@phdthesis{digilib40413,
           month = {May},
           title = {Implementasi Cosine Similarity Dan Na?Ive Bayes Classifier Untuk Mencari Dalil Pada Artikel Islami Berdasarkan Indeks Al-Qur?An},
          school = {UIN Sunan Kalijaga},
          author = {NIM.: 15650002 LANA RAHIM},
            year = {2019},
            note = {Pembimbing: Muhammad Didik Rohmad Wahyudi, S.T., MT},
        keywords = {Cosine Similirity,Naive Bayes,Qur?an, Islamic Articles},
             url = {https://digilib.uin-suka.ac.id/id/eprint/40413/},
        abstract = {The Al-Qur?an Index is a navigation tool that is used to explore the breadth
and diversity of themes in the Qur?an. The Al-Qur?an Index is used as a reference to
get the verses contained in the Qur?an. But in the process of searching for referrals
it is still done manually so that the search process takes a long time.
Building an intelligent system that can classify and search for arguments
from a document in accordance with the Al-Qur?an index is expected to help people,
both Muslims and non-Muslims, to understand and understand the verses in the
Qur?an. With the method of cosine similarity and Naive Bayes can be used to do
classifiers and look for relevant verses according to the Qur?an.
This research was conducted with the preprocessing stage for Islamic articles, weighting with TF-IDF, and calculations with Cosine Similarity. The results
of the tests carried out using confusion matrix were obtained: 38\% accuracy, 9\%
precission, and 8\% recall.}
}