Jurnal Teknokes
Aims JURNAL TEKNOKES aims to become a forum for publicizing ideas and thoughts on health science and engineering in the form of research and review articles from academics, analysts, practitioners, and those interested in providing literature on biomedical engineering in all aspects. Scope: 1. Medical Electronics Technology and Biomedical Engineering: Biomedical Signal Processing and Control, Artificial intelligence in biomedical imaging, Machine learning, and Pattern Recognition in a biomedical signal, Medical Diagnostic Instrumentation, Laboratorium Instrumentation, Medical Calibrator Design, Intelligent Systems, Neural Networks, Machine Learning, Fuzzy Systems, Digital Signal Processing, Image Processing, prosthetics, orthotics, rehabilitation sciences, Mobility Assistive Technology (MAT), Internet of Things (IoT), and Artificial Intelligence (AI) in the prosthetics and orthotics field, Breast Imaging, Cardiovascular Imaging, Chest Radiology, Computed Tomography, Diagnostic Imaging, Gastrointestinal Imaging, Genitourinary, Radiology, Head & Neck, Imaging Sciences, Magnetic Resonance Imaging, Musculoskeletal Radiology, Neuroimaging and Head & Neck, Neuro-Radiology, Nuclear Medicine, Pediatric Imaging, Positron Emission Tomography, Radiation Oncology, Ultrasound, X-ray Radiography, etc. 2. Medical Laboratory Technology: Hematology and clinical chemistry departments, microbiology section of the laboratory, parasitology, bacteriology, virology, hematology, clinical chemistry, toxicology, food and beverage chemistry. 3. Environmental Health Science, Engineering and Technology: Papers focus on design, development of engineering methods, management, governmental policies, and societal impacts of wastewater collection and treatment; the fate and transport of contaminants on watersheds, in surface waters, in groundwater, in soil, and in the atmosphere; environmental biology, microbiology, chemistry, fluid mechanics, and physical processes that control natural concentrations and dispersion of wastes in air, water, and soil; nonpoint-source pollution on watersheds, in streams, in groundwater, in lakes, and in estuaries and coastal areas; treatment, management, and control of hazardous wastes; control and monitoring of air pollution and acid deposition; airshed management; and design and management of solid waste facilities, detection of micropollutants, nanoparticles and microplastic, antimicrobial resistance, greenhouse gas mitigation technologies, novel disinfection methods, zero or minimal liquid discharge technologies, biofuel production, advanced water analytics 4. Health Information System and Technology The journal presents and discusses hot subjects including but not limited to patient safety, patient empowerment, disease surveillance and management, e-health and issues concerning data security, privacy, reliability and management, data mining and knowledge exchange as well as health prevention. The journal also addresses the medical, financial, social, educational, and safety aspects of health technologies as well as health technology assessment and management, including issues such as security, efficacy, the cost in comparison to the benefit, as well as social, legal, and ethical implications. This journal also discussed Intelligent Biomedical Informatics, Computer-aided medical decision support systems using a heuristic, Educational computer-based programs pertaining to medical informatics.
Articles
88 Documents
<![CDATA[Quasi-experimental study on Aloe Vera Gel As A Phytotherapy to Accelerate Perineal Wound Regeneration In Postpartum Mothers At Bpm Pera ]]>
<![CDATA[basaria]]>;
<![CDATA[Retno Wahyuni]]>;
<![CDATA[Hariati Eliana Purba]]>;
<![CDATA[Isyos Sari Sembiring]]>;
<![CDATA[Eva Ratna Dewi]]>;
<![CDATA[Nopalina Suyanti Damanik]]>;
<![CDATA[Titis Jernih Wati Gea]]>
<![CDATA[ Jurnal Teknokes Vol. 18 No. 4 (2025): Desember ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia ]]>
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DOI: 10.35882/jteknokes.v18i4.110
<![CDATA[Perineal wounds are one of the most common complications in postpartum women, causing pain, increasing the risk of infection, and delaying recovery. The lack of effective, safe, affordable, and easily accessible therapies highlights a gap in perineal wound care practices, particularly in primary care. Aloe vera, which contains anti-inflammatory compounds and regenerative bioactives, has the potential to serve as an alternative phytotherapy, but clinical evidence of its effectiveness in perineal wounds remains limited. This study aimed to evaluate the effectiveness of aloe vera gel in accelerating perineal wound healing in postpartum women. The contribution of this research is to strengthen the practice of phytotherapy-based wound care that is safe, affordable, and applicable in primary health care facilities. The study used a quasi-experimental pre-post study design with a control group. Thirty postpartum women with grade I–II perineal wounds were divided into a treatment group (Aloe vera) and a control group (standard care). Healing was evaluated using the REEDA scale, and pain intensity was assessed using a Visual Analogue Scale (VAS) over seven days. Analysis was performed using an independent t-test with a significance level of 0.05. The results showed a significant difference between the two groups. The average healing time for the Aloe vera group was 4.20 days (SD 0.95), faster than the control group, which took an average of 7.00 days (SD 1.20). Statistical tests showed a p-value = 0.001, indicating significant effectiveness of Aloe vera application in accelerating tissue healing. In addition, REEDA and VAS scores on the seventh day were consistently lower in the treatment group, indicating a faster reduction in inflammation and pain. Implicitly, these findings provide a clinical contribution to strengthening safe and affordable phytotherapy-based wound care practices for postpartum mothers, particularly in primary healthcare facilities. This study concluded that aloe vera gel is an effective complementary therapy for accelerating perineal wound healing and improving maternal comfort.]]>
<![CDATA[Isolation, Quantification, and Plaque Morphology Analysis of Lytic Bacteriophages from River Water Targeting Clinical MDR Klebsiella pneumoniae Using the Double-Layer Agar Method ]]>
<![CDATA[Aminah, Aminah]]>;
<![CDATA[Trisna, Citra]]>;
<![CDATA[Sugianto, Fitri Alina]]>;
<![CDATA[Amalia, Gadis]]>;
<![CDATA[Martiningsih, M Atik]]>;
<![CDATA[Faruq, Zulfikar Husni]]>
<![CDATA[ Jurnal Teknokes Vol. 18 No. 4 (2025): Desember ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia ]]>
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DOI: 10.35882/jteknokes.v18i4.113
<![CDATA[Antimicrobial resistance is a growing global health threat and is projected to cause up to 10 million deaths per year by 2050. Klebsiella pneumoniae is a priority pathogen due to its multidrug resistance (MDR) mechanisms, such as extended-spectrum β-lactamases and carbapenemases, which significantly limit therapeutic options and increase the need for antimicrobial alternatives. This study aimed to isolate and quantify active lytic bacteriophages capable of infecting clinical MDR K. pneumoniae from river water samples. Water samples were processed by centrifugation and membrane filtration to remove debris and bacterial cells, then incubated with MDR K. pneumoniae in Luria broth at 37°C to enhance phage adsorption and amplification. Phage detection and enumeration were performed using the double-layer agar method. Plaque morphology was observed to confirm lytic activity, while serial dilutions were used to determine phage titer. Several lytic bacteriophages were successfully isolated from river water samples. The plaques formed were clear, spherical, and well-defined, with some exhibiting halos indicative of possible depolymerase activity. Phage titers ranged from 1.28 × 10³ to 2.00 × 10⁶ PFU/mL, indicating efficient replication against MDR K. pneumoniae without repeated enrichment processes. River water is a potential source of lytic bacteriophages capable of infecting MDR K. pneumoniae. These findings emphasize the role of aquatic environments as natural reservoirs of phages with potential use in the development of future antimicrobial or biocontrol strategies and support the need for further studies on the host range, stability, and therapeutic applications of the isolated phages.]]>
<![CDATA[Analyzing the Sociodemographic and Psychological Factors Influencing the Intention to Consume Single-Use Plastics Among University Students: A Cross-Sectional Quantitative Study ]]>
<![CDATA[Harahap, Alprida]]>;
<![CDATA[Adi Antoni]]>;
<![CDATA[Haslinah Ahmad]]>;
<![CDATA[Anton J. Hadi]]>;
<![CDATA[Nanda Masraini Daulay]]>
<![CDATA[ Jurnal Teknokes Vol. 18 No. 4 (2025): Desember ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia ]]>
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DOI: 10.35882/jteknokes.v18i4.116
<![CDATA[The rising use of disposable plastics among Indonesian university students contributes to the growing problem of plastic waste, making it essential to understand the factors shaping their intentions to use single-use plastics. This research aims to determine the impact of sociodemographic factors (age, education level, and economic status) and psychological factors (subjective norms, emotional motivation, and beliefs) on the intention to use disposable plastic among university students. The study contributes by integrating the Theory of Planned Behaviour (TPB) and the Value-Belief-Norm (VBN) Theory to explain the intention to consume single-use plastics in the Indonesian context, identifying the belief variable as the most dominant factor influencing behavioral intention. The research employed a quantitative descriptive-analytical approach with a cross-sectional design, conducted from April to June 2024. A total of 125 respondents were selected using purposive sampling. Data were collected through questionnaires developed based on the TPB and VBN frameworks, then analyzed using descriptive statistical tests and multivariate logistic regression to identify significant predictors of behavioral intention. The results show that sociodemographic factors, age (p = 0.002), education level (p = 0.000), and economic status (p = 0.000), significantly influence the intention to consume disposable plastics. Likewise, psychological factors, subjective norms (p = 0.001), emotional motivation (p = 0.000), and beliefs (p = 0.000), also have a significant effect, with beliefs emerging as the most dominant factor (Exp(B) = 10.234). The study implies that efforts to reduce single-use plastic consumption among university students should focus on strengthening environmental education and transforming social norms to foster sustainable behaviors. Furthermore, future research with longitudinal designs and broader populations is recommended to enhance the generalizability of these findings.]]>
<![CDATA[Health Information Technology Management Model to Improve User Performance and Satisfaction ]]>
<![CDATA[yuniati, Nining]]>;
<![CDATA[Nugroho, Agung Yuliyanto]]>
<![CDATA[ Jurnal Teknokes Vol. 18 No. 4 (2025): Desember ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia ]]>
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DOI: 10.35882/jteknokes.v18i4.123
<![CDATA[The rapid development of digital technology has reshaped the way healthcare institutions manage information, deliver services, and support clinical decisions. Despite these advances, many hospitals still struggle with inefficiencies resulting from weak Health Information Technology (HIT) governance and limited user skills. Most existing approaches prioritize technical deployment while paying less attention to managerial, organizational, and behavioral factors that are essential for sustainable success. To overcome these limitations, this study introduces and empirically evaluates a comprehensive Health Information Technology Management (HITM) model that combines strategic IT governance, system quality, and user dimensions to improve satisfaction and performance among healthcare professionals. The research examines how governance mechanisms, system quality, and user capabilities affect satisfaction and performance. The specific objectives are to identify the key drivers of system quality, evaluate the relationship between system quality and user satisfaction, and examine how satisfaction impacts user performance. The study contributes theoretically by presenting a more integrated framework that unites concepts from IT governance, Information Systems Success Theory, and Technology Acceptance Theory. It also offers empirical evidence of the importance of managerial structures in driving successful digital transformation in healthcare settings. A survey involving healthcare personnel from three public hospitals in Indonesia was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results demonstrate strong model validity, accounting for 65% of the variance in user satisfaction and 59% of the variance in performance, with predictive relevance (Q²) values of 0.47 and 0.52, respectively. These outcomes demonstrate that mature governance, leadership support, cross-unit collaboration, and systematic user training enhance system quality, satisfaction, and ultimately performance. Future studies should expand testing in broader healthcare contexts with different resource conditions.]]>
<![CDATA[Vision Transformer Enhanced by Contrastive Learning: A Self-Supervised Strategy for Pulmonary Tuberculosis Diagnosis ]]>
<![CDATA[Marlina, Widia]]>;
<![CDATA[Zaky, Umar]]>
<![CDATA[ Jurnal Teknokes Vol. 18 No. 4 (2025): Desember ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia ]]>
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DOI: 10.35882/jteknokes.v18i4.126
<![CDATA[Tuberculosis (TB) diagnosis from Chest X-ray (CXR) images poses a significant challenge in radiology due to the inherent data imbalance and subtle lesion heterogeneity. These factors cause traditional deep learning models, like standard CNNs and conventional Vision Transformers (ViT), to exhibit poor generalization and inadequate sensitivity (recall) for the minority TB class. We address this critical research gap by introducing a novel methodology, an enhanced ViT architecture that leverages Self-Supervised Learning (SSL) via the SimCLR framework, subsequently optimized with an Adaptive Weighted Focal Loss. Our primary objective was to develop a generalizable model that minimizes false negatives without sacrificing overall precision, thereby establishing a new performance benchmark for automated TB detection. The methodology conceptually separates feature learning from SSL pre-training on unlabeled data to generate robust and domain-invariant features, distinct from classification optimization. Adaptive Weighted Focal Loss is employed during fine-tuning to counter majority class gradient dominance mechanistically. We validated this approach using K-Fold Cross-Validation. The final ViT SSL Weighted model achieved a peak internal accuracy of 0.9861 and an AUPRC of 0.9781. Crucially, it maintained generalization stability when externally tested on the TBX11K dataset, securing an AUPRC of 0.9795 and a high recall of 0.9527. This minimal variance strongly confirms the reproducibility and robustness of our features against institutional variation. The resulting high recall directly translates to enhanced diagnostic decision-making, significantly lowering the clinical risk associated with a missed TB diagnosis. This study establishes an effective, stable, and generalizable SSL-based ViT framework, offering a scalable solution for public health efforts in resource-constrained settings.]]>
<![CDATA[Development and Usability Evaluation of the "Si BINTANG" Audiovisual Web Application for Integrated Child Growth and Development Monitoring ]]>
<![CDATA[Sofia, Norlaila]]>;
<![CDATA[Hapisah]]>;
<![CDATA[Noor Adha Aprilea]]>;
<![CDATA[Rusmilawaty]]>;
<![CDATA[Yuniarti]]>;
<![CDATA[Zakiah]]>
<![CDATA[ Jurnal Teknokes Vol. 18 No. 4 (2025): Desember ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia ]]>
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DOI: 10.35882/jteknokes.v18i4.127
<![CDATA[Indonesia’s child growth monitoring system, essential for national stunting prevention, still relies on paper-based tools such as the Child Health Card (KMS), which often face challenges of low parental engagement, fragmented data management, and limited health literacy. Existing digital applications primarily function as data logbooks, lacking interactive audiovisual content that can effectively support parents with diverse literacy levels and learning needs. This gap highlights the urgency for innovative health communication strategies that bridge conventional and digital media to enhance participatory learning and improve community-based child monitoring practices. This study developed and evaluated Si BINTANG (Interactive Barcode-Based Growth and Development Information System). This hybrid audiovisual web platform connects a printed child monitoring book with digital content through QR code technology. The application was designed using a user-centered and health communication approach to enhance parental understanding, motivation, and engagement in monitoring their child's growth and development. A preliminary usability evaluation involving experts and mothers of children under five indicated high system quality, usability, and user acceptance, demonstrating positive responses across functionality, accessibility, and user satisfaction. These results suggest that hybrid digital–print integration can enhance health education by making it more interactive, inclusive, and accessible for families, particularly in low-literacy or resource-limited settings. While the findings show encouraging potential, this study acknowledges several limitations, including the small and localized sample size. Future research will focus on large-scale implementation and impact assessment on parental knowledge, behavioral change, and child health outcomes. The Si BINTANG platform represents a promising direction for strengthening family-based stunting prevention through hybrid digital innovation, contributing to Indonesia’s ongoing digital health transformation and community empowerment agenda.]]>
<![CDATA[Development of an Android-based Stroke Prevention Application ]]>
<![CDATA[Rizani, Khairir]]>;
<![CDATA[Sofia, Norlaila]]>;
<![CDATA[Fratama, Ferry Fadli]]>;
<![CDATA[Imanuddin, M. Rizki]]>
<![CDATA[ Jurnal Teknokes Vol. 18 No. 4 (2025): Desember ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia ]]>
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DOI: 10.35882/jteknokes.v18i4.130
<![CDATA[Stroke remains a significant public health problem in Indonesia, with a prevalence of 8.3 per 1,000 population and a significant contribution to disability and mortality. Limited community health literacy and underutilization of digital health media indicate the need for accessible technology-based stroke prevention interventions. This study aimed to develop and validate a community-oriented Android-based application for stroke prevention using an ADDIE-based Research and Development framework. This study contributes a validated mobile health intervention for community stroke prevention and a replicable development model adaptable to other non-communicable disease prevention programs. The development process included application design, feature and database construction, internal testing, expert validation, and small-group usability testing. experts. Media validation involved three instructional technology experts. A small-group usability test was conducted with 15 adult community members in Banjar Regency, selected through convenience sampling. Data were analyzed using descriptive statistics and feasibility classification. The application obtained a mean score of 4.7 from material experts and 4.9 from media experts, indicating a “Highly Feasible” classification. Usability testing showed an overall mean score of 16.8 out of 20, reflecting strong user acceptance. This study is limited by its small sample size and short-term evaluation without behavioral or clinical outcome assessment. Nevertheless, the application shows potential as a digital health education tool to improve stroke prevention literacy and support community-based prevention programs and national digital health strategies.]]>
<![CDATA[Embedded Machine Learning on ESP32 for Upper-Limb Exoskeletons Based on EMG ]]>
<![CDATA[Triwiyanto, Triwiyanto]]>;
<![CDATA[Maghfiroh, Anita Miftahul]]>;
<![CDATA[Forra Wakidi, Levana]]>;
<![CDATA[Dita Musvika, Syevana]]>;
<![CDATA[Utomo, Bedjo]]>;
<![CDATA[Sumber, Sumber]]>;
<![CDATA[Caesarendra, Wahyu]]>
<![CDATA[ Jurnal Teknokes Vol. 18 No. 4 (2025): Desember ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia ]]>
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DOI: 10.35882/jteknokes.v18i4.134
<![CDATA[Stroke remains one of the primary causes of long-term disability worldwide and frequently results in persistent impairment of upper limb motor function. To support more effective and intensive rehabilitation, there is a need for wearable devices that can interpret muscle activity and autonomously assist limb movement without relying on an external computer. This study aims to design and implement an upper-limb rehabilitation exoskeleton that is driven by electromyography (EMG) signal classification using machine learning and by real-time elbow angle monitoring, with all models deployed directly on an ESP32 microcontroller. The proposed exoskeleton is built from lightweight, ergonomic 3D-printed components and operates in both unilateral and bilateral modes. Its main contributions include: (1) embedding real-time EMG classification models on the ESP32 so that the device can function independently, (2) integrating EMG-based motor control with elbow angle feedback from an MPU6050 inertial measurement unit, and (3) incorporating a load cell to estimate biceps force during training. EMG signals from the forearm flexor muscles are processed to extract statistical features such as variance (VAR), waveform length (WL), integrated EMG (IEMG), and root mean square (RMS). These features are used to train Random Forest, Decision Tree, Support Vector Machine (SVM), and XGBoost classifiers. The trained models are converted to C code using the micromlgen library for execution on the ESP32. System evaluation involved thirty male participants aged 20–25 years with body weights between 50–85 kg. All tested models achieved 100% accuracy in distinguishing relaxed versus grasping muscle contractions, while the correlation of elbow angles between unilateral and bilateral ESP32 systems reached 0.9469, indicating highly consistent motion detection. The Decision Tree model was selected for deployment due to its superior memory efficiency on the microcontroller. These results demonstrate that the developed ESP32-based exoskeleton provides a practical, efficient, and easily integrable solution for wearable stroke rehabilitation]]>
