Item Rating and Football Score Priori Prediction Algorithm

Attempts have been made to resolve various prediction issues relating to recommender system algorithms. In everyday life, there is a lot of need to predict something. For example, when you want to determine which items someone wants to buy or estimate the results of football matches or predict the rating of a movie. It's better if we can sell something that is in accordance with the wishes of the customer. Therefore, algorithm predictions are needed that can produce predictions accurately and precisely. In this paper, algorithm predictions are presented with prior data concepts, where data will be divided into 2 parts, training and testing dataset. There are 5 stages in the Priori Prediction (PP) algorithm starting from the data input process, checking the similarity of data, calculating using the difference function, calculating the predictive score, then evaluating using MAE.PP algorithm is also compared with other recommender system algorithms, which are collaborative filtering, cosine similarity, and content-based filtering in experiments and evaluations. The test results show that the proposed algorithm has satisfactory performance compared to other recommender system.