Prediksi Rating Otomatis Berdasarkan Review Restoran pada Aplikasi Zomato dengan menggunakan Extreme Learning Machine (ELM) - Diajeng Tania Ananda Paramitha; Imam Cholisoddin; Candra Dewi (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2019)
In this modern culture, technology advancement are growing better than we ever discovered before. One of the apps we use to search for information about restaurant in Jakarta are known as Zomato. Zomato is an application that provides various information about a restaurant from it facility, price, review, and rating. Users of The Zomato App can input various information that people haven't aware of about the restaurant into the app. Besides of inputting information into the app, Users of The Zomato App can also input a review and rating of a specific restaurant. The data review is used as an information about the restaurant for the potential customer from The Zomato App but sometimes the data review doesn't yet include a restaurant rating. This lack of misinformation will surely make the restaurant owner to occure some difficulties such as improving the restaurant services status for future outcomes. This research helps to classifying the review into the rating. Test protocol of this research are using a prediction with Extreme Learning Machine (ELM) Methods as it core. The prediction process however are build from a several steps such as pre-processing, word weighting with TF-IDF, and Extreme Learning Machine (ELM) Method calculations. Test result of The ELM parameter provides accuracy result 80,01% with k=10 amount hidden neuron 25 Interval weights -0.5 until 0,5 using function activation Sigmoid biner. We have come to conclusion were ELM method could positively solve the prediction problem exquisitely.