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All Journal BERKALA SAINSTEK Paradigma INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA Jiko (Jurnal Informatika dan komputer) Jurnal Ilmu-Ilmu Kesehatan Jurnal ABDINUS : Jurnal Pengabdian Nusantara Community Empowerment EXPLORER Jurnal Ilmu-Ilmu Kesehatan Sekolah Tinggi Ilmu Kesehatan Garuda Putih Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Journal of Hospital Administration and Management (JHAM) Jurnal Manajemen Sistem Informasi Nuansa Informatika ABDIMAS CSRID ARUMAS Systematic Literature Review Journal Prosiding Seminar Nasional Ilmu Teknik JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Journal of New Trends in Sciences KREATIF: Jurnal Pengabdian Masyarakat Nusantara Global Science: Journal of Information Technology and Computer Science Cyber Security and Network Management
Rudolf Sinaga
Universitas Dinamika Bangsa
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Veterinary Other

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Analisis dan Penerapan Algoritma Naïve Bayes Untuk Klasifikasi Penyakit Diabetes Melitus M Daffa Adrian; Pareza Alam Jusia; Rudolf Sinaga; Azzahra Raihana Adriansyah; Mutammimah Mutammimah
Prosiding Seminar Nasional Ilmu Teknik Vol. 2 No. 2 (2025): Desember: Prosiding Seminar Nasional Ilmu Teknik
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/prosemnasproit.v2i2.114

Abstract

Diabetes Mellitus is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion, insulin action or both. Hyperglycemia is a medical condition in the form of an increase in glucose levels beyond normal limits which is a characteristic of several diseases, especially Diabetes Mellitus, in addition to various other conditions. Diabetes Mellitus is currently a global health threat. Classification is one of the techniques of data mining that can be used to help predict the results of the classification of types of diabetes using the naïve Bayes algorithm. Testing was carried out using 5 evaluation models including rapid miner with 3 options, namely use training set, 5 Fold Cross-Validation, 10 Fold Cross-Validation, and 2 other evaluation models, namely Microsoft Excel and Python. Testing data regarding Diabetes Mellitus has high accuracy in the excel evaluation model, which is 89.00% compared to other evaluation models. Meanwhile, the lowest accuracy is the Python evaluation model which obtains an accuracy of 86.36%. The Naïve Bayes algorithm can be said to be one of the most effective algorithms, both in terms of calculations and the final results, where the test can be used as a basis for diabetes mellitus considering the accuracy results are above 85%.
Analisis Pengaruh Kualitas Layanan terhadap Kepuasan Pengguna pada Website Dinas Kependudukan dan Pencatatan Sipil Kota Jambi Menggunakan Metode Webqual 4.0 Devi Saputra; Pareza Alam Jusia; Rudolf Sinaga; Syaqilla Dinata; Euis Oktapiani
Prosiding Seminar Nasional Ilmu Teknik Vol. 2 No. 2 (2025): Desember: Prosiding Seminar Nasional Ilmu Teknik
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/prosemnasproit.v2i2.115

Abstract

Website Accessible Jambi City Population and Civil Registry Service https://disdukcapil.jambikota.go.id. The problem with the Jambi City Population and Civil Registry Service website is that not all information is available, especially on the Profile menu there is a Media Information sub-menu, Data menu and Facilities and Infrastructure menu. On the Information Media sub-menu, there is a Demographic Data sub-menu, where the contents of the sub-menu are still empty, preventing users from obtaining information. On the Public Facilities and Infrastructure menu from the sub menu, the data cannot be accessed so that it makes users unable to get information. And in the appearance of the Jambi City Population and Civil Registry Service, when accessed via Google Chrome, the appearance is disorganized, so users have to open the website using a laptop/PC to get a website display that is orderly and easy for users to understand. Quality measurement is carried out based on user satisfaction point of view in order to improve the quality of service to the community and make optimal use of the website. In analyzing user satisfactionwebsite DUKCAPIL Jambi using the webqual 4.0 method, there are 4 variables, namely usability (usability), information quality (information quality), interaction quality (interaction quality), and user satisfaction (user satisfaction) and using the software (software) SPSS. Of the 3 hypotheses proposed, all hypotheses were accepted in this study.
System-Level Performance Evaluation of Dilithium2, Falcon-512, and SPHINCS+ for Post-Quantum Secure E-Government Document Signing Rudolf Sinaga; Samsinar Samsinar; Mohd Shahizan Othman
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 10 No 1 (2026)
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v10i1.26424

Abstract

Background: The rapid advancement of quantum computing threatens the cryptographic foundations of e-Government infrastructure, particularly classical public-key algorithms susceptible to Shor's algorithm. Post-Quantum Cryptography (PQC) offers a viable pathway for securing digital signature systems against emerging quantum adversaries. Objective: This study conducts a system-level comparative evaluation of three NIST-standardized PQC digital signature schemes CRYSTALS-Dilithium2, Falcon-512, and SPHINCS+-128s to assess their suitability for secure e-Government document signing workflows. Methods: A simulation-based system-level evaluation is employed, wherein timing values are estimated from official NIST PQC parameter specifications and open-source benchmarks (PQClean, OQS), rather than measured from native cryptographic library executions. Experiments were conducted over 100 iterations, reporting mean ± standard deviation for key generation, signing, and verification times, alongside signature sizes and a RESTful API prototype demonstration. Results: Falcon-512 demonstrates the lowest estimated signing latency approximately five to six times faster than Dilithium2 and over fifty times faster than SPHINCS+-128s with the smallest signature size (666 bytes versus 2,420 and 7,856 bytes respectively). Dilithium2 provides a balanced trade-off between computational efficiency and signature robustness, while SPHINCS+-128s, despite its computational overhead, offers the strongest long-term security guarantees through its stateless hash-based construction. The RESTful API prototype confirms successful multi-scheme integration feasibility. Conclusion: This study recommends Falcon-512 for real-time mobile services, Dilithium2 for centralized server-side authentication, and SPHINCS+-128s for long-term archival security, providing evidence-based guidance for PQC adoption in national e-Government systems aligned with SPBE frameworks and NIST standards.
CyberBERT: A Semantic Search Framework for Security Terminologies Using Transformer Models Rudolf Sinaga; 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.
Analisis Segmentasi Pasien Berdasarkan Persepsi Kualitas Pelayanan dengan Algoritma Clustering Frangky Frangky; Rudolf Sinaga; M. Raihansyah
Explorer Vol 5 No 1 (2025): January 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/explorer.v5i1.1818

Abstract

Patient segmentation based on perceptions of service quality is a crucial step in improving patient experiences, optimizing resources, and enhancing healthcare service quality. However, understanding patients' needs and priorities in depth poses a challenge, particularly for hospitals serving populations with diverse demographic backgrounds. This study aims to cluster patients in a private hospital in Jambi City based on their perceptions of service quality using the K-Means algorithm. Data were collected from a 2022-2023 survey, covering patient demographics and perceptions of service quality. The data were processed through preprocessing steps, including missing value imputation, normalization, and encoding. The optimal number of clusters was determined using the Elbow and Silhouette Score methods. The results revealed three main clusters with distinct characteristics. The first cluster (34.29%) includes patients prioritizing service speed and procedural ease. The second cluster (46.12%) consists of patients who emphasize staff competence and cost fairness as their main priorities. The third cluster (19.59%) comprises patients with higher educational backgrounds who are more critical of facility quality and complaint handling. Evaluation using the Davies-Bouldin index demonstrated good cluster separation (score -0.645). This study concludes that patient segmentation based on perceptions of service quality can serve as a foundation for strategic decision-making to improve hospital service quality. Recommendations for future research include applying other algorithms such as DBSCAN, integrating sentiment analysis, and employing a hybrid approach to predict patient needs. These approaches are expected to provide a deeper understanding and more effective personalization of patient care.
Co-Authors Adha Taufik, Anvika Afriany, Renny Aji Nurrohman Ary Ardiansyah Azzahra Raihana Adriansyah Clarisa Putri Valentina Devi Saputra Dewi Andriyanti Eka Julianti Errissya Rasywir Euis Oktapiani Firyal Najla 'Afifah Frangk Frangky Frangky Frangky Frangky Frangky Frangky Frangky Frangky Taan Frangky, Frangky Ika Widyastuti Irwandi Irwandi Lely Priska D Tampubolon M Daffa Adrian M. Raihansyah M. Yogi Riyantama Isjoni Melda Septriani Mohd Shahizan Othman Mutammimah Mutammimah N, Renny Afriany Nurhadi Nurhadi Pardede, Nadia Pareza Alam Jusia Renny Afriany Renny Afriany Samsinar Samsinar Samsinar Samsinar Samsinar Samsinar Samsinar Samsinar Samsinar Samsinar Samsinar Samsinar Samsinar Samsinar Samsinar Shinta Renova Putri Soomal Fatima Syaqilla Dinata Uswatun Kasanah Yovi Pratama Zhenya, Zhenya Zeldha Elyzvania