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Nur Hijriani Ayuning Sari
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Klasifikasi Dokumen Sambat Online Menggunakan Metode K-Nearest Neighbor dan Features Selection Berbasis Categorical Proportional Difference Nur Hijriani Ayuning Sari; Mochammad Ali Fauzi; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Sambat Online is a platform to facilitate the suggestions, criticisms, complaints or questions from public to the Government of Malang through provided websites or via short messages. Incoming complaints, will be categorized into various fields of SKPD. To make it easier to organize the text and increase the efficiency of the administrator in sorting out and define the field of SKPD, an intelligent systems that can classify documents according to its SKPD's field is needed. K-Nearest Neighbor (K-NN) is a method of classification that will be used to find similarities between documents. Feature selection method used in this research is Categorical Proportional Difference (CPD) to measure the degree of contribution of a word. Started from collecting the test documents and training documents, continue to the preprocessing stage and selection features, weighting, and then do the classification, and analysing the results of the classification system by value of accuracy, precision, recall, and F-Measure. The result is the most optimal performance is the use of k = 1 with featured as much as 100% of 91.84%, which shows better value compared to the featured selection due to the removal of the term with low CPD value.
Co-Authors M. Ali Fauzi Putra Pandu Adikara