A Combination of Algorithmic to Predict Readiness for Change of Narcotics Addicts Rehabilitation Patients

Abstract

This study aims to provide new tools for administering assessment tests regarding URICA-Scale, which initially used the paper based test method, and the calculations were calculated manually. In this study, two algorithms were applied. The Fisher-Yates algorithm performs random permutations that each user can give. It can generate random visualizations and minimize the occurrence of fraud in the process. Then the Simple Additive Weighting (SAW) algorithm plays a role in calculating the calculations that have been selected by the user when making answer choices. In measuring changes in each drug addict, there are several self-report questionnaire scales and algorithms that are applied to obtain achievable results. This paper provides an implementation of a system design in measuring the results of a questionnaire that has been supported by the combination of the Fisher Yates algorithm and the Simple Additive (SAW) in the University of Rhode Island (URICA) Change Assessment Scale for psychometric properties investigations. This algorithm can accommodate the output results in accordance with paper based test calculations so that this system can provide a faster calculation process and minimize until there is an error in the calculation