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All Journal TEKNIK INFORMATIKA Jurnal Ilmu Komputer dan Agri-Informatika Jurnal Pseudocode Teknika: Jurnal Sains dan Teknologi SAMARAH: Jurnal Hukum Keluarga dan Hukum Islam MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Komputasi : Jurnal Ilmiah Ilmu Komputer dan Matematika
Hendra Bayu Suseno
Universitas Islam Negeri Syarif Hidayatullah Jakarta, Indonesia
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences

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Implementation of Convolutional Neural Network with VGG-16 Architecture in Digital Hiragana Handwriting Image Recognition Hendra Bayu Suseno; Fitri Mintarsih; Victor Amrizal; Rheditia Ferdiansyah; Tjut Awaliyah Zuraiyah
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol. 23 No. 1 (2026): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika.
Publisher : Program Studi Ilmu Komputer, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v23i1.65

Abstract

The number of Japanese language learners in Indonesia ranks second at 711,732 people. Hiragana is the first letter to be learned, especially at the beginner level and is usually learned before Katakana and Kanji. Some characters in Hiragana have similar main forms such as nu (ぬ) and me (め), ne (ね) and wa (わ), thus adding complexity to the recognition process. Like previous research that created a Hiragana pronunciation learning application and previous research that was an English writing learning application, allowing people to learn on their own, by applying CNN (Convolutional Neural Network) to recognize written characters, researchers were inspired to apply this in learning to write Hiragana letters. Therefore, researchers created a digital Hiragana handwriting recognition model using the VGG-16 CNN Architecture method so that the model created can later be used in a Hiragana learning application for writing. This study used a dataset in the form of digital Hiragana handwriting images totaling 1518 data with 33 data for each label (46 types of letters). The hyperparameters used in this study to train the model were 5 epochs, a batch size of 32, the Adam Optimizer, and a Learning rate of 0.001. Based on the test results with the aforementioned parameters, the Accuracy value was 98.55%, Precision was 98.91%, Recall was 98.55%, and the F1-Score was 98.51%.
Adopting Cryptocurrency Apps from a Sharia Perspective: The Readiness of Generation Z Muslims in the Digital Technology Era Siti Hanna; Siti Ummi Masruroh; Amrin Amrin; Dewi Aprilia Ningrum; Hendra Bayu Suseno
Samarah: Jurnal Hukum Keluarga dan Hukum Islam Vol. 10 No. 1 (2026): Samarah: Jurnal Hukum Keluarga dan Hukum Islam
Publisher : Islamic Family Law Department, Sharia and Law Faculty, Universitas Islam Negeri Ar-Raniry

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/sjhk.v10.i1.29702

Abstract

The development of Web 3.0 technology has driven the birth of various digital innovations, including cryptocurrency and blockchain-based financial applications. This phenomenon affects the pattern of technology adoption by Generation Z Muslims, who are known to be adaptive to technology but still bound by religious values. This study aims to analyze the readiness of Generation Z Muslims to adopt cryptocurrency applications from a Sharia law perspective and to evaluate their understanding of the provisions of fiqh muamalah in a digital context. The methodology used is a qualitative approach with literature study and document analysis. The study results show that although most Generation Z have high digital skills, there is still a gap in understanding regarding the legal status of cryptocurrency in Islam. Based on the 2021 DSN MUI fatwa, cryptocurrency as a currency is considered haram because it contains elements of gharar and dharar. Still, it can be accepted as a digital asset with clear underlying assets and real benefits. This study concludes that Sharia financial literacy and digital literacy need to be improved simultaneously to support adopting financial technology based on Sharia principles. These findings contribute to developing a sustainable, inclusive, and adaptive digital sharia financial ecosystem to the dynamics of Web 3.0 technology.
Co-Authors Addini Yusmar Alfatta Reza Amrin Andi Malik Rizki Maulana Andrew Fiade Anif Hanifa Setyaningrum Aryajaya Alamsyah Dewi Aprilia Ningrum Diana Nur Yastin Feri Fahrianto Fitri Mintarsih Luh Kesuma Wardhani Muhamad Fahri Muhammad Fahri Nurhayati Nurhayati Priyanti Priyanti Rheditia Ferdiansyah Shofi, Imam Marzuki Siti Hanna Siti Ummi Masruroh Tjut Awaliyah Zuraiyah Velia Handayani Victor Amrizal Victor Amrizal Viva Arifin Viva Arifin