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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Fountain of Informatics Journal Sistemasi: Jurnal Sistem Informasi Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial JITK (Jurnal Ilmu Pengetahuan dan Komputer) J-SAKTI (Jurnal Sains Komputer dan Informatika) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science Jurnal Mantik Journal of Computer System and Informatics (JoSYC) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Pendidikan dan Teknologi Indonesia J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Sains dan Teknologi STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer
Susanto, Erliyan Redy
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary

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Journal : JITK (Jurnal Ilmu Pengetahuan dan Komputer)

 1 
REFORMULATION OF MULTI-ATTRIBUTE UTILITY THEORY NORMALIZATION TO HANDLE ASYMMETRIC DATA IN MADM Puspaningrum, Ajeng Savitri; Susanto, Erliyan Redy; Hendrastuty, Nirwana; Setiawansyah, Setiawansyah
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 2 (2025): JITK Issue November 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i2.7273

Abstract

Multi-Attribute Utility Theory (MAUT) is a widely used multi-attribute decision-making (MADM) method due to its ability to integrate multiple criteria into a single utility value. However, conventional MAUT faces limitations when handling asymmetric data, where standard normalization processes often lead to value distortion and less representative rankings. This study aims to reformulate the normalization function in MAUT to improve adaptability to non-symmetric data distributions and to enhance ranking validity in decision-making. A modification approach called MAUT-A was developed by applying an adaptive normalization mechanism capable of accommodating extreme distributions and outliers by adding Z-score normalization. The performance of MAUT-A was evaluated by comparing the correlation of its ranking results with reference rankings, and the outcomes were benchmarked against conventional MAUT. The experimental findings indicate that conventional MAUT achieved a correlation value of 0.9688 with the reference ranking, while the proposed MAUT-A method achieved a higher correlation of 0.9792. This improvement represents that MAUT-A has better suitability, stability, and reliability in managing asymmetric data. The study contributes by offering a reformulated MAUT framework through adaptive normalization, providing more accurate, stable, and fair ranking outcomes. This approach enhances the validity of MADM applications, particularly in contexts involving asymmetric data distributions
Co-Authors ., Rusliyawati Adela, Marsya Agus Wantoro Amarudin, Amarudin Amelya, Eka Andi Nurkholis Az Zahra, Renny Fatimah Budiman, Ega Cahyana, Agum David Kurniawan DAVID KURNIAWAN Doris Juarsa Eka Pranajaya, Akbar Estri Pratiwi, Kyky Fidya Fadli, Muhammad Fudholi, Muhammad Fahmi Hendratno, Hary Inzaghi, M. Rana Irawan, Made Kevinda Sari Lestari, Ninik Maylanda, Putri Oktaria Misdiantoro, Diky Muhammad Fadli Neneng Neneng Neneng, N Nirwana Hendrastuty Purwanti, Dian Sri Putri, Made Yuninda Rahmada, Alfin Ramadhani, Resvi Restu Anggoro S, Muhammad Ikhsan Setiawansyah Setiawansyah Simarmata, Yohanes Surono, Muhammad Tyas, Khoirunisa Cahyaning Ulum, Faruk Wijaya, Suhenda Yulian, Tri