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All Journal Jurnal Ilmiah Medicamento Berkala Ilmiah Mahasiswa Farmasi
Valentino, Tambunan Matthew
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Biochemistry, Genetics & Molecular Biology Chemistry Health Professions Immunology & microbiology Medicine & Pharmacology Public Health

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ANALISIS BIBLIOMETRIK TERHADAP PENGEMBANGAN PENELITIAN MACHINE LEARNING UNTUK IDENTIFIKASI SENYAWA KIMIA OBAT Valentino, Tambunan Matthew; Adi, I Made Agus Kusuma; Rahmadhani, Bellyna Putri Annisa
Berkala Ilmiah Mahasiswa Farmasi Indonesia Vol. 11 No. 1 (2024): Berkala Ilmiah Mahasiswa Farmasi Indonesia (BIMFI)
Publisher : Ikatan Senat Mahasiswa Farmasi Seluruh Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.48177/bimfi.v11i1.121

Abstract

Introduction: The development of machine learning-based technology has been utilized in various fields of science ranging from education to social work. The field of health science is one that utilizes the application of machine learning technology, this can be proven by the development of technology that helps in the analysis of treatment and chemical compounds of drugs. The bibliometric analysis aims to provide a visualization of related literature metadata on the topic of machine learning for the analysis of chemical compounds of drugs. Methods: The method used was literature collection using the Pubmed database with the keywords "(machine learning) AND (drug structure)". Exclusion factors applied for the search were document type, document access, and publication year. The literature obtained was analyzed bibliometrically using Biblioshiny by Bibliometrix. Bibliometric analysis was analyzed in three clusters. Result: Bibliometric analysis is widely developed by researchers, it can be seen from the number of articles published by researchers. This analysis identified research by 8,301 authors from 79 countries. The largest number of articles relevant to the topic is found in the Scientific Report journal. Conclusion: The utilization of machine learning has grown rapidly in the last 10 years. Bibliometric analysis with Biblioshiny provides a precise visualization of these developments. The bibliometric analysis identified research trends by 8,301 authors from 79 countries between 2014 and 2024. The highest number of publications per year occurred in 2023 and researcher continuity started from 2020. Keywords and collaboration analysed using node and edge from Louvain scheme.
Chitosan-Based Electrospun Nanofibers for Wound Healing: A Systematic and Bibliometric Synthesis of Material Design and Biological Performance Wiguna, I Gede Adi; Rupiasih, Ni Nyoman; Valentino, Tambunan Matthew; Setyawan, Eka Indra
Jurnal Ilmiah Medicamento Vol 12 No 2 (2026): Jurnal Ilmiah Medicamento
Publisher : Fakultas Farmasi Universitas Mahasaraswati Denpasar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36733/medicamento.v12i2.14768

Abstract

Background: Chronic wound pathogenesis is associated with infection, inflammation, oxidative stress, and poor tissue regeneration, creating a major clinical challenge. Electrospun nanofibers, especially using chitosan, may be promising therapy with various advantages.Objective: This research investigated design strategies and methodological factors affecting the therapeutic efficacy and translational potential of chitosan-based electrospun nanofibers for wound healing.Methods: Advances in the research field, formulation characteristics, production specifications, biological efficacy, and comparability between studies were evaluated through a systematic analysis of 23 studies and a bibliometric analysis of 186 articles published between 2015 and 2025.Results: The annual growth rate of publications is 29.24%, indicating growing interest in the methods of multifunctional wound-dressing methods. This allows evaluation of different studies to understand the characteristics of chitosan for electrospinning. Most studies employed single-layer nanofiber scaffolds incorporating medium- to high- molecular weight chitosan, with varying copolymer, bioactive, and crosslinker compositions, as well as electrospinning parameters, particularly applied voltage and flow rate. However, differences in production processes, biological assessment methods, and wound models limited the comparability of the studies. Healing outcomes were more dependent on mechanism-based approaches that addressed the underlying causes of injuries.Conclusion: The results demonstrate that differences in manufacturing conditions, material composition, and biological assessment can strongly affect the interpretation across studies.
Co-Authors Adi, I Made Agus Kusuma Eka Indra Setyawan Ni Nyoman Rupiasih Rahmadhani, Bellyna Putri Annisa Wiguna, I Gede Adi