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All Journal Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Infomedia MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Ilmu Komputer dan Bisnis Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Mitra Masyarakat (JPMM) SmartComp The Indonesian Journal of Computer Science
Majid Rahardi
Universitas Amikom Yogyakarta
Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Social Sciences Other

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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

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Comparative Analysis of EfficientNet-B0 and ViT-B16 for Multiclass Classification of Green Coffee Beans Syaputra, Muh. Rezky; Rahardi, Majid
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11563

Abstract

Green coffee bean classification plays an important role in the coffee supply chain, as bean quality has a direct impact on the taste and final quality of the product. The USK-Coffee dataset, which consists of four bean object classes defect, longberry, peaberry, and premium, is photographed under varied lighting conditions and capture angles, thus challenging the accuracy of conventional visual models. Although lightweight CNN models have been used, not many studies have directly compared transformer-based architectures (ViT-B16) and modern efficient CNNs (EfficientNet-B0) for green coffee bean classification under real conditions. With transfer learning strategy, image augmentation (resize, flip, rotation, color jitter, random crop), and normalization, we evaluate the performance of both models on the dataset. ViT-B16 achieved 85% accuracy on the test data (F1-score 0.85), with a fast batch inference latency of 0.0074 seconds per batch. EfficientNet-B0 achieved 87% accuracy (F1-score 0.87), with a slower batch latency (0.0106 seconds per batch). However, EfficientNet-B0 is significantly faster for single image inference (real-time) (0.035 seconds) compared to ViT-B16 (0.426 seconds). This trade-off higher accuracy/faster single inference on EfficientNet-B0 vs. faster batch processing on ViT-B16 shows that both are feasible for edge computing-based classification systems.
L2IC and MobileViT-XXS for BISINDO Alphabet Recognition Artamma, Chanan; Rahardi, Majid
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11575

Abstract

This study proposes a Landmark-to-Image Conversion (L2IC) approach integrated with the MobileViT-XXS architecture for Indonesian Sign Language (BISINDO) alphabet recognition. The method converts 42 hand keypoints, extracted using MediaPipe Hands into normalized 224×224 grayscale images to capture spatial hand patterns more effectively. These L2IC representations are then used as input to the MobileViT-XXS model, trained for 30 epochs with a learning rate of 0.001. Experimental results show that the model achieves an accuracy and Macro F1-Score of 97.98%, outperforming baseline approaches using raw RGB images and MLP-based classification on numerical keypoints. While the model demonstrates strong performance in controlled offline experiments, further evaluation is required to assess its robustness under real-world dynamic BISINDO usage and deployment on resource-limited devices. These findings indicate that the L2IC representation effectively captures essential spatial information, contributing to high recognition accuracy in static BISINDO hand gesture classification.
Co-Authors Abdulloh, Ferian Fauzi Afrig Aminuddin Alfian Difa’ul Amien Amelia, Hemas Anggita Andrika, Muhammad Yusuf Aristawidya, Winda Ardelia Artamma, Chanan Asadulloh, Bima Pramudya Bernadhed, Bernadhed Ekayanda, Gilang Elik Hari Muktafin Febianty, Dennita Noor Harianto, Fetrus Jari Indriyatmoko, Toto Joang Ipmawati Kusnawi Kusnawi Kusrini Kusrini Laiskodat, Fransisko Andrade Latupono, Ali Samsul Lefi, Nadia Martha M. Ikhsan Malik Bagaskara Mawar, Heni Sapta Mulia Sulistiyono Musthofa, Alif Nafiatun Sholihah Nandini, Kety Nolejanduma, Dionisius Nusaca Redegnosis Nur'aini, Linnda Prawidya Nurhayati, Lutfiana Deka Pandiangan, Van Daarten Rayadhani, Windy Aldora Rida, Rachmasari Annisa Rizqi Sukma Kharisma Rohmad Fajarudin Salim, Edwin Ibrahim Syaputra, Muh. Rezky Sylvester, Gunawan Toto Indriyatmoko Uyock Anggoro Saputro Vabilla, Sheila Anggun Yudha, Muhammad Agung Reza