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All Journal Jurnal AbdiMas Nusa Mandiri Jurnal Informatika
Meutia Raissa Emiliana
Universitas Bina Sarana Informatika
Computer Science & IT Decision Sciences, Operations Research & Management Education Energy Environmental Science Mathematics Physics Social Sciences Other

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Comparative Optimization of EfficientNetB3, MobileNetV2, and ResNet50 for Waste Classification Sarifah Agustiani; Haryani Haryani; Agus Junaidi; Rizky Rachma Putri; Meutia Raissa Emiliana
Jurnal Informatika Vol. 12 No. 2 (2025): October
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/

Abstract

Waste management is an important challenge in protecting the environment and public health. Improperly managed waste can cause pollution and hinder the recycling process. This study aims to classify waste based on images by optimizing three deep learning architectures, namely EfficientNetB3, MobileNetV2, and ResNet50, to determine the model with the best performance. The dataset comes from the Kaggle platform, consisting of 4,650 images in six categories: battery, glass, metal, organic, paper, and plastic. The research stages include preprocessing, data augmentation, model development, and evaluation using accuracy, precision, recall, and F1-score metrics. The results show that EfficientNetB3 with the Adam optimizer achieved the best performance with 93% accuracy, followed by ResNet50 with 91%, while MobileNetV2 ranged from 70–73% depending on the optimizer. Variations in optimizers were found to affect model performance, while data augmentation improved generalization capabilities, especially in classes with limited samples. This research confirms the potential of deep learning methods in supporting automatic waste classification systems and provides a basis for the development of technology-based waste management systems in the future.
PENINGKATAN KAPASITAS KWT SERUNI MELALUI PARTICIPATORY ACTION RESEARCH DALAM URBAN FARMING DAN HIDROPONIK Kusmayanti Solecha; Duwi Cahya Putri Buani; Furi Indriyani; Meutia Raissa Emiliana; Resti Dhea Putri Apriliani
Jurnal AbdiMas Nusa Mandiri Vol. 7 No. 2 (2025): Periode Oktober 2025
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/abdimas.v7i2.7265

Abstract

This community service program aims to enhance the capacity and self-reliance of the Seruni Women Farmer Group (KWT Seruni) in supporting food security through training on urban farming and hydroponic cultivation, implemented using a Participatory Action Research (PAR) approach. The program engaged lecturers, students, and group members in stages of socialization, training, technology implementation, mentoring, and sustainability planning. Evaluation results indicated a 12% improvement in participants’ understanding based on pre-test and post-test scores, demonstrating the program’s effectiveness in strengthening technical competence. Technological implementation, including the construction of a seed house and the use of pH and TDS meters, resulted in 1,500 high-quality seedlings and a hydroponic pakcoy harvest of 18.4 kg. Participants successfully applied practical skills independently, particularly in nutrient management and the cultivation of economically valuable crops. The program also fostered an internal training system for new members and generated socio-economic benefits, such as increased household income and strengthened women’s roles in agriculture. Overall, this activity aligns with SDGs 1, 2, 5, and 12.
Co-Authors Agus Junaidi Agustiani, Sarifah Duwi Cahya Putri Buani Furi Indriyani Haryani Kusmayanti Solecha Resti Dhea Putri Apriliani Rizky Rachma Putri