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Zubaidah Al Ubaidah Sakti
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Identifikasi Jenis Penyakit Mental Ansietas Menggunakan Metode Modified K-Nearest Neighbor Zubaidah Al Ubaidah Sakti; Budi Darma Setiawan; Mochammad Ali Fauzi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

On every levels of society and age must have experienced anxiety, from early state to disorder state. Not everyone knows how to deal with it, if it not treated it would become dangerous mental illness for mental and physical condition. There are six kind of anxiety , that is General Anxiety Disorder, Panic Disorder, Social Anxiety Disorder, Specific Phobia, Obsessive Compulsive Disorder, and Post Traumatic Stress Disorder. In this research will be conducted the identification for kind of anxiety based on Hamilton Rating Scale of Anxiety (HIRS) questionnaire with Modified K-nearest Neighbor (MKNN) for the research method. Unlike K-Nearest Neighbor (KNN), MKNN is another version of that where on MKNN training data must be validated first and for the class voting would be weighted. This research indicates that MKNN could identify anxiety better on unbalanced data used 96 training data and 24 test data with value of h=1 and optimum value of K=3 with best average result 95%, while on balanced data with optimum value of K=2 best average result is 93,333%. This research also indicates as comparison with KNN that in this case resulted on KNN has better result processing balanced and unbalanced data because of noisy data on weighted process, and the result from K-fold Cross Validation that conclude the system is capable enough.
Co-Authors Budi Darma Setiawan M. Ali Fauzi