Implementation of Word Recommendation System Using Hybrid Method for Speed Typing Website

Typing is one of the most frequently done activities in society therefore a medium is necessary to help train typing words that are often mistyped. Methods used in this research are the Content-Based Filtering Algorithm to gather the words that have a similar pattern to the words that are often mistyped based on the user's previous typing records and the Collaborative Filtering Algorithm that uses other users typing pattern to recommend the words. The result of this study shows the Collaborative Filtering Algorithm was able to gather words that are hard to type by the user with an accuracy of 49.2%, dan the Collaborative Filtering able to predict the score on how difficult for the user to type a word with the result of Root Mean Square Error (RMSE) value of 0.82 and with the Root Mean Square Percentage Error (RMSPE) value of 30% from the actual value, and a website which is the combination of the two algorithms with the result of 28% of the total word that is recommended was indeed difficult to type by the user with the typing speed of 103 WPM, and 72.3% for the user that has a typing speed of 39 WPM.