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All Journal Jurnal Pengabdian Kepada Masyarakat Radisi Journal of Computer Science Artificial Intelligence and Communications
Alfiarini
STMIK Bina Nusantara Jaya Lubuklinggau
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Education Engineering Social Sciences

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Sosialisasi Dampak Penggunaan Smartphone Terhadap Siswa Siswi Mts Ittihadiyah Karang Dapo Musi Rawas Utara Deni Apriadi; Alfiarini; Robi Yanto
Jurnal Pengabdian kepada Masyarakat Radisi Vol 1 No 3 (2021): Desember
Publisher : Yayasan Kajian Riset dan Pengembangan RADISI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55266/pkmradisi.v1i3.56

Abstract

The rise of smartphone users or smart phones is increasingly widespread in various circles, not to mention smartphone users from among students of various ages. This is inseparable from the impact of the COVID-19 pandemic, which requires all schools to conduct online learning, from Kindergarten (TK), Elementary School, Junior High School and Middle School and above or equivalent. Starting from the need for smartphones for the benefit of student learning, but ended with the misuse of smartphones that were used to access negative things that had an impact on students. MTS Ittihadiyah Karang Dapo is one of the schools that implement online learning. 82% of students have a smartphone and 20% do not have a smartphone. From the survey results, 91% of students are not supervised by their parents in using smartphones. After taking the pre-test, 85% of students do not know the impact that arises from the use of smartphones. After following the socialization and doing a post test, there was an increase in understanding of the impact of using a smartphone.
Workshop Kewirausahaan Berbasis Teknologi Bagi Siswa Sekolah Menengah Kejuruan Ulu Rawas Deni Apriadi; Alfiarini; Robi Yanto
Jurnal Pengabdian kepada Masyarakat Radisi Vol 2 No 2 (2022): Agustus
Publisher : Yayasan Kajian Riset dan Pengembangan RADISI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55266/pkmradisi.v2i2.144

Abstract

The development of technology brings business opportunities for young people. 89% of Indonesia's population are Smartphone users, which is equivalent to 167 million people. Based on the current potential, technology-based businesses have enormous opportunities. However, until now, the entrepreneurial spirit of college graduates and vocational school graduates in Indonesia is still weak. Based on the field survey on the SMKN Rawas Ulu, Musi Rawas Utara Regency, we found that most of the students are not familiar with the technopreneurship . The absence of a special topic on it and the lack of information might be causing the lack of understanding and interest in entrepreneurship. We also found that student's knowledge and understanding of technoprenuership increased after a technology-based entrepreneurship workshop was conducted. In addition, students' motivation and mindset changed about technology-based business. This can be seen from the post-test results as much as 57% of students wish to become a technopreneur
Analysis of Historical Student Visit Data Using Time Series Algorithm Sri Ramadhany; Sahara Abdy; Alfiarini
Journal of Computer Science, Artificial Intelligence and Communications Vol 1 No 2 (2024): November 2024
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v1i2.16

Abstract

The analysis of historical student visit data plays a critical role in understanding student behavior, optimizing campus resources, and enhancing service delivery in educational institutions. This study presents an analytical approach to examine patterns and trends in student visitations using a time series algorithm. By leveraging historical datasets from campus access logs, we aim to identify periodic behaviors, peak visitation times, and anomalies that may reflect special events or system irregularities. The research employs time series methods such as moving average, exponential smoothing, and ARIMA (AutoRegressive Integrated Moving Average) to forecast future student visit patterns based on previous trends. Data preprocessing, normalization, and visualization techniques are applied to ensure data quality and interpretability. The results demonstrate that student visits tend to follow specific weekly and monthly patterns, with increased activity near academic deadlines or events. The ARIMA model, in particular, shows strong predictive accuracy with minimal error margin. This analysis not only provides insights for administrative planning—such as scheduling staff, managing facilities, or enhancing security—but also serves as a foundation for developing intelligent decision-support systems. In conclusion, applying time series algorithms to historical student visitation data proves effective in predicting future trends, thereby supporting data-driven decision-making processes within educational institutions.
Co-Authors Deni Apriadi Robi Yanto Sahara Abdy Sri Ramadhany