Prediction of Electricity kWh Sales in Pontianak City Using Linear Regression Method

Rido Safaryansyah; Alda Cendekia Siregar; Istikoma

doi:10.59934/jaiea.v4i3.1011

Authors

Rido Safaryansyah Universitas Muhammadiyah Pontianak
Alda Cendekia Siregar Universitas Muhammadiyah Pontianak
Istikoma Universitas Muhammadiyah Pontianak

DOI:

https://doi.org/10.59934/jaiea.v4i3.1011

Keywords:

Prediction of kWh electricity sales, simple linear regression method, website based.

Abstract

This study presents the development of a web-based system to predict monthly electricity sales (in kWh) in the city of Pontianak using the Simple Linear Regression method. The main objective is to build a system capable of estimating electricity demand for the latest period and projecting the required kWh for the following month. The system uses 24 months of historical electricity sales data as the basis for prediction, allowing it to identify trends and patterns over time. After applying the regression calculation, the system predicted the next month's electricity sales to be 93,394,700 kWh. This result indicates that the system's prediction aligns with historical trends, demonstrating the model's reliability and potential accuracy. The relationship between the independent and dependent variables used in the model is linear and causal, making this method suitable for forecasting electricity consumption. Additionally, the system includes data visualization features on the website to enhance user understanding and simplify analysis. These visual tools help stakeholders to interpret predictions more effectively. Overall, the system serves as a practical and efficient solution to support electricity demand planning, resource management, and decision-making processes for local authorities and energy providers in Pontianak.

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