the economy of the village community. Methods: A participatory approach through the dissemination of information on superior crops and the planting of fruit trees as parent plants. Results: The presence of superior parent plants with high productivity can meet the needs and improve the economy of the Karanganyar Village community. Conclusions: The community is able to produce food for family and community needs by having highly productive and adaptive parent plants.
Rekayasa Waktu Dan Temperatur Penyulingan Untuk Peningkatan Rendemen Minyak Atsiri Kulit Jeruk Lemon (Citrus Limon. L) Fadila, Abil; Nurjanah, Sarifah; Rosalinda, Rosalinda
JURNAL REKAYASA DAN MANAJEMEN AGROINDUSTRI Vol 14 No 1 (2026): Maret
Publisher : Department of Agroindustrial Technology, Faculty of Agricultural Technology, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JRMA.2026.v14.i01.p08

Abstract

Lemon processing generates a substantial amount of peel waste, accounting for approximately 40-50% of the total fruit weight. The lemon peel, particularly the flavedo layer, contains essential oil compounds with the potential to be developed into value-added products through distillation. This study evaluates the influence of distillation duration and temperature parameters on the yield and physicochemical quality of essential oil derived from lemon peel waste. The experiment employed a Factorial Completely Randomized Design (CRD) with two factors: distillation time (P = 4, 5, 6, 7, and 8 hours) and distillation temperature (T = 83, 90, 100, 110, and 117°C). The observed parameters included oil yield, specific gravity, refractive index, acid value, and solubility in 70% alcohol. Data were processed using Analysis of Variance (ANOVA) followed by Duncan's Multiple Range Test (DMRT) at a 95% confidence level. The findings indicate that distillation time significantly affects the essential oil yield, whereas temperature variations within the tested range do not show a significant impact. The highest yield of 0.84% was achieved at a distillation time of 8 hours at 100°C. The resulting essential oil exhibited a specific gravity of 0.851 g/mL, a refractive index of 1.473, an acid value of 5.60 mg KOH/g, and a 1:10 solubility in 70% alcohol, all of which meet quality standards. These results demonstrate that optimizing distillation conditions can enhance yield while maintaining the quality of lemon peel essential oil.
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 Mahatmayana, I Ketut Manu Miftakhul Bakhrir Rozaq Khamid Prastyo, Hadi Rosalinda Rosalinda Saliha, Ilmiasa Sarifah Nurjanah Supriadi, Devie Rienzani Syabena, Muhammad Farrel Umadi, Sarah Sakinah