Mental health and machine learning technology that are trending among students provide a presentation that mental health awareness and technology use will have an impact in the future. This research aims to provide awareness of Satya Wacana Christian University data about mental health that can be identified using machine learning technology. The use of K-Means Clustering in clustering has been done in various types of research. Mental health scale that can recognize the state felt by Satya Wacana Christian University students based on answers to questions. The answers are in the form of a numeric scale, so the data is used in Orange3 for clustering using the K-Means algorithm. Analysis on the scale data of UKSW students who have 32 data has a silhouette k = 3 in cluster 1 of the depressed category has the results of 11 students seen in the 2018 batch and above in the depressed category and 1 data of 2020 batch students. In cluster 2 has 12 data which has the results of the 2018, 2019 and 2020 generations in the prosperous category. Cluster 3 of the harmonious category has data on 9 students whose classes are various in 2017, 2018 and 2019. The results in each cluster provide an overview of the effect of batch on mental health where many of the early year batches are in the prosperous category then the depressed category with the 3rd year batch and there are students who are able to balance their mental health with harmonious categories scattered in each batch.
Copyrights © 2023