Rancang Bangun Sistem Pemantauan dan Forecasting Konsumsi Energi Listrik Menggunakan Internet of Things dan Algoritma Seasonal Time Series

Haykal, Fikri (2022) Rancang Bangun Sistem Pemantauan dan Forecasting Konsumsi Energi Listrik Menggunakan Internet of Things dan Algoritma Seasonal Time Series. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Bangunan kantor maupun gedung kampus seperti di Institut Teknologi Sepuluh Nopember menggunakan energi listrik yang tentunya tidak sedikit. Setiap gedung memiliki banyak sumber listrik sehingga sulit untuk memantau konsumsi energi listrik secara mendetail yang bisa saja menyebabkan pemborosan konsumsi energi listrik.
Pengembangan sebuah sistem monitoring akan membantu untuk memudahkan pemantauan konsumsi energi listrik. Implementasi sistem bisa disesuaikan dengan titik mana saja maupun perangkat apa saja yang akan dipantau. Dalam pengembangannya, dibuat juga sebuah sistem forecasting yang memungkinkan untuk memprediksi konsumsi listrik selama 30 hari kedepannya. Sistem deteksi anomali tentunya akan membantu proses penghematan konsumsi listrik dengan memberi notifikasi apabila suatu titik menggunakan daya yang tidak semestinya.
Penggunaan prinsip Internet of Things menjadi kunci utama dalam cara kerja alat dalam sistem ini. Platform website digunakan untuk mengembangkan antarmuka utama dari sistem, dan dibangun dengan framework CodeIgniter 4. Algoritma seasonal digunakan untuk melakukan forecasting dan juga akan berguna untuk sistem deteksi anomali. Klasifikasi konsumsi daya dibedakan menjadi tiga, yaitu konsumsi normal, konsumsi tinggi serta konsumsi tidak wajar.
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Office and campus buildings, such as the Sepuluh Nopember Institute of Technology, use quite a bit of electrical energy. Every building has many sources of electricity so it is difficult to monitor the consumption of electrical energy in detail which can lead to waste of electricity consumption.
The development of a monitoring system will help to facilitate the monitoring of electrical energy consumption. The implementation of the system can be adjusted to any point or device to be monitored. In its development, a forecasting system is also made that allows to predict electricity consumption for the next 30 days. The anomaly detection system will certainly help the process of saving electricity consumption by giving notifications if a point uses improper power.
The use of the Internet of Things principle is the main key in how the tools in this system work. The website platform is used to develop the main interface of the system, and is built with the CodeIgniter 4 framework. Seasonal algorithms are used for forecasting and will also be useful for anomaly detection systems. The classification of power consumption is divided into three, namely normal consumption, high consumption and abnormal consumption.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	anomaly detection, codeigniter 4, energy monitoring, pzem-004t, seasonal forecasting, time series
Subjects:	T Technology > T Technology (General) > T174 Technological forecasting T Technology > T Technology (General) > T57.5 Data Processing
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information Technology > 59201-(S1) Undergraduate Thesis
Depositing User:	Fikri Haykal
Date Deposited:	19 Feb 2022 06:02
Last Modified:	31 Oct 2022 03:35
URI:	http://repository.its.ac.id/id/eprint/94578

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