Pengklasteran Laporan Tugas Akhir Berdasarkan Abstrak Menggunakan Metode Rapid Automatic Keyphrase Extraction Dan Average Linkage Hierarchical Clustering

Fatmawati, Mega (2017) Pengklasteran Laporan Tugas Akhir Berdasarkan Abstrak Menggunakan Metode Rapid Automatic Keyphrase Extraction Dan Average Linkage Hierarchical Clustering. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Tugas Akhir merupakan salah satu syarat wajib mahasiswa S1 ITS untuk mendapatkan gelar sarjana. Setiap mahasiswa tingkat akhir seringkali kesulitan dalam menentukan pokok pembahasan atau topik apa yang akan dibahas di laporan Tugas Akhir. Oleh karena itu, pada penelitian ini disajikan pengklasteran laporan Tugas Akhir berdasarkan abstrak. Metode Rapid Automatic Keyphrase Extraction (RAKE) digunakan untuk mengekstraksi kata penting yang ada di abstrak laporan Tugas Akhir mahasiswa ITS. Parameter jumlah kata peting pada RAKE mempengaruhi kualitas pengklasteran dokumen. Metode Average Linkage Hierarchical Clustering digunakan untuk pengklasteran laporan Tugas Akhir mahasiswa ITS. Hasil pengklasteran berdasarkan jumlah kata penting dapat memberikan informasi mengenai topik – topik dalam bentuk cluster – cluster. Pada Tugas Akhir ini uji coba dilakukan terhadap 3 data departemen yaitu Matematika, Fisika dan Teknik Perkapalan. Berdasarkan hasil uji coba, pengklasteran terbaik dilakukan dengan menggunakan 2 kata penting.

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The final project is one of the conditions of the compulsory undergraduate students of Institut Teknologi Sepuluh Nopember (ITS) to get a degree. Every student who wants to work the final assignment usually difficult to determine the topics will be covered in the final project reports.. Therefore, in this study presented clustering final project reports based on abstract. A method of Rapid Automatic Keyphrase Extraction (RAKE) is used to extraction the important words that exist in ITS student final project abstracts. Average Linkage method of Hierarchical Clustering are used to clustering reports student final project ITS. Clustering results based on word count can provide information on important topics – topics in a cluster. In this final project trials conducted against the 3 departments namely mathematics, physics and marine engineering. Based on the results of the experiment, best clustering using 2 important words.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Rapid Automatic Keyphrase Extraction, Pengklasteran, Tugas Akhir, Average Linkage Hierarchical Clustering
Subjects: Q Science > QA Mathematics > QA278 Cluster Analysis. Multivariate analysis. Correspondence analysis (Statistics)
Divisions: Faculty of Mathematics and Science > Mathematics > 44201-(S1) Undergraduate Thesis
Depositing User: Mega Fatmawati .
Date Deposited: 12 Dec 2017 02:42
Last Modified: 06 Mar 2019 03:44
URI: http://repository.its.ac.id/id/eprint/46865

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