PERANCANGAN ALAT BANTU ANALISIS SENTIMEN BERDASARKAN ULASAN PENGGUNA APLIKASI POST DARI GOOGLE PLAY STORE UNTUK PENDUKUNG KEPUTUSAN - Rayhan Fuadi, M.
POST App is an information system application of transaction and reporting for various types of businesses. Currently, when compared to similar cash register applications, POST App has a low user satisfaction rating and number of downloads on Google Play Store. Therefore, the developers of the POST App need an effort to improve the app's performance from user reviews through user sentiment information and several dominant topics on why users like or dislike the POST App. This knowledge becomes an input for the company to support operational or managerial decisions and to plan strategic business steps to improve the competitiveness of the application. In this study, the CRISP-DM methodology is used with a text mining and natural language processing (NLP) approach to perform sentiment analysis and topic modeling of POST App user reviews from Google Play Store. The sentiment