Open AccessCertainty factor and dempster-shafer method analysis for early detection of final year student depression
Author(s) -
Ressy Dwitias Sari,
Reni Rahmadani,
Tansa Trisna Astono Putri,
Harvei Desmon Hutahaean,
Sriadhi Sriadhi
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/830/3/032007
Subject(s) - certainty , weighting , test (biology) , dempster–shafer theory , depression (economics) , measure (data warehouse) , psychology , confidence interval , computer science , artificial intelligence , statistics , machine learning , data mining , mathematics , medicine , paleontology , geometry , macroeconomics , biology , economics , radiology
Academic loads in writing a thesis cause difficulties to students to complete their studies. This problem can be solved with the application of an expert system with early detection of depressive final-year students that compares Certainty Factor method and Dempster-Shafer method. Certainty Factor method used to measure facts certainty or rules in defining the level of expert confidence, while the Dempster-Shafer method combines uncertainty that has characteristics according to the way of thinking of experts but has a mathematical basis. The purpose of comparing these methods is to get the most appropriate and best method for early detection of depression. The methodology used in this study is a comparative test between two methods, with a mechanism (1) Collecting data related to the depression of final year students; (2) Data acquisition and weighting of confidence values; (3) Calculate formulations from both methods; (4) Perform a comparative test to obtain conclusions. Certainty Factor method is the most appropriate and the best model in early detection of depression, because Certainty Factor method revealed that the more symptoms are given, the higher the probability of detection of depression.