Open AccessText analysis on health product reviews using r approach
Author(s) -
Nasibah Husna Mohd Kadir,
Sharifah Aliman
Publication year - 2020
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v18.i3.pp1303-1310
Subject(s) - automatic summarization , computer science , unstructured data , sort , analytics , information retrieval , set (abstract data type) , text graph , product (mathematics) , table (database) , process (computing) , key (lock) , text processing , baseline (sea) , natural language processing , data science , data mining , big data , oceanography , geometry , mathematics , computer security , programming language , geology , operating system
In the social media, product reviews contain of text, emoticon, numbers and symbols that hard to identify the text summarization. Text analytics is one of the key techniques in exploring the unstructured data. The purpose of this study is solving the unstructured data by sort and summarizes the review data through a Web-Based Text Analytics using R approach. According to the comparative table between studies in Natural Language Processing (NLP) features, it was observed that Web-Based Text Analytics using R approach can analyze the unstructured data by using the data processing package in R. It combines all the NLP features in the menu part of the text analytics process in steps and it is labeled to make it easier for users to view all the text summarization. This study uses health product review from Shaklee as the data set. The proposed approach shows the acceptable performance in terms of system features execution compared with the baseline model system.