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All Journal International Transactions on Artificial Intelligence (ITALIC) Journal of Computer Science and Technology Application
Mustofa Kamal
University of Raharja
Computer Science & IT Control & Systems Engineering Library & Information Science Other

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Application of RESTful Method with JWT Security and Haversine Algorithm on Web Service-Based Teacher Attendance System Suryari Purnama; Mustofa Kamal; Ahmad Bayu Yadila
International Transactions on Artificial Intelligence Vol. 2 No. 1 (2023): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v2i1.400

Abstract

A teacher attendance system utilizing fingerprints has been implemented at Ponpes Daarul Muttaqien II. However, fingerprint recognition errors frequently occur if the scanner is unclean. Teachers fill out an attendance update form for various reasons, including forgotten attendance, damaged fingerprints, and unnoticed absences. The Human Resources Bureau receives updates from around 28 instructors within one week. Statistics reveal that 30% of instructors update due to finger injuries preventing recognition, and 70% due to forgetting. Amid the COVID-19 pandemic, organizations advise remote work. Similarly, only specific sections, like technical and security units, require attendance at Ponpes Daarul Muttaqien II. Due to the potential risks of linking fingerprints to virus transmission, this study proposes a web-based attendance system. It employs the RESTful API approach, JWT Security, and the Haversine Formula Algorithm. The system mandates employees to be within 100 meters of a designated coordinate point for attendance. The system tracks attendance status, arrival and delay times, and absence status. Future enhancements might involve facial recognition for more robust validation. In conclusion, this innovative approach addresses attendance challenges, offering adaptability, security, and potential fraud prevention.
Revolutionizing Logistics Business Models through Big Data and Blockchain: A Business Model Canvas Analysis Indah Ainun Mutiara; Yusuf Febriansyah; Mustofa Kamal; Ramzi Zainum Ikhsan; Tane Williams
CORISINTA Vol 1 No 2 (2024): August
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/corisinta.v1i2.28

Abstract

The world is moving quickly towards automation and digitalization in the modern era. This change is becoming crucial to corporate competitive strategies, especially in the logistics industry. The use of data in organizational decision-making is an essential aspect of this digital and automated environment. Several business sectors are implementing Big Data and Blockchain technologies to improve organizational capabilities by developing effective business processes. This inexorably affects the development of new business models that fit the changing global business landscape. The Business Model Canvas (BMC) is an effective tool for analyzing internal and external business model changes. A SWOT analysis of these business model transformations is necessary to explain the new business process changes further. First, the analysis shows that for businesses to function at their best, current technological advancements—particularly in Big Data and Blockchain—will continue to disrupt them. Second, there have been significant internal and external changes to intra- and inter-organizational relationships due to the implementation of Big Data and Blockchain. Thirdly, the benefits of Blockchain and Big Data technologies for business, especially logistics, can be further explained by SWOT analysis.
Co-Authors Ahmad Bayu Yadila Indah Ainun Mutiara Ramzi Zainum Ikhsan Suryari Purnama Tane Williams Yusuf Febriansyah