Review Produk Iphone dengan Analasis Sentimen menggunakan Algoritma Text Mining TF-IDF
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Devanta Abraham Tarigan
*
Politeknik Negeri Medan, Medan,
Indonesia
(*) Corresponding Author
Abstract
The iPhone is a product that has become a major concern in society and has become one of the main needs in everyday life. However, sometimes the iPhone often faces several problems that need attention. One problem that is often the main focus is the fairly high price. Therefore, we need a system that can determine the public's view of the iPhone product. This research uses text mining and TF-IDF to determine people's views on iPhone products. Text mining can be defined as the discovery of new, previously unknown information and the automatic extraction of valuable information from text from different sources. Meanwhile, TF-IDF is used to determine the frequency value of words in a document. In this research, sentiment refers to people's views on iPhone products, whether positive or negative. The final result of this sentiment analysis is that the positive sentiment value is 68.65% while the negative sentiment value is 31.35%. This is expected to provide information about the extent to which iPhone products are accepted by the public. By understanding people's sentiments, Apple company can take necessary actions to improve product quality and user satisfaction. Apart from that, this research also introduces the concept of Text Mining and the TF-IDF algorithm as a powerful tool for analyzing text data in the context of sentiment analysis.
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