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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Elektron Jurnal Ilmiah Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Journal of Applied Agricultural Science and Technology Jurnal Media Elektro : Journal of Electrical Power, Informatics, Telecommunication, Electronics, Computer and Control System Kilat Energi & Kelistrikan Jurnal Ilmiah Sutet Jurnal Teknik TERANG : Jurnal Pengabdian Pada Masyarakat Menerangi Negeri Indonesian Journal of Electrical Engineering and Computer Science Nusantara Journal of Multidisciplinary Science
Adri Senen
Institut Teknologi PLN
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering

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Journal : International Journal of Electrical and Computer Engineering

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Determination of biomass energy potential based on regional characteristics using adaptive clustering method Alvianingsih, Ginas; Hashim, Haslenda; Jamian, Jasrul Jamani; Senen, Adri
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i1.pp46-55

Abstract

Determining the energy potential of biomass is the first step in selecting the most suitable and efficient energy conversion technology based on regional characteristics. The approach to estimating and determining biomass potential generally uses geospatial technology related to collecting and processing data about mapping an area. Unfortunately, this method is inadequate for simulating the interaction between variables, nor can it provide accurate predictions for the biomass supply chain. As a result, the results obtained from this method tend to be biased and macro, particularly in regions experiencing rapid land-use development. In this paper, the author has developed a clustering methodology with a fuzzy c-means (FCM) algorithm to determine biomass energy potential based on regional characteristics to produce data clusters with high accuracy. Grouping the characteristics of clustering-based areas involves grouping physical or abstract objects into classes or similar objects.
Co-Authors Adella Wendy Putri Alvianingsih, Ginas Anggaini, Dwi ARIF KURNIAWAN Christine Widyastuti Dini, Hasna Satya Dwi Anggaini Dwi Anggaini Dwi Anggaini Eko Supriyanto Fikri, Zul Hakimul Batih Hashim, Haslenda Hasna Satya Dini Jamani Jamian, Jasrul Jamian, Jasrul Jamani Oktaria Handayani Perdana Putera, Perdana Ridha Yasser Satya Dini, Hasna Titi Ratnasari Titi Ratnasari Titi Ratnasari Tri Wahyu Oktaviana Putri Yoakim Simamora Zainal Arifin