<![CDATA[This study implements the Damerau-Levenshtein algorithm for an Indonesian spelling checking and correction system based on the distance editing approach. The main objective of this study is to develop a system capable of automatically detecting and correcting spelling errors at the character level through a matching process against the KBBI dictionary and the Indonesian corpus. The methods used include data collection, text pre-processing, system design, and implementation of the Damerau-Levenshtein algorithm which includes insertion, deletion, substitution, and transposition operations. Testing was conducted using 25 test data consisting of standard words and modified words for typographical errors. The results show that the system is able to measure all test data with an accuracy level of 100% on a limited dataset. In addition, the average Damerau-Levenshtein Distance value of 0.84 indicates that most errors are in the light category. Evaluation using a confusion matrix produces precision, recall, and F1-score values of 100% each. These results indicate that the Damerau-Levenshtein algorithm is effective in handling character-based spelling errors. However, the system still has limitations in handling complex semantic contexts and language variations. Therefore, further research is recommended to integrate language model-based approaches to improve the system's accuracy and generalization on real-world data.]]>
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