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Sentiment Analysis Of Detergen Products At Suzuya Mall Rantauprapat Navie Bayes Method Nurhikmah Nasution; Ibnu Rasyid Munthe; Gomal Juni Yanris
Jurnal Mantik Vol. 6 No. 1 (2022): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v6i1.2269

Abstract

Suzuya Mall Rantauprapat is an Indonesian convenience store chain with numerous locations. Based on data from top brands from 2014 to 2018, we discovered that the market share of powder detergent is uncertain each year. Powder detergent companies must understand consumer desires and monitor the position of their products on a regular basis in order to anticipate market share changes.Data is cleaned by removing capital letters and punctuation marks, followed by feature extraction. Feature Extraction aims to perform calculations and comparisons that can be used for the classification of an image. Nave Bayes is a method or stage of data processing with the nave bayes method. The Naive Bayes classifier is a method of classifying based on Bayes'' tyrannology. It uses probability and statistical methods first put forward by Thomas Bayes. The classification model is then assessed to determine its accuracy and performance in computer science.Data set is data that has been changed in the form of tabulation from research data into excel form. After the data is processed by the naïve bayes method, the confusion matrix is obtained as follows. It can be known the factors that consumers use in choosing detergent products are the fragrance factor, price, foam produced, and the effect on the hands.Machine learning, specifically Nave Bayes, will be used in this research methodology. The Naive Bayes classifier is a method of classification rooted in Bayes'' theorem. A confusion matrix is a table that contains many rows of test data that the classification model predicts to be true or false. Process data mining can be made up of any number of nested operators that are described in XML files and built using RapidMiner.
Sentiment Analysis of Detergen Products at Suzuya Mall Rantauprapat Navie Bayes Method NURHIKMAH NASUTION
Jurnal Mantik Vol. 6 No. 1 (2022): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Suzuya Mall Rantauprapat is an Indonesian convenience store chain with numerous locations. Based on data from top brands from 2014 to 2018, we discovered that the market share of powder detergent is uncertain each year. Powder detergent companies must understand consumer desires and monitor the position of their products on a regular basis in order to anticipate market share changes.Data is cleaned by removing capital letters and punctuation marks, followed by feature extraction. Feature Extraction aims to perform calculations and comparisons that can be used for the classification of an image. Nave Bayes is a method or stage of data processing with the nave bayes method. The Naive Bayes classifier is a method of classifying based on Bayes'' tyrannology. It uses probability and statistical methods first put forward by Thomas Bayes. The classification model is then assessed to determine its accuracy and performance in computer science.Data set is data that has been changed in the form of tabulation from research data into excel form. After the data is processed by the naïve bayes method, the confusion matrix is obtained as follows. It can be known the factors that consumers use in choosing detergent products are the fragrance factor, price, foam produced, and the effect on the hands.Machine learning, specifically Nave Bayes, will be used in this research methodology. The Naive Bayes classifier is a method of classification rooted in Bayes'' theorem. A confusion matrix is a table that contains many rows of test data that the classification model predicts to be true or false. Process data mining can be made up of any number of nested operators that are described in XML files and built using Rapid Miner.