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All Journal El-Furqania : Jurnal Ushuluddin dan Ilmu-Ilmu Keislaman Router : Jurnal Teknik Informatika dan Terapan Repeater: Publikasi Teknik Informatika dan Jaringan Router : Jurnal Teknik Informatika dan Terapan
Muhammad Romadhon
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Religion Computer Science & IT Other

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Pengharaman “Khamar” Dalam Al-Qur’an (Aplikasi Semiotika Charles Sanders Peirce) Muhammad Romadhon
El-Furqania : Jurnal Ushuluddin dan Ilmu-Ilmu Keislaman Vol. 10 No. 01 (2024): Februari
Publisher : STAI Al-Mujtama Pamekasan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54625/elfurqania.v10i01.7429

Abstract

In this paper, Charles Sanders Peirce's semiotic hypothesis is utilized, in particular triad (representamen, object and interpretant) to uncover the stages in regards to the denial of Khamar in the Qur'an as a sign. The strategy for this examination is subjective substance investigation, to be specific exploration that means to distinguish the message of a media as an object of examination. From this examination, it very well may be inferred that the refrains of the Qur'an which talk about the law with respect to khamr are surely completed bit by bit until they are prohibited on the grounds that considering the mischief and advantages of intoxicants are fortified by the translation and Asbabunnuzul of the section. Research like this absolutely should be created to grow the investigation of the Qur'an and the legitimacy of the Qur'an in different spaces and times. Keyword: Al-Qur’an, Khamar, Semiotika.
Integrasi Sistem Presensi Pegawai Berbasis Web dengan Geolokasi dan Swafoto di PT Gresik Migas Muhammad Romadhon; Deni Sutaji
Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 3 No. 2 (2025): April: Repeater : Publikasi Teknik Informatika dan Jaringan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/repeater.v3i2.402

Abstract

The manual attendance system using paper at work locations other than offices at PT Gresik Migas creates challenges in the effectiveness and efficiency of employee attendance records. This study implements a web-based attendance system that integrates geolocation and selfie features to improve the accuracy and efficiency of attendance recording. The system was developed using native PHP for backend, jQuery for frontend, MySQL as database, and Leaflet JS for geolocation implementation. Implementation results show the system was successfully implemented in 5 different locations with a 50-meter validation radius and used by 40 employees. This system enables real-time attendance monitoring through an admin dashboard and produces more efficient attendance records compared to the previous manual system.
Implementasi YOLOv8 dan Local Binary Pattern Histogram (LBPH) untuk Simulasi Presensi Muhammad Romadhon; Deni Sutaji
Router : Jurnal Teknik Informatika dan Terapan Vol. 3 No. 3 (2025): Router : Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v3i3.622

Abstract

Attendance is an essential activity in both educational institutions and companies, serving as an indicator of discipline, presence, and individual responsibility. Conventional attendance systems that still rely on manual journals often face several problems, such as vulnerability to manipulation, data loss, and physical damage. Meanwhile, modern methods such as fingerprint, QR code, RFID, and GPS are not entirely ideal since each has its own limitations in terms of cost, accuracy, user convenience, and potential misuse. For instance, fingerprint systems raise hygiene concerns due to shared use, while QR code and GPS methods are prone to fraud and location spoofing. To address these challenges, this study proposes a face-based attendance simulation system by integrating the YOLOv8 algorithm for face detection and Local Binary Pattern Histogram (LBPH) for face recognition. YOLOv8 was chosen for its ability to detect faces in real time with high speed and accuracy, while LBPH is employed for face recognition due to its robustness in handling variations in facial features and its relatively low computational requirements. This makes the system efficient even when implemented on medium-specification devices. The system was tested on 25 participants with a total of 250 attendance attempts. Based on the confusion matrix analysis, the system achieved outstanding performance with 98.4% accuracy, 98.4% precision, 100% recall, and a 99.2% F1-score. Furthermore, the system automatically recorded attendance dates and times with an average latency of 69.185 ms, proving its capability to operate quickly and reliably in real-world scenarios. Nevertheless, several limitations were observed, such as decreased accuracy when the face moved too quickly during image capture, as well as potential performance degradation under extreme lighting conditions. Despite these challenges, the proposed system demonstrates excellent performance and offers a promising solution for efficient, hygienic, and fraud-resistant attendance management applicable to both educational and professional environments.
Implementasi YOLOv8 dan Local Binary Pattern Histogram (LBPH) untuk Simulasi Presensi Muhammad Romadhon; Deni Sutaji
Router : Jurnal Teknik Informatika dan Terapan Vol. 3 No. 3 (2025): Router : Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v3i3.622

Abstract

Attendance is an essential activity in both educational institutions and companies, serving as an indicator of discipline, presence, and individual responsibility. Conventional attendance systems that still rely on manual journals often face several problems, such as vulnerability to manipulation, data loss, and physical damage. Meanwhile, modern methods such as fingerprint, QR code, RFID, and GPS are not entirely ideal since each has its own limitations in terms of cost, accuracy, user convenience, and potential misuse. For instance, fingerprint systems raise hygiene concerns due to shared use, while QR code and GPS methods are prone to fraud and location spoofing. To address these challenges, this study proposes a face-based attendance simulation system by integrating the YOLOv8 algorithm for face detection and Local Binary Pattern Histogram (LBPH) for face recognition. YOLOv8 was chosen for its ability to detect faces in real time with high speed and accuracy, while LBPH is employed for face recognition due to its robustness in handling variations in facial features and its relatively low computational requirements. This makes the system efficient even when implemented on medium-specification devices. The system was tested on 25 participants with a total of 250 attendance attempts. Based on the confusion matrix analysis, the system achieved outstanding performance with 98.4% accuracy, 98.4% precision, 100% recall, and a 99.2% F1-score. Furthermore, the system automatically recorded attendance dates and times with an average latency of 69.185 ms, proving its capability to operate quickly and reliably in real-world scenarios. Nevertheless, several limitations were observed, such as decreased accuracy when the face moved too quickly during image capture, as well as potential performance degradation under extreme lighting conditions. Despite these challenges, the proposed system demonstrates excellent performance and offers a promising solution for efficient, hygienic, and fraud-resistant attendance management applicable to both educational and professional environments.
Co-Authors Deni Sutaji Rini Herdiani Sunirah Sunirah