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All Journal Prosiding SNATIF JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Community Development Journal: Jurnal Pengabdian Masyarakat Sewagati INTER TECH
Arif Arizal, Arif
Teknik Informatika Universitas Bhayangkara Surabaya
Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Languange, Linguistic, Communication & Media Public Health Social Sciences Other

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Journal : INTER TECH

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Tinjauan Integrasi Teknologi Deep Learning Untuk Revolusi Industri Dalam Sistem Siber-Fisik Zainal, Rifki Fahrial; Alim, Syariful; Arizal, Arif; Purnama, Rangsang
INTER TECH Vol 3 No 1 (2025): INTER TECH
Publisher : Fakultas Teknik Universitas Bhayangkara Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/i.v3i1.1266

Abstract

An important development in industrial automation is the combination of deep learning with cyber-physical systems (CPS), which allows systems to make data-driven, intelligent decisions with little assistance from humans. With an emphasis on its capacity to handle massive amounts of data for tasks including object detection, semantic segmentation, predictive maintenance, and autonomous control, this research investigates the revolutionary effects of deep learning on CPS. It looks at how technology has developed from early frameworks that relied on visual cues to complex systems that use cutting-edge neural networks that can function in dynamic, unstructured contexts. The study also emphasizes how important it is to integrate ethical frameworks, organizational preparedness, and human-centered design in order to successfully implement CPS. This study analyzes important trends, obstacles, and best practices that influence the application of deep learning in CPS through an extensive examination of recent literature. The significance of CPS in facilitating the Industry 4.0 and Industry 5.0 paradigms—which prioritize sustainability, human-machine collaboration, and real-time adaptation in industrial processes—is given particular attention.
Sistem Pakar Hukum Darah Wanita Pada Masa Haid Dengan Menggunakan Metode Naïve Bayes Maqdisi, Ali; Hamidah, Mas Nurul; Arizal, Arif
INTER TECH Vol 3 No 2 (2025): INTER TECH
Publisher : Fakultas Teknik Universitas Bhayangkara Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/i.v3i2.1612

Abstract

Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem pakar yang dapat memberikan keputusan terkait hukum darah wanita selama masa haid berdasarkan metode Naïve Bayes. Metode Naïve Bayes dipilih karena kemampuannya dalam melakukan klasifikasi berbasis probabilitas, sehingga dapat memberikan hasil yang akurat berdasarkan data masukan pengguna. Sistem ini dirancang untuk membantu pengguna, khususnya wanita Muslim, dalam memahami hukum darah haid, istihadhah, dan nifas dengan lebih mudah dan cepat. Hasil pengujian menunjukkan bahwa sistem pakar ini memiliki tingkat akurasi yang tinggi dalam memberikan rekomendasi hukum yang relevan, sehingga dapat dijadikan alat bantu edukasi dan konsultasi.
Co-Authors Adityo, R.Dimas Alim, Syariful Alim, Syariful Alim, Syariful Bagus Ananda Kurniawan, Bagus Ananda Hamidah, Mas Nurul Maqdisi, Ali Muslichah Erma Widiana Nurina, Putri Oktavia Rizky Suis Rangsang Purnama Rani Purbaningtyas, Rani Rifki Fahrial Zainal Sudrajat, Vicinthia Veren Suyanto Suyanto Suyanto Wardoyo, Tri Wardoyo, Tri