files from machine learning practitioners.
Machine Learning Team:
- M304DSY1803 - Dinar Wahyu Rahman – Universitas Pembangunan Nasional Veteran Jakarta - [Active]
- M132DSX1825 – Sabrina Tiara Bachtiar – Universitas Airlangga - [Active]
- M251DSX2939 – Muhammad Teguh Prastyo – Universitas Muhammadiyah Malang - [Active]
TENAN: a travel app that can search for tourist destinations chosen by tourists, accommodation such as hotels will be netted, simple, only one action. the accommodation location is adjusted to the coordinates where the user is located. without having to look for both separately, in contrast to similar travel applications.
Collaborative Filtering Recommendation system to predict user preferences or interests based on patterns or associations between users and the items they like. The main concept behind collaborative filtering is that if two users have similar preferences or behaviors in the past, then they are likely to have similar preferences in the future. TENAN using Item-Based Collaborative Filtering. This method predicts user preferences by looking at the similarities between the items selected by the user and other items. If two items have similarities in user preferences, it is likely that the item whose preferences are unknown will also be liked by that user.
We use a dataset of tourist destinations in Indonesia originating fromm here. And for the Hotel Accommodation dataset at here.