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Jurnal Pharmactive
Published by Institut Teknologi dan Kesehatan Bintang Persada
ISSN : -     EISSN : 28293444     DOI : -
Core Subject : Education, Social,
Environmental Science Other
Initially LPPM Institut Teknologi dan Kesehatan Bintang Persada published a journal that aimed to accommodate campus internal lecturers at Institut Teknologi dan Kesehatan Bintang Persada in publishing scientific papers. Because the lecturers who want to carry out publications come from various fields of science, such as Clinical andCommunity Pharmacy, Pharmaceutical Analysis, Herbal Medicine, Pharmaceutical Techology, Management of Pharmacy, etc. the published journal seems not to have a clear focus area (accepting all types of articles). In addition, efforts to improve journal management by LPPM, as well as accreditation demands for scientific periodicals / journals determined by related parties. FOCUS AND SCOPE Clinical and Community Pharmacy Pharmaceutical Analysis Herbal Medicine Pharmaceutical Technology Management of Pharmacy
Arjuna Subject : Pharmacology, Toxicology and Pharmaceutics - Pharmacology, Toxicology and Pharmaceutics (Lain-Lain)
Articles 67 Documents
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ANALISIS TINGKAT PENGETAHUAN DAN PERILAKU DALAM MENGKONSUMSI VITAMIN D3 DAN E PADA KONSUMEN DI APOTEK X BADUNG Ika Indah Indraswari, Putu; Ayu Apriliani; A.A Bagus Suryantara
Journal Pharmactive Vol. 4 No. 2 (2025): Jurnal Pharmactive Oktober
Publisher : Institut Teknologi dan Kesehatan Bintang Persada

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Abstract

Vitamins are organic substances that cannot be synthesized by the body and are classified into fat-soluble and water-soluble types. Vitamins D3 (cholecalciferol) and E (tocopherol) are among the most frequently consumed by the public to meet daily nutritional needs and support immune function. This study aimed to analyze the level of knowledge and behavior of respondents regarding vitamin consumption and to examine the influence of age and last education level on these two variables. This research employed a prospective method with a quantitative approach. A total of 86 respondents were selected using purposive sampling. Data were collected using structured questionnaires and analyzed using SPSS software with the Chi-Square test. The results showed that there was no significant relationship between knowledge level and either age or education level (p > 0.05). However, there was a significant relationship between behavior and age (p < 0.05), while no relationship was found between behavior and education level (p > 0.05). These findings indicate that age plays an important role in shaping vitamin consumption behavior, although it does not directly influence knowledge. Meanwhile, the last level of education does not significantly affect either knowledge or behavior. An educational approach that takes age into account as a dominant factor is needed to improve behavior regarding vitamin consumption.
PERBANDINGAN UJI AKTIVITAS ANTIOKSIDAN INFUSA DAN DEKOKTA BUNGA TELANG (Clitoria ternatea L.) DENGAN METODE DPPH Ni Luh Gde Mona Monika; I Made Wahyu Yogatama; Nyoman Rudi Kusuma; Ni Putu Ria Artini
Journal Pharmactive Vol. 4 No. 2 (2025): Jurnal Pharmactive Oktober
Publisher : Institut Teknologi dan Kesehatan Bintang Persada

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Abstract

Free radicals are highly reactive molecules that can cause cellular damage and contribute to the development of various degenerative diseases. Butterfly pea flower (Clitoria ternatea L.) is a traditional medicinal plant rich in antioxidant compounds such as flavonoids, anthocyanins, and phenolics. This study aimed to evaluate the antioxidant activity of infusion and decoction preparations of butterfly pea flowers using the DPPH method. The research was conducted through laboratory experiments by measuring the IC?? value using UV-Vis spectrophotometry. The results showed that the infusion extract exhibited very strong antioxidant activity with an IC?? value of 31.25 ppm, while the decoction extract demonstrated moderate antioxidant activity with an IC?? value of 128.66 ppm. The positive control, Vitamin C, showed very strong antioxidant activity with an IC?? value of 14.04 ppm. Based on these findings, the infusion method is more effective at extracting antioxidant compounds than the decoction method. The infusion of butterfly pea flower has potential to be developed as a natural antioxidant source.
TERAPI ANTIBIOTIK UNTUK TRAVELLER’S DIARRHEA DI ASIA TENGGARA : TINJAUAN GLOBAL TERKINI DAN TANTANGAN RESISTENSI MIKROBA: Antibiotic Therapy for Traveler’s Diarrhea in Southeast Asia: Current Global Review and Challenges of Microbial Resistance I Made Wiracana; Wahyuni W.Udi
Journal Pharmactive Vol. 4 No. 2 (2025): Jurnal Pharmactive Oktober
Publisher : Institut Teknologi dan Kesehatan Bintang Persada

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Abstract

Traveler’s diarrhea (TD) is defined as the passage of three or more loose stools within a 24-hour period occurring during or shortly after travel. Southeast Asia is classified as a high-risk region, with an incidence rate of TD of at least 20%. The majority of TD cases are caused by bacterial pathogens, particularly Escherichia coli. In Southeast Asia, other organisms, including Campylobacter, are also frequently implicated. Although multiple clinical guidelines recommend antibiotic therapy for TD, antimicrobial resistance has emerged as a major challenge in its management. Despite available prevention and treatment guidelines, the development of antibiotic resistance in Southeast Asia after 2019 has not been adequately addressed in previous reviews. This narrative review aims to fill the gap identified in Hitch’s (2019) review by evaluating antibiotic therapy patterns for TD in the Southeast Asian context, with a specific focus on microbial resistance. The study employed a narrative review approach based on the PRISMA-P 2015 guidelines. Six studies or review articles addressing antibiotic resistance patterns among TD-related pathogens in Southeast Asia were included. The findings demonstrate substantial resistance of Campylobacter to fluoroquinolone antibiotics. Azithromycin remains the recommended therapy for moderate to severe TD; however, ciprofloxacin prescribing for TD is still reported in the Bali region.
PERANCANGAN SISTEM PHARFACILLE BERBASIS WEBSITE DENGAN METODE AGILE Septa Malan Vergantana
Journal Pharmactive Vol. 5 No. 1 (2026): Jurnal Pharmactive April
Publisher : Institut Teknologi dan Kesehatan Bintang Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64036/pharmactive.v5i1.96

Abstract

This research designed a web-based pharmacy information system named PHARFACILLE to resolve the problems of delayed report generation, stock recording errors, and inefficient customer service caused by the use of manual systems. The approach applied in this study involved qualitative research methods and software development utilizing the Agile method. The system design was systematically outlined using standard modeling language through the evaluation of functional modules in stages. The results indicated that the developed system successfully integrated cashier transactions, prescription records, drug stock management, inventory ordering, and financial reporting. The utilization of this system improved operational data accuracy, accelerated the service process, and reduced the dependency on manual recording. The designed system effectively facilitated the transformation of pharmacy management into a modern, transparent, and accountable digital environment.
NATURAL LANGUAGE PROCESSING UNTUK EKSTRAKSI INFORMASI ADVERSE DRUG REACTIONS DARI ELECTRONIC HEALTH RECORDS: SYSTEMATIC REVIEW I Gede, Irvan Pramanta Andika; Wiradarma, Riska; May Arfian, Dody
Journal Pharmactive Vol. 5 No. 1 (2026): Jurnal Pharmactive April
Publisher : Institut Teknologi dan Kesehatan Bintang Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64036/pharmactive.v5i1.100

Abstract

Adverse drug events (ADEs) contribute to 5-10% of hospitalizations and cost approximately USD 30 billion annually, yet spontaneous reporting systems capture only 5-10% of actual ADEs due to severe underreporting. This systematic review analyzed 60 peer-reviewed studies (2019-2025) on natural language processing (NLP) methods for extracting ADE information from electronic health record (EHR) clinical notes, following PRISMA 2020 guidelines across five databases (PubMed, IEEE Xplore, ACL Anthology, Scopus, Web of Science). Results demonstrate that transformer-based models, particularly BioBERT and ClinicalBERT, represent the state-of-the-art with F1-scores of 0.85-0.92 on benchmark datasets (n2c2 2018, MIMIC-III, MADE1.0), significantly outperforming rule-based systems (+15-20%) and traditional machine learning methods (+8-12%). Domain-specific pre-training on clinical text proved crucial, improving performance by 3-5% over general BERT models. However, critical challenges persist: negation and speculation detection (30-40% of medical mentions require contextual disambiguation), temporal reasoning for determining ADE onset relative to drug exposure, ambiguous medical abbreviation resolution, and causality assessment. A significant lab-to-clinic gap of 10-15% performance degradation was identified, with only 8% of studies reporting actual clinical deployment experiences. Reproducibility remains problematic, with merely 23% of studies sharing code and 15% providing trained models. Future priorities include developing few-shot learning approaches to address limited labeled data (~5,000 annotated clinical notes publicly available), enhancing model interpretability through explainable AI methods, conducting multi-center external validation studies, and establishing standardized evaluation protocols. This review provides evidence-based guidance for researchers developing NLP methods, practitioners implementing ADE detection systems, and policymakers formulating standards for NLP-based pharmacovigilance.
APLIKASI MACHINE LEARNING DALAM PREDIKSI INTERAKSI OBAT: SYSTEMATIC REVIEW May Arfian, Dody; I Gede, Irvan Pramanta Andika; Wiradarma, Riska
Journal Pharmactive Vol. 5 No. 1 (2026): Jurnal Pharmactive April
Publisher : Institut Teknologi dan Kesehatan Bintang Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64036/pharmactive.v5i1.104

Abstract

Drug-drug interactions (DDIs) represent a significant challenge in modern pharmacotherapy, contributing to 17-23% of adverse drug reaction-related hospitalizations. Machine learning (ML) has emerged as a promising approach for computational DDI prediction, yet a comprehensive synthesis of methodologies, performance benchmarks, and clinical translation challenges remains lacking. This systematic review aims to identify and evaluate ML algorithms applied to DDI prediction, compare their performance across different datasets and validation strategies, analyze feature representation methods, and identify critical gaps impeding clinical deployment. Following PRISMA 2020 guidelines, we conducted a systematic search across five electronic databases (PubMed, IEEE Xplore, Scopus, Web of Science, Google Scholar) for studies published between January 2019 and March 2025. Dual independent screening and extraction were performed with quality assessment using adapted PROBAST criteria. Included studies were analyzed for algorithm types, feature representations, datasets, validation strategies, and performance metrics. From 1,285 initial records, 60 high-quality studies were included. Graph neural networks (GNNs) emerged as state-of-the-art methods (mean F1-score: 0.931 ± 0.024), significantly outperforming traditional ML (0.842 ± 0.038, p < 0.001) and deep neural networks (0.893 ± 0.031, p = 0.003). Multi-modal approaches integrating chemical structure, biological targets, and phenotypic data achieved highest performance (F1: 0.945-0.982). DrugBank was the most utilized dataset (63.3% of studies), though severe class imbalance (positive:negative ratio 1:20 to 1:50) posed significant challenges. Critical gaps identified include: cold-start problem (18.3% performance degradation for unseen drugs), interpretability issues (45% black-box models), and minimal real-world validation (only 6.7% used EHR data). A severe reproducibility crisis was evident, with only 11.7% of studies fully reproducible. While ML-based DDI prediction has achieved impressive benchmark performance, substantial challenges remain for clinical translation. Priority research directions include: developing explainable AI methods for biological validation, addressing cold-start generalization through meta-learning and transfer learning, conducting multi-center real-world validation studies, establishing standardized evaluation protocols, and implementing federated learning infrastructure for privacy-preserving collaboration. Community-wide efforts toward reproducibility, standardization, and responsible deployment are essential for translating computational advances into clinically impactful systems that enhance medication safety.
PERANCANGAN SISTEM INFOPRMASI APOTEK PHARFACILLE BERBASIS WABSITE DENGAN TIGA TAHAP METODE AGAILE I Kadek , Krisna Angga Pamungkas; Moch , Anwar Fery Rais; I Gede, Irvan Pramanta Andika
Journal Pharmactive Vol. 5 No. 1 (2026): Jurnal Pharmactive April
Publisher : Institut Teknologi dan Kesehatan Bintang Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64036/pharmactive.v5i1.105

Abstract

The development of information technology has driven digital transformation across various sectors, including pharmaceutical services in pharmacies. Common problems faced by pharmacies that still rely on manual systems include inaccurate stock recording, delays in report generation, and low service efficiency. This study aims to design and develop a web-based pharmacy information system named PHARFACILLE to improve the effectiveness and accuracy of pharmacy operational management. The method used in this study is the Software Development Life Cycle (SDLC) combined with the Agile approach using the Scrum framework. System development was carried out iteratively through several sprints, covering planning, analysis, design, implementation, and evaluation stages. System modeling was conducted using Unified Modeling Language (UML) to describe system requirements and process flows. The results show that the PHARFACILLE system was successfully developed with main features including user authentication, sales dashboard, cashier system, inventory management, ordering and goods receiving management, and financial reporting. Integration between modules enables real-time data updates, thereby improving stock accuracy and transaction efficiency. Based on the development results, this system has the potential to enhance pharmacy service quality, accelerate operational processes, and support managerial decision-making through more accurate and structured data presentation.

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