ANALISIS SENTIMEN PENGGUNAAN APLIKASI TRANSPORTASI ONLINE PADA ULASAN GOOGLE PLAY STORE MENGGUNAKAN ALGORITMA SVM (SUPPORT VECTOR MACHINE)

Abstrak

Public transportation is a necessity for some people to carry out their daily activities. In the current digital era, public transportation can be accessed online using a smartphone through applications available on the Google Play Store, for example online transportation applications that are currently popular, namely Grab, Gojek, and Maxim. Online transportation services have disrupted the traditional transportation industry and provided a more convenient and efficient alternative for people. However, as is the case with any innovation, online transportation services have also faced several challenges regarding regulation, security, and their impact on the transportation sector as a whole. Since there have been new features in the application such as food & shop services, online transportation applications have experienced a surge in downloads. Users often read reviews and check ratings before downloading apps on the Google Play Store. Forming the best software title is less important because it has nearly the same downloads and ratings. Sentiment analysis of a number of online transportation applications on the Google Play Store was carried out to determine which one has the greatest predicate. This user review analysis uses a Support Vector Machine (SVM) which in several studies is known to have a fairly high level of accuracy because of its ability to identify the best online transportation application based on reviews from comments on the Google search engine..