Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal NUMERICAL (Jurnal Matematika dan Pendidikan Matematika) Journal Zetroem Ensiklopedia Research and Community Service Review
Hirawati Lubis
Universitas Pamulang
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Social Sciences Other

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
OPTIMALISASI LITERASI KEAMANAN DIGITAL MELALUI EDUKASI PERLINDUNGAN KONSUMEN UNTUK MENCEGAH PENIPUAN ONLINE Hirawati Lubis; Syarkawi Syarkawi; Yulianti Rusdiana; Putri Maharani Fauziah; Syamsul Bahtiar; Aji Santoso; Rinanda Syahputri; Ana Farkhi Mufarohah
Ensiklopedia Research and Community Service Review Vol 5, No 3 (2026): Vol. 5 No. 3 Juni 2026
Publisher : Lembaga Penelitian dan Penerbitan Hasil Penelitian Ensiklopedia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33559/err.v5i3.3936

Abstract

The rapid growth of digital technology has increased public exposure to cyber fraud and digital consumer risks, while digital literacy among community members remains limited. This community service program aimed to enhance public awareness and knowledge of cyber fraud prevention and digital consumer protection through simulation-based education. The program was implemented at RPTRA Serdang Baru using lectures, interactive discussions, practical simulations, educational booklets, digital learning media, and post-test evaluation. The results indicated improved participant understanding of common cyber fraud schemes, personal data protection, and appropriate responses to digital fraud incidents. The program also strengthened participants' confidence in conducting safe digital transactions. These findings demonstrate that interactive educational approaches effectively improve community digital literacy and support safer participation in the digital environment.Keywords: Digital literacy; Cyber fraud prevention; Consumer protection; Simulation-based education
Development of an Air Quality Classification System Using SMOTE-Based Random Forest and XAI Analysis Arip Kristiyanto; Hirawati Lubis
ZETROEM Vol 8 No 1 (2026): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v8i1.7586

Abstract

South Tangerang City is a critical environmental issue that requires an accurate and transparent classification system. This study aims to develop an air quality classification model using a machine learning algorithm integrated with data balancing techniques and model interpretation methods. The methodology used includes pre-processing of Air Pollutant Standard Index (ISPU) data for the 2020–2022 period into three categories: Good, Moderate, and Unhealthy. The dataset used is 1096, Synthetic Minority Over-sampling Technique (SMOTE) is applied to handle class imbalance, and hyperparameter optimization is performed using GridSearchCV. The experimental results show that the Random Forest algorithm outperforms the baseline SVM and KNN models, achieving an accuracy of 0.81 and an F1-Score of 0.75 after SMOTE and tuning. Explainable AI (XAI) analysis using SHAP reveals that sulfur dioxide (SO₂) is the most dominant feature influencing model decisions, and it is spatially correlated with industrial activities and heavy transportation in the South Tangerang area. The final model was then deployed to the Hugging Face Spaces cloud platform via the Gradio interface to provide publicly accessible classification services. This study demonstrates that integrating Random Forests and SHAP produces a classification system that is not only highly performant but also scientifically transparent, supporting air pollution mitigation.
Analisis Konektivitas Graf pada Ayat - Ayat Al-Quran Menggunakan Minimum Spanning Tree dan Degree Centrality Hirawati Lubis; Toriq Roziq
Numerical: Jurnal Matematika dan Pendidikan Matematika Vol. 9 No. 2 (2025)
Publisher : Universitas Ma'arif Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25217/numerical.v9i2.6865

Abstract

This study aims to support the computational identification of Quranic themes through a graph theory–based approach. As a case study, the analysis focuses on verses discussing the virtues of the Quran within the framework of graph algorithm applications. The verses are modeled as a graph using an adjacency matrix to represent semantic connectivity between them. The thematic structuring process is conducted by constructing a Minimum Spanning Tree (MST) using the Kruskal Algorithm to obtain an optimal connectivity structure among vertices, followed by the application of Degree Centrality to identify structurally influential vertices corresponding to Quranic verses. The results demonstrate that the combined application of MST and Degree Centrality effectively visualizes the thematic structure of the verses and highlights verses with dominant structural roles in the context of Quranic virtues. Furthermore, the Louvain Algorithm is applied to detect thematic communities, revealing natural clustering patterns that contribute to a more systematic and interpretable thematic mapping. These findings contribute to the advancement of computational Quranic studies by reinforcing data-driven thematic analysis and structured graph-based representations.
Co-Authors Aji Santoso Ana Farkhi Mufarohah Arip Kristiyanto Putri Maharani Fauziah Rinanda Syahputri Rusdiana, Yulianti Syamsul Bahtiar Syarkawi Toriq Roziq