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Aplikasi Stemming Kata Bahasa Lampung Dialek Api Menggunakan Pendekatan Brute-Force dan Pemograman C#
Author(s) -
Zaenal Abidin,
Aldi Wijaya,
Donaya Pasha
Publication year - 2021
Publication title -
jurnal media informatika budidarma/jurnal media informatika budidarma
Language(s) - English
Resource type - Journals
eISSN - 2614-5278
pISSN - 2548-8368
DOI - 10.30865/mib.v5i1.2483
Subject(s) - noun , computer science , linguistics , natural language processing , artificial intelligence , verb , mathematics , philosophy
Lampung is one of the areas on the island of Sumatra that has the regional language and script of Lampung. In this province there are two main regional dialects, namely the dialect of fapi and the dialect of nyo. Research efforts for the preservation of the Lampung language digitally have been conducted by researchers from various Universities. The research stemming from Lampung dialects of api is based on the findings of the fact that the dictionary-based Lampung dialects of the Lampung language dialect cannot translate the affix words. Stemming of Lampung language dialects of api is worked with a Brute-force approach. In the Lampung language there are inflexional verbs and derivational verbs. Inflexional verbs are verbs formed from bases that are also categorized verbs while derivational verbs are verbs formed from bases that are categorized in addition to verbs such as nouns, adjectives, adverbs, pronouns and numerals. The purpose of this research is to (1) conduct word stemming with a Brute-force approach, (2) produce an application as a Lampung language word Stemmer dialect of api using C # programming language and online database using Firebase. The methods used in this study consisted of (1) Researchers are looking for, identifying, recording, manually typing 2000 words following the basic words of the Lampung dialect of api, (2) creating a stemming algorithm with a Brute-force approach (3) testing applications that have made. As for the result obtained is the application is able to do word stemming for words that have been identified in 2000 words and if stemming can not be done then the facility is provided to update the database used in the application to be used for stemming because the stemming application is very supportive of the application dictionary-based translation engine. The urgency of Stemming application research is to address the affix word in the Lampung language machine translation machine translation application for further research

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