Rancang Bangun Sistem Pemantauan Warna Produk Minyak Goreng Berbasis IoT

Hanan, Harish (2025) Rancang Bangun Sistem Pemantauan Warna Produk Minyak Goreng Berbasis IoT. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Kualitas minyak goreng merupakan salah satu indikator penting dalam industri pangan, terutama bagi usaha mikro, kecil, dan menengah (UMKM) di Indonesia. Salah satu tantangan utama dalam menjaga mutu minyak goreng adalah penurunan kualitas akibat pemakaian berulang, yang ditandai oleh perubahan warna dan peningkatan kekeruhan. Penilaian secara manual tidak hanya bersifat subjektif tetapi juga rawan kesalahan. Untuk mengatasi masalah tersebut, penelitian ini merancang sistem pemantauan warna dan kekeruhan minyak goreng berbasis Internet of Things (IoT) yang bekerja secara otomatis dan real-time. Sistem ini mengintegrasikan sensor warna TCS3200 dan sensor kekeruhan optik dengan mikrokontroler ESP32. Data yang diperoleh dari sensor dikirim melalui konektivitas Wi-Fi dan ditampilkan pada aplikasi Android kotlin, memungkinkan pemantauan jarak jauh dan efisien. Penelitian dilakukan dengan menguji beberapa sampel minyak goreng, baik yang baru maupun yang telah digunakan, guna mengetahui akurasi dan performa sistem. Hasil pengujian menunjukkan bahwa sensor kekeruhan bekerja dengan sangat baik. Pada minyak baru yang jernih, sensor menunjukkan akurasi hingga 99% tanpa error. Bahkan saat digunakan pada minyak bekas yang lebih keruh, akurasi tetap tinggi, berkisar 97–99%. Untuk pengukuran warna, sensor mampu menangkap perubahan nilai RGB, meskipun akurasi sedikit menurun pada sampel yang lebih keruh karena hamburan cahaya oleh partikel dalam minyak. Secara keseluruhan, sistem ini terbukti efektif dalam mendeteksi penurunan mutu minyak goreng. Teknologi ini berpotensi membantu UMKM melakukan kontrol kualitas secara lebih efisien, objektif, dan berbasis data.
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The quality of cooking oil is one of the important indicators in the food industry, especially for micro, small, and medium enterprises (MSMEs) in Indonesia. One of the main challenges in maintaining the quality of cooking oil is the degradation of quality due to repeated use, which is characterized by discoloration and increased turbidity. Manual assessment is not only subjective but also error-prone. To overcome this problem, this study designed an Internet of Things (IoT)-based cooking oil color and turbidity monitoring system that works automatically and in real-time. The system integrates a TCS3200 color sensor and an optical turbidity sensor with an ESP32 microcontroller. The data obtained from the sensors is sent over Wi-Fi connectivity and displayed on the kotlin Android app, enabling remote and efficient monitoring. The research was carried out by testing several cooking oil samples, both new and used, to determine the accuracy and performance of the system. The test results show that the turbidity sensor works very well. In the new clear oil, the sensor shows up to 99% accuracy with no errors. Even when used on cloudier waste oils, accuracy remains high, in the range of 97–99%. For color measurements, the sensor is capable of capturing changes in RGB values, although accuracy decreases slightly on cloudier samples due to light scattering by particles in oil. Overall, this system has proven to be effective in detecting a decline in the quality of cooking oil. This technology has the potential to help MSMEs carry out quality control more efficiently, objectively, and data-based.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Minyak goreng, IoT, kekeruhan, warna, pemantauan warna. Cooking oil, IoT, turbidity, color, color monitoring.
Subjects:	Q Science > QC Physics > QC271.8.C3 Calibration Q Science > QC Physics > QC389 Light--Transmission--Mathematical models. Q Science > QC Physics > QC475 Photoluminescence T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image processing--Digital techniques. Image analysis--Data processing.
Divisions:	Faculty of Vocational > Instrumentation Engineering
Depositing User:	Harish Hanan
Date Deposited:	06 Aug 2025 02:17
Last Modified:	07 Aug 2025 02:53
URI:	http://repository.its.ac.id/id/eprint/127683

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