Optimizing the Fuzzy Membership Function in SAW to Detect Types of Psychopaths

Authors

  • Al-Khowarizmi Al-Khowarizmi
  • Ajulio Padly Sembiring Politeknik Negeri Medan
  • Vicky Rolanda Universitas Potensi Utama

Keywords:

DSS, Psychological Disorders, Types of Psychopaths, SAW, Fuzzy

Abstract

The use of a decision support system (DSS) can assist in making decisions quickly and precisely according to targets. Many problems that occur can be solved by using SPK, one of which is to determine psychological disorders, in this case to determine the type of psychopath where there are many psychopathic sufferers and difficult to detect. The algorithm that can be used in a decision support system is to use the Optimized Simple Additive Weighting (SAW) Algorithm with the Fuzzy membership function. In this paper, a case analysis is analyzed, namely determining psychological disorders by asking several questions so that the results of this study are a conclusion about psychological disorders, especially psychopaths, including: primary psychopath, secondary psychopath, distempered psychopath and charismatic psychopath which are obtained from the highest score of each. decision making process.

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Published

2021-04-28

How to Cite

Al-Khowarizmi, A.-K., Sembiring, A. P., & Rolanda, V. . (2021). Optimizing the Fuzzy Membership Function in SAW to Detect Types of Psychopaths. International Journal of Data Science, Computer Science and Informatics Technology (InJODACSIT), 1(1), 29–34. Retrieved from http://ojs.polmed.ac.id/index.php/InJODACSIT/article/view/418

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