Penggunaan Algoritma Naïve Bayes pada Klasifikasi Judul Proyek Akhir Berdasarkan Kelompok Bidang Kompetensi (KBK)

Dini Nurmalasari, H. Yuliantoro, Saleha Indri Yanti
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Abstract

The Final Project is one of the graduation requirements that must be met by Caltex Riau Polytechnic students. The title of the final project is submitted by students through the SIAK system. Currently, students who submit titles will choose their own type of KBK from the inputted title. So that a problem arises where the title of the final project does not match the KBK it should or the KBK is wrong. This is due to the ignorance of students in analyzing the title data of the final project that will be submitted. For this reason, a system is needed to classify Final Project titles based on CBC automatically. The system created is a system that can classify KBK automatically based on the description of the title of the Final Project by using text mining methods and nave Bayes algorithms. The system can also detect the percentage of similarity of the entered title with the existing title in the system database. The algorithm used to generate the percentage of title similarity is cosine similarity with text mining method.
基于能力组(KBK)对最终项目标题分类的Naive Bayes算法的使用
期末设计是加德士廖内理工学院学生必须完成的毕业要求之一。期末设计题目由学生通过SIAK系统提交。目前,提交题目的学生将从输入的题目中选择自己的KBK类型。因此,当最终项目的标题与KBK不匹配或KBK错误时,就会出现问题。这是由于学生在分析将要提交的期末项目的标题数据时的无知。因此,需要一个基于CBC自动分类Final Project标题的系统。所创建的系统是利用文本挖掘方法和朴素贝叶斯算法,根据Final Project题目的描述,自动对KBK进行分类的系统。系统还可以检测输入的标题与系统数据库中现有标题的相似度百分比。生成标题相似度百分比的算法是基于文本挖掘的余弦相似度算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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