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All Journal Jurnal Ilmiah Farmasi SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Pharmasipha Jurnal Ilmiah Kesehatan Majalah Farmasetika Jurnal Riset Kefarmasian Indonesia Jurnal Layanan Masyarakat (Journal of Public Service) Jurnal Integrasi Kesehatan dan Sains Lumbung Farmasi : Jurnal Ilmu Kefarmasian Sainstech Farma: Jurnal Ilmu Kefarmasian Jurnal Pengabdian Masyarakat Asia Medfarm: Jurnal Farmasi dan Kesehatan Jurnal Kesehatan Tambusai Kieraha Medical Journal Jurnal Pengabdian Masyarakat Indonesia Maju (JPMIM) Jurnal Ilmiah Ibnu Sina (JIIS): Ilmu Farmasi dan Kesehatan Jurnal Farmasi Etam Jurnal Ilmu Multidisplin Asian Journal of Healthcare Analytics Jurnal Pepadu Jurnal Pengabdian Pada Masyarakat Salus Publica Jurnal Farmasi Galenika Journal of Pharmascience
Taufiqurrahman, Muh
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Antioxidant Retention and Physicochemical Characterization of Instant Ginger Powder Formulation as a Functional Beverage Pijaryani, Indria; Muh. Taufiqurrahman
Asian Journal of Healthcare Analytics Vol. 5 No. 1 (2026): May 2026
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ajha.v5i1.16477

Abstract

This study aims to formulate an instant ginger rhizome extract powder and comprehensively evaluate its physicochemical characteristics and antioxidant retention capacity as a functional beverage. This experimental research employed four variations of ginger powder concentration (0%, 5%, 10%, and 15%) using the wet granulation method. Evaluation results indicated that all formulations met the required standards, with moisture content below 5% and favorable flowability. The 15% formulation (F3) proved to be the most optimal, demonstrating strong antioxidant activity with an IC50 value of 65.50 ppm. Overall, this formulation produces a powdered beverage with excellent physicochemical stability and measurable nutraceutical efficacy, making it a viable candidate for functional food.
Pemanfaatan Probiotik Asam Laktat dalam Susu Kuda Sumbawa sebagai Bahan Baku Tabir Surya Muh Taufiqurrahman; Adhe Septa Ryan; Maria Elvina Tresia Butar-Butar; Indria Pijaryanti
Journal of Pharmascience Vol. 11 No. 1 (2024): Jurnal Pharmascience
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jps.v11i1.16652

Abstract

Susu kuda Sumbawa merupakan susu murni dari kuda liar yang dipelihara oleh petani organik di Indonesia. Kandungan asam laktat pada susu kuda Sumbawa jarang digunakan untuk produk non pangan. Asam laktat (lactic acid), dikategorikan sebagai salah satu asam α-hidroksi (AHA), adalah asam organik dengan gugus hidroksil pada posisi alfa. Asam laktat dapat diproduksi baik dengan fermentasi mikroorganisme atau dengan sintesis kimia dan berguna sebagai tabir surya serta antioksidan. Tabir surya merupakan senyawa yang dapat melindungi kulit dari efek sinar ultraviolet yang dipancarkan matahari. Penelitian diawali dengan mengidentifikasi bahan uji dengan melakukan analisis asam laktat yang bertujuan untuk mengetahui jumlah total asam laktat yang terdapat pada sampel susu kuda kemudian dilakukan pengujian SPF, %TP dan %TE. Hasil dari pengujian ini termasuk dalam perlindungan maksimal karena memiliki faktor perlindungan matahari <15, serta kandungan asam laktat dalam susu kuda terbukti efektif sebagai tabir surya dengan nilai SPF yaitu 9,4. Hasil pengukuran persentase eritema (% TE) dan persentase pigmentasi (% TP) susu kuda berada dalam standar dengan masing-masing nilai %Te sebesar 9,3% dan nilai %Tp sebesar 47,5%  termasuk kategori Suntan standar. Kata Kunci: SPF, Persentase Eritema, Persentase Pigmentasi, Suntan, Tabir surya Sumbawa horse milk is pure milk from wild horses raised by organic farmers in Indonesia. The lactic acid content in Sumbawa horse milk is rarely used for non-food products. Lactic acid, categorized as one of the α-hydroxy acids (AHAs), is an organic acid with a hydroxyl group at the alpha position. Lactic acid can be produced either by the fermentation of microorganisms or by chemical synthesis and is used as a sunscreen as well as an antioxidant. Sunscreen is a compound that can protect the skin from the effects of ultraviolet rays emitted by the sun. The study was started by identifying the test material by carrying out lactic acid analysis which aims to determine the total amount of lactic acid present in the horse milk sample and then tested for SPF, %TP and %TE. The result of this test is that the effect of sunscreen on Sumbawa mare's milk is very good, namely 9.4 which is included in the maximum protection because it has a sun protection factor <15. The results of measurements of the percentage of erythema (% TE) and percentage of pigmentation (% TP) of mare's milk were in the standard with each %Te value of 9.3% and %Tp value of 47.5% including the standard suntan category.
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.
Co-Authors Abdul Rahim Adhe Septa Ryan Agus, Adhe Septa Ryant Alichia Ayu Susan Angel Natalia Nainggolan Angela Dewi Sartika Hiyang Awan, Kevin Imanuel Beang, Marcelino Edo Ba Citraningsih, Ni Putu Dewi Dinda Alya Arianti Donangsia Wunga Sogen Dwi Retno Sari, Dwi Retno Erika Sudin Faizatun Falen Sindi Ayugistia Falen Sindi Ayugistia Fransiska Novita Sari Gilbert Luhat, Martin Helena Aritonang Hutagalung, Remita Ully Iju, Sesilia Karolina Indria Pijaryanti Johandi, Egedius Harley Karolina Yordan Leli Nurlaeli Luhung, Sisilia Maria Elvina Tresia Butar-Butar MZ, Sariati Nainggolan, Angel Natalia Nor Istiqomah Nur Cholis Majid Nurillahi Febria Leswana Pamungkas, Asih Rahayu Pijaryani, Indria Ping, Maria Floriana Putri, Dian Cantika Remita Ully Hutagalung Risny Oklyan Ryan, Adhe Septa Selvina, Selvina Sherlina Puspita Silaban Erllin Tirza Stevany Simanullang, Raymon Sister Sianturi Siswa Setyahadi Syafriana, Vilya Tokan, Santa Eufrasia Carolin Wijikinasih, Wijikinasih Yesi Bayaq