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All Journal e-Jurnal Arus Elektro Indonesia CIRCUIT: Jurnal Ilmiah Pendidikan Teknik Elektro JBT (JURNAL BISNIS dan TEKNOLOGI) Indonesian Journal of Computing, Engineering, and Design Journal Zetroem JASEE Journal of Application and Science on Electrical Engineering Journal of Telecommunication, Electronics and Control Engineering (JTECE) TEKIBA : Jurnal Teknologi dan Pengabdian Masyarakat Skyhawk: Jurnal Aviasi Indonesia Jurnal Fortech SinarFe7 Journal of Science Technology (JoSTec) Logic : Jurnal Rancang Bangun Dan Teknologi Journal of Educational Engineering and Environment Media Elektrik Jurnal FORTECH Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Journal of Renewable Energy and Smart Device
Charis Fathul Hadi
Universitas PGRI Banyuwangi
Agriculture, Biological Sciences & Forestry Arts Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences Other

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The Design of an Integrated IoT and Artificial Intelligence System forFish Quality Degradation Diagnosis Fathul Hadi, Charis; Mutamimah, Dewi; Hidayat, Firman
Circuit: Jurnal Ilmiah Pendidikan Teknik Elektro Vol. 10 No. 1 (2026)
Publisher : PTE FTK UIN Ar-Raniry

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/6kcj8y61

Abstract

In post-harvest handling, fish quality assessment is typically carried out using traditionalsensory observations, which are potentially resulting in inconsistent diagnoses.Furthermore, prior research has not fully integrated the Internet of Things (IoT) withartificial intelligence for fish quality diagnostics, and it frequently concentrates on asingle quality metric. This study aims to design and evaluate an integrated system basedon IoT and artificial intelligence using a Case-Based Reasoning (CBR) approach fordiagnosing fish quality degradation. The developed system utilizes IoT-based sensors tomonitor physicochemical parameters, such as temperature, pH, and gas indicators, withreal-time data transmission to a cloud platform. The collected data are analyzed using aCBR model as a decision support system. Performance evaluation was conducted using120 testing data under controlled storage conditions and validated through expert assessment. The results show that the system achieves a diagnostic accuracy of 92.5%,with precision of 91.8%, recall of 93.2%, and an F1-score of 92.5%. In addition, the system has an average data transmission latency of 0.87 seconds, enabling near real-time diagnosis. These findings indicate that the system provides accurate and efficient diagnosis of fish quality degradation and supports post-harvest quality management. 
An Intelligent Case Based Reasoning Approach for Diagnosing Fish Quality Decline Using IoT Charis Fathul Hadi; Dewi Mutamimah; Firman Hidayat
Journal of Renewable Energy and Smart Device Vol. 4 No. 1 August 2026
Publisher : PT. Global Research Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66314/joresd.v4i1.731

Abstract

Indonesia ranks as one of the world’s largest fish producers, with an annual production of 6.54 million tons. Among the most economically valuable marine commodities is scad fish (Decapterus spp.). However, fish quality deterioration remains a major challenge due to environmental conditions, post-harvest handling, and inadequate storage methods. This study integrates Internet of Things (IoT) technology and Case-Based Reasoning (CBR) to diagnose fish quality deterioration in real time. Data were collected over a 24-hour period using IoT sensors that monitored temperature, humidity, pH, and ammonia levels. The CBR algorithm compared sensor data with historical cases through similarity measurements to provide diagnostic outcomes. Results indicate that between 07:00 and 09:00, fish maintained freshness (pre-rigor stage) with a similarity of 96.66%. However, quality decreased significantly from 12:00 to 06:00, reaching a similarity of 71.06% at 06:00. Findings highlight that temperature and ammonia levels are key factors driving spoilage, while humidity accelerates microbial growth and pH variation reflects rigor and post-rigor phases. The proposed system achieved a diagnostic accuracy of 96.47% compared to expert evaluations. These results demonstrate the system’s reliability in monitoring fish quality and its potential application in seafood supply chains. By minimizing spoilage, the system provides both economic and societal benefits through improved food safety and distribution efficiency. This study contributes a practical and scalable approach for intelligent food monitoring systems.
Co-Authors Adi Mulyadi Adi Pratama Putra Adi Pratama Putra Agus Budi Santosa Agustin, Cici Ahmad Martin Yusa Ahmad Sulthoni Sulthoni Ananta, Viky Andre Ramadhan Anggagana, Dwi Gita Arif Fahmi Arif Setiawan Penulis Arya T Candra As’ari, Hasyim Bagus Pramono Bambang Sri Kaloko Bambang Suprianto . Burhanuddin Nur Dewi Mutamimah Dewi Sartika DEWI SARTIKA Dewi Sartika Dimas Priagung Banar Dwi Cahyo Kurniawan Fajar Alam Fery Ardiansyah Firman Hidayat Firman Hidayat Fita Lestari, Riska Fuad Ardiyansyah Hasan Basri Hasyim As'ari Ikhwanul Qiram Ikwanul Qiram Liswanto , Budi M.Najib Fikri Fadillah malik yuhanas Megandhi Gusti Wardhana Moh Anas Ridwan Mohamad Diki Mohamad Diki Mohammad Nurcholis Mokhamad Yani Muh Fainal Lawasi Muh. Fainal Lawasi Muhamad Khoirul Anam Muhammad Zainal Roisul A Muhammad Zainal Roisul Amin Muliyono Muliyono Muliyono Muliyono, Muliyono Mulyadi, Adi Nurmahmudy, Widie Nurullita, Hervina Prasetyo, Andiko Putra, Adi Pratama Ratna Mustika Yasi Rezki Nalandari Risk Fita Lestari Riska Fita Lestari Riska Fita Lestari Rizki Nafianto Pratama Sari, Dessy Ana Laila Siti Tsaniyatul Miratis Sulthoniyah Sutrisno, Viky Ananta Untung Suryadhianto Varied Agus Wahyu Triyanto Viky Ananta Sutrisno Wardatun Ni'mah Widhi Winata Sakti