Polynomial Regression Model Utilization to Determine Potential Refuse-Derived Fuel (RDF) Calories in Indonesia

Luqman Luqman (), Sarifuddin Madenda and Prihandoko Prihandoko
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Luqman Luqman: Faculty of Energy Telematics, Institut Teknologi PLN, Jakarta 11750, Indonesia
Sarifuddin Madenda: Department of Information Technology, Gunadarma University, Depok 16424, Indonesia
Prihandoko Prihandoko: Department of Information Technology, Gunadarma University, Depok 16424, Indonesia

Energies, 2023, vol. 16, issue 20, 1-14

Abstract: Waste-to-energy (WTE) is one of the Indonesian government’s programs aiming to meet the target of achieving a new and renewable energy (NRE) mix, as well as one of the solutions proposed to overcome the problem of waste. One of the products of WTE is energy derived from raw material waste (refuse-derived fuel/RDF). Using the formula y = 0.00003 x 5 − 0.0069 x 4 + 0.6298 x 3 − 24.3245 x 2 + 432.8401 x + 55.7448 with R 2 = 0.9963, which was obtained by comparing a scatter plot diagram from the RDF calorie test dataset produced through a bio-drying process, the potential RDF calories produced using the waste composition dataset taken from each region in Indonesia can be calculated. The results of the calculations using the determined equations produce a list of provinces with RDF calorie potential, ordered from the largest to the smallest, using which the government can determine which areas are the main priority for processing waste into energy. Thus, through this method, the target of 5.1% renewable energy sourced from waste can be achieved by 2025.

Keywords: polynomial regression; prediction model; renewable energy; refuse-derived fuel; waste to energy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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