<![CDATA[The development of information technology currently has a very important role and can be utilized in facilitating all human activities from various aspects, including activities that take place in the health sector such as hospitals which already use many information systems specifically designed to handle various supplies or inventory. At the Rantau Prapat Regional Hospital, data collection on medical equipment supplies still uses manual methods, namely visiting and recording the equipment that needs to be equipped to each polyclinic one by one, which takes quite a long time and the medical equipment inventory team has difficulty prioritizing which tools must be equipped first for each polyclinic, so that continue to maintain the number of treatment numbers in each clinic, especially in dental and oral clinics. Therefore, we need a system for recommending dental medical equipment based on the dental diseases frequently suffered by patients and the number of treatments per year. In building a web-based dental medical tool recommendation system, researchers used the K-Nearest Neighbor (KNN) algorithm method to classify new objects based on attributes and training samples. The working principle of KNN is to find the shortest distance between the data used and its K closest neighbors in the training data and produce more accurate and effective data.]]>
