METODE COSINE SIMILARITY UNTUK KLASIFIKASI PENGARSIPAN DATA PEGAWAI DI PT PLN DISJAYA
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
SITOMPUL, RIFKA RAHMA YANI
Yudho, Satrio
Siregar,, Riki Ruli A
Yudho, Satrio
Siregar,, Riki Ruli A
Subject
Teknik Informatika
Datestamp
2022-09-21 03:58:46
Abstract :
Archiving is the process of storing and managing archived documents according to a particular filling system. At PT PLN Disjaya employee data archiving is carried out in 3 stages: file sorting, file scanning and file number input. The problem that arises in the archiving of data is that employee data that has been entered into the system is only stored just like that into a folder available on the desktop without any direct distribution process into the predetermined category classification, the number of employee data that must be archived in a day there are 100 data even more. Time needs in the process of archiving employee data that must be archived spend 5-15 minutes for one employee data. The purpose of this study is that the input data can be distributed directly and properly classified into 6 categories, namely: application categories, job categories, family categories, education categories, reward or punishment categories and other categories. The method used is Cosine Similarity which serves to show the similarity between test documents and training documents. This method goes through the process of processing first to get the value of TF ID weighting, then the calculation of the similarity results of each employee's data. Accuracy results obtained from the Cosine Similarity method are as follows: the similarity is 70%.
Archiving is the process of storing and managing archived documents according to a particular filling system. At PT PLN Disjaya employee data archiving is carried out in 3 stages: file sorting, file scanning and file number input. The problem that arises in the archiving of data is that employee data that has been entered into the system is only stored just like that into a folder available on the desktop without any direct distribution process into the predetermined category classification, the number of employee data that must be archived in a day there are 100 data even more. Time needs in the process of archiving employee data that must be archived spend 5-15 minutes for one employee data. The purpose of this study is that the input data can be distributed directly and properly classified into 6 categories, namely: application categories, job categories, family categories, education categories, reward or punishment categories and other categories. The method used is Cosine Similarity which serves to show the similarity between test documents and training documents. This method goes through the process of processing first to get the value of TF ID weighting, then the calculation of the similarity results of each employee's data. Accuracy results obtained from the Cosine Similarity method are as follows: the similarity is 70%.
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