Estimation of Fines Amount in Syariah Criminal Offences Using Adaptive Neuro-Fuzzy Inference System (ANFIS)

Authors

  • Ahmad Fitri Mazlam School of Informatics and Applied Mathematics, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia.
  • Wan Nural Jawahir Hj Wan Yussof School of Informatics and Applied Mathematics, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia.
  • Rabiei Mamat School of Informatics and Applied Mathematics, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia.

Keywords:

Adaptive Neuro Fuzzy Inference System (ANFIS), Amount of Fines, Syariah Criminal,

Abstract

All Syariah criminal cases, especially in khalwat offence have its own case-fact, and the judges typically look forward all the facts which were tabulated by the prosecutors. A variety of criteria is considered by the judge to determine the fines amount that should be imposed on an accused who pleads guilty. In Terengganu, there were ten (10) judges, and the judgments were made by individual ijtihad upon the trial to decide the case. Each judge has a stake, principles and distinctive criteria in deciding fines amount on an accused who pleads guilty and convicted. This research paper presents Adaptive Neuro-fuzzy Inference System (ANFIS) technique for estimating fines amount in Syariah (khalwat) criminal. Data sets were collected under the supervision of registrar and syarie judge in the Department of Syariah Judiciary State Of Terengganu, Malaysia. The results showed that ANFIS could estimate fines efficiently than the traditional method with a very minimal error.

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Published

2017-10-20

How to Cite

Mazlam, A. F., Hj Wan Yussof, W. N. J., & Mamat, R. (2017). Estimation of Fines Amount in Syariah Criminal Offences Using Adaptive Neuro-Fuzzy Inference System (ANFIS). Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(3-5), 153–156. Retrieved from https://jtec.utem.edu.my/jtec/article/view/2985

Issue

Vol. 9 No. 3-5: Special Issue on Software Engineering III

Section

Articles

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