Klasifikasi Kesehatan Mental Menggunakan K-Nearest Neighbor (Studi Kasus : Kesehatan Mental Guru Sekolah Dasar Inklusi Di Pekanbaru)

Chairunissa, Ovira (2022) Klasifikasi Kesehatan Mental Menggunakan K-Nearest Neighbor (Studi Kasus : Kesehatan Mental Guru Sekolah Dasar Inklusi Di Pekanbaru). Other thesis, Universitas Islam Riau.

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Abstract

Classification of mental health with k - nearest neighbor algorithm is a system that can be used as a means to predict the level of mental health of teachers who teach in inclusive elementary schools in Pekanbaru. Veit and ware divide mental health into two sides of psychological distress and psychological well being. The attributes used to mental health on psychological distress include anxiety, depression, and loss of behavioral/emotional control, on psychological well being embracing general positive affected, emotional ties, and life satisfaction. This system aims to predict the level of mental health of teachers who teach in inclusive schools which consists of very low, low, medium, high, and very high categories. From the test of data train as much 32 mental health data gotten the result of accuracy as much 86.667% for the training data with the most optimal K value, the K value 9 in the psychological distress aspect and the accuracy as much 92.667% with the optimal K value 3 in the psychological well being aspect. therefore can be concluded that this system helps students or researchers classify mental health on psychological distress and psychological well being.

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