NAÏVE BAYES AND BLACK BOX TESTING IMPLEMENTATION ON SENTIMENT ANALYSIS OF ALOE VERA PRODUCT REVIEWS

Autor:	Putri Ambarwati
Rok vydání:	2020
Předmět:	biology Computer science business.industry White-box testing Sentiment analysis biology.organism_classification computer.software_genre Aloe vera Naive Bayes classifier Product reviews Artificial intelligence business computer Natural language processing
Zdroj:	Jurnal Techno Nusa Mandiri. 17:95-100
ISSN:	2527-676X 1978-2136
DOI:	10.33480/techno.v17i2.1453
Popis:	Aloe vera soothing gel is one of the best-selling products and the most widely reviewed on the Althea Korea website. This product has been reviewed by 1,448 users on the Althea website. The result of the research can be used to minimize mistakes in product purchases. Besides, through a review of a product, the company can analyze the level of customer satisfaction and can be a suggestion for improvements in the future. Therefore, a system is needed to analyze the sentiment towards aloe vera soothing gel to determine the review as a positive or negative sentiment. The method used in this research is the Naïve Bayes method and uses the classification carried out by linguists as a reference for determining positive and negative sentiment. There are two tests carried out in this research, namely confusion matrix testing and black-box testing. The result of the confusion matrix test found an accuracy of 94.62% and the result of black-box testing showed that the output produced was by the application functionality.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::e742d13f8fdb92553e5007e0dece16e8 https://doi.org/10.33480/techno.v17i2.1453 Zobrazit plný text záznamu