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Komarudin, Agus
Universitas Jenderal Achmad Yani
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Deteksi Pneumonia Menggunakan Explainable AI: Model Hibrid CNN–ViT dan Grad-CAM Atika Hendryani; Vita Nurdinawati; Agus Komarudin
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 14 No 4: November 2025
Publisher : This journal is published by the Department of Electrical and Information Engineering, Faculty of Engineering, Universitas Gadjah Mada.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v14i4.19822

Abstract

Pneumonia detection through medical imaging presents a significant challenge, particularly in regions with limited access to healthcare professionals. This study presents an explainable artificial intelligence (XAI) model that integrates convolutional neural network (CNN) and vision transformer (ViT) to enhance the accuracy of pneumonia diagnosis using chest X-ray images. The proposed research aims to enhance diagnostic accuracy by providing explanations through gradient-weighted class activation mapping (Grad-CAM) visualization. The methodology includes image preprocessing, local feature extraction via CNN, and global spatial relationship modelling using ViT. The model was trained on a preprocessed chest X-ray dataset and evaluated using standard performance metrics such as accuracy, precision, recall, and F1 score. The proposed CNN-ViT model was assessed using chest X-ray datasets for pneumonia detection. The experimental results demonstrated that the model achieved an accuracy of 96.5%, precision of 96%, recall of 96%, and F1 score of 94%, These results indicate that the integration of CNN and ViT effectively enhances classification performance and provides a reliable tool for medical image analysis. Furthermore, Grad-CAM visualizations highlight the critical regions in the images that influence the model’s predictions, thereby enhancing interpretability. Compared to conventional models, this approach offers improved transparency in AI-driven diagnostics. Consequently, the proposed model represents a promising and reliable diagnostic tool, particularly beneficial in underserved or remote areas with limited medical infrastructure. Additionally, this research opens opportunities for the development of transparent and XAI-based diagnostic systems.
Komparasi Kinerja Model Machine learning Berbasis Metadata Produk untuk Prediksi Popularitas Produk Elektronik pada Marketplace Lazada Indonesia Aziz Apriadi, Eko; Komarudin, Agus; Julianto, Ribut
JURNAL ILMU KOMPUTER, SISTEM INFORMASI, TEKNIK INFORMATIKA Vol 5 No 1 (2026)
Publisher : PT Akom Media Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study explores the use of product metadata to predict the popularity of electronic products in the Lazada Indonesia marketplace. By using machine learning models, including Logistic Regression, Random Forest, and XGBoost, this study shows that simple metadata such as product category, brand, price, and rating are sufficiently informative to build predictive models. The results indicate that although Logistic Regression delivers the lowest performance due to its linear nature, both Random Forest and XGBoost provide significant improvement. XGBoost achieves the best results with the highest accuracy and F1-score, making it the most effective model for predicting product popularity. These findings highlight the complexity of e-commerce data, which requires more flexible models to capture non-linear patterns and interactions among product features. This study contributes to e-commerce management by providing insights into the use of machine learning for inventory management, promotional strategies, and product placement in digital marketplaces
GAME DESIGN EDUKASI PENGENALAN WISATA CIANJUR MENGGUNAKAN METODE MECHANICS DYNAMICS AESTHETICS Muhammad Aditya Putra; Agus Komarudin; Fatan Kasyidi
Jurnal Komputasi Vol. 12 No. 1 (2024): Jurnal Komputasi
Publisher : Jurusan Ilmu Komputer Fakultas MIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v12i1.252

Abstract

The development of educational games plays a crucial role as a means to introduce interesting tourist destinations in the era of technological advancement. In this research, the development of an educational game named "Cianjur Adventure" was conducted with the aim of introducing tourist attractions in Cianjur. The development of this game utilized the Mechanic Dynamics Aesthetics (MDA) Framework. The MDA Framework consists of three main components: mechanics, dynamics, and aesthetics. Mechanics represent specific rules or algorithms that guide the interaction between players and the game. Dynamics emerge as a result of these interactions, while aesthetics encompass the responses and experiences felt by the player. To assess the performance of this game, playtesting was conducted. The results of the testing indicate that the "Cianjur Adventure" game functions well and has successfully achieved its primary goal, which is to provide information related to tourism in Cianjur. By using this game, players can experience an engaging adventure and gain deeper knowledge about tourist destinations in Cianjur.
Co-Authors Ade Kania Ningsih, Ade Kania Ade Kanianingsih Aditya Prakasa Aek Mustofa Aghnie Kurnia Aini Nurul Akhmadi Surawijaya Al Farisi, Muhammad Farid Alda Amorita Azza Alfarizi, Muhammad Bayu Ardi Asep Id, Hadiana Atika Hendryani Azhari, Anissa Azzahra, Bunga Juliana Bambang Suparapto Damayanti, Ariesta Daswara Djajasasmita Dea Destiani Deka P Gustiawan Denny Hidayat Tri Nugroho Devian, Devian Dewi Purnamasari Diansyah Andri Ramdhany Dimitri Mahayana Djamal, Esmeralda Contesa Eddie Khrisna Putra Edvin Ramadhan Erlangi, Fauzan Erlangi, Fauzan Erry Fuadillah Esmeralda C Djamal Esmeralda C Djamal Esmeralda C Djamal Esmeralda C. Djamal Esmeralda C. Djamal Esmeralda C. Djamal Esmeralda C. Djamal Fadilah, Vira Hasna Fahmi Yusron Fiddin Faiza Renaldi Faiza Renaldi, Faiza Fajri Rakhmat Umbara Farhan Fadilah Farid Purwanto Ferdi Zulkarnain Ferry Kurniawan Fitra Arifiansyah Galih Rakasiwi Gunawan Abdillah Gunawan Abdillah Gunawan Abdillah Gunawan Abdillah, Gunawan Hadiana, Asep Id Hadimas Aprilian, Doni Hafiz, Aliy Handayani, Indah Nursyamsi Hanif Abdul Aziz, Nabil Hardianto, Mohamad Aris Hartono, Rudi Ifo Wahyu Pratama Ike - Festiana Iman Muhdi Inggit Sumirah Irvan Herdiansyah Iskandar Iskandar Julianto, Ribut Kania Ningsih, Ade Kartika N Oktaviani Kasyidi, Fatan Kresna Septyana Ekaputra Krishna Putra, Eddie Kuncoro Buwono Kurniawan Ikhsan Kurniawan, Alexander Tommy Kurniawan, Fadhlika Kusuma Wardany M.Naufal Rafirhan Mandala, Muhamad Bintang Maulina, Ninda Melina Melina Mia Narulita Anggraeni Mohamad Aris Hardianto Muhammad Aditya Putra Muhammad Dwi Laksono Muhammad Iqbal Zulfikar Mulyasari, Cicik Rafka Muthoharoh, Luluk Nasy`an Taufiq Al Ghifari Nendra Cahya Permana Neni Nuraeni Nenza Nurfirmansyah Nisa, Khoirotun Novianti, Sri Hutamy Nuari Anisa Sivi Nugraha, Faisal Okta Nugraha, Faisal Okta Nugraha, Mochammad Ganjar Nur Muhammad Hasyim Nurhakim, Riri Qorib Nurputra, Windi Raihan Nurul Sabrina, Puspita Oki Iskandar Oryza Habibie Rahman P., Tacbir Hendro Pamungkas, Muhammad Putra Poppi Lodaya Pradana, Muhammad Rifqi Pramudjianto, Imam Wibowo Prima Nugraha Ramdani, Rahmat Muhamad Rasyid Ibnu Prasetyo Rezki Yuniarti Rezky Yuniarti Ridwan Ilyas Rifky Ekayama Rikarda, Willy Artanika Rikarda1, Willy Artanika Rizki Abdilah Rizkyawan, Ferdi Rozak Arief Pratama Sari, Reni Permata Sari, Wiwin Rita Sartika Dewi Selia Aysiah Septia Wahyuni Setyawati, Astri Sivi, Nuari Anisa Sopwatun Anisa Sri Hutamy Novianti Susana, Ernia Tacbir Hendro Pudjiantoro Vita Nurdinawati Wahidah, Nina Ikhwati Wahyu Eko Zulianto Wardani, Mathilda Fitri Wina Witanti Wina Witanti Wini Afrilia Wirajaya Putra, Basudewa Yajid Ichsan Syifa Yanuar, Muhammad Rizki Yulison H. Crisnanto Yulison Herry Chrisnanto