Clustering Mining Equipment Productivity Data Using K-Means Algorihtm

There are many factors that affect the productivity of mining equipment, one which is condition equipment when it used. Knowing machines on mandatory for supervisors in activities. In analyzing data large quantities requires a lot energy and time, so classification model needed can categorize based its performance. Data Mining process uses statistical, mathematical, artificial intelligence machine learning techniques to extract information. The results obtained duration work has impact correlation value between maintenance tool. analysis also carried out by clustering using K-Means model. conclusion supports with less working affects productivity. result shows variables divide categories tool performance techniques.