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

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.