Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jurnal Menata Global Science: Journal of Information Technology and Computer Science
Frangky
Unknown Affiliation
Humanities Computer Science & IT Social Sciences Veterinary

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
PERANAN MOTIVASI SEBAGAI FAKTOR PENDORONG MINAT KUNJUNGAN WISATAWAN MANCANEGARA Nasution, Mohamad Nur Afriliandi; Hendra Syaiful; Agung Edy; Frangky
JURNAL MENATA Vol. 1 No. 2 (2022): NOPEMBER
Publisher : Puslitabmas Batam Tourism Polytecnic

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The purpose of this study is to explain the interest of tourists to come to Batam because of COVID-19, foreign tourist visits have increased again, but this has not been matched by the interest of tourists to return to religious tourist attractions, especially those in the Batam City Mosque. Through this research, an approach was carried out by looking at two different factors, firstly the push factors and pull factors for the arrival of these tourists, especially from international tourists. In this article the researcher only focuses on the driving factors, while the other factors will be a separate study supported by data after these driving factors are published. Through the driving factors for tourist arrivals, it can be explained that there are several important indicators that accompany it as encouragement, including educational, interpersonal, physiological, driving attractions, amenities, accessibility and additional services affecting foreign tourist tourism. The analysis of this research data uses a quantitative approach with explanatory methods. Sampling was carried out by accidental sampling method with intentional sampling technique. The sample used in this study has a 10% margin of error while the number of samples used is 102 respondents. The results showed that the driving factors of education, interpersonal, and physiological had a positive and significant effect on the interest of foreign tourists to return to religious tourism destinations for mosques in Batam City. What must be strengthened is the improvement of the completeness of the facilities for religious tourism activities.
CyberBERT: A Semantic Search Framework for Security Terminologies Using Transformer Models Sinaga, Rudolf; Frangky
Global Science: Journal of Information Technology and Computer Science Vol. 1 No. 4 (2025): December: Global Science: Journal of Information Technology and Computer Scienc
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/globalscience.v1i4.179

Abstract

: The rapid expansion of cybersecurity standards and threat intelligence frameworks has led to significant semantic fragmentation among security terminologies, hindering effective information retrieval and interoperability across systems. Traditional keyword-based search approaches are inadequate for capturing the contextual meaning of security terms, particularly within formal frameworks such as NIST, MITRE ATT&CK, and CWE. This study addresses this challenge by proposing CyberBERT, a transformer-based semantic search framework designed to align cybersecurity terminologies through deep contextual representation and ontology-driven reasoning. Research Objectives: The primary objective of this research is to develop a semantic retrieval model capable of understanding conceptual relationships between security terms beyond lexical similarity. Methodology: The proposed methodology fine-tunes a BERT-based model on the NIST Glossary corpus using a combination of masked language modeling and triplet loss objectives to generate discriminative semantic embeddings. These embeddings are further aligned with cybersecurity ontologies, including MITRE ATT&CK and CWE, to enhance semantic consistency and explainability. Semantic retrieval is performed using cosine similarity within a 768-dimensional embedding space and evaluated using Mean Reciprocal Rank (MRR) and Precision@K metrics. Results: Experimental results demonstrate that CyberBERT achieves an MRR of 0.832, outperforming domain-adapted baselines such as SecureBERT and CyBERT. The integration of ontology alignment improves semantic accuracy by over 6%, while robustness evaluations confirm resilience against adversarial linguistic perturbations. Visualization using t-SNE reveals coherent semantic clustering aligned with the five core NIST Cybersecurity Framework functions. Conclusions: In conclusion, CyberBERT effectively bridges semantic gaps across cybersecurity terminologies by combining transformer-based contextual learning with ontological reasoning. The framework offers a robust, interpretable, and scalable solution for semantic search, supporting improved interoperability and knowledge discovery in cybersecurity operations and standards harmonization.
Co-Authors Agung Edy Hendra Syaiful Nasution, Mohamad Nur Afriliandi Rudolf Sinaga