Sentiment Analysis of the Maps Application uses the SVM method and Predicts the Growth of Maps Application Users
Ilham Fariz Asya1,a*) , Tukino 2,b*) , Baenil Huda3,c), Aprilia Putri Nardilasari4,d), Risa Nur Islami5,e), Muhammad Khaerudin 6,f)

Universitas Buana Perjuangan Karawang

Abstract

Sentiment analysis is a users assessment of a product or service according to user knowledge. The Maps application (google Maps, MAPs.ME and Waze) each offer different types of services to attract users. The types of services that are easy to access, valid information, polite driver attitudes and attractive promos offered at any time on the Maps application have an impact on users of the maps application to use services on an ongoing basis. The Maps application as a service requires user opinion or user judgment to become an interesting data bank to observe using the sentiment analysis method and Support Vector Machine. Knowing the types of services that suit the needs of users of the Maps application Data is taken from the Twitter database for the types of applications Google Maps, MAPs.ME and Waze. Data were analyzed using sentiment analysis with the Support Vector Machine method, rapidminer. The map application service assessment model yielded three ratings for map application providers, namely Google Maps with 89.73%, Maps.me with 86.40% and Waze with 79.47% which indicated by the number of users increasing every year. Thus Maps users can choose a maps application according to the quality of service and service rating offered by the map application provider, while the maps application provider can take advantage of the results of sentiment analysis to make service improvements

Keywords: Sentiment Analysis, SVM, Maps, Growth

Topic: Engineering