Analysis of Indonesia^s Primary Energy Mix Using Analytical Hierarchy Process (AHP) and Linear Programming (LP) Methods

Tomi Nugroho1,a), Fadhil Mahdyrianto1,b), and Mixsindo Korra Herdyanti1,2,c)

Analysis of Indonesia^s Primary Energy Mix Using Analytical Hierarchy Process (AHP) and Linear Programming (LP) Methods
Tomi Nugroho1,a), Fadhil Mahdyrianto1,b), and Mixsindo Korra Herdyanti1,2,c)

1Department of Mining Engineering, Faculty of Mining and Petroleum Engineering, Institut Teknologi Bandung, Jl. Ganesa No.10, Lb. Siliwangi, Kecamatan Coblong, Kota Bandung, Jawa Barat 40132 , Indonesia
2 Mining Engineering Department, Faculty of Earth Technology and Energy, Universitas Trisakti, Jalan Kyai Tapa No. 1, Tomang, Grogol Petamburan, West Jakarta 11440, Indonesia

a) Corresponding author: tominugroho2281[at]gmail.com
b) fadhilrianto[at]gmail.com
c) mixsindokorra[at]trisakti.ac.id

Abstract

Global challenges in the energy sector are prompting countries to formulate more holistic and sustainable policies. In Indonesia, energy needs are supported by four main sources: coal, oil, gas, and new renewable energy (NRE). To determine the optimal energy mix, a Multi-Criteria Decision Making (MCDM) approach, such as the Analytical Hierarchy Process (AHP), is applied to primary energy policies. AHP serves as a guide in establishing energy mix proportions through the application of Linear Programming (LP). The primary goal of this study is to establish the best combination of energy mix for coal, oil, gas, and New Renewable Energy (NRE) in Indonesia. This research uses a quantitative approach with AHP and LP methods. Primary data were collected through questionnaires evaluated in the AHP, while secondary data were also used in the AHP evaluation and Benefit Cost Ratio (BCR) calculations. The study involved 23 experienced respondents from various energy sectors and used secondary data as criteria for AHP evaluation, supporting technical calculations to find the most optimal energy combination. The application of linear programming with the simplex method was used to determine the percentage of energy mix, where the objective function is to maximize the economics of each energy source by incorporating the results of AHP preferences. The results of the study show that the composition of the primary energy mix for coal is 35%, oil 15%, gas 20%, and New and Renewable Energy (NRE) 30%.

Keywords: Primary Energy Mix, Analytical Hierarchy Process, Benefit Cost Ratio, Linear Programming

Topic: Mineral and Energy Regulation and Economics