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Anjelika Hutapea
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Penerapan Algoritme Modified K-Nearest Neighbour Pada Pengklasifikasian Penyakit Kejiwaan Skizofrenia Anjelika Hutapea; Muhammad Tanzil Furqon; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 10 (2018): Oktober 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Schizophrenia is a disease that has a soul crack or a splitting of personality. Problems of mental disorder almost in all countries in the world. Schizophrenia has 5 types: Paranoid, Hebephrenic, Catatonic, Unspecified and Simplex.The similarity of symptoms causes the paramedic difficulty to determine the class of Schizophrenia. Therefore, a system that aims to Schizophrenia classification by applying one of the classification method Modified K-Nearest Neighbor (MKNN). The system will perform the step by calculating the distance of assymetric binary, the calculation of the validity value and weight voting value in order to get the final result that will be used to determine the classification based on the value of K that has been determined. The testing of this system consist of testing the effect of K value and testing the influence of K-Fold value. The result of testing the effect of K value gives the greatest accuracy equal to 37,045% at K=7 and K-Fold=10. The result of testing the effect of K-Fold value gives the greatest accuracy of 28,4462% at K-Fold=5.
Co-Authors Indriati Indriati Muhammad Tanzil Furqon