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All Journal Al-Manahij: Jurnal Kajian Hukum Islam BERKALA SAINSTEK MAHKAMAH: Jurnal Kajian Hukum Islam Mazahib Al-Daulah : Jurnal Hukum dan Perundangan Islam Constitutional Review JURNAL KAJIAN TEKNIK ELEKTRO International Journal on Emerging Mathematics Education BERNAS: Jurnal Pengabdian Kepada Masyarakat International Journal of Robotics and Control Systems JCOMENT (Journal of Community Empowerment) Al-Manahij : Jurnal Kajian Hukum Islam Berdikari : Jurnal Pengabdian kepada Masyarakat Jurnal Ilmiah Ilmu Terapan Universitas Jambi Jurnal Lektur Keagamaan El 'Aailah KAMI MENGABDI Jurnal Pengkajian Penelitian Syariah dan Ilmu Hukum
Ahmad Rofii
Institut Agama Islam Negeri (IAIN) Syekh Nurjati - Cirebon
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LEGITIMASI PERKAWINAN BEDA AGAMA DALAM PERSPEKTIF HUKUM ISLAM DAN HUKUM POSITIF Nur Rukhama; Ahmad Rofii
INKLUSIF (JURNAL PENGKAJIAN PENELITIAN SYARIAH DAN ILMU HUKUM) Vol. 9 No. 1 (2024): Juni 2024
Publisher : UIN Siber Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/inklusif.v9i1.14100

Abstract

Perkawinan ialah sah menurut hukum agama dan kepercayaan sebagaimana yang telah diatur dalam UU No.1 Tahun 1974. Akan tetapi, melihat pada karektiristik masyarakat Indonesia yang plural dengan berbagai agama, mengakibatkan dapat terjadinya perkawinan beda agama. Pemberlakuan UU No. 23 Tahun 2006 menjadi sarana bagi para pelaku perkawinan beda agama agar perkawinan dapat dilangsungkan tanpa berdasarkan pada hukum agama. Permasalahan dalam penelitian ini yaitu mengenai pandangan hukum islam dan hukum posistif mengenai perkawinan beda agama di Indonesia serta pertimbangan hakim terkait legitimasi perkawinan beda agama di  Indonesia. Penelitian ini  menggunakan pendekatan secara empiris dan normatif. Pada teknik pengumpulan data dilakukan melaui wawancara serta studi kepustakaan. Hasil penelitian menunjukkan bahwa pandangan hukum islam melarang perkawinan beda agama. Berdasarkan hukum positif, pengaturan perkawinan beda agama hanya sebatas pada pencatatan perkawinan yang bersifat administratif. Akan tetapi pada prakteknya, hakim dapat menafsirkan lain terhadap bunyi suatu pasal. Sehingga  terhadap kasus yang sama, pertimbangan hukum hakim dapat berbeda antara hakim yang satu dengan hakim yang lain.
AN EVENT DRIVEN FRAMEWORK INTEGRATING RANDOM MATRIX THEORY AND DEEP LEARNING FOR ACTIVE VOLTAGE CONDITIONER INSTALLATION DECISION IN ELECTRICAL DISTRIBUTION SYSTEMS Rofii, Ahmad; Wijonarko, Panji; Sobirin, Muhammad; Kristyawati, Desy
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 10 No. 4 (2026): Volume 10, Nomor 4, August 2026
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v10i4.55945

Abstract

Voltage sags are frequent disturbances in industrial power systems that can disrupt system operations and cause equipment malfunctions. The proposed framework integrates Random Matrix Theory (RMT) to identify disturbance patterns. It evaluates the severity, vulnerabilities, and operational impact of voltage sag events using the Information Technology Industry Council (ITIC) curve. This research uses event data, disturbance type, associated equipment, disturbance duration, and three-phase voltage measurements to predict the temporal evolution of ITIC conditions in pattern disturbance dynamics. Deep learning models, namely Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), are then employed to predict the temporal evolution of ITIC conditions. Based on power metering unit measurements, the observed voltage variations were non-linear, yet the RMT stability index (Ψ) remained within ITIC tolerance limits. The severity of stability disturbances was successfully evaluated, and the GRU model demonstrated superior predictive performance compared to the LSTM model. Consequently, the industry requires an AVC system—aligned with the combined stability-severity-risk paradigm and the prediction results—to effectively mitigate voltage compensation risks through precise AVC operation. These findings demonstrate that integrating RMT-based fault analysis, ITIC-based severity assessment, and deep learning-based prediction offers a more systematic and predictive approach to voltage sag assessment than relying solely on empirical evaluation. Consequently, this enables more accurate determination of AVC installation requirements, thereby effectively mitigating faults. The implication is a shift in how AVC requirements are assessed—moving from a reactive to a predictive approach—thereby reducing the risk of inadequate or unnecessary compensation.
Co-Authors abriantoro, adji putra Alaydiah, Fifi Alfaris, Dean Anam, Syaeful Aryanti, Agustina Busono Soerowirdjo Da Conceição, Giovani Costa Almeida Diyajeng Luluk Karlina Edy Setyawan Fajri, Julfi Fauziah, Rifana gunawan, setia Hamdala, Marcia Rizky Hamzah Fansuri Herawati, Mila Herlina Muzanah Zain Huda, Rizki Ismail, Ibnu Aly Jefik Zulfikar Hafizd Khana, Rajes Kristyawati, Desy Kusuma, Ridho Alpha Lutfi Ramadhan, Muhammad Maulana, Rifkih Mohamad Rana Mufit, Choirul Muhammad Sobirin Muhammad Zaki Mubarok Muhtadi Irvan, Muhtadi Muliadi, Jemie Nasruddin Nasruddin Nur Rukhama Putri, Zelanti Deviana Rahmadani, Gilang Rizaldi, Mario Rizky, M. Haikal Rudi Irawan Santoso, Kukuh Aris Sembiring, Silsila Jana Firdasa Setiawati, Suci Siswahyudianto Sugianto Sugianto Sunardi Sunardi Sundara, Denny Magni Tawakal, Ikbal Tiorivaldi Tiorivaldi Wahyu Caesarendra Wasman Wasman, Wasman Widya Cahyadi Wijonarko, Panji