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All Journal Jurnal SOLMA Indonesian Journal of Data and Science
Anggraeni, Kartika Nur
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Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Other

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Teknologi Tepat Guna dalam Kegiatan Sosial dan Ekonomi di Desa Pudak Wetan: Sebuah Program Kuliah Kerja Nyata Tematik Nimasari, Elok Putri; Pasa, Faiz Danendra Ahnaf; Wijaya, Arma; Muzaky, Moh Azis Rosyid; Devara, Gilang Ariaghi; Nurfaisandi, Moh Rifqi; Pratama, Bayu Setiawan Putra; Pinastiko, Cundoko; Mahendra, Diky Ferdhinan Anca; Pratiwi, Intin Rista; Anggraeni, Kartika Nur; Mursyidin, Dimas Alif; Septian, Gilang Cahyo; Purnomo, Dicky; Anggraini, Marcellina; Noviati, Mariska Anggun; Apriliyani, Disa
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.v14i3.19130

Abstract

Pendahuluan: Kegiatan Kuliah Kerja Nyata (KKN) umumnya berfokus pada aktivitas sosial, sehingga penerapan teknologi praktis untuk pemberdayaan masyarakat sering terabaikan. Desa Pudak Wetan, wilayah terluar di Kabupaten Ponorogo yang berada di dataran tinggi, memiliki struktur ekonomi berbasis pertanian dan peternakan dengan tingkat kemiskinan yang relatif tinggi. Rendahnya pemahaman dan keterampilan masyarakat dalam memanfaatkan teknologi digital menjadi hambatan peningkatan produktivitas serta pengembangan peluang ekonomi lokal. Metode: Pendekatan partisipatif berbasis teori community engagement melalui pelatihan dan praktik langsung dengan melibatkan mahasiswa Teknik Informatika, Teknik Mesin, dan Teknik Elektro. Hasil: Materi pelatihan meliputi panel surya, Internet of Things, website desa, running text, serta aplikasi Microsoft Office untuk administrasi dan ekonomi desa. Warga dan staf desa menunjukkan peningkatan keterampilan dalam penggunaan teknologi tepat guna. Kesimpulan: Program ini meningkatkan kapasitas digital desa dan penerapan ilmu keteknikan untuk pembangunan daerah.
Automated Waste Image Classification with Weighted Scoring Using MobileNetV2 on the OLSAM Platform Anggraeni, Kartika Nur; Astuti, Arin Yuli; Zulkarnain , Ismail Abdurrozzaq
Indonesian Journal of Data and Science Vol. 6 No. 3 (2025): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v6i3.295

Abstract

This study presents the development of an automated waste image classification system for the OLSAM platform to enhance community participation in waste management. The objective is to integrate a lightweight CNN-based classifier with a weighted point calculation mechanism for five waste categories. A dataset of 1,500 images was used, split into 80% training, 10% validation, and 10% testing. The MobileNetV2 architecture was applied to perform image classification, while a weighted reward mechanism assigned points based on the detected waste type and its weight. The model achieved its best performance at epoch 65, reaching an accuracy of 96.67% and a weighted F1-score of 0.97. These results indicate that combining CNN-based recognition with a weighted point system effectively supports user engagement and promotes sustainable waste-sorting behavior within community waste management systems.
Co-Authors Anggraini, Marcellina Apriliyani, Disa Astuti, Arin Yuli Devara, Gilang Ariaghi Elok Putri Nimasari, Elok Putri Mahendra, Diky Ferdhinan Anca Mursyidin, Dimas Alif Muzaky, Moh Azis Rosyid Noviati, Mariska Anggun Nurfaisandi, Moh Rifqi Pasa, Faiz Danendra Ahnaf Pinastiko, Cundoko Pratama, Bayu Setiawan Putra Pratiwi, Intin Rista Purnomo, Dicky Septian, Gilang Cahyo Wijaya, Arma Zulkarnain , Ismail Abdurrozzaq