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All Journal MIND (Multimedia Artificial Intelligent Networking Database) Journal Society: Jurnal Pengabdian Masyarakat
Adli, Muhammad Arkan
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Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences

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Implementasi Game Pengenalan Binatang di TK Putra I Bandung Miftahuddin, Yusup; Kristiana, Lisa; Anindia, Hana Nathania; Sugiharto, Ariq Bagus; Adli, Muhammad Arkan; Nurrahmayanti, Fadhilah; Setiyawati, Setiyawati
Society : Jurnal Pengabdian Masyarakat Vol 4, No 1 (2025): Januari
Publisher : Edumedia Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55824/jpm.v4i1.511

Abstract

The animal recognition game application is designed to support interactive learning at TK Putra 1 Bandung, Arcamanik District, Bandung City. This application aims to provide an engaging learning experience where young children can learn about various animals, their habitats, sounds, and distinctive features. Interactive elements such as animal images, sounds, and videos are presented in an enjoyable way, allowing children to learn in an engaging and active manner. Features such as quizzes, clickable buttons, and animations support children’s engagement, enhance curiosity, and encourage active participation in the learning process. The application is also designed to make it easier for teachers and staff to deliver interactive content, ensuring that learning takes place in an enjoyable and effective manner.
Implementasi Game Pengenalan Binatang di TK Putra I Bandung Miftahuddin, Yusup; Kristiana, Lisa; Anindia, Hana Nathania; Sugiharto, Ariq Bagus; Adli, Muhammad Arkan; Nurrahmayanti, Fadhilah; Setiyawati, Setiyawati
Society : Jurnal Pengabdian Masyarakat Vol. 4 No. 1 (2025): Januari
Publisher : Edumedia Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55824/jpm.v4i1.511

Abstract

The animal recognition game application is designed to support interactive learning at TK Putra 1 Bandung, Arcamanik District, Bandung City. This application aims to provide an engaging learning experience where young children can learn about various animals, their habitats, sounds, and distinctive features. Interactive elements such as animal images, sounds, and videos are presented in an enjoyable way, allowing children to learn in an engaging and active manner. Features such as quizzes, clickable buttons, and animations support children’s engagement, enhance curiosity, and encourage active participation in the learning process. The application is also designed to make it easier for teachers and staff to deliver interactive content, ensuring that learning takes place in an enjoyable and effective manner.
Pendekatan Augmentasi Citra Fundus pada Model EfficientNet untuk Klasifikasi Tingkat Keparahan Retinopati Diabetik dengan Dataset Tidak Seimbang CHAZAR, CHALIFA; ADLI, MUHAMMAD ARKAN; PARDEDE, JASMAN; ICHWAN, MUHAMMAD
MIND (Multimedia Artificial Intelligent Networking Database) Journal Vol 10, No 2 (2025): MIND Journal
Publisher : Institut Teknologi Nasional Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/mindjournal.v10i2.180-194

Abstract

AbstrakRetinopati diabetik (RD) adalah komplikasi diabetes mellitus yang menyerang pembuluh darah retina dan berpotensi menyebabkan kebutaan jika tidak terdeteksi dini. Citra fundus retina berperan penting dalam mendeteksi serta mengklasifikasikan tingkat keparahan RD karena mampu menampilkan kelainan secara jelas. Tantangan utama dalam klasifikasi RD adalah ketidakseimbangan data antar kelas. Penelitian ini mengusulkan penggunaan EfficientNet-B0 dengan augmentasi gambar terarah pada dataset APTOS 2019. Hasil evaluasi menunjukkan peningkatan akurasi dari 73,84% menjadi 82,56% serta F1-score 0,8241. Peningkatan signifikan terlihat pada kelas minoritas, misalnya Mild dari 0,1429 menjadi 0,65 dan Severe dari 0,087 menjadi 0,4211. Temuan ini membuktikan bahwa augmentasi terarah efektif dalam mengurangi bias kelas mayoritas dan meningkatkan keandalan model.Kata kunci: augmentasi, EfficientNet, ketidakseimbangan kelas, retinopati diabetikAbstractDiabetic retinopathy (DR) is a complication of diabetes mellitus that affects the retinal blood vessels and may lead to blindness if not detected early. Fundus images play a crucial role in detecting and classifying the severity of DR as they clearly reveal pathological abnormalities. The main challenge in DR classification lies in the imbalance across severity classes. This study proposes the use of EfficientNet-B0 combined with targeted image augmentation on the APTOS 2019 dataset. The evaluation results show an improvement in accuracy from 73.84% to 82.56% and a F1-score of 0.8241. Significant gains are observed in minority classes, such as Mild (from 0.1429 to 0.65) and Severe (from 0.087 to 0.4211). These findings demonstrate that targeted augmentation is effective in reducing majority-class bias and improving model reliability.Keywords: class imbalance, data augmentation, diabetic retinopathy, EfficientNet 
Co-Authors Anindia, Hana Nathania Chazar, Chalifa Jasman Pardede KRISTIANA, LISA Miftahuddin, Yusup Muhammad Ichwan Nurrahmayanti, Fadhilah Setiyawati, Setiyawati Sugiharto, Ariq Bagus