Bimantara, Rahardian Dewa (2017) Implementasi Fitur Temu Kembali Informasi SLiMS Pada Web Manajemen RBTC. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Ruang Baca Teknik Informatika ITS menggunakan Senayan Library Management System (SLiMS) sebagai dasar arsitektur pembangunan sistem informasi perpustakaan digital guna mempermudah mahasiswa maupun staf untuk mencari informasi. Seiring bertambahnya jumlah dokumen dalam repositori digital, Fitur temu kembali informasi yang ada tidak dapat mengimbangi sehingga mahasiswa menemukan banyak kendala dalam mendapatkan informasi. Mahasiswa sering mencari referensi guna memilih topik tugas akhir dan tesis yang sedang populer. Fitur temu kembali informasi tambahan perlu dibangun sebagai solusi permasalahan tersebut. Clustering topik-topik tugas akhir dan tesis juga bisa menjadi salah satu cara untuk menggali informasi bagi rencana pengembangan kurikulum maupun perencanaan pengambilan topik tugas akhir dan tesis yang sedang populer sebagai rekomendasi. Fitur temu kembali informasi yang dibangun diharapkan bisa mempermudah mahasiswa untuk memperoleh informasi dan pengetahuan yang menjadi kebutuhannya. Fitur pencarian yang baru dibangun dengan metode yang biasa digunakan dalam sistem temu kembali informasi, yakni Vector Space Model. Proses clustering topik tugas akhir dan tesis menggunakan K-Means Clustering, dan membagi topik-topik menjadi beberapa kelompok sesuai dengan bidang minat Teknik Informatika ITS. Fitur pencarian yang dibangun dapat mencari dengan kriteria yang lebih detil dari yang ada di RBTC. Abstrak tercluster secara merata pada tiap cluster yang terbentuk, tetapi nilai kualitas cluster masih sangat rendah untuk jumlah kelompok delapan, tetapi tinggi untuk jumlah kelompok tiga karena pembagian bidang minat Teknik Informatika juga masih belum sepenuhnya terpisah. ===================================================================================== ITS Informatics Engineering Reading Room uses Senayan Library Management System (SLiMS) as the basic architecture of digital library information system in order to facilitate students and staff to find information. With increasing number of documents in the digital repository, feature information retrieval cannot be offset so that the students do not find many obstacles in getting information. Students often find references to elect the undergraduate thesis and thesis topics that are popular. Additional features of information retrieval needs to be built as a solution to these problems. Clustering topics of undergraduate thesis and thesis could also be one way to gather information for planning, curriculum development and planning decision and the undergraduate thesis and thesis topic that is popular as a recommendation. Features built by information retrieval expected to facilitate students to acquire information and knowledge into their needs. The new search feature is built with a method commonly used in information retrieval system, the Vector Space Model. Clustering process undergraduate thesis topic and thesis using the K-Means Clustering, and split the topics into certain amount of groups according to their areas of interest ITS Informatics Engineering. The new search feature can search by more detailed criteria than in RBTC. Abstracts are clustered almost evenly on each cluster, but the value of the quality of the cluster is very low for eight groups yet high for three, because of the division of areas of interest of Informatics is still not completely separated.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | Text Mining; Tugas Akhir; Tesis; Dokumen; K-Means Clustering; Vector Space Model; Undergraduate Thesis; Thesis; Document; K-Means Clustering; Vector Space Model |
| Subjects: | Z Bibliography. Library Science. Information Resources > ZA Information resources > Z699.5 Information storage and retrieval systems |
| Divisions: | Faculty of Information Technology > Informatics Engineering > 55201-(S1) Undergraduate Thesis |
| Depositing User: | - RAHARDIAN DEWA BIMANTARA |
| Date Deposited: | 20 Apr 2017 02:14 |
| Last Modified: | 22 Dec 2017 07:10 |
| URI: | https://repository.its.ac.id/id/eprint/3765 |
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