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All Journal Jurnal Kesehatan Gigi Jurnal Ilmiah Kedokteran Wijaya Kusuma Journal of Health (JoH) Indonesian Contemporary Nursing Journal (ICON Journal) Jurnal Surya Masyarakat Jurnal Biomedika Community Development Journal JIDAN (Jurnal Ilmiah Bidan) Medika Alkhairaat : Jurnal Penelitian Kedokteran dan Kesehatan Journal of Intelligent Computing and Health Informatics (JICHI) Jurnal Pengabdian dan Peningkatan Mutu Masyarakat (JANAYU) Jurnal Midwifery PHARMACOLOGY, MEDICAL REPORTS, ORTHOPEDIC, AND ILLNESS DETAILS (COMORBID) Prosiding Seminar Nasional Unimus
Mudyawati Kamaruddin
Program Pascasarjana Ilmu Laboratorium Medik Universitas Muhammadiyah Semarang
Religion Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences Other

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Identification of Neisseria gonorrhoeae Bacteria Using a Convolutional Neural Network (CNN) Based on Image Classification Maulana, Haris; Kamaruddin, Mudyawati; Suyanto, Agus; Rabban, Auliyaur
PHARMACOLOGY, MEDICAL REPORTS, ORTHOPEDIC, AND ILLNESS DETAILS Vol. 5 No. 1 (2026): JANUARY
Publisher : Transpublika Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55047/comorbid.v5i1.1963

Abstract

Neisseria gonorrhoeae (gonococcus) is the primary bacterium responsible for the sexually transmitted infection gonorrhea, which is transmitted through sexual contact. Traditional identification methods, such as Polymerase Chain Reaction (PCR), are still widely used but have limitations in terms of cost, time, and the need for multiple reagents. This study aims to develop a faster and more efficient identification method using Artificial Intelligence (AI) through a Convolutional Neural Network (CNN) approach based on the Inception V3 architecture. The dataset used consists of 84 JPEG images, comprising 42 images of Neisseria gonorrhoeae and 42 non-Neisseria images. The model was trained using 50 epochs with an early stopping mechanism, which optimally halted at epoch 25, achieving a training accuracy of 94.74% and a validation accuracy of 100%. The resulting model achieved 96% classification accuracy, correctly identifying all 8 positive and 4 negative test images. These findings indicate that CNN based on Inception V3 is effective in classifying Neisseria gonorrhoeae images and has strong potential as a fast, accurate, and efficient diagnostic alternative.
Plasma medicine in Indonesian wound care: Clinical potential, implementation barriers, and practice recommendations Warsono, Warsono; Kamaruddin, Mudyawati; Ahmad, Rasheed
Indonesian Contemporary Nursing Journal (ICON Journal) Vol. 10 No. 2 (2026): Volume 10 Number 2 February 2026
Publisher : Faculty of Nursing, Universitas Hasanuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/icon.v10i2.49821

Abstract

Both acute and chronic wounds remain significant challenges in Indonesian healthcare services. Postoperative wounds, diabetic ulcers, traumatic wounds, and infected wounds impose substantial clinical, financial, and psychosocial burdens on patients, families, and the healthcare system. The high incidence of non-communicable diseases, such as diabetes, limited availability of modern wound care facilities in many regions, and risk of nosocomial infections complicate the wound healing process and increase the length of hospital stay. Plasma medicine, particularly nonthermal plasma (cold atmospheric plasma), has emerged as an innovative approach to wound care. Nonthermal plasma can generate reactive oxygen and nitrogen species, electric fields, and low-dose UV radiation, all of which collectively contribute to antimicrobial effects, modulation of inflammation, and stimulation of tissue regeneration without causing thermal damage to healthy tissue (Kamaruddin et al., 2024). Various studies have shown that plasma-based wound therapy can reduce microbial load, improve granulation, and accelerate wound closure, particularly in chronic, hard-to-heal wounds.
Metagenomic Analysis of Intestinal Microbiota Derived from Stool Samples of Third-Trimester Pregnant Women Kamaruddin, Mudyawati; Zamzam, Miftahul Khairiyah; Pratama, Rahadian; Nur, AbdurRahman Shakhr; Muthiadin, Cut; Sembiring, Christine; Triananinsi, Nurhidayat; Nurisyah, Nurisyah; Dewi, Ratnasari; Fatmawati, Fatmawati; Erniawati, Erniawati; Jusni, Jusni; Basmiati, Basmiati
Jurnal Ilmiah Kedokteran Wijaya Kusuma Vol. 14 No. 1 (2025): MARET 2025
Publisher : Universitas Wijaya Kusuma Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30742/jikw.v14i1.4173

Abstract

Background: The human gut microbiota plays a unique role in metabolism, immunity, and nutrient absorption.  Various studies on the gut microbiota have identified a link between changes in bacterial abundance in the gut known as dysbiosis (imbalance) and the pathogenesis of certain disorders. It is known that an imbalance in the ratio of the phyla Firmicutes and Bacteroidetes has been associated with various chronic diseases, including inflammatory bowel disease and metabolic disorders. The Firmicutes/Bacteroidetes (F/B) ratio is a measure used to assess gut microbiota composition, which is believed to play a significant role in intestinal health and metabolism. Studies suggest that a higher F/B ratio is often associated with obesity and other metabolic conditions. Objective: This study aims to carry out metagenomic analysis of third-trimester pregnant women's faecal samples to predict degenerative diseases using third-generation whole genome sequencing, namely PromethION nanopore technology.  Method: Nanopore Technology: DNA sequencing of faecal samples from pregnant women in the third trimester was performed using the Oxford Nanopore Technology (ONT) device based on the Ligation Sequencing gDNA - Native Barcoding Kit 24 V14 and following its guidelines. Result: Based on the quality and quantity of total DNA reads from 20 stool samples from pregnant women, only 4 samples were continued for analysis (1A, 2A, 3A and 4A). The results of the abundance of intestinal microbiota based on the most abundant phylum are Proteobacteria, Bacteriodetes, and Firmicutes. Conclusion: Meanwhile, based on species abundance, it shows that Prevotella copri (phylum Bacteriodetes) is abundant in samples 2A, 3A and 4A, while in sample 1A the most abundant species is Succinivirio dextrinosolvens (phylum Proteobacteria). Bacteroidetes are a group of Gram-negative bacteria that are often found to increase in individuals with type 2 diabetes and obesity
Co-Authors A. Haryanti Ganie Ganie A. Maya Rupa Anjeli Agus Suyanto Ahmad, Rasheed Akhmad Rivandi Akhmad rivandi Andi Asriany Andi Harmawati Novriani HS Andi Yuyun Dian Pertiwi Angle Ananta Ani T Prianti Asriany Ayu Puspaning Tyas, Dyah Basmiati, Basmiati Budi Santoso Cahyawan, Diawan Cut Muthiadin DaffaPutra Mahardika Defi Nurul Hayati Dewi Purnamasari Dewi Purnamasari Dewi Ratnasari Eka Kurnia, Eka Erniawati Erniawati, Erniawati Fasilah Basri Fatmawati, Fatmawati Haerani Hasrawati Hasriani Saleng Havida Widyastuti Hendra Stevani Idar Karlina Ika Handayani Ika handayani Isnayanti Ivonne Siswanty Jalil, Jumirah Juni Nauli Jusni Jusni Jusni, Jusni Kasmawati Lili Andriani Lisdayanti Malisa Nisaul Alim Marlina Azis Maulana, Haris Mega Dwi Setyaningrum Megawati, Ani Minarti Minarti Misnawaty Misnawaty Misnawaty Misriyani Misriyani Mubarak, Abdul Haris Muhammad Raihan Shane Ady Nugroho Muhammad, Munawir MUKRIMAH MUKRIMAH, MUKRIMAH Muli Sukmawaty Ningsih, Sri Nita Ariani Nur Nita Ariani Nur Nita Ariani Nur Noveppy Cahya Permatasari Nur, AbdurRahman Shakhr Nurasia Nurasia Nurfaizah Alza Nurhayani Nurhayani Nurhidayat Triananinsi Nurhidayat Triananinsi Nurhidayat Triananinsi Nurhidayat Triananinsi Nurisyah, Nurisyah Nurqalbi Nurqalbi Nurqalbi SR Nursaima Siregar Nurul Amalia Sari Nurul Hidayah Bohari Pia, Pia Prianti, Ani T Rabban, Auliyaur Rafidah Rafidah Rahadian Pratama Ratna Sulistyorini Ratna Sulistyorini, Ratna Ratnasari Dewi Rina Mariana Rinda Aulia Utami Risnayanti Rizka Yolanda Febiaocti Sembiring, Christine Siti Usmia Sri Darmawati Sri Suhartati Sri wahyuni Sukmawati Sumarni Sumarni Sumarni Sumarni Sutrani Syarif Syarif, Sutrani Triananinsi, Nurhidayat Ulfa Dillah Usmia, Sitti Warsono Warsono Widyastuti, Havida Zamzam, Miftahul Khairiyah