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All Journal Jurnal Ilmiah Farmasi SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal Ilmiah Kesehatan Amerta Nutrition PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat JURNAL MEDIA KESEHATAN Majalah Farmasetika Lumbung Farmasi : Jurnal Ilmu Kefarmasian Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Empathy Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat Indonesia Maju (JPMIM) Asian Journal of Healthcare Analytics Miracle Get Journal
Pijaryani, Indria
Universitas Mulawarman
Agriculture, Biological Sciences & Forestry Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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Hubungan Antara Food Coping Strategi dan Ketahanan Pangan Rumah Tangga Miskin di Wilayah Pesisir, Hutan Tropis dan Perkotaan Provinsi Kalimantan Timur: Hubungan Antara Food Coping Strategi dan Ketahanan Pangan Rumah Tangga Miskin di Wilayah Pesisir, Hutan Tropis dan Perkotaan Provinsi Kalimantan Timur Aryatika, Karera; Pijaryani, Indria; Wahyuni, Leny Eka Tyas
Amerta Nutrition Vol. 10 No. 1SP (2026): AMERTA NUTRITION SUPPLEMENTARY EDITION
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/amnt.v10i1SP.2026.122-137

Abstract

Background: Food security remains a major challenge for low-income households, especially in geographically and socioeconomically diverse regions such as tropical forests, coastal areas, and urban settings. Food coping strategies are crucial mechanisms used by households to address food insecurity. Objectives: This study aims to examine the relationship between food coping strategies and food security among low-income households in coastal, tropical forest, and urban areas of East Kalimantan Province, Indonesia. Methods: A cross-sectional quantitative study was conducted in three regions: Samarinda City (urban), Muara Badak (coastal), and Muara Wahau (tropical forest). Respondents were selected using simple random sampling. Data were collected using structured questionnaires on socio-demographics, food coping strategies (RCSI), and food security status (US-HFSSM). Statistical analyses included chi-square tests, t-tests, ANOVA, and correlation analysis. Results : The majority of households in tropical forest areas demonstrated high coping strategies (72.5%) and good food security (82.4%). Coastal households had the lowest coping capabilities (56.4%) and the highest rate of food insecurity (50%). In urban areas, 44.3% of households remained food insecure despite better access to food markets. Conclusions:There is a significant relationship between food coping strategies and food security, particularly in tropical forest and urban areas. Households in tropical forests benefit from local natural resources and traditional knowledge, enhancing their food security. In contrast, coastal and urban areas require targeted interventions to strengthen adaptive capacities and food access among low-income households.
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.
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 Alichia Ayu Susan Anggreini, Putri Arief, Maryam Jamila Aryatika, Karera Badriyah, Lulu'ul Dinda Alya Arianti Donangsia Wunga Sogen Dzikri, Akhmad Eka Tyas Wahyuni, Leny Evilia, Evilia Fadilla, Raisa Falen Sindi Ayugistia Fatriansari, Asih Fitriyana Fitriyana, Fitriyana Fitriyati, Fitriyati Gama, Sabaniah Indjar Hanis Kusumawati Rahayu Iju, Sesilia Karolina Junaidin, Junaidin Linda F., Noor Mahmudah, Febria Maria Elvina Tresia Butar-Butar Maxianus K. Raya Nainggolan, Angel Natalia Nastitie Cinintya Nurzihan Nisaa, Nur Rezky Khairun Nurillahi Febria Leswana Nurul Afiah Onny Ziasti Fricillia Ryan, Adhe Septa Simanullang, Raymon Siregar, Vita Olivia Taufiqurrahman, Muh Wahyuni, Leny Eka Tyas Wirapuspita Wisnuwardani, Ratih Yanuarti, Gita