Abstract
Background: Market prediction is an important thing that needs to be analyzed deeply. Business intelligence becomes an important analysis procedure for analyzing the market demand and satisfaction. Since business intelligence needs a deep analysis, sentiment analysis becomes a powerful algorithm for analyzing customer review regarding to the business intelligence analysis.Objective: In this study, we perform a sentiment analysis for identifying the business intelligence analysis in GO-JEK.Methods: We use Twitter posts collected from the Twint library which consists of 3111 tweets. Since the dataset did not provide a ground truth, we perform Microsoft Text Analytic for determining positive, neutral, and negative sentiment. Before applying Microsoft Text Analytic, we conduct a pre-processing step to remove the unwanted data such as duplicate tweets, image, website address, etc.Results: According to the Microsoft Text Analytic, the results are 666 positive sentiment numbers, 2055 neutral sentiment numbers, and 127 negative sentiment numbers.Conclusion: According to these results, we conclude that most GO-JEK customers are satisfied with the GO-JEK services. In this research, we also develop classification model to predict the sentiment analysis of new data. We use some classifier algorithms such as Decision Tree, Naïve Bayes, Support Vector Machine and Neural Network. In the result, the system shows that the decision tree provides the best performance.
Highlights
Predicting market demand and customer satisfaction requires an extensive market research to predict the market demand and customer satisfaction
We perform Microsoft Text Analytics API to give label for each data. This process obtained 2055 neutral sentiments, 666 positive sentiments and 127 negative sentiments considering the number of sentiment score provided by Microsoft Text Analytics API
According to the experimental result of sentiment analysis described in the section C, we conclude that Microsoft Text Analytics was very useful to give data label since unlabeled data were much published
Summary
Predicting market demand and customer satisfaction requires an extensive market research to predict the market demand and customer satisfaction. Business intelligence known as BI has become an important analytical procedure for analyzing market demand and satisfaction. BI is related as a technology used to analyze the business data regarding to the decision making process based on prediction analysis and provided the data enhancement process followed by an analytical technology which is widely used in several aspects such as market intelligence, e-commerce, e-health etc. Product defines as information about empowering organizations to predict the service, customer satisfaction, competitor, marketplace, technology, etc. These two important things become a necessary part in market research and have a powerful analysis result to predict the market demand and customer satisfaction [1, 3]. Business intelligence becomes an important analysis procedure for analyzing the market demand and satisfaction. The system shows that the decision tree provides the best performance
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