Implementasi Cosine Similarity Dan Na¨Ive Bayes Classifier Untuk Mencari Dalil Pada Artikel Islami Berdasarkan Indeks Al-Qur‘An

LANA RAHIM, NIM.: 15650002 (2019) Implementasi Cosine Similarity Dan Na¨Ive Bayes Classifier Untuk Mencari Dalil Pada Artikel Islami Berdasarkan Indeks Al-Qur‘An. Skripsi thesis, UIN Sunan Kalijaga.

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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.

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