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All Journal International Journal of Public Health Science (IJPHS) Pharmacon Jurnal Kebidanan Dan Kesehatan Tradisional Journal Of Nursing Practice Journal of Pharmacopolium Chemistry Indonesian Journal of Chemical Research Viva Medika: Jurnal Kesehatan, Kebidanan dan Keperawatan Pharmacoscript Jurnal Ilmiah Farmako Bahari Borneo Journal Of Pharmascientech Journal of Pharmaceutical and Health Research Jurnal Kesehatan: Jurnal Ilmu- Ilmu Keperawatan, Kebidanan, Farmasi dan Analis Kesehatan Pelita Abdi Masyarakat Pharmacy Reports Jurnal Ilmiah Farmasi Akademi Farmasi Jember Kolaborasi Jurnal Pengabdian Masyarakat Jurnal Farmasi Sains dan Praktis Pharmacy Genius SEMINAR NASIONAL PENELITIAN DAN PENGABDIAN KEPADA MASYARAKAT Jurnal Farmasi Indonesia Journal of Pharmaceutical and Sciences. Journal of Advanced Health Informatics Research Daarul Ilmi: Jurnal Pengabdian Kepada Masyarakat
Ikhwan Yuda Kusuma
Program Studi Farmasi, Universitas Harapan Bangsa Purwokerto
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Immunology & microbiology Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Medicine & Pharmacology Nursing Public Health Veterinary Other

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Analisis Bibliometrik Global Pemanfaatan Artificial Intelligence Dalam Penelitian Resistensi Antimikroba Periode 2015–2025 Nurrahma, Alfiya Hana; Kusuma, Ikhwan Yuda; Ramadhani, Nadia; Nufus, Ayatun; Saputri, Abelia; Haryanti, Sri; Putri, Renanda Nabila
Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat 2025 Prosiding Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat (SNPPKM 2025)
Publisher : Universitas Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35960/snppkm.v4i1.1358

Abstract

Antimicrobial resistance (AMR) is a growing global health threat. Artificial Intelligence (AI) offers innovative approaches to the detection, prediction, and management of resistance through advanced data analysis. This study aims to map the research landscape of AI utilisation in AMR for the period 2015–2025 through bibliometric analysis. A search on PubMed (4 September 2025) yielded 2,078 documents (1996–2025), and after applying year restrictions, 2,009 articles were analysed. The total output of countries reached 11,943 publications, with China (5,570), the United States (2,896), and India (755) as the main contributors. Four thematic clusters were identified: machine learning, bacterial resistance, deep learning, and antimicrobial stewardship. The results showed a sharp increase in publications until 2025, with the journals Antibiotics, Frontiers in Microbiology, and Scientific Reports dominating. The study confirmed the important role of AI in supporting resistance detection and precision medicine, but challenges such as data limitations, algorithmic bias, and global research inequality still require attention.
Pengetahuan Masyarakat Tentang Antibiotik dan Faktor Sosiodemografi di Indonesia: Implikasi Terhadap Swamedikasi dan Resistensi Antimikroba Lauale, Evangelina Natali Theresya; Kusuma, Ikhwan Yuda; Mailatunnazza, Nova; Veronica, Laila; Putri, Melisa Mareta; Hilmi, Nahla Habibah; Amalia, Najwa Nurul; Izati, Fina Karunia
Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat 2025 Prosiding Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat (SNPPKM 2025)
Publisher : Universitas Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35960/snppkm.v4i1.1360

Abstract

Antibiotics are essential drugs for treating infectious diseases; however, limited public knowledge regarding their proper use contributes to self-medication practices and accelerates antimicrobial resistance. This study aimed to assess the level of antibiotic knowledge among the Indonesian population and analyze its association with sociodemographic factors. A cross-sectional survey was conducted using an online questionnaire distributed through social media, involving 487 respondents from various regions of Indonesia. Data were analyzed using Chi-square tests with SPSS version 27. The results revealed that 63.45% of respondents had high knowledge of antibiotics, 24.85% had moderate knowledge, and 11.70% had low knowledge. Female participants were more likely to demonstrate higher knowledge compared with males (OR = 2.009; 95% CI: 1.336–3.021; p < 0.001), while respondents with a bachelor’s degree showed greater knowledge than those with lower education levels. Occupational and regional differences were observed but were not statistically significant. These findings indicate that although the majority of respondents possessed a good understanding of antibiotics, a considerable proportion still demonstrated poor knowledge, potentially increasing the risk of irrational use. Targeted educational interventions and stricter regulation of antibiotic distribution are essential strategies to enhance public literacy and reduce the threat of antimicrobial resistance in Indonesia.
Peran Media Sosial dalam Meningkatkan Literasi Kesehatan Masyarakat tentang Penggunaan Antibiotik yang Rasional di Indonesia: Cross-Sectional Study veronica, Laila; Kusuma, Ikhwan Yuda; Wibawa, Navyzhah Aulia Aulia Putri; Khosyi, Nathania Elsa; Lauale, Evangelina Natali Theresya; Afifah, Maulina Nurul; Destiannesvi, Anggie
Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat 2025 Prosiding Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat (SNPPKM 2025)
Publisher : Universitas Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35960/snppkm.v4i1.1361

Abstract

Antimicrobial resistance is a serious global health problem, including in Indonesia, mainly due to the irrational use of antibiotics. The widespread use of social media opens up opportunities as a fast and interactive means of health education. This study aims to analyze the role of social media in increasing public knowledge about antibiotic use. The study used a cross-sectional design with an online survey conducted from December 2024 to May 2025, involving 581 respondents from various provinces in Indonesia. Data were collected through an online questionnaire covering demographics, social media usage patterns, and antibiotic knowledge. Data analysis was performed using SPSS version 27 with descriptive tests, and Chi-square. The results showed that the majority of respondents had moderate knowledge (63.5%), followed by high (34.9%) and low (1.5%). Age, gender, education, occupation, and social media usage are significantly related to knowledge levels. Older respondents, women, those with a bachelor's degree or higher, and civil servants tend to have better knowledge. Google (72.85%) and Twitter (64.29%) users also demonstrate higher knowledge levels compared to users of other platforms. In conclusion, social media plays an important role in improving public health literacy because social media has a very wide reach in Indonesia, information can be disseminated quickly and interactively, and it is easier for the public to understand educational content through social media than through conventional media such as television or brochures. Social media can be used as an effective strategy to reduce antibiotic resistance through more targeted and accessible education.
Development of a Pilot Chatbot to Detect Interactions Between Monotherapy and Combination Therapy with Captopril Using a Local (LLM) in Cardiovascular Therapy Ikhwan Yuda Kusuma; Afriza Pujiati; Khamdiyah Indah Kurniasih; Siti Setianingsih; Bizhar Ahmed Tayeb; Nur Arifin Akbar; Muhammad Syaiful Aliim
Journal of Advanced Health Informatics Research Vol. 4 No. 1 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jahir.v4i1.422

Abstract

Cardiovascular diseases (CVDs), including hypertension and heart failure, remain major contributors to global morbidity and mortality and frequently require long-term polypharmacy. The concurrent use of multiple medications increases the risk of drug–drug interactions (DDIs), which may reduce therapeutic effectiveness, increase toxicity, and contribute to adverse drug reactions. This study aimed to develop and validate a locally deployed large language model (LLM)-based chatbot for detecting drug–drug interactions involving captopril in both monotherapy and combination therapy settings. A development and validation study was conducted using DDI data obtained from DrugBank and Drugs.com. The chatbot was developed using the LLaMA-3 model integrated with LangChain, Ollama, and FastAPI and was evaluated through iterative testing and 5-fold cross-validation. System performance was assessed using accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), while usability was evaluated using the System Usability Scale (SUS) and Single Ease Question (SEQ) questionnaires completed by pharmacists. The chatbot demonstrated progressive performance improvement throughout development and achieved excellent performance during final validation involving 300 drug pairs, with an accuracy of 99.0%, sensitivity of 100.0%, specificity of 98.0%, PPV of 100.0%, and NPV of 92.0%, exceeding all predefined acceptance thresholds. Usability testing indicated only fair to moderate usability, with a mean SUS score of 65.0 and a mean SEQ score of 5.0, suggesting that further refinement of the user interface and workflow may be required. The locally deployed LLM-based chatbot demonstrated satisfactory diagnostic performance and preliminary feasibility for captopril-related DDI screening. Although the system showed promising classification performance, additional usability optimization and evaluation in real-world clinical workflows are needed before broader implementation can be considered as a pharmacist-supportive screening system.
Development of Smartotc Mobile Application with Clinical Decision Support System (CDSS) to Support Pharmacists in Managing Common Cold Ikhwan Yuda Kusuma; Khaniva Khalilia Alazhar; Peppy Octaviani; András Érszegi; Muhammad Iqbal; Muhammad Syaiful Aliim
Journal of Advanced Health Informatics Research Vol. 4 No. 1 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jahir.v4i1.423

Abstract

Common cold is a highly prevalent self-limiting respiratory illness and a frequent reason for self-medication and community pharmacy consultations. Variability in pharmacists’ clinical decision-making may affect the quality of care, highlighting the need for evidence-based decision-support tools. This study developed SmartOTC, a mobile application incorporating a Clinical Decision Support System (CDSS) to support pharmacists in managing common cold cases through symptom assessment, over-the-counter medication recommendations, patient education, and referral support. A pilot quasi-experimental before-and-after study was conducted among 10 community pharmacists in Indonesia as part of a preliminary evaluation of the application. The application was developed using Android Studio and a Python-based CDSS algorithm and evaluated through functional feasibility, task performance, usability, user experience, and expert validation assessments. SmartOTC demonstrated high technical performance, achieving a 92.73% success rate, a 0% crash rate, and a mean response time of 2.89 seconds. Significant improvements in task performance and response times were observed following implementation. However, these findings should be interpreted within the context of a pilot study with a limited sample size. The application demonstrated positive user experience and strong content validity, while usability outcomes suggested opportunities for further improvement. The findings are further limited by the single-site study setting and the absence of patient-level outcome evaluation. SmartOTC shows promise as a digital decision-support tool to support pharmacists in the management of common cold cases and warrants further evaluation in real-world pharmacy practice.
Promosi Literasi Antibiotik Sejak Dini melalui Media Infografis dan Komik pada Siswa Sekolah Dasar Ikhwan Yuda Kusuma; Supriani Supriani; Fiqih Nurkholis; Septi Nurkhasanah; Afriza Pujiati; Khaniva Khalilia Alazhar
Daarul Ilmi: Jurnal Pengabdian Kepada Masyarakat Vol. 3 No. 2 (2025): Daarul Ilmi: Jurnal Pengabdian Kepada Masyarakat (Juli-Desember 2025)
Publisher : LPPM STIKes Muhammadiyah Ciamis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52221/daipkm.v3i2.977

Abstract

Introduction: Irrational use of antibiotics remains a major global and national public health challenge, contributing to the accelerating problem of antimicrobial resistance. Low antibiotic literacy is a key determinant of inappropriate antibiotic use, and misconceptions often develop from an early age due to limited health education. Therefore, promotive and preventive educational strategies targeting children are essential to foster appropriate antibiotic use and long-term behavioral change. Objective: The purpose of this community service activity was to promote and improve antibiotic literacy among elementary school students through the use of infographic and comic-based educational media. Method: This community service activity was conducted using a qualitative descriptive approach with a participatory educational design based on Participatory Action Research. The intervention employed visual educational media in the form of infographics and an educational comic titled “Una and the Mission to Finish Antibiotics.” Data were collected through participatory observation, interactive discussions, and simple written interviews, and analyzed using thematic analysis. Result: The activity revealed three main response patterns among students: positive responses characterized by a clear understanding of antibiotic use and the importance of completing therapy, partial responses indicating basic understanding but conceptual confusion, and limited responses reflecting minimal comprehension. Most students demonstrated high engagement and increased awareness of appropriate antibiotic use. Conclusion: Infographic and comic-based education is an effective and child-appropriate strategy for promoting early antibiotic literacy. This approach supports preventive efforts in pharmaceutical and public health education and has strong potential to encourage rational antibiotic use when integrated into school-based learning.
Skala dan Pola Penggunaan Antibiotik Pada Infeksi Saluran Pernapasan Akut (ISPA) : Surveilans ATC/DDD 2021-2025 Di RSUD Prof. Dr. Margono Soekarjo Putri Dwi Anggraeni; Ikhwan Yuda Kusuma; Peppy Octaviani; Silma Kaaffah
Pharmacogenius Journal Vol 5 No 2 (2026): Pharmacy Genius
Publisher : Yayasan Inspirasi El Burhani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56359/pharmgen.v5i2.1183

Abstract

Pendahuluan: Infeksi saluran pernapasan akut (ISPA) merupakan salah satu penyebab utama rawat inap dan penggunaan antibiotik di seluruh dunia serta berkontribusi terhadap meningkatnya resistensi antimikroba. Pemantauan penggunaan antibiotik sangat penting untuk mendukung penggunaan antibiotik yang rasional dan memperkuat program antimicrobial stewardship. Tujuan: Penelitian ini bertujuan untuk mengevaluasi kuantitas dan pola penggunaan antibiotik pada pasien rawat inap dengan ISPA dengan metode Anatomical Therapeutic Chemical/Defined Daily Dose (ATC/DDD) dan Drug Utilization 90% (DU90%). Metode: Penelitian deskriptif retrospektif ini menggunakan data rekam medis pasien dewasa yang didiagnosis ISPA (kode ICD-10 J00–J06 dan J20–J22) di RSUD Prof. Dr. Margono Soekarjo, Indonesia, selama periode 2021–2025. Penggunaan antibiotik dihitung sebagai DDD/100 patient-days berdasarkan metodologi WHO ATC/DDD, sedangkan pola peresepan dianalisis menggunakan metode DU90%. Hasil: Total 237 pasien memenuhi kriteria inklusi dengan total konsumsi antibiotik sebesar 502,49 DDD/100 patient-days dengan penggunaan tahunan berkisar antara 81,13–120,51 DDD/100 patient-days. Antibiotik yang paling banyak digunakan adalah sefiksim, seftriakson, azitromisin, levofloksasin, dan seftazidim. Analisis DU90% menunjukkan bahwa tujuh jenis antibiotik menyumbang sekitar 90% dari total penggunaan, yang didominasi oleh antibiotik kategori Watch menurut klasifikasi WHO AWaRe. Kesimpulan: Penggunaan antibiotik pada pasien rawat inap dengan ISPA didominasi oleh antibiotik spektrum luas kategori Watch. Surveilans penggunaan antibiotik secara berkelanjutan menggunakan metode ATC/DDD dan DU90% diperlukan untuk mendukung program antimicrobial stewardship serta mengoptimalkan penggunaan antibiotik di rumah sakit.
Analysis of Social Media Content on Tiktok And Youtube Shorts Regarding The Representation of The Human Papillomavirus (HPV) Vaccine in Indonesia Yussri Yahya; Silma Kaaffah; Ikhwan Yuda Kusuma; Siti Setianingsih
Pharmacogenius Journal Vol 5 No 2 (2026): Pharmacy Genius
Publisher : Yayasan Inspirasi El Burhani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56359/pharmgen.v5i2.1210

Abstract

Background: Human Papillomavirus (HPV) is the primary cause of cervical cancer, making HPV vaccination a key strategy for cervical cancer prevention. As social media has become an increasingly important source of health information, evaluating the quality and credibility of HPV vaccine-related content on digital platforms is essential. Objective: This study aimed to analyze the characteristics, quality, credibility, understandability, and educational value of HPV vaccine-related videos on TikTok and YouTube Shorts in Indonesia. Method: A cross-sectional content analysis was conducted on 200 publicly accessible videos, comprising 100 TikTok videos and 100 YouTube Shorts videos identified using the keyword “HPV vaccine.” Video characteristics, uploader categories, content topics, and presentation styles were analyzed descriptively, while information quality was assessed using the Journal of the American Medical Association (JAMA) benchmark criteria, Global Quality Score (GQS), modified DISCERN (mDISCERN), and the Patient Education Materials Assessment Tool (PEMAT). Result: TikTok videos generated substantially higher audience engagement than YouTube Shorts, whereas YouTube Shorts demonstrated greater information credibility and reliability based on higher JAMA and mDISCERN scores. Vaccination targets, vaccination schedules, and vaccine types were the most frequently discussed topics, while vaccine mechanisms, side effects, and misinformation were addressed less frequently. Both platforms demonstrated high educational quality, with a mean GQS score of 4.43 and PEMAT-T scores exceeding 98%, indicating excellent understandability and actionability. However, source attribution and scientific referencing remained limited across both platforms. Conclusion: TikTok and YouTube Shorts have considerable potential as effective channels for HPV vaccine communication in Indonesia. Strengthening evidence-based communication practices and improving information transparency are essential to enhance public trust, increase vaccine confidence, and support cervical cancer prevention efforts.
Development and partial least squares structural equation modeling (PLS-SEM) validation of an instrument assessing ChatGPT adoption in clinical pharmacy education Septi Nurkhasanah; Ikhwan Yuda Kusuma; Silma Kaaffah; Sunarti Sunarti; Bizhar Ahmed Tayeb; Muhammad Iqbal
Pharmacy Reports Vol. 6 No. 1 (2026): Pharmacy Reports
Publisher : Indonesian Young Scientist Group and UPN Veteran Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51511/pr.143

Abstract

The rapid adoption of ChatGPT in health-profession education has created new opportunities for personalized learning, clinical reasoning support, and academic productivity. However, concerns regarding information reliability, ethical use, and overreliance on artificial intelligence remain insufficiently understood, particularly in clinical pharmacy education. This study aimed to develop and validate a multidimensional instrument for assessing ChatGPT adoption among Indonesian pharmacy students and to examine the structural relationships among its determinants using Partial Least Squares Structural Equation Modeling (PLS-SEM). A cross-sectional study was conducted using convenience sampling between January – March 2026 among 398 pharmacy students from Indonesian higher education institutions with prior ChatGPT experience. The instrument comprised six domains: Knowledge, Perception, Perceived Usefulness, Concern, Application, and Ethics and Usage Boundaries. Content validity was excellent (I-CVI, S-CVI/Ave, and S-CVI/UA = 1.00), while internal consistency and convergent validity were satisfactory (Cronbach's α = 0.857–0.951, composite reliability (ρC) = 0.896–0.959, and AVE = 0.634–0.814). Structural model analysis revealed that Perception (β = 0.630, p < 0.001) and Perceived Usefulness (β = 0.367, p < 0.001) were positively associated with Concern, whereas Concern was negatively associated with Application (β = −0.201, p < 0.001). Perceived Usefulness was also negatively associated with Ethics and Usage Boundaries (β = −0.061, p = 0.021). These findings indicate that pharmacy students recognize both the educational value and potential risks of ChatGPT. The validated instrument may facilitate future evaluations of generative AI adoption and support responsible AI integration in pharmacy education.
Co-Authors Abely, Nastasya Anis Afifah, Maulina Nurul Afnida Dwi Lestari Afriza Pujiati Almas Amalul Fasha Alvin Ulinnuha Amalia, Najwa Nurul Amelia Damayanti András Érszegi Annima Alfi Fauqina Apriliansa, Elza Puspita Arrina Sabilahaq Awang Pardigantara Azizah Azizah Bella Aisya Fitri Bizhar Ahmed Tayeb Bizhar Ahmed Tayeb Cecep Darwis Muttaqin Destiannesvi, Anggie Desy Nawangsari Dian Pitaloka Priasmoro, Dian Pitaloka dina febrina DM, Peppy Oktaviani Elza Puspita Apriliansa Fajar Rinawati Fasha, Almas Amalul Fauziah , Fauziah Fauziah Fauziah Fina Rudiyanti Fiqih Nurkholis Galih Samodra Galih Samodra Gita Fitriyani Halimatu Sa'diah Halimatu Sa’diah Hikmanti, Arlyana Hilmi, Nahla Habibah Ike Mardiati Agustin Irmawan Andri Izati, Fina Karunia K, Khamdiyah Indah Khamdiyah Indah Kurniasih Khaniva Khalilia Alazhar Khaniva Khalilia Alazhar Khasanah, Khuswatun Khosyi, Nathania Elsa Kurniasih, Khamdiyah Indah Kusnandar Anggadiredja Lauale, Evangelina Natali Theresya Linda Sukiatno Mailatunnazza, Nova Maryanti, Nelly Misworo, Misworo Muhammad Iqbal Muhammad Iqbal Muhammad Syaiful Aliim Muhammad Syaiful Aliim Nadia Ramadhani Nafi'ah, Inti Kalun nawangsari, desi Nawangsari, Desy Nida Nuridayah Noryana Novia Wulandari Nuari, Doni Anshar Nufus, Ayatun Nur Arifin Akbar Nur Islamiah Nurkholis, Fiqih NURLAELA NURLAELA Nurrahma, Alfiya Hana Peppy Octaviani Peppy Octaviani Peppy Octaviani Peppy Octaviani Dian Megasari Prabandari, Rani Pratiwi, Amelia Candra Putri Dwi Anggraeni Putri, Melisa Mareta Putri, Renanda Nabila Rani Prabandari Rani Prabandari Safitri, Cindy Ade Samodra, Galih Saputri, Abelia Sari, Destika Ambar Satyadewi, Putu Ratna Hari Septi Nurkhasanah Septi Nurkhasanah Silma Kaaffah Silma Kaaffah Sita Nur Faradila Sita Siti Setianingsih Sri Haryanti Sunarti Sunarti Sunarti Sunarti Sunarti Supriani Supriani Suryo Ediyono Susanto, Kharisma Evelyne Eka Susilo Rini Tresnowati, Gulita Indah umi sangadah Veronica, Laila Wibawa, Navyzhah Aulia Aulia Putri Wilis Sukmaningtyas Yuli Yuli Maesaroh Yuni Asri Yussri Yahya Yutia Ihza Komala Yuyun Pujiarti