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Design of Company Management Dashboard With Machine Learning Analysis For Optimization of Arcade Game Centre Operations Dedy Andriyanto; Antonius Darma Setiawan; Sinka Wilyanti
Al-Kharaj: Journal of Islamic Economic and Business Vol. 7 No. 3 (2025): : All articles in this issue include authors from 3 countries of origin (Indone
Publisher : LP2M IAIN Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24256/kharaj.v7i3.7942

Abstract

The growth of the digital entertainment industry, especially arcade game centers, demands an effective and data-driven management system to improve operational efficiency and customer experience. This study aims to design a company management dashboard integrated with machine learning analysis to optimize arcade game center operations. This dashboard is designed to provide real-time data visualization and support strategic decision-making through predictive analysis of machine performance, usage trends, and customer behavior. The research methods used include collecting primary and secondary data from the arcade game center transaction system, designing the system using a waterfall approach, and implementing machine learning algorithms such as K-Means for customer segmentation and Random Forest for machine failure prediction. The results of the study show that the developed dashboard is able to provide relevant and accurate information efficiently, and supports data-driven decision-making. With this system, the company can minimize machine downtime, increase customer satisfaction, and design more targeted promotional strategies. This study proves that the integration between management dashboards and machine learning technology can be an innovative solution for operational optimization in the arcade game center industry. Further implementation is recommended for the development of financial analysis features and integration with customer loyalty systems.
Analysis of Information Technology Maturity Level For Academic Services Using Cobit 2019 Framework: Case Study of Global University Jakarta Ary Wibowo; Antonius Darma Setiawan; Sinka Wilyanti
Al-Kharaj: Journal of Islamic Economic and Business Vol. 7 No. 3 (2025): : All articles in this issue include authors from 3 countries of origin (Indone
Publisher : LP2M IAIN Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24256/kharaj.v7i3.7999

Abstract

The use of information technology (IT) in managing academic services at universities is a strategic step to improve service efficiency and quality. Universitas Global Jakarta has implemented an academic information system, but still encounters obstacles in terms of information accuracy and control, indicating the need for an evaluation of the implemented IT governance. This study aims to assess the maturity level of IT governance in Universitas Global Jakarta's academic services using the COBIT 2019 framework, specifically the Delivery, Service, and Support (DSS) domain. The research method used is a qualitative descriptive approach with data collection techniques in the form of observation, interviews, and documentation studies. The results show that several processes in the DSS domain have not reached an optimal level of maturity, especially in the aspects of operational supervision and control. This finding indicates the need for improvements in the implementation of IT governance to be more aligned with the university's strategic objectives and able to support academic services sustainably.
Alat Deteksi Kebakaran Dan Kebocoran Gas Dengan Notifikasi Telegram Menggunakan Mikrokotroler ESP-32 Rahmat Hidayat; Sinka Wilyanti; Legenda Prameswo; Arisa Olivia Putri; Hamzah Hamzah; Brainvendra Widi Dionova
JITEL (Jurnal Ilmiah Telekomunikasi, Elektronika, dan Listrik Tenaga) Vol. 6 No. 1: March 2026
Publisher : Jurusan Teknik Elektro, Politeknik Negeri Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Keamanan dapur rumah tangga penting mengingat tingginya risiko kebakaran dan kebocoran gas LPG. Penelitian ini mengembangkan sistem deteksi dan penanggulangan dini berbasis mikrokontroler ESP32 dengan dukungan Internet of Things (IoT) dan konektivitas Wi-Fi. Sistem mengintegrasikan sensor MQ-2 untuk mendeteksi asap/gas mudah terbakar, KY-026 untuk mendeteksi nyala api, dan DHT11 untuk memantau kenaikan suhu. Untuk meminimalkan false alarm, sistem aktif hanya saat terdeteksi nyala api disertai suhu >40°C atau konsentrasi asap/gas >400 ppm. Saat kondisi berbahaya, data sensor diproses oleh ESP32 yang kemudian mengirim notifikasi real-time melalui Telegram Bot, mengaktifkan buzzer sebagai peringatan, serta mengendalikan pompa air melalui relay sebagai upaya penanggulangan. Pengujian pada berbagai kondisi dapur menunjukkan MQ-2 efektif mendeteksi gas di atas 300 ppm, KY-026 optimal pada jarak 20 cm dan sudut 0–45°, serta DHT11 akurat mencatat kenaikan suhu pada simulasi kebakaran. Kinerja jaringan memenuhi standar QoS ITU-T G.1010 dengan delay 191,83 ms, jitter 195,65 ms, throughput 4,24 Kbps, dan tanpa packet loss. Sistem mencapai tingkat notifikasi 100% dengan respons cepat, akurat, dan andal, sehingga efektif meningkatkan keamanan dapur melalui deteksi dini serta penanggulangan otomatis terhadap kebakaran dan kebocoran gas.