A Swear Word Detection System in SKPD Website Content of Bali Province Government - Melinda, Ester; Parwita, Wayan Gede Suka (Lembaga Penelitian dan Pengabdian kepada Masyarakat, 2021)
The website is one of the information service systems needed by the community to carry out various public service activities. It's just that it is necessary to do a word-checking process on the website to avoid swear words, especially on government service websites. Checking swear words on the website takes a long time, done by reading every website content that the admin will add. So we need a system that can check swear words on the website. The purpose of the research is to simplify detecting swear words on the SKPD website. In this study, a system was designed and built that can detect swear words when the admin adds and changes website content and validates criticism and suggestions that visitors have added by implementing text mining. This study uses the Nazief and Adriani algorithms for the stemming process and the Term Frequency algorithm for the weighting process. The test method used is accuracy measure. From the test results, the accuracy value is 88%, precision of 78.57%; recall of 100%; and f measure by 88%. The results obtained have not been maximized because the system has not been able to read the sentence structure, so that a word that should not be used as a swear word in a document/text becomes detected by the system as a swear word, for example, the word dog detected in the text of the news about rabid dogs.