Fuzzy Inference System For Recommendation Of Student's Depression Level

Abstract

Depression is common in modern society and can cause various kinds of problems, for example behavioral, social and psychological problems. Sanggar Kegiatan Belajar 26 Bintaro is a non-formal educational institution that does not yet have counseling teachers like other formal schools, so tools are needed to carry out early detection of students' depression levels in the form of a depression level recommendation system whether at normal, mild, moderate or severe levels which is useful for Teacher to provide the right solution. The method used in this research is fuzzy logic with seven (7) input variables sourced from the Depression Anxiety Stress Scale-21 (DASS-21) questionnaire and four output variables, namely normal mild level depression, moderate level depression and severe level depression. The programming language used is Python using the Simpful library. The results of the research are measurements using DASS-21 for depression. The recommendation results are the same as using the fuzzy logic method, so that fuzzy logic can be used to make recommendations for early detection of students' depression levels.