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All Journal Health Notions Majalah Patologi Indonesia MMJ (Mahakam Midwifery Journal) Midwifery Care Journal Indonesian Journal of Multidisciplinary Science Formosa Journal of Science and Technology (FJST) International Journal of Scientific Multidisciplinary Research (IJSMR) Mahakam Nursing Journal (MNJ) Jurnal Penelitian Sistem Informasi Medic Nutricia : Jurnal Ilmu Kesehatan Jurnal Media Akademik (JMA) Jurnal Kesehatan Masyarakat Indonesia (JKMI)
Nina Mardiana
Poltekkes Kemenkes Kaltim
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Combinations of Pakcoy (Brassica Rapa L) Juice and Anti Hypertension Drugs for Lowering Blood Pressure in Hypertension Pregnant Women in Handil Baru Health Center Year 2023 Ulfa Siti Mardiyah; Nina Mardiana; Damai Noviasari; Ernani Setyawati
International Journal of Scientific Multidisciplinary Research Vol. 1 No. 8 (2023): September 2023
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ijsmr.v1i8.6241

Abstract

Handil Baru Health Center had cases of hypertension in 2021 as many as 27 cases of pregnant women and 1 case of maternal death and 40 LBW babies was found, one of the causes of preterm parturition was due to mothers experiencing preeclampsia or eclampsia. So far, midwives have tried to reduce cases of hypertension through counseling. To determine the effect of a combination of Pakcoy (Brassica rapa L) juice and anti-hypertensive drugs on reducing blood pressure in hypertensive pregnant women at the Handil Baru Health Center. This type of research is quasi-experimental, with a One Group Pre-Test – Post-Test Design without a Control Group. The population is all hypertensive pregnant women at the Handil Baru Health Center in January-July 2023 totaling 14 people. The sampling technique in this study is total sampling, so that the sample fits the population. data using independent t test. Results: There is an effect of hypertension medication and Pakcoy (Brassica rapa L) juice on blood pressure (p value 0.000 <α: 0.05). Support for hypertension medication can be given Pakcoy juice, because Pakcoy which contains potassium, calcium and magnesium can help lower blood pressure naturally. Consuming 4,700 milligrams of potassium daily can lower blood pressure caused by high sodium intake. There is a combination effect of giving Pakcoy juice (Brassica rapa L) and anti-hypertensive drugs on blood pressure in hypertensive pregnant women at the Handil Baru Health Center about 19%. Handil Baru Health Center is expected to socialize health education about preventing hypertensive pregnant women
KINERJA OTAK DALAM BERFIKIR FILSAFAT Nina Mardiana; Muntaha Nour
Jurnal Media Akademik (JMA) Vol. 3 No. 12 (2025): JURNAL MEDIA AKADEMIK Edisi Desember
Publisher : PT. Media Akademik Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62281/wm2n4205

Abstract

Penelitian ini untuk mengungkap bagaimana cara kerja otak dan berfikir secara filsafat atau mendalam. Otak mreupakan organ dalam tubuh manusia yang berperan sebagai pusat sistem saraf. Organ ini mengkoordininir berbagai kegiatan tubuh termasuk dalam berfikir. Konsep berpikir filosofis mencakup cara berpikir yang bersifat radikal, universal, konseptual, koheren atau konsisten, serta sistematis. Melalui kerangka berpikir filsafat, individu dapat membentuk sikap dan mengambil tindakan secara objektif, efisien, terarah, dan proporsional. Dalam penulisan ini penelinti menggunakan metode library research atau kajian pustaka. Dalam penelitian ini menunjukkan bahwa berfikir merupakan ciri manusia, namun tidak semua berfikir masuk kategor berfikir ecara filsafat. Untuk berfikir secara filsafat ada tahapan yang harus dilaluinya. Seperti logis atau masuk akal dan dapat dibuktikan secara ilmiah, selain itu juga koheren atau keterpaduan serta konsistensi dalam arah berfikir sehingga dapat menghasilkan pemahaman yang maksimal, memiliki korelasi atau keterhubungan antar konsep dan gagasan yang saling terkait sehingga menghasilkan cara pandang yang holistik bukan secara parsial. Dan yang terakhir adalah radikal yaitu berfikir yang menelusuri permasalahan sampai ke akar-akarnya untuk mendapatkan penyelesaian yang tepat.
Analisis Big Data Perpajakan untuk Mendeteksi Potensi Kecurangan Pelaporan Pajak Febryawan Yuda Pratama; Angga Rahmat Pinanggih; Yessica Fara Desvia; Nina Mardiana; Aura Mutiara Zahra
JURNAL PENELITIAN SISTEM INFORMASI (JPSI) Vol. 4 No. 2 (2026): Mei: JURNAL PENELITIAN SISTEM INFORMASI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jpsi.v4i2.3877

Abstract

Tax administrations are undergoing a fundamental transition from conventional audit practices based on manual inspection and limited sampling toward data-driven supervision supported by big data analytics, artificial intelligence, and digital transaction infrastructures. However, developing economies, particularly in Southeast Asia, continue to face structural constraints such as fragmented legacy systems, informal economic activities, uneven digital literacy, corruption risks, weak data interoperability, and evolving privacy regulations. This study aims to develop a contextual framework for detecting potential tax-reporting fraud by integrating big data tax analytics, localized machine learning, explainable artificial intelligence, blockchain-enabled value-added tax data integrity, and socio-organizational governance. The study adopts a mixed-method sequential explanatory approach combined with Design Science Research. The methodological design integrates policy and institutional analysis, machine learning model design, and socio-organizational validation using secondary literature, Southeast Asian case studies, regulatory review, and simulated data architecture. The main contribution of this study is the Contextual Tax Analytics with AI and Blockchain Framework, or C-TAX-AIB Framework, consisting of three interrelated layers: Data Layer, Analytics Layer, and Governance and Human Layer. The Data Layer proposes a hybrid blockchain architecture for e-Faktur and value-added tax reporting integrity; the Analytics Layer introduces localized machine learning and explainable AI to support transparent risk scoring and anomaly detection; and the Governance and Human Layer embeds privacy protection, taxpayer digital literacy, auditor readiness, and trust-building mechanisms. The framework advances prior studies by moving beyond algorithmic fraud detection toward an integrated governance model suitable for developing economies. The study provides theoretical implications for public finance analytics and practical guidance for ASEAN tax administrations in designing accountable, explainable, and context-sensitive digital tax systems.
Integrasi ISO 27001, Zero Trust, dan AI untuk Keamanan Sistem Informasi Keuangan Kampus Nina Mardiana; Yessica Fara Desvia; Angga Rahmat Pinanggih; Febryawan Yuda Pratama; Farah Diva Fadila
JURNAL PENELITIAN SISTEM INFORMASI (JPSI) Vol. 4 No. 2 (2026): Mei: JURNAL PENELITIAN SISTEM INFORMASI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jpsi.v4i2.3879

Abstract

Financial information systems in higher education institutions manage highly sensitive assets, including tuition payments, scholarships, payroll, vendor transactions, budgeting, and institutional financial reporting. Although ISO/IEC 27001:2022 provides a risk-based foundation for establishing an Information Security Management System, its implementation in universities is frequently constrained by fragmented governance, limited resources, complex asset environments, inconsistent managerial commitment, cultural resistance, and limited real-time monitoring capability. This study aims to develop an integrated security evaluation model for campus financial information systems by combining ISO/IEC 27001:2022, Zero Trust Architecture, AI-driven threat detection, security maturity assessment, and human-factor analysis. The study adopts a mixed-method sequential explanatory design integrated with Design Science Research. Quantitative stages include asset identification, risk scoring, ISO 27001 control gap analysis, maturity assessment, Zero Trust readiness assessment, and AI-driven detection readiness assessment. Qualitative stages include document analysis, semi-structured interviews, observation, expert judgment, and thematic analysis to examine organizational, cultural, and behavioral factors influencing security control effectiveness. The proposed outcome is the HEFIS-ISMS Model, an integrated framework consisting of seven layers: ISO 27001 control compliance, risk-based asset protection, security maturity, human and organizational factors, Zero Trust readiness, AI-driven detection readiness, and improvement roadmap. The model is expected to address the static and compliance-oriented limitations of conventional ISO 27001 assessments by introducing adaptive access control, continuous monitoring, anomaly detection readiness, and phased implementation guidance. The study contributes theoretically to cybersecurity governance in higher education and practically to risk-prioritized security improvement for resource-constrained universities.
Pengembangan Sistem Keamanan Data Berbasis Blockchain untuk Perlindungan Informasi Sensitif di Sektor Keuangan Angga Rahmat Pinanggih; Nina Mardiana; Febryawan Yuda Pratama; Yessica Fara Desvia; Arman Maulana
JURNAL PENELITIAN SISTEM INFORMASI (JPSI) Vol. 4 No. 2 (2026): Mei: JURNAL PENELITIAN SISTEM INFORMASI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jpsi.v4i2.3880

Abstract

The protection of sensitive information in the financial sector requires a security architecture capable of preserving confidentiality, integrity, availability, auditability, and regulatory accountability across multiple institutions. Conventional centralized security models remain vulnerable to single points of failure, unauthorized access, data manipulation, and limited transparency in inter-organizational data sharing. Blockchain offers tamper-resistant records, decentralized trust, and verifiable audit trails; however, its direct implementation in financial systems is constrained by scalability limitations, smart contract vulnerabilities, privacy leakage, and conflicts between immutable ledgers and data protection principles. This study aims to develop a blockchain-based data security system for protecting sensitive financial information by integrating permissioned blockchain and Zero-Knowledge Proofs. The proposed method adopts a consortium-oriented permissioned blockchain architecture, represented by Hyperledger Fabric, to ensure controlled participation, certificate-based identity management, endorsement policies, and auditable transaction validation. Smart contracts are designed as policy-enforcement components for consent management, access authorization, data commitment, revocation, and audit logging. Zero-Knowledge Proofs are incorporated to verify customer attributes, eligibility, and access rights without disclosing raw personal or financial data. Sensitive information is stored off-chain in encrypted form, while the blockchain records only cryptographic commitments, hashes, consent states, and audit events. The expected result is a security model that improves data integrity, controlled access, privacy-preserving verification, and compliance-oriented accountability while reducing unnecessary exposure of sensitive data on-chain. The implication of this research is the provision of a technically coherent framework for financial institutions seeking to adopt blockchain securely in regulated environments, especially where data confidentiality, auditability, and privacy compliance must be achieved simultaneously.
Co-Authors Angga Rahmat Pinanggih Arman Maulana Aura Mutiara Zahra Ayyik Busromaqoli Damai Noviasari Dian Ardiyanti Dwi Hendriani Ernani Setyawati Esti Nur Rahayu Evy Nurachma Farah Diva Fadila Febryawan Yuda Pratama Grace Carol Sipasulta Imam Susilo Juliati Lushinta, Lidia Meitty Albertina Muntaha Nour Nouvalia Putri Rahman, Gajali Rita Kirana Sonya Yulia Ulfa Siti Mardiyah Wiryanto Wiryanto Yessica Fara Desvia Yona Polin