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All Journal Jurnal Ilmiah Farmasi Majalah Farmaseutik Jurnal Riset Kefarmasian Indonesia Medfarm: Jurnal Farmasi dan Kesehatan Jurnal Kesehatan Tambusai Jurnal Farmasi Etam Journal of Innovation Research and Knowledge Jurnal Ilmu Multidisplin Journal of Biotechnology and Natural Science Pharmacon: Jurnal Farmasi Indonesia
Simanullang, Raymon
Sekolah Tinggi Ilmu Kesehatan Dirgahayu Samarinda, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Dentistry Economics, Econometrics & Finance Education Health Professions Immunology & microbiology Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health Social Sciences

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EVALUASI PENGGUNAAN OBAT ANTIHIPERTENSI PADA PASIEN HIPERTENSI DI UPTD PUSKESMAS JUANDA KOTA SAMARINDA Wijikinasih, Wijikinasih; Muh. Taufiqurrahman; Raymon Simanullang
Jurnal Riset Kefarmasian Indonesia Vol. 7 No. 3 (2025): Jurnal Riset Kefarmasian Indonesia
Publisher : APDFI (Asosiasi Pendidikan Diploma Farmasi Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33759/v7i3.771

Abstract

The increasing use of antihypertensive drugs may raise the potential for irrational use. Irrational management of hypertension can worsen the patient’s condition and trigger complications such as stroke, heart disease, and kidney failure. This study was a descriptive study with retrospective data collection using purposive sampling. Data were obtained from electronic medical records in the e-Puskesmas application of hypertensive patients. The results showed that 85.8% of antihypertensive drug use was in accordance with hypertension management based on the Decree of the Minister of Health of the Republic of Indonesia No. HK.01.07/MENKES/1936/2022 on Clinical Practice Guidelines for Physicians in Primary Healthcare Facilities (PHC) and the JNC VIII Guidelines. These findings indicate that most antihypertensive drug use in primary healthcare facilities has followed current management standards, although approximately 14.2% of cases still demonstrate potential irrational use. This highlights the need for continuous evaluation and improved adherence to clinical guidelines in order to minimize the risk of complications.
Utilizing big data and data mining to detect adverse drug reactions in pharmacovigilance systems Taufiqurrahman , Muh.; Simanullang, Raymon; Alichia Ayu Susan; Nainggolan, Angel Natalia; Dinda Alya Arianti; Donangsia Wunga Sogen; Falen Sindi Ayugistia; Pijaryani, Indria
Jurnal Ilmiah Farmasi Vol. 22 No. 1 (2026): Jurnal Ilmiah Farmasi
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/jif.vol22.iss1.art2

Abstract

Background: Adverse Drug Reactions (ADRs) remain a global health problem, increasing morbidity, mortality, and costs. The Spontaneous Reporting System (SRS), while central to pharmacovigilance, suffers from underreporting and delayed signal detection. Advances in big data and data mining offer solutions to these limitations.Objective: This review evaluates the use of statistical, Bayesian, and artificial intelligence (AI)-based methods to improve early detection of ADR signals in large pharmacovigilance databases.Method: A literature review was conducted on 12 studies applying statistical methods (reporting odds ratio and proportional reporting ratio), Bayesian approaches, and AI techniques (machine learning and natural language processing) to datasets including FAERS, WHO VigiBase, VigiFlow, and national AEFI systems.Results: Disproportionality analysis aided early screening but was limited in detecting rare events and prone to false positives. Bayesian methods improved stability and accuracy for low-frequency signals. Machine learning enhanced predictive performance and reduced false alarms, while NLP facilitated processing of unstructured reports. The combined application of these methods enhanced sensitivity, specificity, and validity of pharmacovigilance systems. Conclusion: The integration of big data with statistical, Bayesian, and AI approaches significantly advances pharmacovigilance by enabling faster and more accurate ADR detection, though challenges in data quality, privacy, and clinical validation remain.
Hubungan Tingkat Stres Terhadap Pola Tidur Serta Dampaknya Terhadap Perilaku Swamedikasi Pada Mahasiswa STIKES Dirgahayu Samarinda Celly Delfia Tusau; Muh Taufiqurrahman; Raymon Simanullang
Jurnal Farmasi Etam (JFE) Vol 6 No 1 (2026): Juni
Publisher : Unit Penelitian dan Pengabdian Kepada Masyarakat (UPPM) STIKES Dirgahayu Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52841/jfe.v6i1.896

Abstract

Penelitian ini dilatarbelakangi oleh tingginya tingkat stres akademik pada mahasiswa tingkat akhir yang dapat memengaruhi kualitas tidur serta mendorong perilaku swamedikasi. Kondisi tersebut dapat mendorong mahasiswa melakukan swamedikasi tanpa pengawasan tenaga kesehatan untuk mengatasi keluhan seperti sakit kepala, kelelahan, maupun gangguan tidur. Penelitian ini bertujuan untuk menganalisis hubungan tingkat stres terhadap pola tidur serta dampaknya terhadap perilaku swamedikasi pada mahasiswa STIKES Dirgahayu Samarinda. Penelitian ini menggunakan metode kuantitatif dengan pendekatan deskriptif analitik dan desain cross sectional. Populasi penelitian adalah seluruh mahasiswa tingkat akhir Program Studi S-1 Farmasi, S-1 Keperawatan, dan D-3 Keperawatan STIKES Dirgahayu Samarinda dengan jumlah sampel sebanyak 67 responden yang dipilih menggunakan teknik purposive sampling. Instrumen yang digunakan yaitu Perceived Stress Scale (PSS-10) untuk mengukur tingkat stres, Pittsburgh Sleep Quality Index (PSQI) untuk mengukur kualitas tidur, serta kuesioner perilaku swamedikasi. Analisis data menggunakan analisis deskriptif dan uji Chi-Square (χ²). Hasil penelitian diharapkan menunjukkan adanya hubungan yang signifikan antara tingkat stres dengan pola tidur serta adanya kecenderungan perilaku swamedikasi pada mahasiswa yang mengalami kualitas tidur buruk dan gangguan tidur.
Co-Authors -, mardiana - Adhe Septa Ryant A Agus, Adhe Septa Ryant Alichia Ayu Susan Antonius Mario Claret Tophi Making Celly Delfia Tusau Chairun Wiedyaningsih Clara Ritawany Sinaga Dinda Alya Arianti Donangsia Wunga Sogen Falen Sindi Ayugistia Helena Aritonang Liniati Geografi Maria Elvina Tresia Butar-Butar Mochammad Tri Norcahyo Muhammad Evan MZ, Sariati Nainggolan, Angel Natalia Nurillahi Febria Leswana Pijaryani, Indria Sinaga, Clara Ritwany Sister Sianturi Sriminarty Tambing Taufiqurrahman, Muh Tikes, Roivelisko Tri Murti Andayani Wijikinasih, Wijikinasih