Handling of dental disease problems requires that it be handled quickly and correctly, but not all teams of dental experts can carry out treatment quickly due to the lack of a team of dental experts who are in the workplace or hospital 24 hours a day.  Apart from that, the public also has very little knowledge of information about dental disease, so that to treat dental disease, people have to consult a dentist. To classify images of dental disease, feature extraction is needed. Feature extraction is taking characteristics of an object that can describe the image. One example of image feature extraction used is Red, Green, Blue (RGB). This feature extraction is often used to identify or classify an image. Dental image data that will be used in the classification process are tooth abrasion, anterior crosbite, cavities and gingivitis. K-Nears Neigbor is the simplest data mining algorithm.  The aim of this algorithm is to find the results of the closest distance classification for each object.  In determining the distance, the data is initially divided into two parts, namely training data and testing data. After receiving the training data and testing data, the distance from each testing data (Equilidence Distance) to the training data is calculated. The K-Nearest Neighbors method can be applied to classify dental disease based on images of types of dental disease using Matlab software. As a result of the image data training process, 40 image data were input, training results obtained were 100%.

Libraries as information service providers require information systems that can manage data and information effectively and efficiently. Information system audits are needed to evaluate information system performance and ensure organizational goals are achieved. This research aims to analyze library service information system audits using the COBIT 5 framework, because it focuses on services and service requests. The stages of an ABC library service audit include determining audit objectives, identifying library services using the Framework, capability level analysis, testing controls and evidence at the capability level, verifying results, and compiling audit results reports and recommendations. Audits carried out for library services focus on Process Domains DSS01 and DSS02.