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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Intellect : Indonesian Journal of Learning and Technological Innovation Coreid Journal INTERNAL (Information System Journal) The Indonesian Journal of Computer Science ISTEK
Wildan Budiawan Zulfikar
UIN Sunan Gunung Djati
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Other

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Optimalisasi Layanan Konsultasi Fiqih Mawaris Berbasis Chatbot dengan Pendekatan Rule-Based Irfan, Mohamad; Lustinasari, Kholisah; Zulfikar, Wildan Budiawan
TELKA - Telekomunikasi Elektronika Komputasi dan Kontrol Vol 11, No 3 (2025): TELKA
Publisher : Jurusan Teknik Elektro UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/telka.v11n3.284-292

Abstract

Ilmu fara'id merupakan cabang ilmu yang membahas pembagian harta warisan berdasarkan syariat Islam. Allah telah menetapkan aturan pembagian kekayaan yang harus diikuti sesuai dengan ajaran agama. Proses pembagian warisan melibatkan identifikasi harta peninggalan dan ahli waris, serta meliputi tahapan seperti menentukan bagian (furudh), asal masalah, dan menghitung siham. Namun, proses ini kerap menjadi tantangan bagi umat Islam awam yang tidak memiliki pemahaman mendalam tentang ilmu fara'id. Penelitian ini bertujuan untuk mengoptimalkan layanan konsultasi fiqh warisan berbasis chatbot. Metode yang digunakan adalah pendekatan Rule-Based untuk menyederhanakan dan mengatasi kompleksitas pembagian warisan. Hasil pengujian menunjukkan bahwa prototipe chatbot ini mampu menangani skenario ahli waris suami, istri, anak perempuan, dan anak laki-laki. Dalam pengujian, sistem menggunakan 18 aturan dan 30 data uji, menghasilkan tingkat akurasi sebesar 93%. Hasil ini menunjukkan bahwa pendekatan berbasis aturan pada sistem konsultasi fiqh mawaris ini cukup efektif dan dapat menjadi solusi praktis bagi masyarakat. The science of fara'id focuses on the distribution of inheritance based on Islamic law. Allah has prescribed rules for wealth distribution that must be followed in accordance with religious teachings. The inheritance division process involves identifying the estate and heirs, as well as stages such as determining shares (furudh), the origin of the problem, and calculating siham. However, this process often poses challenges for lay Muslims who lack a deep understanding of fara'id. This study aims to optimize Islamic inheritance consultation services using a chatbot-based system. The method employed is a Rule-Based approach to simplify and address the complexities of inheritance distribution. Experimental results indicate that the chatbot prototype successfully processes scenarios involving heirs such as the husband, wife, daughter, and son. The system was tested with 18 rules and 30 test cases, achieving an accuracy rate of 93%. These findings suggest that the Rule-Based approach implemented in this fara'id consultation system is effective and offers a practical solution for the community.
MOVIE RATING PREDICTION USING NEURAL FACTORIZATION MACHINES (NFM) APPROACH Khairani, Jessy Faujiyyah; Zulfikar, Wildan Budiawan; Lukman, Nur
ISTEK Vol. 14 No. 2 (2025)
Publisher : Fakultas Sains dan Teknologi UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/istek.v14i2.2598

Abstract

This research is motivated by the difficulty viewers have in finding movies that suit their tastes amid the large number of movies being produced. Current movie ratings are often based solely on direct assessments by viewers without considering factors such as genre, audience age category, and movie synopsis. This study aims to predict movie ratings using the Neural Factorization Machines (NFM) approach. The research method includes data preparation, which covers dataset file merging, age category mapping, data cleaning, text conversion to lowercase, regular expression removal, removal of non-English text, tokenization, lemmatizing, word embedding, one-hot encoding, and label encoding. The modeling process was carried out by building an NFM model consisting of feature inputs, embedding layers, bi-interaction layers, hidden layers, and prediction scores. Model evaluation was carried out by setting hyperparameters, namely epoch and batch size, to optimize model performance. This study was conducted with 9 tests using a combination of epochs (30, 50, and 100) and batch sizes (64, 128, and 256). The evaluation results show that the lowest MSE value, which means the best, in the training data is 1.181 with a batch size of 256 and an epoch of 100, and in the validation data is 1.230 with a batch size of 256 and an epoch of 100. However, in the test data, the configuration with a batch size of 128 and 50 epochs gave the best MSE of 1.280. Although the model showed the best performance in the training and validation data with a batch size of 256 and 100 epochs, the evaluation graph indicated overfitting. These findings show that the NFM model is capable of predicting movie ratings based on genre, audience age category, and movie plot description.
Co-Authors Aaz Muhammad Hafidz Azis Agung Wahana Aldy Rialdy Atmadja Ali, Hapid Angelyna, Angelyna Ayu Puji Rahayu Cecep Nurul Alam, Cecep Nurul Cepy Slamet Deden Suparman, Deden Dian Sa’adillah Maylawati Diena Rauda Ramdania Firmansyah, Esa Imam Fahmi Fadillah Jumadi Jumadi Jumadi Jumadi Khairani, Jessy Faujiyyah Lillah, M. Rival Ridautal Lillah Lustinasari, Kholisah Maylawati, Dian Sa’adillah Mohamad Irfan Mohamad Irfan, Mohamad Muhammad Ghufron Naufal Rahman, Muhammad Noorsyahbannie, Mochamad Najib Budi Nur Lukman Pebri Alkautsar Raihan Raihan, Raihan Rialdy Atmadja, Aldy Tubagus Putra, Fauzan Herdika Wahyudin Darmalaksana Wisnu Uriawan, Wisnu Yana Aditia Gerhana