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All Journal RABIT: Jurnal Teknologi dan Sistem Informasi Univrab
Rujianto Eko Saputro
Amikom Purwokerto University
Computer Science & IT Engineering

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DETEKSI DINI KATARAK BERBASIS CITRA MATA MENGGUNAKAN METODE DEEP LEARNING CONVOLUTIONAL NEURAL NETWORK (CNN): EARLY DETECTION OF CATARACT BASED ON EYE IMAGES USING DEEP LEARNING METHOD: CONVOLUTIONAL NEURAL NETWORK (CNN) Anindya Novia Ramadani; Rujianto Eko Saputro
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.7914

Abstract

Cataract is one of the leading causes of visual impairment that requires early detection to prevent more severe conditions. This study aims to develop an image classification model based on Convolutional Neural Network (CNN) using the EfficientNetB0 architecture with a transfer learning approach and progressive training strategy to distinguish between normal and cataract eye images. The dataset used was obtained from Kaggle, consisting of two classes, namely normal and cataract eye images, which were then processed through preprocessing stages including resizing, normalization, and data augmentation. The dataset was divided into training and validation data with a ratio of 80:20. The model was trained in two stages, where Stage 1 involved freezing the entire EfficientNetB0 base model, and Stage 2 applied fine-tuning on selected layers to improve performance. The experimental results show that the model achieved a validation accuracy of 87.60% with a loss value of 0.3742. Evaluation using precision, recall, and F1-score indicates that the model performs relatively balanced, but shows better performance in recognizing normal eye images compared to cataract images. This is reflected in the higher recall value for the normal class and the relatively high false negative rate in the cataract class. In conclusion, the proposed CNN model based on EfficientNetB0 is capable of classifying cataract and normal eye images; however, further improvements in dataset size, model architecture, and training strategy are required to achieve better performance for reliable medical-based early detection systems.
IMPLEMENTASI MOTION GRAPHIC PADA ANIMASI 'AKSI 3M PLUS' MENGENAI PENCEGAHAN PERKEMBANGBIAKAN NYAMUK AEDES AEGYPTI : IMPLEMENTATION OF MOTION GRAPHICS IN THE ANIMATION "AKSI 3M PLUS" ON THE PREVENTION OF AEDES AEGYPTI MOSQUITO BREEDING Viqki Nur Fajar; Rujianto Eko Saputro
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8088

Abstract

Dengue Hemorrhagic Fever (DHF) remains a significant public health issue caused by the transmission of the dengue virus through Aedes aegypti mosquitoes. One of the most effective prevention efforts is the implementation of the 3M Plus movement; however, information dissemination is still largely conducted through conventional media, which are often less engaging and interactive. This study aims to implement motion graphics in the animation entitled “Aksi 3M Plus” as an educational medium for preventing the breeding of Aedes aegypti mosquitoes. The research employed the ADDIE development model, consisting of Analysis, Design, Development, Implementation, and Evaluation stages. The analysis stage involved identifying media requirements through interviews with the Banyumas Health and Family Planning Office. The design stage produced storyboards and visual asset concepts. During the development stage, vector-based visual assets were created and colored. Motion graphics were implemented using the CapCut application by applying keyframe animation techniques to create dynamic visual movements. The evaluation stage was conducted using the Alpha Testing method involving a subject matter expert and an animation expert. The evaluation results achieved an average score of 92.06%, categorized as excellent. Therefore, the “Aksi 3M Plus” motion graphic animation is considered suitable as an educational medium for DHF prevention.
Co-Authors Anindya Novia Ramadani Viqki Nur Fajar