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All Journal Jurnal Ekonomi Bisnis dan Kewirausahaan Jurnal Sistem Informasi dan Ilmu Komputer
Rafi Hilal Zahir
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Computer Science & IT Economics, Econometrics & Finance Other

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STRATEGI PENGEMBANGAN BISNIS HIVE STUDIO AGENCY DENGAN PENDEKATAN BUSINESS MODEL CANVAS Raihan Yuanda; Rafi Hilal Zahir; Ihsan Lana Valenza; Wien Kuntari
Jurnal Ekonomi Bisnis dan Kewirausahaan Vol. 1 No. 6 (2024): Desember : Jurnal Ekonomi Bisnis dan Kewirausahaan (JEBER)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/wq2cme31

Abstract

The creative industry has become one of the most strategic sectors in global economic development, including in Indonesia. Hive Studio Agency, a digital creative startup, offers graphic design, website development, and digital solutions such as domain and hosting. Despite significant growth potential, the company faces challenges due to intense competition and a lack of an adaptive business model. This study analyzes the company's strategy using the Business Model Canvas (BMC) approach to identify key elements for improvement. Findings indicate that Hive Studio Agency can enhance competitiveness and sustainability by refining value propositions, optimizing customer relationships, and strengthening key partnerships. The research contributes to developing actionable strategies for Hive Studio Agency and provides insights for other startups in navigating the dynamic digital creative industry.
Implementasi Sistem Deteksi Kantuk Secara Real-Time Bagi Pengemudi Menggunakan Metode Eye Aspect Ratio Mochammad Fadiil Thoriq; Muhammad Fathi Ramdhana; Desinta Nur Rahma; Najla Amelia Putri; Rafi Hilal Zahir; Gema Parasti Mindara; Endang Purnama Giri
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 4 (2024): November : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i4.4226

Abstract

Traffic accidents are one of the leading causes of death worldwide, where drowsiness while driving is a significant factor that reduces driver alertness. This study develops a real-time driver drowsiness detection system using the Eye Aspect Ratio (EAR) method to avoid this. EAR calculates the ratio of the upper and lower eyelid distances to detect signs of drowsiness based on changes in eye shape. This system utilizes the OpenCV and Dlib libraries to identify faces and measure EAR, with a threshold of 0.25 as a warning trigger. If the EAR value drops below the threshold in several consecutive frames, the system automatically activates an alarm to increase driver alertness. With the advantages of cost efficiency and ease of implementation without additional hardware, this system is suitable for various types of vehicles. The results show that this system is effective in providing early warnings, thus helping to reduce the risk of accidents due to drowsiness.
Co-Authors Desinta Nur Rahma Endang Purnama Giri Gema Parasti Mindara Ihsan Lana Valenza Kuntari, Wien Mochammad Fadiil Thoriq Muhammad Fathi Ramdhana Najla Amelia Putri Raihan Yuanda