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All Journal Jurnal PkM MIFTEK Journal of Intelligent Systems Technology and Informatics
Nashrulloh, Muhammad Hallaj
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Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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PENINGKATAN PENYADARAN MASYARAKAT DI DESA PASANGGRAHAN TERKAIT LINGKUNGAN SEHAT Rahayu, Sri; Nurlatifah, Hilda; Maharani, Windy Putri; Prasetiowati, Lulu; Fatimah, Rahma Siti; Subagja, Moh Yahman; Annurulloh, Anugrah Dwi; At-Thoriq, Muhammad; Nashrulloh, Muhammad Hallaj; Mardiana, Dindin; Saumi, Lea Siti; Fadilah, Azki; Torik, Givari Zabal; Khoerudin, Muhammad; Faisal, Moch Rizky; Iskandar, Rio Januar; Hamzah, Doni; Ridwan, Ridwan; Fawaz, Azriel Al; Nurjaman, Muhammad Ilyas; Ramadhan, Asep Shantika
Jurnal PkM MIFTEK Vol 5 No 2 (2024): Jurnal PkM MIFTEK
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/miftek/v.5-2.1959

Abstract

Penelitian ini bertujuan untuk meningkatkan kesadaran masyarakat Desa Pasanggrahan terkait lingkungan sehat melalui serangkaian kegiatan Kuliah Kerja Nyata (KKN). Metode yang digunakan adalah pendekatan kuantitatif, melibatkan 20 tokoh masyarakat formal sebagai responden. Kegiatan yang dilaksanakan meliputi seminar di sekolah dasar, kerja bakti, sosialisasi pemilahan sampah, pemberian tong sampah, dan loka karya. Hasil penelitian menunjukkan peningkatan signifikan dalam pemahaman dan partisipasi masyarakat terhadap lingkungan sehat, terutama dalam kegiatan posyandu dan pengelolaan sampah. Meskipun demikian, tantangan implementasi dan keberlanjutan program masih ada. Program ini berhasil meningkatkan kesadaran masyarakat, namun diperlukan langkah-langkah lanjutan untuk memastikan dampak jangka panjang, termasuk penyediaan fasilitas penunjang, edukasi berkelanjutan, dan penguatan kolaborasi antar pemangku kepentingan. Penelitian ini memberikan kontribusi penting dalam upaya peningkatan kualitas hidup masyarakat desa melalui pengelolaan lingkungan sehat yang berkelanjutan.
Fruit Image Classification Using CNN With EfficientNet Architecture for Visual Education Nashrulloh, Muhammad Hallaj; Subarkah, Adie
Journal of Intelligent Systems Technology and Informatics Vol 1 No 2 (2025): JISTICS, July 2025
Publisher : Aliansi Peneliti Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64878/jistics.v1i2.9

Abstract

Advancements in artificial intelligence and computer vision have significantly influenced education, particularly by enhancing visual-based learning for young learners. One promising application is fruit image classification, which helps students recognize and differentiate fruits through visual cues. Traditional methods often struggle with varied backgrounds and lighting conditions, making deep learning models more suitable. This study aims to develop an efficient fruit classification system using the EfficientNetB0 architecture within a convolutional neural network (CNN) framework. This study evaluates the model's effectiveness as a visual learning tool in educational contexts while ensuring computational efficiency. The dataset, sourced from Kaggle, consists of eight fruit categories: apples, bananas, kiwis, lemons, passion fruits, peaches, pineapples, and raspberries. It was split into training and validation sets with an 80:20 ratio using stratified random sampling to ensure balanced class representation during evaluation. Preprocessing steps included resizing images to 224×224 pixels, normalization with EfficientNet preprocessing, and data augmentation techniques to improve generalization. A custom classification head was added, and the EfficientNetB0 base was frozen. Training employed the Adam optimizer, categorical cross-entropy loss, early stopping, and class weighting across 30 epochs. The model achieved a validation accuracy of 99%, with near-perfect precision, recall, and F1-score across all classes. The confusion matrix showed minimal misclassification, indicating strong generalization even among visually similar fruits. In conclusion, the EfficientNetB0-based model demonstrates high accuracy, balance, and computational efficiency. It is ideal for integrating interactive visual learning tools to enhance concept recognition in educational settings, particularly among early learners.
Co-Authors Annurulloh, Anugrah Dwi At-Thoriq, Muhammad Fadilah, Azki Faisal, Moch Rizky Fatimah, Rahma Siti Fawaz, Azriel Al Hamzah, Doni Iskandar, Rio Januar Khoerudin, Muhammad Maharani, Windy Putri Mardiana, Dindin Nurjaman, Muhammad Ilyas Nurlatifah, Hilda Prasetiowati, Lulu Ramadhan, Asep Shantika Ridwan, Ridwan Saumi, Lea Siti SRI RAHAYU Subagja, Moh Yahman Subarkah, Adie Torik, Givari Zabal