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All Journal Jurnal Informatika dan Multimedia Hunafa: Jurnal Studia Islamika Paradigma
Rudy Arianto, Rudy
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Religion Humanities Computer Science & IT Social Sciences

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Perancangan dan Pembuatan Aplikasi Kelas Virtual Muslam, Muhammad; Sukya, Fadelis; Arianto, Rudy
Jurnal Informatika dan Multimedia Vol 6 No 1 (2014): Jurnal Volume 6, No 1 (2014)
Publisher : Teknik Informatika Politeknik Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Banyak perguruan tinggi masih menggunakan sistem manual dalam pembelajaran dan menggunakan media kertas. Hal tersebut mengakibatkan pencarian data sulit dilakukan dan memerlukan banyak waktu. Oleh karenanya perlu dibangun kelas virtual yang memiliki fasilitas untuk mengelola materi, manajemen tugas dan nilai secara digital. Sistem ini dibangun dengan menggunakan bahasa pemrograman PHP dan menggunakan database mysql. Terdapat beberapa fitur. Antara lain: kegiatan perkuliahan, perekaman data mahasiswa, pengumpulan tugas, dan pemberian nilai tugas. Pada aplikasi kelas virtual ini belum terdapat fitur kuisioner, dan hanya dapat menangani penilaian tugas saja. Saran untuk pengembangan aplikasi yakni dengan membarikan fitur video chating, kuisioner, dan pemberian nilai selain nilai tugas.
CLASSIFICATION OF TAFSIR MAUDHU'I MAHMUD SYALTUT Amir, Asrul; Arianto, Rudy; Misbahuddin, Adriyan
Hunafa: Jurnal Studia Islamika Vol 20 No 2 (2023): Hunafa: Jurnal Studia Islamika
Publisher : State Islamic University of Datokarama Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24239/jsi.Vol20.Iss2.712

Abstract

Various methods of exegesis have been born which in essence are attempts to reveal the meanings of the Qur'an. The most popular maudhu'i (thematic) interpretation method for this matter. The majority of scholars are of the opinion that maudhu'i interpretation is revealing the meanings of the Qur'an and explaining its more general meanings, and explaining difficult-to-understand pronunciations. This article uses the library research method (Library Research) which requires qualitative data. This research is based on the contents of books, journals, and other library sources. This method is very commonly used so it is easy to understand. The objectives to be achieved from this article are to find out the biography of Mahmud Syltut, to find out the identity of the printed book to the method used by Mahmud Shaltut in writing his commentary. So that we can find the meaning of the word Maudhu'i according to Mahmud Syaltut "That the maudhu'i method, in addition to other methods, is a very good method, especially for materials published to the public, with the aim of giving them instructions about various kinds of guidance. contained in the Koran.
Support Vector Machine with FastText Word Embedding for Hate Speech Aspect Categorization Mardiana, Aida Milati; Rozi, Imam Fahrur; Arianto, Rudy
Paradigma - Jurnal Komputer dan Informatika Vol. 27 No. 2 (2025): September 2025 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v27i2.5127

Abstract

Freedom of expression on Twitter often leads to issues such as hate speech, which may include provocation, incitement, or insults based on race, religion, gender, and other aspects. To address this issue, machine learning techniques can be applied to automatically classify hate speech. Therefore, this study aims to implement a machine learning–based approach for automatic hate speech aspect classification and to evaluate the accuracy of the obtained results. Support Vector Machine is used as the classifier method, with FastText as the word embedding method in the categorization process of hate speech aspects. The categorized aspects include abusive, individual, group, religion, race, physical, gender and other. The dataset used in this research is a collection of Indonesian tweets from Kaggle, which have been classified into each aspect. This study also tested combinations of preprocessing methods, namely filtering with stemming and the FastText pre-trained model. From the test results of the application of the Support Vector Machine method with FastText word embedding, with parameters C value = 1.0, gamma = 1.0 and RBF kernel and the ratio between training data and testing data is 90:10, the best results were obtained accuracy 98%, precision 98%, recall 98% and F1-Score 97% on Physical and Gender aspects. In addition, this study also tested if it did not use fasttext word embedding and the accuracy results showed 84%, precision 74%, recall 86% and F1 Score 79% in the abbusive aspect.
Co-Authors Amir, Asrul Fadelis Sukya, Fadelis Imam Fahrur Rozi Mardiana, Aida Milati Misbahuddin, Adriyan Muhammad Muslam, Muhammad