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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Teknik Industri ASEAN Journal of Systems Engineering J@TI (TEKNIK INDUSTRI) Jurnal Rekavasi SITEKIN: Jurnal Sains, Teknologi dan Industri JURNAL PASTI (PENELITIAN DAN APLIKASI SISTEM DAN TEKNIK INDUSTRI) Jurnal Optimasi Sistem Industri Jurnal Ilmiah Teknik Industri JOURNAL OF INDUSTRIAL AND MANUFACTURE ENGINEERING Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Jurnal Teknik Industri : Jurnal Hasil Penelitian dan Karya Ilmiah dalam Bidang Teknik Industri Jurnal Mutu Pangan : Indonesian Journal of Food Quality International Journal of Advances in Data and Information Systems Jurnal Media Teknik dan Sistem Industri Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Optimasi Teknik Industri (JOTI) Industrika : Jurnal Ilmiah Teknik Industri Go-Integratif : Jurnal Teknik Sistem dan Industri Green Intelligent Systems and Applications Journal of Industrial Engineering and Halal Industries Spektrum Industri IJoICT (International Journal on Information and Communication Technology)
Achmad Pratama Rifai
Department Of Mechanical And Industrial Engineering, Universitas Gadjah Mada
Religion Agriculture, Biological Sciences & Forestry Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Public Health Transportation Other

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Real-Time Coffee Bean Defect Detection Based on SNI 01-2907-2008 Standards Using Lightweight YOLOv5s Architecture Nanda Aptana Irsyadul Bahy; Achmad Pratama Rifai
IJoICT (International Journal on Information and Communication Technology) Vol. 12 No. 1 (2026): Vol.12 No.1 Jun 2026
Publisher : School of Computing, Telkom University

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Abstract

Physical quality control of coffee beans in Indonesia, which relies heavily on manual sorting methods, has limitations in terms of consistency, time efficiency, and subjective observation. This study aims to develop an automated system for detecting physical defects in coffee beans using a Deep Learning-based Object Detection algorithm with the YOLOv5s architecture, aligned with SNI 01-2907-2008 regulations. Through a training mechanism that combined hyperparameter optimization and data augmentation across 20 defect classification classes, the developed model achieved robust generalization performance, with a global mAP@0.5 of 0.867 and a mAP@0.5-95 of 0.601. A prediction time evaluation of average 14 ms confirmed the model's capability for real-time sorting system implementation. However, a per-class metric decomposition analysis revealed performance heterogeneity, where the model showed superior accuracy on distinctive morphological features but struggled with texture bias and contrast ambiguity in minor defect classes and foreign materials. Crucially, the model's low computational demand presents a cost-effective solution for Small and Medium-sized Enterprises (SMEs), enabling the adoption of automated quality control without the need for expensive high-end hardware infrastructure. Overall, this study validates the effectiveness of YOLOv5 as an objective and standardized digital inspection instrument to support the modernization of the national coffee industry's post-harvest process.
Co-Authors Afrido Ainayyah Bintang Agista Akbar, Hafizh Naufaly Al Kautsar, M. Nurudduja Albab, Disya Amalia Ikhsani Ulil Aldyno, Achmad Farhan Alfarasyied Syahrizad Amirah Meutia Noorfadila Ananta, Vhysnu Satya Andiny Trie Oktavia Andri Nasution Anom , Mauli Ardyaksa Diptya Pramudita Arista Adriani Armaisya, Dimas Dwi Arulloh Sonja Asa Pragasel Natuna Asfandima, Ilhan Alim Astungkara, Arya Wijna Astungkatara, Arya Wijna Awal, Syifa Maulvi Zainun Azim, Ahmad Fadhil Basirun, Arif Reza Briliananda, Silvyaniza Buchari, Muhammad Achirudin Dawi Karomati Baroroh Devita Ayuni Kusumaningsih Evan Alvaro Radeva Fadilah, Andara Fahreza Baskara Hediandra Fath, Hamzah Fatiha Widyanti Fauzi, Rifqi Fransisca Astri Dianswari Gopal Sakarkar Hajad, Makbul Hans Bastian Wangsa Hans, Feishal Rey Hartanti, Sri Hasibuan, Narsico Rafael Hideki Aoyama Hikam , Azka Huu Tho, Nguyen Ihsan Ramadhana Jordiva Fernanda Junaidi, Faiza Ulinnuha Kafi, Mochamad Egidio Pramudya Khania O.P.P. Nugraha Korin, Filbert Kusumaningsih, Devita Ayuni Kusumastuti, Putri Adriani Ludwika, Adinda Sekar Manalu, Haposan Vincentius Mohamad, Rakan Raihan Ali Muchammad Ismail Muhammad, Audi Ziyad Afkar Muhtar , Dini Nanda Aptana Irsyadul Bahy Nandila, Alisyafira Sayyidina Naufal Nur Akmal Nguyen , Huu Tho Nguyen, Huu Tho Nguyen, Huu-Tho Nur Mayke Eka Normasari Nurraudah, Restu Oda, Ahlam Nauf Oktavia, Andiny Trie Pamungkasari, Panca Dewi Penchala, Sathish Kumar Permana, Ari Pohan, Rafi Naufal Al Mochtari Pratama, Dhika Wahyu Priansyah, Adi Prihatmaja, Dhonadio Aurell Azhar Puspadewa, Paskalis Krisna Puspitasari, Afifa Putra, Dimas Zaki Alkani Putri, Oktaviana Rabbani, Haidar Rachmadi Norcahyo Radhitya Virya Paramasuri Sunarso Rahmawatie, Noor Athiea Ramadhan, Fairuzzaky Safira, Aretha Safitri, Tari Hardiani Saifurrahman, Anas Saptomo, Amanat Bintang Sari Ningsih Sari, Dwi Kumala Sarudi As., L. M. Setiawan, Kevin Stephen Setyo Tri Windras Mara Shalehah, Mar’atus Sholihati, Ira Diana Susilo, Nazhifa Rahmi Sutoyo, Edi Syahdan Haris Abdilah Tama, Mradipta Nindya Tanaji, Irvantara Pradmaputra Thawafani, Lathiifah Tho, Nguyen Huu Valencia, Bella Renata Violita Anggraini Wangi Pandan Sari Wibisono, Ragil Aditya Windras Mara, Setyo Tri Wiraningrum, Rakyan Galuh Yana, Anak Agung Istri Anindita Nanda