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All Journal Jurnal Scientia Jurnal Info Sains : Informatika dan Sains Jurnal Ilmiah Multidisiplin Indonesia Jurnal Komputer Indonesia (JU-KOMI) Journal Health of Indonesian
Sipra Barutu
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Agriculture, Biological Sciences & Forestry Computer Science & IT Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Health Professions Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health

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Optimizing Big Data Analytics in the Era of Digital Transformation Sipra Barutu
Jurnal Komputer Indonesia (Ju-Komi) Vol. 3 No. 02 (2025): Jurnal Komputer Indonesia (JU-KOMI), April 2025
Publisher : SEAN Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/ju-komi.v3i02.757

Abstract

Digital transformation requires organizations to manage large, diverse, and high-velocity data to support effective decision-making. Big Data Analytics (BDA) plays a strategic role in this process through its ability to transform raw data into valuable insights for organizations. This study aims to analyze strategies for optimizing BDA in the digital transformation era by emphasizing the integration of technology, information systems, and organizational capabilities. The research uses a qualitative descriptive approach through a literature review of journals, industry reports, and scientific publications from 2018 to 2025. The findings indicate that the success of BDA optimization is determined by three key synergies: (1) robust and scalable technology, (2) integrated and secure information systems, and (3) adaptive and innovative organizational capabilities. The integration of these three aspects enables organizations to enhance operational effectiveness, strengthen competitiveness, and accelerate the success of digital transformation. Therefore, optimizing BDA is not merely a matter of technological implementation but a comprehensive transformation of how organizations think, make decisions, and create value in the digital era.
Patient Hypertension Modeling Using Decision Tree: Analysis of Age, Symptoms, Fatty Food Intake, Salt Intake, Medication Count, and Blood Pressure Using RapidMiner Manahan Tua Tinambunan; Sipra Barutu
Jurnal Komputer Indonesia (Ju-Komi) Vol. 3 No. 02 (2025): Jurnal Komputer Indonesia (JU-KOMI), April 2025
Publisher : SEAN Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/ju-komi.v3i02.758

Abstract

Hypertension is a chronic disease characterized by persistently elevated blood pressure and remains a major global health problem. Various interacting factors, including age, salt and fatty food intake, medication use, and blood pressure, influence the risk and symptoms of hypertension. This study aims to identify patterns and characteristics of hypertension patients and determine the most influential factors using data mining techniques. A quantitative approach with the Decision Tree algorithm was applied using RapidMiner Studio. The analysis involved data preprocessing, model training and validation, and identification of influential variables. The Decision Tree analysis revealed that medication use is the main determinant of symptom patterns in hypertension. In patients not taking medication, symptoms were mainly influenced by salt intake and blood pressure, where low salt intake was associated with nausea and moderate salt intake with varied symptoms, especially headaches. In patients taking medication, symptom patterns were affected by the combination of salt and fatty food intake. High salt and fat consumption were associated with dizziness, while moderate intake was related to fatigue. Hypertension symptoms are determined not only by blood pressure but also by lifestyle factors and medication use. The Decision Tree model effectively identifies hierarchical relationships among these factors, providing valuable insights for healthcare professionals to design more targeted hypertension management and prevention strategies.
Design Of A Debit And Credit Financial Information System Prototype Method Ami Abdul Jabar; Zulham Sitorus; Sipra Barutu; Nelviony Parhusip
Jurnal Info Sains : Informatika dan Sains Vol. 13 No. 03 (2023): Informatika dan Sains , Edition December 2023
Publisher : SEAN Institute

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

Abstract

The absence of an available financial information system makes it difficult to record financial records and prepare financial reports, making it difficult for company leaders to understand their company's financial condition and make decisions. The legal entity company which was founded in 2018 has not yet utilized technology in carrying out financial records and preparing financial reports, especially debits and credits. This research aims to design a debit and credit Financial Information System using the Prototype Method at PT Bangkit Mulya Prakoso Teknik.The results include relational database design, activity diagrams, use case diagrams, and interface displays. It is hoped that this system design can improve corporate financial governance, make a significant contribution, and become a role model for other companies facing similar challenges.
Co-Authors Ami Abdul Jabar Darmeli Nasution Khairul Khairul, Khairul Manahan Tua Tinambunan Meiarni Situkkir Muhammad Fauzan Pratama Muhammad Iqbal Nelviony Parhusip Risca Sri Mentari Rizka Fadillah Simamora, Siska Sitorus, Zulham Sugeng Pranoto Sulis Sutiono Tuti Andriani