Implementasi Metode Kalman Filter untuk Mengurangi Noise Pengukuran Sensor pH dan TDS Pada Sistem Monitoring Water Torrent

Nusantara, Yaafi' Pratama (2023) Implementasi Metode Kalman Filter untuk Mengurangi Noise Pengukuran Sensor pH dan TDS Pada Sistem Monitoring Water Torrent. Diploma thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Sistem monitoring water torrent merupakan sistem terintegrasi untuk memantau kualitas air yang tersimpan dalam unit penyimpanan air. Jangkauan pengamatan kualitas air yang dilakukan sistem monitoring water torrent mencakup nilai tingkat keasaman air (pH) dan total partikel dalam air atau Total Dissolved Solid (TDS). Dalam situasi nyata, nilai hasil pengukuran oleh sensor tidak secara mutlak dapat diandalkan. Terdapat fenomena yang mengakibatkan nilai pengukuran sensor berfluktuasi dengan derajat yang tidak konstan. Simpangan nilai yang tidak diinginkan tersebut disebut dengan noise. Interferensi nilai ukur akibat noise dialami seluruh sensor, tidak terkecuali sensor yang digunakan pada sistem monitoring water torrent. Noise menimbulkan dampak negatif, yaitu kesalahpahaman user dalam menafsirkan hasil deteksi sensor. Penelitian ini secara khusus menganalisis penerapan salah satu teknik penyaringan, yaitu Kalman Filter untuk mengurangi noise pengukuran sensor pH dan sensor TDS. Digunakan prototipe sistem monitoring water torrent dalam penelitian ini. Prototipe yang dirancang tersusun atas Arduino Nano (sebagai kontroler), sensor pH PH-4502C, dan sensor TDS DFRobot SEN0244. Seluruh nilai pengukuran yang diperoleh kemudian divisualisasikan pada sebuah LCD display. Komponen penyusun lain adalah wadah bervolume 750 cc sebagai prototipe unit penyimpanan air. Pengujian diawali dengan proses tuning metode Kalman Filter. Setelah kombinasi nilai paling efektif ditentukan, dilakukan komparasi nilai pengukuran sensor tanpa metode dan setelah implementasi Kalman Filter. Implementasi metode Kalman Filter mampu menekan nilai Mean Absolue Percentage Error (MAPE) yang disebabkan oleh noise pada pengukuran sensor TDS sebesar 3,22% dan pada pengukuran sensor pH sebesar 0,88%. Kalman Filter juga lebih efektif dalam menanggulangi simpangan pengukuran akibat noise dibandingkan dengan metode Moving Average Filter. MAPE Kalman Filter 0,29% lebih rendah pada pengukuran sensor TDS, dan 0,23% lebih rendah pada sensor pH, apabila dikomparasikan dengan hasil estimasi Moving Average Filter.
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Water torrent monitoring system is an integrated system to measure several parameters at the water reservoir unit. One of the measured parameter is water quality. The system observes the acidity (pH) and Total Dissolved Solid (TDS) of the stored water. Practically, measurement value acquired by a sensor is unreliable. Through detailed observation, there is a phenomenon that causing fluctuative sensor measurement value. This phenomenon is referred as a noise. Noise affected every sensor, including sensors used at water torrent monitoring system. Noise potentially deliver negative impacts to an established system, one of them is misinformation. Hence, scientific manipulation to reduce the amount of noise on a sensor measurement value is required in order to produce more reliable and precise information for the users. This study particularly analyse the implementation of a filtering technique, Kalman Filter, to reduce measurement noise on pH and TDS sensor. During the observation, Kalman Filter method is implemented on a prototype. The water torrent monitoring system prototype is constructed by Arduino Nano, pH sensor PH-4502C, TDS sensor DFRobot SEN0244, and a LCD display to visualize the measurement output. Kalman Filter able to reduce measurement error caused by noise, by 3,22% on TDS sensor, and 0,88% on pH sensor.

Item Type:	Thesis (Diploma)
Uncontrolled Keywords:	Sensor, Noise, pH, TDS, Pengukuran, Kalman Filter, Measurement
Subjects:	H Social Sciences > HA Statistics > HA31.7 Estimation T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3070 Automatic control T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK351 Electric measurements. T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7871.674 Detectors. Sensors
Divisions:	Faculty of Vocational > 36304-Automation Electronic Engineering
Depositing User:	Yaafi' Pratama Nusantara
Date Deposited:	07 Aug 2023 02:07
Last Modified:	07 Aug 2023 02:07
URI:	http://repository.its.ac.id/id/eprint/103643

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