Indonesian Journal of Electrical Engineering and Computer Science Vol. 7, No. 3, September 2017, pp. 846 ~ 854 DOI: 10.11591/ijeecs.v7.i3.pp846-854  846 Received June 2, 2017; Revised August 13, 2017; Accepted August 29, 2017 Classification Of Category Selection Title Undergraduate Thesis Using K-Nearest Neighbor Method Ratih Kumalasari Niswatin * , Ardi Sanjaya Departement of Informatics Engineering/University of Nusantara PGRI Kediri, Campus II, Mojoroto Gang I No. 6, Mojoroto, Kediri, Jawa Timur, Indonesia *Corresponding author, e-mail: ratih.workmail@gmail.com Abstract This research makes the classification system of category selection title undergraduate thesis title use k-nearest neighbor method. This research will be conducted on the students of Informatics Engineering Department Faculty of Engineering, Universitas Nusantara PGRI Kediri. The purpose of making this system is to employee department and students to more easily make a classification of category selection undergraduate thesis title based on the field of interest and field of expertise of each student. The method used to classify the selection of undergaduate thesis title categories is k-nearest neighbor method using several criteria based on students' interests and expertise in a particular field or course. The result of this sitem is an information category of undergraduate thesis title of students who have been processed based on the field of interest and field of expertise of each student. Keywords: classification, undergraduate thesis, k-nearest neighbor Copyright © 2017 Institute of Advanced Engineering and Science. All rights reserved. 1. Introduction The university is the organizer of academic education for students [1]. Students as college products can be used as a reference to show the success of education. The success of student achievement can be seen from several factors such as cumulative grade point value (GPA) obtained by students, duration of student study, and student thesis score. In this research will be discussed one of the above factors is the success of student undergraduate thesis score. Understanding undergraduate thesis according to a large dictionary of the Indonesian language is a scientific essay that must be written by students as part of the final requirements of academic education [2]. Based on this, every final year student must take and complete the undergraduate thesis as the graduation requirement from higher education. But in reality many students have difficulty in choosing the category and title of the graduate thesis according to the field of interest and the field of expertise, therefore in this research will be made a classification system of category selection of student undergraduate thesis title using k-nearest neighbor (k-nn) method. Nearest neighbor is an approach to finding a case by calculating the proximity between a new case and an old case, based on a weighted fit of a number of features [3]. Nusantara University PGRI Kediri is a private university in Kediri City which has five Faculties, one of which is the Faculty of Engineering which has five study programs namely: Informatics Engineering, Mechanical Engineering, Electrical Engineering, Industrial Engineering and Information Systems. This research will be conducted in Informatics Engineering Study Program to assist the department in classifying the category of student's undergraduate thesis title and assisting the final grade students to choose the title category of undergraduate thesis based on the field of interest and the area of expertise. The problems can be formulated in this research are how to apply k-nearest neighbor method to classify the selection of undergraduate thesis title categories of students based on their field of interest and field of expertise and how to apply k-nearest neighbor method for the proper and accurate classification of category selection of student undergraduate thesis title. The purpose of this research is to Apply k-nearest neighbor method for classification of undergraduate thesis title categories based on the field of interest and the field of expertise of