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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 12, 2019.
Abstract: Stemming in each language has a different process and is determined according to the structure of the language. Stemming is mostly used as a complete step in the processing of words and phrases. There are many stemming algorithms available, and some used as a process for word processing. One function of stemming is to detect word errors in Indonesian. In this study, researchers created the Indonesian words error detection system using Nazief and Adriani algorithm. In the trials conducted, the system will accept text input obtained from the user. Then the system will preprocess the text. In this study, there are three stages of preprocessing, namely tokenization, case folding, and filtering. After the stages in preprocessing are finished, the system will call each word for the process of stemming. The results of the stemming will be compared with the base words available in the database. If it does not match, then the word is highlighted and is considered an error word. The first finding is the Nazief Adriani's algorithm can be able to detect words error until 100%. The second finding is the Nazief Adriani's algorithm also detect non-words error, the accuracy of detecting is 97.464%.
Anton Yudhana, Abdul Fadlil and Muhamad Rosidin, “Indonesian Words Error Detection System using Nazief Adriani Stemmer Algorithm” International Journal of Advanced Computer Science and Applications(IJACSA), 10(12), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0101231
@article{Yudhana2019,
title = {Indonesian Words Error Detection System using Nazief Adriani Stemmer Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0101231},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0101231},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {12},
author = {Anton Yudhana and Abdul Fadlil and Muhamad Rosidin}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.