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Hario Guritno
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science

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MODEL KLASTERISASI GENRE CERPEN KOMPAS MENGGUNAKAN K-MEANS Hario Guritno; Stefanus Santosa
Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 13 No 1 (2017): Jurnal Teknologi Informasi CyberKU Vol. 13, no 1
Publisher : Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro

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Abstract

Information in the form of a text document can be found at any time on print media. Every time the community is faced with the current wave of information like the arrival in the form of unstructured text documents and have penetrated our lives and culture. Unstructured information comes closer all the entities of the world community. The mass media published the newspaper every day is the biggest contributor to human relations around the world. KOMPAS newspaper published every Sunday always insert the rubric of short stories in it. There is a problem to distinguish the genre of stories with one another. This research proposed a model of classify KOMPAS short stories with K-Means algorithm to get the solution. Accuracy of this proposed model using the Davies Bouldin Index (DBI) is 0.001.
Co-Authors Stefanus Santosa