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Katarina N. Lakonawa
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Computer Science & IT

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NAZIEF-ADRIANI STEMMER DENGAN IMBUHAN TAK BAKU PADA NORMALISASI BAHASA PERCAKAPAN DI MEDIA SOSIAL Katarina N. Lakonawa; Sebastianus A. S. Mola; Adriana Fanggidae
J-Icon : Jurnal Komputer dan Informatika Vol 9 No 1 (2021): Maret 2021
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v9i1.3749

Abstract

The use of non-standard language is increasingly prevalent in communication on social media. The use of indefinite language is not limited to sentences, clauses, or phrases but also word usage. In this study, the nonstandard word (NSW) will be normalized to the Indonesian standard word (SW). The Nazief-Adriani stemmer (NAS) method was developed into a nonstandard stemmer (NSS) by increasing its ability to detect non-standard additives. The Needleman-Wunsch similarity algorithm is used to weight the matches. The test results with the Mean Reciprocal Rank (MRR) of 3,438 NSW found that the use of NSS with the number of queries = 9 (Q = 9) had the highest of 79.26% with an average of 50.48%. Meanwhile, MRR testing using NAS with Q = 9 got the highest result of 72.87% and an average of 47.23%. Of the two MRR tests carried out, there were 3 letters that had the highest stemming results, both in tests using NAS and using NSS, namely the initial letters r, f and j. The most significant increase in MRR value occurs in the initial letters 'd', 'n' and 't' which are the initial letters of some non-standard affixes.
Co-Authors Adriana Fanggidae Adriana Fanggidae Sebastianus A. S. Mola