the development of information technology is currently progressing, multimedia is one of the right way to facilitate the delivery of information in the form of audiovisual form of 3D animation. Utilizing multimedia to convey information is as one way in an effort to publish the traditional architecture of the Lombok area, especially the traditional house of Belek Sembalun Lawang Village in the form of 3D animation using blender software that can be used as a medium of learning. Belek Village is a large village/village parent which was first created consisting of seven houses that are the forerunner of Sembalun Village. By using 3D animation is expected to provide solutions and alternatives in the process of introduction and learning about the traditional architecture of Lombok traditional house especially the traditional house of Belek Village, so that in the process of learning and recognition becomes more unique and interesting, as well as learning media and introduction of traditional house of Belek Village, 3D animation can also provide an advantage in publication efforts and documentation of history and culture of Sembalun Lawang Villag.

In implementing the performance evaluation of lecturers, a monitoring and evaluation Information System based system has been developed, better known as e-monevin. Assessment is conducted by students on lecturers who take courses taken by students in the current semester. The results of the student assessment are taken into consideration in the assembly of lecturers. Performance is a way, behavior, and ability of a person. The performance of lecturers is assessed by how to carry out their duties and responsibilities as educators in delivering material to students. Measurement and evaluation of lecturers’ performance seen from several aspects one of which is the field of education and teaching. The purpose of this study is to determine the performance of lecturers in the field of education and teaching through e-mononevin using Rapid Miner software in data processing. The data processing technique used is the K-Nearest Neighbor (K-NN) algorithm. From the test results that have been done using the K-NN algorithm in K-Fold Cross Validation with different number of validations, the best accuracy value obtained shows that the K-NN algorithm using number of validation 6 and 9, with an accuracy value of 96.30 %.

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