<![CDATA[The problem with most mining companies is a lack of information on the availability of ready-to-use (purchase or rent) heavy equipment and information on providers of heavy equipment spare parts, heavy equipment owners who have difficulty finding a market to sell or rent their equipment. Transaction processes that have been taking place so far have used telephone lines, chats and person-to-person emails where this is felt to be less effective and efficient. This research methodology contains stages regarding the process and procedure of data collection, method analysis procedures, system development procedures as well as the time and place of research. The purpose of this study is to implement the user based filtering recommendation machine method on mining equipment rental systems. The results of the study show that the recommendation system that has been built has succeeded in providing appropriate recommendations to customers who have made mining equipment rental transactions based on the parameters of the results of the recommendation accuracy test. The algorithm of the user based filtering recommendation engine method can be applied to the mining tool recommendation system that has been built. Based on testing the accuracy of the recommendation values, each value obtained in the calculation of the Mean Absolute Error (MAE) is 0.00936 so that the resulting recommendation accuracy is 99.99%. Then for the value of the Mean Absolute Percentage Error (MAPE) obtained a value of 27.84%, and for the value of the Mean Squared Error (MSE) obtained was 0.01702.]]>
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