Ichsan Taufik
Universitas Islam Negeri Sunan Gunung Djati Bandung

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The search for science and technology verses in Qur’an and hadith Ichsan Taufik; Mohamad Jaenudin; Fatimah Ulwiyatul Badriyah; Beki Subaeki; Opik Taupik Kurahman
Bulletin of Electrical Engineering and Informatics Vol 10, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i2.2629

Abstract

Currently, the Vector Space Model algorithm has been widely implemented for the document search feature because of its reliability in retrieving information. One of them in the search for verses of the Qur'an based on the translation. However, if the phrase or word used is different (even though it has one meaning) with the word in the document in the database, the system will not display the verse. As we know that the Qur'an has a very deep meaning, so an interpretation of the verse is needed. Therefore, this research focuses on implementing the Vector Space Model (VSM) algorithm for searching verses and hadiths in science and technology by using the discussion parameters of these verses or hadiths. The test results obtained with 20 keyword samples using metric recall were 81% with an average time of 2.24 seconds.
Implementasi Algoritma BERT untuk Question and Answer System Terkait Hadist dalam Bentuk Virtual Youtuber Moch Arsyil Albany; Ichsan Taufik; Ichsan Budiman
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 15 No 02 (2025): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v15i02.1704

Abstract

In this digital era, the integration of Islamic teachings with advanced technology has become essential. This research focuses on developing an Islamic QnA system using Artificial Intelligence in the form of a Virtual YouTuber (VTuber). The system leverages the IndoBERT-SQuAD algorithm for Natural Language Processing, particularly in handling questions about hadiths. By employing prototype methodology, the system underwent stages of analysis, design, implementation, and evaluation. Confidence score and F1-score metrics were utilized to assess the system's performance. After contextual grouping, the model demonstrated significant improvement, achieving an F1-score of 0.96875. Despite these advancements, the system still faces challenges in providing accurate long-form answers. This research contributes to the application of technology in Islamic education, offering a practical solution for making hadith knowledge more accessible and appealing to the younger generation.