Implementasi algoritma fuzzy C-means pada perangkat lunak bantu pengklasteran hasil pencarian hadist shahih

Sofyan, Muhamad (2016) Implementasi algoritma fuzzy C-means pada perangkat lunak bantu pengklasteran hasil pencarian hadist shahih. Diploma thesis, UIN Sunan Gunung Djati Bandung.

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Abstract

INDONESIA Proses pengambilan data pada search engine yang masih memakai metode konvensional masih menyusahkan user dalam mencari dokumen-dokumen yang diperlukan. Hasil dari pencarian itu masih berisi dokumen yang tidak relevant yang masih harus diseleksi secara manual oleh user. Clustering merupakan salah satu teknik dalam pengkategorian dokumen. Ide dasarnya merupakan dengan mengelompokan dokumen-dokumen ke dalam grup-grup atau cluster berdasarkan kemiripan (similarity) antar dokumen, sehingga dokumen yang berhubungan dengan suatu topik tertentu ditempatkan pada cluster yang sama. Dengan algoritma Fuzzy C-Means maka hasil pencarian hadits shahih akan di cluster atau dikelompokan beradasarkan kemiripan kata antar dokumen. Berdasarkan pengujian yang telah dilakukan sistem dapat mengelompokan hasil pencarian hadits shahih berdasarkan kemiripan kata. Selain itu, berdasarkan pengujian sistem dan pengujian manual menghasilkan bahwa algoritma fuzzy c-means memiliki tingkat akurasi sebesar 82,4% yang bekerja pada sistem pencarian hadits shahih. ENGLISH The process of retrieving data on search engines that still use conventional methods still troublesome users in finding the necessary documents. The result of the search it still contains documents that are not relevant are still to be selected manually by the user. Clustering is one of the techniques in this document. The basic idea is with group documents into group or cluster based on similarity between documents, so that the documents related to a given topic are placed on the same cluster. With Fuzzy C-Means Algorithm, then the search result will be in the saheeh ahaadeth cluster or group on word similarity between documents. Based on the testing that has been done the system can group search results based on the similarity of hadeeth said. In addition, based on testing systems and testing manual Fuzzy C-Means Algorithm that generates have the accuracy of 82.4% who worked on the search system Saheeh ahaadeeth.

Item Type: Thesis (Diploma)
Uncontrolled Keywords: Fuzzy C-Means; Sistem Pencarian; Clustering; Search Engine;
Subjects: Data Processing, Computer Science > Computer Science Education
Divisions: Fakultas Sains dan Teknologi > Program Studi Teknik Informatika
Depositing User: rofita fita robi'in
Date Deposited: 23 May 2019 12:07
Last Modified: 23 May 2019 12:07
URI: http://digilib.uinsgd.ac.id/id/eprint/20567

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