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All Journal Journal of Computer Networks, Architecture and High Performance Computing
Rosnelly , Rika
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Computer Science & IT Education

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Sentiment Analysis on Cyanide Case After 'Ice Cold' Aired with NLP Method using Naïve Bayes Algorithm Hizria, Rahmatika; Sarwadi, Sarwadi; Hasibuan, Rabiatul Adawiyah; Ritonga, Ramadhani; Rosnelly , Rika
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3408

Abstract

Information technology is developing increasingly rapidly, and the reach of the Internet has expanded even to remote areas. The public increasingly uses social media as a source of information that discusses all aspects of people's lives. Social media has a vital role for most people, one of which is the news of the cyanide coffee case. The Cyanide Coffee case was discussed again by netizens after Netflix raised this case in a documentary film entitled Ice Cold, which made the public even more convinced of the irregularities of the case. Based on this, sentiment analysis is needed to extract comments to obtain public opinion information. The sentiment analysis aims to create a sentiment model to determine public comments on this case. Therefore, this research was conducted to find out and classify public sentiment on the Cyanide Coffee Case using the Natural Language Processing (NLP) method, which is a text preprocessing process followed by the tokenization stage. Data filtering was used using Indonesian Stopwords, and then normalization was continued using Porter Stemmer. In this study, data collection was carried out based on public comments on Ice Cold shows on the TikTok platform using TikTok Comments Scraper. The test results show that the classification using naïve Bayes obtained the results of 22 negative comments, 4052 neutral comments and 34 positive comments. The classification results of this study are 87% accuracy, 97.6% precision, 87% recall, and 91.9% F-Score.
Analysis of String Matching Application on Serial Number Using Boyer Moore Algorithm Tarigan, Dede A.; Buaton, Adiyanto O.; Briyandana , Briyandana; Safitri, Erica R.; Rosnelly , Rika
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3410

Abstract

Nowadays, technology has become the most important pillar in business management. The rapid development of technology has a significant impact on various aspects of business, from operational efficiency to marketing strategies. Applications are very important in a company or agency. With an information system, companies and agencies can easily guarantee the quality of information that will be presented for decision-making. Now, much information can be easily obtained quickly, thanks to information technology. The speed and accuracy of information delivery is a challenge for all producers in running their business. Boyer-Moore algorithm is one of the algorithms that can be used in the Barcode Generator application to scan barcode product serial numbers. The Boyer-Moore algorithm method functions to find sequence numbers. The development process requires several stages of investigation in the form of data collection techniques, problem identification, application of the Boyer-Moore algorithm, implementation, and system testing. This iterative process makes the application of string matching with the Boyer-Moore algorithm technique into a very accurate application suitable for text search. This process is done by giving a pattern to the text. Therefore, the final result of string matching text search using the Boyer-Moore algorithm technique requires nine iterations. In the 9th iteration, the text and pattern conditions are matched or sequential. From the results of the manual computational search analysis work of applying the Boyer Moore string matching algorithm, several stages of the process are made, namely iterations 1 to 9, as a search step to determine string matches. In addition, patterns can be used with the number of shifts of patterns or text up to 13 times.
Co-Authors Briyandana , Briyandana Buaton, Adiyanto O. Hasibuan, Rabiatul Adawiyah Hizria, Rahmatika Ritonga, Ramadhani Safitri, Erica R. Solly Aryza Tarigan, Dede A.