@thesis{thesis,
		author={Febriyanto  Firman Giri and Luqman  Luqman and Rifai  Mochamad Farid},
		title ={PENENTUAN DOKUMEN LAMPIRAN SURAT KETERANGAN PENDAMPING IJAZAH (SKPI) MENGGUNAKAN METODE TERM FREQUENCY – INVERSE DOCUMENT FREQUENCY (TF-IDF) DAN VECTOR SPACE MODEL (VSM) (STUDI KASUS : STT-PLN JAKARTA)},
		year={2018},
		url={http://156.67.221.169/4707/},
		abstract={At PLN Technical College (STT-PLN), the determination type of document
attachments letter a companion qualifications (SKPI) are still done manually. This
research aims to provide an alternative to determine the type of document
attachments to SKPI. The methods are applied to build the system is Text Mining,
Term Frequency Inverse Document ? Freqeuncy (TF-IDF) and Vector Space Model
(VSM). Text mining to perform processing of data, where the data to be processed is
title and data from document SKPI, while VSM to perform classification based on the
highest weighting of each document. This research can recommend six types of
categories to be the determination of the types of SKPI. Among them is the
international language, championship award, character education, final project/thesis,
internship industry and also the experience of the organization. In this research, the
author uses the model of software development is a Cross-Industry Standard Process
for Data Mining (CRISP-DM). The results of this research use 30 test data that has
an accuracy rate of 93.33%.}
		}