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ALGORITMA K-NEAREST NEIGBOR MODEL EUCLIDEAN DISTANCE DALAM KLASIFIKASI KELULUSAN PESERTA BAHASA INDONESIA PENUTUR ASING PADA BALAI BAHASA SUMATERA UTARA Hot Riris Siburian; Efori Buulolo; Hukendik Hutabarat
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 3, No 1 (2019): Smart Device, Mobile Computing, and Big Data Analysis
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v3i1.1585

Abstract

The North Sumatra Language Center also organizes an Indonesian language program for foreign speakers (BIPA) is an Indonesian language learning skills program (speaking, writing, reading, and listening) for foreign speakers. That so far the Balai Bahasa office has had difficulty classifying the graduation of Indonesian Foreign Speakers (BIPA) participants who are eligible to pass and who have not passed. So that complaints occur from participants.To overcome the above problems, it is necessary to classify graduation based on previous BIPA participant data. K-Nearest Neigbor Euclidean Distance model which is a method for classifying / grouping an object based on certain criteria. By using the K-Nearest neigbor algorithm in grouping BIPA participants by using various criteria, it is hoped that foreigners can speak Indonesian more quickly.Keywords: Indonesian Foreign Speakers, K-Nearest Neigbor Algorithm