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All Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer) Info Abdi Cendekia
Nurusysyifa, Saela
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Religion Computer Science & IT Health Professions Library & Information Science Social Sciences

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Pendampingan Optimalisasi Produksi Maggot di Bank Sampah IPPEC Sukabumi untuk Meningkatkan Perekonomian Lokal Ramdhani, Lis Saumi; Farlina, Yusti; Riyanto, Andi; Nurusysyifa, Saela; Septiani, Asti
Info Abdi Cendekia Vol. 8 No. 2: Desember 2025
Publisher : Lembaga Penelitian Universitas YARSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33476/iac.v8i2.187

Abstract

Permasalahan sampah organik di Kabupaten Sukabumi mendorong lahirnya inovasi pengelolaan berbasis masyarakat, salah satunya melalui Bank Sampah IPPEC yang mengembangkan budidaya Maggot (larva Black Soldier Fly). Namun, keterbatasan sarana produksi, pencatatan keuangan manual, dan strategi pemasaran konvensional menyebabkan kapasitas dan daya saing produk rendah. Kegiatan pengabdian masyarakat ini bertujuan mengoptimalkan produksi Maggot melalui transfer teknologi tepat guna, digitalisasi manajemen dan penguatan pemasaran digital. Metode yang digunakan adalah Participatory Action Research dengan tahapan analisis situasi, pengadaan mesin pencacah, sangrai, pur, pembangunan instalasi air bersih, pelatihan aplikasi IPPEKas serta pendampingan strategi branding dan promosi digital. Evaluasi dilakukan melalui pra–post test, wawancara dan monitoring. Hasil menunjukkan peningkatan produksi hingga 50% dalam tiga bulan, efisiensi pencatatan keuangan naik 86% serta penjualan meningkat 30%. Simpulan kegiatan menegaskan bahwa integrasi teknologi, manajemen dan pemasaran digital efektif memperkuat kapasitas mitra dan berpotensi direplikasi pada UMKM lain. Rekomendasi diarahkan pada diversifikasi produk, pemeliharaan mesin, perluasan jaringan pemasaran serta integrasi teknologi IoT dan kecerdasan buatan untuk keberlanjutan usaha
DATA AUGMENTATION EFFECTS ON PROTONET FEW-SHOT YELLOW DISEASE SEVERITY IN CHILI LEAVES Saputra, Rizal Amegia; Wajhillah, Rusda; Farlina, Yusti; Noviani, Hani; Nurusysyifa, Saela
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 3 (2026): JITK Issue February 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i3.7458

Abstract

Yellow curling disease in chili plants is one of the leading causes of declining horticultural productivity because it reduces the quality and quantity of crops. Variations in symptoms at each level of severity make the identification process difficult, especially when labeled data is minimal. This study proposes a Prototypical Network-based Few-Shot Learning (FSL) approach with VGG16 architecture as a feature extractor. Five augmentation techniques, namely horizontal flip, rotation, zoom, brightness, and contrast adjustment, were used to increase data diversity in data-scarce conditions. Experiments were conducted with N-way K-shot configurations (2–5 classes; 1, 5, and 10 examples per class) to evaluate the impact of augmentation on prototype representation stability. Results show that increasing the number of examples per class consistently improves accuracy from 34.6% in 5-way 1-shot to 49.4% in 5-way 10-shot without augmentation. However, the use of augmentation decreases performance in higher N-way scenarios because it increases intra-class variability. The t-SNE visualization reinforces this study, where the healthy and severely diseased classes are clearly separated, while the intermediate class shows overlap. The novelty of this study is that it is the first to evaluate the impact of augmentation strategies on prototype representation stability in the agricultural domain with limited data. The results of this Few-Shot Learning approach are effective for plant disease classification despite the limited dataset.
Co-Authors Andi Riyanto Lis Saumi Ramdhani Noviani, Hani Rizal Amegia Saputra Rusda Wajhillah, Rusda Septiani, Asti Yusti Farlina