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All Journal Jurnal Math-UMB.EDU Jurnal Media Akademik (JMA) Journal of Engineering, Electrical and Informatics
Elmi Rahmawati
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Religion Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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PEMAHAMAN KONSEPTUAL TENTANG STANDARD OPERATING PROCEDURE (SOP) DASAR, TUJUAN, MANFAAT, DAN PENERAPAN Subandi; Elmi Rahmawati; Hasanah Inayati
Jurnal Media Akademik (JMA) Vol. 2 No. 6 (2024): JURNAL MEDIA AKADEMIK Edisi Juni
Publisher : PT. Media Akademik Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62281/v2i6.394

Abstract

Penelitian ini bertujuan untuk menganalisis efektivitas penerapan Standard Operating Procedure (SOP) pada suatu peusahaan atau organisasi, berdasarkan tujuh hal pokok dalam SOP yaitu: efisiensi, konsistensi, minimalisasi kesalahan, penyelesaian masalah, perlindungan tenaga kerja, peta kerja, dan batasan pertahanan. Penelitian ini menggunakan analisis kajian pustaka dan menggunakan metode pengumpulan data yang berkaitan dengan tema jurnal, lalu peneliti melakukan reduksi data, yaitu mengelompokkan, memilah, dan menghapus beberapa yang tidak diperlukan atau mendukung. Metode analisis data yang digunakan adalah reduksi data, penyajian data, dan penarikan kesimpulan. Dari tujuh indikator efektivitas SOP, empat indikator menunjukkan bahwa penerapan SOP sudah efektif. Maka dari itu, dapat disimpulkan bahwa Standard Operating Procedure (SOP) adalah acuan utama mengenai tahapan yang berhubungan dengan aktivitas kerja dalam sebuah perusahaan, dan SOP bersifat mengikat dan membatasi bagaimana karyawan bekerja. Dengan menerapkan SOP yang memiliki peta kerja yang rinci, kegiatan yang dilakukan akan berjalan secara sistematis dan mempermudah perusahaan untuk mencapai tujuannya sesuai dengan visi dan misi secara sistematis, tepat waktu, dan dapat dipertanggung jawabkan.
Exploring the Synergy Between Artificial Intelligence and Blockchain in Enhancing Cybersecurity Solutions Deval Gusrion; Fitri Firdalius; Elmi Rahmawati
Journal of Engineering, Electrical and Informatics Vol. 5 No. 3 (2025): October: Journal of Engineering, Electrical and Informatics
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v5i3.5567

Abstract

This research investigates the integration of Artificial Intelligence (AI) and blockchain technologies to develop a more robust and adaptive cybersecurity framework. Amid the growing complexity and frequency of cyber threats, traditional security systems are increasingly insufficient in ensuring data integrity, threat detection, and operational transparency. The study aims to explore how the synergy between AI and blockchain can address these limitations and enhance digital security infrastructures. A qualitative exploratory approach was employed, utilizing a Systematic Literature Review (SLR) of 42 peer-reviewed articles published between 2020 and 2025. The analysis revealed three dominant integration models: AI-based anomaly detection with blockchain-secured logging, smart contracts for automated incident response, and blockchain-based identity verification enhanced by AI behavioral analysis. The proposed framework demonstrated a high detection rate (94.3%), low response latency (0.7 seconds), and improved auditability compared to state-of-the-art approaches. These findings suggest that combining AI's predictive capabilities with blockchain’s immutable and decentralized architecture offers a more comprehensive cybersecurity solution. However, challenges such as computational overhead, energy consumption, and interoperability issues remain. The study concludes that the integrated approach not only enhances resilience and transparency but also provides a scalable foundation for future cybersecurity systems, especially in critical sectors such as healthcare, finance, and government services.
IMPROVING INFORMATICS STUDENTS’ MATRIX ALGEBRA CONCEPTUAL UNDERSTANDING THROUGH A PYTHON-BASED LEARNING TRAJECTORY : Padang, Indonesia Syelfia Dewimarni; Elmi Rahmawati; Lili Rismaini
Jurnal Math-UMB.EDU Vol. 13 No. 2 (2026): MARCH
Publisher : Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/math-umb.edu.v13i2.9463

Abstract

In matrix algebra courses, conceptual understanding remains low. This is due to the lack of integration and relevance of mathematics learning to their competency, namely informatics engineering. Learning trajectory instruction, characterized by sequential learning and Python computing applications relevant to students, provides a solution to improve students' matrix algebra conceptual understanding. The purpose of this study was to examine students' understanding of mathematical concepts in algebra by implementing a Python-based learning trajectory model. This study was a quasi-experimental study with posttest-only control group design. The sample was taken using a random sampling technique. A sample size of 69 students was selected, consisting of 33 students from the experimental class and 36 students from the control class. The results of this study present the difference in the average test scores for understanding matrix algebra concepts between the experimental and control classes. The t-test showed that t-test (3.469) > t-table (1.997), with α = 0.05 (df = 67), indicating that H1 was accepted, stating that the Python-based Learning trajectory model is effective as an alternative learning strategy to strengthen students' matrix algebra conceptual understanding. Keywords: Learning Trajectory; Python; Conceptual Understanding; Matrix Algebra
Co-Authors Deval Gusrion Fitri Firdalius Hasanah Inayati Ida Ayu Putu Sri Widnyani Rismaini, Lili Syelfia Dewimarni