Deteksi Anomali Konduktivitas Air Menggunakan Kalman Filter

Wahyu Sukestyastama Putra; Muhammad  Koprawi; Wahid Miftahul  Ashari; Jeki  Kuswanto

doi:10.12928/biste.v4i1.6188

Authors

Wahyu Sukestyastama Putra Universitas Amikom Yogyakarta
Muhammad Koprawi Universitas Amikom Yogyakarta
Wahid Miftahul Ashari Universitas AMIKOM Yogyakarta
Jeki Kuswanto Universitas AMIKOM Yogyakarta

DOI:

https://doi.org/10.12928/biste.v4i1.6188

Abstract

Water quality is an essential part of shrimp farming. Data integrity is one of the challenges in building a water conductivity monitoring system. Data read by the sensor should represent the physical conditions that occur. However, some factors can cause abnormal data changes. This abnormal data change can occur due to sensor damage or an attempt to sabotage the pool. In this study, a data anomaly detection algorithm was built using the Kalman filter and standard deviation to solve the problem of determining the normal range of data. The designed algorithm was then tested and evaluated using Arduino nano, Arduino mega, and Wemos D1 Microcontrollers to determine the algorithm's performance on limited computing devices. Based on the data analysis that has been carried out, it is found that the anomaly detection algorithm based on the Kalman filter has an accuracy of 92.5% and can detect anomaly data that occurs with TPF = 1 and FNR = 0 values. The implementation of the detection algorithm on the microcontroller shows that WEMOS D1 (ESP8266) has an excellent average computational speed of 27.99 us. As for the stability of the Arduino Nano (ATMEGA328) and Arduino Mega 2560 (ATMEGA 2560) microcontrollers, the computation time deviation is about 2.8 us.

Kualitas air merupakan bagian penting pada budidaya udang. Salah satu tantangan dalam membangun sebuah sistem monitoring konduktivitas air adalah Keutuhan data. Suatu data yang terbaca oleh sensor seharusnya mewakili kondisi fisik yang terjadi. Akan tetapi ada faktor-faktor dapat menyebabkan perubahan data yang tidak wajar. Perubahan data yang tidak wajar ini dapat terjadi karena disebabkan kerusakan sensor maupun adanya upaya sabotase pada kolam. Pada penelitian ini dibangun sebuah algoritma deteksi anomali data menggunakan Kalman filter dan standar deviasi untuk mengatasi masalah penentuan rentang data normal. Algoritma yang dirancang kemudian diuji dan dievaluasi dengan menggunakan Mikrokontroller Arduino nano, Arduino mega dan Wemos D1 untuk mengetahui performa algoritma yang dirancang pada perangkat komputasi terbatas. Berdasarkan analisis data yang telah dilakukan didapatkan hasil bahwa algoritma deteksi anomali berbasis kalman filter memiliki akurasi 92,5% dan dapat mendeteksi data anomali yang terjadi dengan nilai TPF =1 dan FNR=0. Implementasi algoritma deteksi pada mikrokontroller menunjukkan bahwa WEMOS D1 (ESP8266) memiliki rata-rata kecepatan komputasi yang baik yaitu 27,99 us. Sedangkan untuk kestabilan mikrokontroller Arduino Nano (ATMEGA328) dan Arduino Mega 2560 (ATMEGA 2560) memiliki deviasi waktu komputasi sekitar 2,8 us.

Author Biography

Wahyu Sukestyastama Putra, Universitas Amikom Yogyakarta

SCOPUS: 57190380841

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