A Hybrid Approach to Typo Correction in Indonesian Documents Using Levenshtein Distance

This study developed a typo correction system for the Indonesian language by integrating the Levenshtein Distance algorithm with empirical methods. The system is designed to improve the accuracy of typo detection and correction in Indonesian texts, which feature complex morphological structures such as prefixes, suffixes, and compound words. The findings show that the system achieved a precision rate of 92% and an F1-score of 90.5%, indicating high reliability in providing relevant correction suggestions. Additionally, the system demonstrated efficiency in processing time, with an average of 0.8 seconds for short texts and 5.3 seconds for longer texts. The use of empirical methods enables the system to handle complex language variations, resulting in more contextually appropriate correction suggestions. User feedback indicated high satisfaction with the interface and the relevance of the suggestions provided. Overall, this research makes a significant contribution to the development of more adaptive and efficient typo correction systems for the Indonesian language and opens up opportunities for further development in the context of other similar languages.

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Publication Details

Journal
Journal of Technology Informatics and Engineering
Published
2024-08-19
DOI
https://doi.org/10.51903/jtie.v3i2.184
Citations
2
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
0.69
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article

A Hybrid Approach to Typo Correction in Indonesian Documents Using Levenshtein Distance

Yan Song, Joseph Teguh Santoso
2 citations
Journal of Technology Informatics and Engineering
Natural Language Processing Techniques
0.69
article

A Hybrid Approach to Typo Correction in Indonesian Documents Using Levenshtein Distance

Yan Song, Joseph Teguh Santoso
article en
2 citations

Abstract

This study developed a typo correction system for the Indonesian language by integrating the Levenshtein Distance algorithm with empirical methods. The system is designed to improve the accuracy of typo detection and correction in Indonesian texts, which feature complex morphological structures such as prefixes, suffixes, and compound words. The findings show that the system achieved a precision rate of 92% and an F1-score of 90.5%, indicating high reliability in providing relevant correction suggestions. Additionally, the system demonstrated efficiency in processing time, with an average of 0.8 seconds for short texts and 5.3 seconds for longer texts. The use of empirical methods enables the system to handle complex language variations, resulting in more contextually appropriate correction suggestions. User feedback indicated high satisfaction with the interface and the relevance of the suggestions provided. Overall, this research makes a significant contribution to the development of more adaptive and efficient typo correction systems for the Indonesian language and opens up opportunities for further development in the context of other similar languages.

Journal of Technology Informatics and EngineeringVol. 3(2)
Nanjing University of Information Science and Technology (CN)
Quality Education
Openalex Percentile: Top 25%
Natural Language Processing Techniques
0.69
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