SISTEM KLASIFIKASI UNTUK MENENTUKAN TINGKAT STRESS MAHASISWA SECARA UMUM MENGGUNAKAN METODE K-NEAREST NEIGHBORS - Sopwatun Anisa; Agus Komarudin; Edvin Ramadhan (Jurnal Informatika Teknologi dan Sains (Jinteks), 2024)
Stress is often the main challenge faced by students due to academic and social demands in the educational environment. Factors such as nervousness, inability to control oneself, worry, etc. are several stress triggers, all of which can have a negative impact on students' physical and mental health. This research aims to identify the level of stress experienced by students using the K-Nearest Neighbors (KNN) method and evaluate the accuracy of the results of this research. The KNN method is used to classify student stress levels based on similarity or closeness to other data in the dataset. By using data taken from the data.world site, the results of this research show that the KNN method is able to achieve an accuracy of 91.58%. In addition, the precision, recall, and f1-score values are 76.10%, 73.11%, and 74.17% respectively. This research makes an important contribution in understanding student stress levels and shows the effectiveness of the KNN method in classifying stress data. It is hoped that these results will help in the development of better strategies for managing and reducing stress among college students.