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All Journal Jurnal Teknologi Dan Sistem Informasi Bisnis West Science Social and Humanities Studies Scientechno: Journal of Science and Technology
Amalia Hanifa
Politeknik LP3I
Humanities Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Law, Crime, Criminology & Criminal Justice Public Health Social Sciences

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Aplikasi Sistem Pakar Mendiagnosa Penyakit Degenerasi Macula Menggunakan Metode Certainty Factor Berbasis Web Abrar Hadi; Amalia Hanifa
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 5 No 2 (2023): April 2023
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v5i2.795

Abstract

An expert system is a system that seeks to adopt human knowledge into computers that are designed to represent the ability to solve problems like an expert. This system helps all people solve their problems or just look for quality information that can only be obtained with a dedicated expert. This study describes how the Expert System diagnoses Macular Degeneration using the Certainty Factor method. This method obtained the possible disturbances value experienced by the community. This Expert System program is implemented in the PHP programming language where MySQL as the database. As the result, this system is easy to use (user-friendly) and easy to develop and useful for those who want to know about Macular Degeneration.
Analysis of the Use of IoT in Attendance Management and Productivity Monitoring on Employee Performance and Operational Efficiency in Central Java Manufacturing Industry Budi Sulistiyo Nugroho; M. Syahputra; Amalia Hanifa; Ihsan Werleam; Chevy Herli Sumerli A.
West Science Social and Humanities Studies Vol. 2 No. 10 (2024): West Science Social and Humanities Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsshs.v2i10.1359

Abstract

This study investigates the impact of Internet of Things (IoT) usage in attendance management and productivity monitoring on employee performance and operational efficiency in the manufacturing industry of Central Java. Using a quantitative approach, data were collected from 270 respondents and analyzed with Structural Equation Modeling-Partial Least Squares (SEM-PLS 3). The results indicate that IoT-driven systems in both attendance management and productivity monitoring have a significant positive effect on employee performance and operational efficiency. Specifically, IoT-enabled attendance management improves workforce accountability and discipline, while productivity monitoring enhances real-time feedback and workflow optimization. These findings highlight the critical role of IoT technology in transforming workforce and operational management in manufacturing, contributing to improved performance and efficiency. The study provides valuable insights for decision-makers in the manufacturing industry regarding the adoption of IoT technologies to enhance competitiveness and operational outcomes.
Enhancing Algorithmic Thinking through Computational Tools: A Study on High School Computing Education Rahmawati Rahmawati; Omar Khan; M Syahputra; Amalia Hanifa; Ediaman Sitepu
Scientechno: Journal of Science and Technology Vol. 3 No. 3 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientechno.v3i3.1657

Abstract

The importance of algorithmic thinking in modern education has grown significantly, particularly in the context of computing education in high schools. As computational tools become more accessible, their role in enhancing students' problem-solving abilities has gained considerable attention. This study investigates how computational tools can improve algorithmic thinking among high school students and their overall engagement with computing subjects. The primary objective is to assess the impact of integrating computational tools, such as programming environments and visual coding platforms, on students' development of algorithmic skills. The study adopts a mixed-methods approach, combining quantitative data from pre-and post-tests measuring algorithmic thinking skills, and qualitative data through interviews and classroom observations. A total of 150 high school students from various educational backgrounds participated in the study over one semester. The results indicate a significant improvement in students’ algorithmic thinking abilities after exposure to computational tools, particularly in areas such as problem decomposition, abstraction, and logical reasoning. Additionally, students reported higher levels of motivation and interest in computing subjects. In conclusion, the integration of computational tools in high school computing education not only enhances algorithmic thinking but also fosters greater student engagement. These findings highlight the potential of using technology to bridge the gap between theoretical concepts and practical application in computing education. Further research is encouraged to explore long-term effects and the scalability of these methods across diverse educational settings.
Co-Authors Abrar Hadi Budi Sulistiyo Nugroho Chevy Herli Sumerli Ediaman Sitepu Ihsan Werleam M Syahputra M. Syahputra Omar Khan Rahmawati Rahmawati