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All Journal Jurnal Sains, Teknologi dan Komputer
Muhammad Havis Hidayat
Universitas Muhammadiyah Sumatera Utara
Agriculture, Biological Sciences & Forestry Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Development of an iot-based starfruit ripeness detection system using esp32-cam and a weight sensor Muhammad Havis Hidayat; Halim Maulana
Jurnal Sains, Teknologi & Komputer Vol. 3 No. 2 (2026): Jurnal Sains, Teknologi & Komputer (SAINTEK)
Publisher : Lembaga Riset Mutiara Akbar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/saintek.v3i2.1317

Abstract

Starfruit (Averrhoa carambola L.) is a horticultural commodity with potential for development in export markets. However, manual postharvest sorting may result in errors and inconsistencies in determining fruit ripeness and size. This study aims to develop an automatic system for detecting the ripeness and size of starfruit using an ESP32-CAM, a weight sensor (load cell and HX711), a Convolutional Neural Network (CNN) algorithm, and the Internet of Things (IoT). The system determines the size category based on fruit weight according to SNI 4491:2009, while fruit images are processed using a CNN to classify ripeness into three categories: unripe, partially ripe, and fully ripe. The classification results are transmitted in real time via Telegram. Testing on 30 samples showed that the CNN achieved an accuracy of 86.6%, while the load cell sensor produced an average measurement error of approximately 1–2%. These results indicate that the system is capable of automatically sorting starfruit based on ripeness and size while enabling remote monitoring of the results. The system has the potential to improve sorting consistency and support starfruit quality management in accordance with established standards.
Co-Authors Halim Maulana