Classification System of Indonesian Language Thesis Documents in Computer Science Department using K-Means Algorithm
Boldson Herdianto Situmorang1, Rezky Ramadhan Alkausar2, Prihastuti Harsani3
1Boldson Herdianto Situmorang, Department of Computer Science, Pakuan Bogor University, Indonesia.
2Rezky Ramadhan Alkausar, Department of Computer Science, Pakuan Bogor University, Indonesia.
3Prihastuti Harsani, Department of Computer Science, Pakuan Bogor University, Indonesia.
Manuscript received on 03 August 2019 | Revised Manuscript received on 26 August 2019 | Manuscript Published on 05 September 2019 | PP: 138-141 | Volume-8 Issue-2S7 July 2019 | Retrieval Number: B10330782S719/2019©BEIESP | DOI: 10.35940/ijrte.B1033.0782S719
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Thesis is a scientific paper created by the student as a final requirement on his final academic education to earn a bachelor’s degree. Students of the Computer Science Department at Pakuan University are faced with the difficulty of finding the previous thesis references to determine the desired thesis theme because the clustering of the thesis documents is set based on the writing year only and not based on the theme classifications which includes Software Engineering, Hardware Programming, Artificial Intelligence, and Network Computer. A computer based system will be developed where the data in the Thesis document will be processed through text pre-processing which aims to convert unstructured document data into structured so that it can be read by the system, then grouped using K-Means Algorithm.
Keywords: Classification System, Thesis Documents, K-Means Algorithm.
Scope of the Article: Classification