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All Journal The Scientific Journal of Information Systems
Nugraha, Fahmi Rizky
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Biochemistry, Genetics & Molecular Biology Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Environmental Science

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Automated Financial Report Summarization Using Python: A PDF-Based Approach Nugraha, Fahmi Rizky
Scientific Journal of Information System Vol. 3 No. 2 (2025): Scientific Journal of Information System
Publisher : Universitas Utpadaka Swastika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70429/sjis.v3i2.240

Abstract

Financial reports are often lengthy, complex, and filled with domain-specific jargon, making itdifficult for analysts and stakeholders to extract key insights efficiently. This study proposes anautomated summarization system using Natural Language Processing (NLP) techniques to generateconcise and coherent summaries of financial reports. The system employs a two-stage summarizationarchitecture combining extractive and abstractive methods based on Transformer models such asBART, PEGASUS, and T5. Evaluation on simulated financial document datasets demonstrates thatthe hybrid two-stage model achieves the highest ROUGE scores and information retention ratescompared to single-model baselines. The results indicate that NLP-driven summarization cansignificantly reduce analysts’ workload and improve financial decision-making speed
Comparative Analysis of Cloud Service Models for Professional Use: IaaS, PaaS, and SaaS Alfaujianto, Moh; Nugraha, Fahmi Rizky; Muttaqi, Fajar; Zogara, Lukas Umbu
Scientific Journal of Information System Vol. 4 No. 1 (2026): Scientific Journal of Information System
Publisher : Universitas Utpadaka Swastika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70429/sjis.v4i1.310

Abstract

This study aims to conduct a structured comparative analysis of cloud computing service models-Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS)-for professional use across multiple sectors. A quantitative comparative approach was employed using data collected from scientific literature and semi-structured interviews involving 15 professionals from education, business, and technology sectors. Each model was evaluated based on five parameters: flexibility, scalability, cost efficiency, user control, and sector relevance using a Likert scale (1–5). The results indicate that IaaS achieved the highest score in flexibility (5.0) and user control (5.0), PaaS showed balanced performance across development-related parameters (average score 4.2), while SaaS demonstrated the highest cost efficiency (5.0). These findings highlight that no single model is universally superior, and selection should be aligned with organizational priorities. This study contributes by providing a parameter-based quantitative comparison framework to support decision-making in cloud service adoption.
Co-Authors Alfaujianto, Moh Lukas Umbu Zogara Muttaqi, Fajar