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All Journal Media Statistika JURNAL SISTEM INFORMASI BISNIS Telematika : Jurnal Informatika dan Teknologi Informasi Seminar Nasional Informatika (SEMNASIF) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) bit-Tech G-Tech : Jurnal Teknologi Terapan International Journal of Advances in Data and Information Systems ESTIMASI: Journal of Statistics and Its Application Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Nusantara Science and Technology Proceedings Jurnal Teknik Informatika (JUTIF) Journal of Technology and Informatics (JoTI) International Journal of Data Science, Engineering, and Analytics (IJDASEA) International Journal Of Computer, Network Security and Information System (IJCONSIST) Journal of International Conference Proceedings Journal of Data Mining and Information Systems Parameter: Jurnal Matematika, Statistika dan Terapannya Jurnal PETISI (Pendidikan Teknologi Informasi) Joong-Ki
Kartika Maulida Hindrayani
Faculty Of Computer Science, Universitas Pembangunan Nasional “Veteran” Jawa Timur, Surabaya 60294, Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology

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Journal : bit-Tech

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Intelligent Detection of Spermatozoa Motility Using YOLOv5: Toward Efficient and Accurate Male Fertility Analysis Christina Halim; Wahyu Syaifullah JS; Kartika Maulida Hindrayani; I Gede Susrama Mas Diayasa
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.3231

Abstract

Detecting multiple spermatozoa in microscopic videos remains a complex challenge due to their small size, high velocity, frequent overlap, and inconsistent illumination. This study introduces an enhanced real-time detection framework using the YOLOv5 deep learning algorithm, representing a significant advancement over previous Computer-Assisted Sperm Analysis (CASA) systems that primarily relied on classical image processing or earlier YOLO versions (e.g., YOLOv3, YOLOv4). Unlike these predecessors, the proposed YOLOv5-based model integrates Cross Stage Partial (CSP) architecture and optimized feature pyramid networks, allowing for superior detection of small, fast-moving spermatozoa with reduced computational complexity and model size. A curated dataset of sperm motility videos was processed through standardized steps—frame extraction, contrast enhancement, and manual annotation—to ensure uniformity and data quality. The model, trained via transfer learning on images of 640×640 pixels over 50 epochs, achieved a precision of 0.6333, recall of 0.627, and mAP@0.5 of 0.618, while maintaining real-time performance at 93 frames per second (FPS). Compared to YOLOv4, the proposed framework reduced training time by two-thirds (from 3 hours to 1 hour) and decreased model size from 244 MB to 13.8 MB, without compromising accuracy. These improvements establish YOLOv5 as a lightweight and scalable AI model for sperm detection, enabling automated, objective, and reproducible motility assessment. Clinically, this approach enhances the precision and consistency of male fertility diagnostics, paving the way toward AI-driven reproductive health evaluation and more accessible fertility screening solutions in both advanced and resource-limited laboratory settings.
Comparison of the Effectiveness IndoBERT and mBERT for Sentiment Analysis of SME Customer Reviews Selena Nurmanina Afandy; Kartika Maulida Hindrayani; Aviolla Terza Damaliana
bit-Tech Vol. 8 No. 3 (2026): bit-Tech - IN PROGRESS
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3501

Abstract

This study presents a structured comparative evaluation of IndoBERT and Multilingual BERT (mBERT) for three-class sentiment classification of customer reviews from Pawonkoe Banyuwangi, an Indonesian small and medium-sized enterprise (SME). Motivated by the limited transferability of IndoNLU-style benchmarks to real SME feedback, the central question is whether monolingual versus multilingual transformers remain reliable when fine-tuned on small, domain-specific, and operationally noisy datasets. A total of 365 survey-based reviews (January–December 2024), which is substantially smaller than typical transformer fine-tuning corpora, served as the empirical basis. Models were fine-tuned under matched hyperparameters and evaluated using a single stratified hold-out train–test split (not cross-validation), reporting accuracy, precision, recall, and F1-score. To reflect the deployed pipeline, mBERT additionally incorporates the original 1–5 rating as an auxiliary numeric signal alongside the review text, whereas IndoBERT is trained on text only. The results reveal a substantial performance gap: mBERT achieved 81% test accuracy, whereas IndoBERT reached 48% under the same evaluation setting. Because the label distribution is strongly imbalanced (with very few negative instances), these aggregate scores should be interpreted as overall effectiveness rather than minority-class robustness. Overall, the findings indicate that multilingual representations combined with auxiliary rating information can generalize more effectively in low-resource SME scenarios, while IndoBERT appears more sensitive to data scarcity in this context. The study offers practical guidance for model selection in resource-constrained Indonesian sentiment analytics and contributes evidence on transformer behavior beyond curated benchmarks.
Co-Authors Adhigiadany, Chelsea Ayu Afidria, Zulfa Febi Ahmad, Davin Anezta Aisyah Kirana Putri Isyanto Alfiansyah , Achmad Dzulfiqar Altetiko, Faizal Johan Alzam, Muhammad Arsyad Amelia, Meisya Vira Amri Muhaimin Aviolla Terza Damaliana Azizah, Alisa Jihan Betty Dewi Puspasari Bhalqis, Anissa Andiar Brescia Ayundina Yuniarossy Budi, Aditya Septa Burhan Syarif Acarya Christina Halim Christina, Enzelica Vica Damaliana, Aviolla Terza Diyasa, I Gede Susrama Mas Dwi Arman Prasetya Elmaliyasari, Shifa Eristya Maya Safitri Fahrudin, Tresna Maulana Fajar Ramadhani Fernando, Moch. Firman I Gede Susrama Mas Diayasa idhom, Mohammad Imelda Widya Ningrum Isyanto, Aisyah Kirana Putri Jauharis Saputra, Wahyu Syaifullah Kartini Kartini Made Hanindia Prami Swari Maulana F, Tresna Mohammad Idhom Ningrum, Imelda Widya Ningrum, Lisya Septyo Nur Aini Rakhmawati Pakpahan, Vera Febrianti Pratiwi, Nanda Aulia Prismahardi Aji Riyantoko Purwadwika, Reza Sadiya Putri, Milla Akbarany Baktiar Putro, R. Kokoh H. rachmanto, Nugroho Fajar Riskiyah, Ameliyah Risnaldy Novendra Irawan Riyantoko, Prismahardi Aji Rizkiyah, Selly Rizqin, Indira Zein Safira, Alya Mirza Saputra, Wahyu S. J. Saputra, Wahyu Syaifullah Jauharis Selena Nurmanina Afandy Shindi Shella May Wara Tresna Maulana F Tresna Maulana Fahruddin Tresna Maulana Fahrudin Tresna Maulana Fahrudin Trimono Trimono, Trimono Wahyu Syaifullah JS Wardati, Nanda Kurnia Wibowo, Muhammad Bagas Satrio