Estimation of fines amount in syariah criminal offences using adaptive neuro-fuzzy inference system (ANFIS) enhanced with analytic hierarchy process (AHP)

Ahmad Fitri Mazlam (Universiti Malaysia Terengganu)
Wan Nural Jawahir Hj Wan Yussof (Universiti Malaysia Terengganu)
Rabiei Mamat (Universiti Malaysia Terengganu)

International Journal of Electrical and Computer Engineering
Vol 9, No 6: December 2019

All syariah criminal cases, especially in khalwat offence have their case-fact, and the judges typically look forward to 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 the individual decision upon the trial to decide the case. Each judge has a stake, principles and distinctive criteria in determining fines amount on an accused who pleads guilty and convicted. This research paper presents an Adaptive Neuro-fuzzy Inference System (ANFIS) technique combining with Analytic Hierarchy Process (AHP) for estimating fines amount in Syariah (khalwat) criminal. Datasets 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+AHP could estimate fines efficiently than the traditional method with a very minimal error.