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All Journal INTERNAL (Information System Journal) ISTEK
Aditia Gerhana, Yana
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Education Electrical & Electronics Engineering Other

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Klasifikasi Citra Ras Kucing Berbasis CNN dengan Metode MobileNet-V2 Hermawan, Ramadhan Anugrah; Taufik, Ichsan; Aditia Gerhana, Yana
INTERNAL (Information System Journal) Vol. 8 No. 1 (2025)
Publisher : Masoem University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32627/internal.v8i1.1390

Abstract

This study evaluates the performance of a Convolutional Neural Network (CNN) using the MobileNet-V2 architecture in classifying four cat breeds. The lack of public understanding in distinguishing cat breeds, especially due to the prevalence of mixed breeds, presents a significant challenge in accurate identification. The model was tested across multiple epochs to observe training and validation accuracy, aiming to assess its effectiveness and stability. Experimental results show that the highest validation accuracy of 93.81% was achieved at epoch 90. Although the model performed well, further optimization is needed to address overfitting and improve generalization capability. This research contributes to the development of an automated breed identification system that can be applied in education, adoption processes, and veterinary healthcare.
Implementation of Augmented Reality for Javanese Script Recognition Using FAST Corner Detection Algorithm Sukma Kanugrahan, Panji; Aditia Gerhana, Yana; Rauda Ramdania, Diena
ISTEK Vol. 14 No. 1 (2025)
Publisher : Fakultas Sains dan Teknologi UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/istek.v14i1.2141

Abstract

The aim of this research is to design and develop an Augmented Reality (AR) application to help junior high school students learn and recognize Aksara Jawa by leveraging the FAST Corner Detection algorithm and Marker-Based Tracking techniques to enhance interactivity and engagement. Using AR technology, students can explore Aksara Jawa characters in an engaging way, with 3D objects displayed in real time as they scan designated markers. The research methodology involves literature review, observation, and interviews with educators, while the application development follows the Multimedia Development Life Cycle (MDLC) to ensure quality. Testing shows the application accurately detects markers and displays 3D objects for the intended characters, and feedback from both teachers and students confirms its effectiveness and appeal. Further development of features and content is recommended to make the application even more beneficial and aligned with the needs of Aksara Jawa language education.
Co-Authors Hermawan, Ramadhan Anugrah Ichsan Taufik, Ichsan Rauda Ramdania, Diena Sukma Kanugrahan, Panji