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SISTEM MONITORING KUALITAS MINYAK JELANTAH SEBAGAI BAHAN BAKU BIODIESEL BERBASIS INTERNET OF THINGS
Minyak jelantah memiliki potensi besar sebagai bahan baku biodiesel untuk mengurangi ketergantungan bahan bakar fosil dan mengatasi limbah lingkungan. Namun, produksi biodiesel memerlukan pengendalian mutu ketat pada parameter kritis seperti kadar air, kekeruhan, dan densitas. Sistem monitoring manual menunjukkan kelemahan signifikan seperti kesalahan manusia, ketidakmampuan menyajikan data real-time, dan kesulitan analisis data historis. Diperlukan sistem monitoring otomatis yang dapat mengukur parameter kualitas minyak jelantah secara presisi dan real-time. Merancang dan mengembangkan sistem monitoring kualitas minyak jelantah berbasis Internet of Things (IoT) yang dapat memantau parameter kualitas secara real-time dengan akurasi tinggi. Penelitian menggunakan metode eksperimen dengan sistem berbasis IoT yang mengintegrasikan mikrokontroler ESP32, sensor Load Cell HX711 (pengukuran berat), sensor ultrasonik HC-SR04 (pengukuran volume), dan sensor LDR LM393 (kekeruhan). Data diproses dan dikirim ke platform Blynk dengan validasi standar SNI 7182:2015. Sistem mencapai akurasi tinggi dengan error rata-rata <1% untuk pengukuran berat dan volume. Sensor Load Cell mencapai akurasi ±99,81% dengan error 0,15%. Pengujian sampel menunjukkan minyak mentah tidak memenuhi standar SNI (densitas 480 kg/ml, intensitas cahaya 823,3 Lux) dengan status Tidak layak, sedangkan minyak terfilter layak (densitas 862,22 kg/m³, intensitas cahaya 975 Lux). Sistem monitoring berbasis IoT berhasil diimplementasikan dengan akurasi tinggi dan kemampuan real-time monitoring. Sistem mampu menentukan kelayakan minyak jelantah sesuai standar SNI, memberikan solusi efektif untuk mendukung produksi biodiesel berkelanjutan. Used cooking oil has great potential as a biodiesel feedstock to reduce dependence on fossil fuels and address environmental waste. However, biodiesel production requires strict quality control over critical parameters such as water content, turbidity, and density. Manual monitoring systems show significant weaknesses such as human error, inability to present real-time data, and difficulty analyzing historical data. An automated monitoring system is needed that can precisely and in real-time measure the quality parameters of used cooking oil. Designing and developing a real-time waste cooking oil quality monitoring system based on the Internet of Things (IoT) that can monitor quality parameters with high accuracy. The research uses an experimental method with an IoT-based system that integrates the ESP32 microcontroller, the HX711 Load Cell sensor (weight measurement), the HC-SR04 ultrasonic sensor (volume measurement), and the LM393 LDR sensor (turbidity). Data is processed and sent to the Blynk platform with standard SNI 7182:2015 validation. The system achieves high accuracy with an average error of <1% for weight and volume measurements. The Load Cell sensor achieves an accuracy of ±99.81% with an error of 0.15%. Sample testing showed that the crude oil did not meet SNI standards (density 480 kg/ml, light intensity 823.3 Lux) and was deemed unsuitable, while the filtered oil was suitable (density 862.22 kg/m³, light intensity 975 Lux). The IoT-based monitoring system was successfully implemented with high accuracy and real-time monitoring capabilities. The system is capable of determining the suitability of used cooking oil according to SNI standards, providing an effective solution to support sustainable biodiesel production.
KODEPRODI56203#Pendidikan Teknik Otomasi Industri dan Robotika_S1, Universitas Pendidikan Indonesia
SISTEM MONITORING KUALITAS MINYAK JELANTAH SEBAGAI BAHAN BAKU BIODIESEL BERBASIS INTERNET OF THINGS (Text)
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TK Electrical engineering. Electronics Nuclear engineering