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All Journal Elimensi Journal of Electrical Engineering
Mohamad Jauharul Muhsin
Kadiri Islamic University
Automotive Engineering Computer Science & IT Electrical & Electronics Engineering Engineering Mechanical Engineering

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Design of Rhodamine-B Detection System for Ketchup Based on Internet of Things (IoT) Using TCS3200 and K-NN Mohamad Jauharul Muhsin; Diah Arie Widhining Kusumastutie; Danang Erwanto
Journal of Electrical Engineering Vol. 4 No. 01 (2026): Elimensi : Journal of Electrical Engineering
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/elimensi.v4i01.651

Abstract

Rhodamin B is a synthetic dye that is prohibited from being used in food because it can harm health. This study aims to design a Rhodamin B detection system in tomato sauce based on the Internet of Things (IoT) using TCS3200 color sensors and the K-Nearest Neighbor (K-NN) method. The sensor TCS3200 used to read the RGB value of the sauce sample that had been reacted using the Rhodamin B Test Kit, then the data was processed using the K-NN method to determine the classification results. The detection results are displayed on the LCD and sent to the Firebase Realtime Database using the ESP32 so that they can be monitored in real-time. This study used a dataset consisting of 250 training samples (divided into five Level 0 to Level 4 classes with 50 samples per class) and used 10 sauce samples and tested 3 times in each with a total of 30 tests. Based on the results of testing on various K values, the following accuracy levels were produced: K=1 (86.67%), K=3 (93.33%), K=5 (96.67%), and K=7 (93.33%). The K=5 value provided the best performance by accurately classifying 29 out of 30 test samples, of which only one sample was misclassified. In addition, the quality of lighting also affects the results of sensor readings so that it affects the classification process. Thus, the system is able to detect Rhodamin B in tomato sauce well and can be used as a practical IoT-based detection alternative.
Co-Authors Danang Erwanto Diah Arie Widhining Kusumastutie