News Opinion Classification Application With Support Vector Machine Algorithm Using Framework Codeigniter


Rizal Tjut Adek(1*), Muhammad Fikry(2), Umar Khalil(3),


(1) Universitas Malikussaleh
(2) Universitas Malikussaleh
(3) Universitas Malikussaleh
(*) Corresponding Author

Abstract


News is an information that contains a lot of data, one of which is data about opinion / sentiment. The opinion / sentiment data of a news can be used for many things. To get the opinion value of a news, it is necessary to do a sentiment analysis technique on the news data that wants to know the level of opinion produced. Sentiment analysis is a technique that uses the data mining method. To see the height of the opinion value of a news item, the Support Vector Machine algorithm is used, which is one of the algorithms in the data mining method that is able to classify data sets into two classes. Using the CodeIgniter framework based on the PHP programming language, an application was developed that can classify the news into two classes, namely the positive class and the negative class. By using 100 pieces of news data from the national news portal, namely detik.com, about 700 sentences and more than 1000 words are generated which are then classified using the SVM algorithm. Applications are able to achieve an accuracy rate of 76%

Keywords


Data Mining, Support Vector Machine, Framework Codeigniter

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DOI: https://doi.org/10.31289/jite.v5i1.5189

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