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.
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<![CDATA[Effectiveness of Specialized Cervical Collars in Reducing Pain Associated with Cervical Syndrome among Computer Workers ]]>
<![CDATA[zubaidi, Alfan]]>;
<![CDATA[Suprayogi, Dody]]>;
<![CDATA[akbar, Muh Syaiful]]>
<![CDATA[ Jurnal Teknokes Vol. 18 No. 2 (2025): June ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia ]]>
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<![CDATA[Cervical syndrome is a prevalent musculoskeletal disorder among computer workers, primarily caused by prolonged static postures and poor ergonomic practices. It leads to chronic neck pain, muscle stiffness, and reduced work productivity. Addressing this issue, ergonomic interventions such as specialized cervical collars can help mitigate discomfort and prevent further complications. This study aims to evaluate the effectiveness of a customized cervical collar in reducing neck pain among computer workers in Karanganyar Regency. Specifically, it investigates whether a specially designed collar provides more effective pain relief compared to commercially available collars. This study contributes to occupational health by proposing an ergonomic intervention that may improve the well-being of computer workers. It highlights the potential benefits of personalized cervical support, which may influence workplace ergonomic policies and musculoskeletal disorder prevention strategies. A pre- and post-test experimental design was used to assess pain reduction using the Visual Analog Scale (VAS). The study involved 80 computer workers diagnosed with cervical syndrome. Participants underwent a baseline pain assessment using the VAS before the intervention. The intervention group used a customized cervical collar, while the control group used a standard commercial collar. Pain levels were reassessed after a specified intervention period. Data were analyzed using paired t-tests to evaluate the significance of pain reduction, with additional correlation analysis conducted to examine relationships between pre- and post-intervention scores. The findings revealed a significant reduction in neck pain within the intervention group. The mean pain score decreased from 4.29 to 2.25 (p < 0.001), with a large effect size (Cohen’s d = 2.401). Correlation analysis showed a meaningful relationship (r = 0.292, p = 0.009) between pre- and post-intervention pain levels, confirming the effectiveness of the customized cervical collar. This study demonstrates that a customized cervical collar is highly effective in reducing neck pain among computer workers. These results support its use as an ergonomic intervention for preventing work-related musculoskeletal disorders. Future research should explore long-term benefits and compliance rates in various occupational settings.]]>
<![CDATA[Digital Innovation for Monitoring the Mental Health of Students at UPN "Veteran" East Java Using the PHQ-9 Instrument ]]>
<![CDATA[maulana, Hendra]]>;
<![CDATA[Citra, Delia]]>;
<![CDATA[Sari, Lintang]]>;
<![CDATA[Safana, Tsabita]]>;
<![CDATA[Aprilia, Erica]]>
<![CDATA[ Jurnal Teknokes Vol. 18 No. 2 (2025): June ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia ]]>
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<![CDATA[Mental health issues, especially depression, are increasingly prevalent among university students in Indonesia, primarily due to academic, social, and emotional pressures during the transition from adolescence to adulthood. This study developed and evaluated UWAYS, a mobile application designed to assist the early detection of depressive symptoms using the Patient Health Questionnaire-9 (PHQ-9). The app features include an interactive PHQ-9 self-assessment, historical tracking of assessment results, and automatic initial recommendations based on score classifications. Involving 100 active students of UPN “Veteran” East Java, the results showed that most participants fell within the mild to moderate depression categories, with sleep disturbance and low self-confidence as the most common symptoms. The System Usability Scale (SUS) assessment yielded an average score of 77.3, indicating good usability and positive user acceptance. These findings confirm that UWAYS provides an accessible, practical, and user-friendly tool for independent mental health screening among students. This application serves as an initial step to support mental health management in the campus environment and offers potential for further integration with university counseling services. The study also highlights that the lack of early detection mechanisms on campus remains a gap that can be addressed through digital innovation like UWAYS, which combines scientific accuracy, data confidentiality, and ease of use to encourage proactive mental health awareness among students.]]>
<![CDATA[Evaluating the Reliability of SpO₂ and BPM Readings in Commercial Smartwatches Compared to a Standard Oximeter ]]>
<![CDATA[Wibowo, Kusnanto Mukti]]>;
<![CDATA[Royan, Royan]]>;
<![CDATA[Latif, Abdul]]>;
<![CDATA[Susanto, Fani]]>;
<![CDATA[Fatiatun, Fatiatun]]>;
<![CDATA[Irmawanto, Rudi]]>;
<![CDATA[Che Ani, Norhidayah]]>
<![CDATA[ Jurnal Teknokes Vol. 18 No. 2 (2025): June ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia ]]>
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<![CDATA[The advancement of wearable technology has enabled commercial smartwatches to monitor vital health parameters such as blood oxygen saturation (SpO₂) and heart rate (BPM). This study aimed to evaluate the accuracy of SpO₂ and BPM readings from three commercial smartwatches: Realme C2 Pro, Oraimo 2 Plus OSW-32N, and Haylou LS02 Pro by comparing them to a standard medical-grade oximeter (Beurer PO40). A total of 34 participants were recruited, representing a range of skin tones identified using the Fitzpatrick Skin Type Scale (Types I–V). Statistical analyses, including Pearson’s correlation and Bland-Altman plots, were used to assess the relationship and agreement between devices. Results showed that the Realme C2 Pro provided the highest accuracy, with 99.58% for SpO₂ and 98.515% for BPM, while the Haylou LS02 Pro showed the lowest accuracy at 99.24% for SpO₂ and 97.29% for BPM. Bland-Altman analysis revealed small biases and narrow limits of agreement, indicating that the smartwatches produced readings closely aligned with those of the medical device. Despite minor discrepancies, all smartwatches demonstrated strong potential for health monitoring applications. The discussion highlights factors influencing measurement accuracy, including sensor quality, algorithm performance, and user-specific variables such as skin tone. These findings support the role of smartwatches as accessible tools for early health detection and continuous monitoring. Although not intended to replace clinical instruments, properly optimized smartwatches can complement healthcare systems by enabling timely interventions and enhancing disease management.]]>
<![CDATA[AI-Powered Holter for Affordable and Accurate Arrhythmia Detection ]]>
<![CDATA[Nyatte, Steyve]]>;
<![CDATA[Leatitia, Guiadem]]>;
<![CDATA[steve, Perabi]]>;
<![CDATA[Essiane, Ndjakomo]]>
<![CDATA[ Jurnal Teknokes Vol. 18 No. 2 (2025): June ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia ]]>
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<![CDATA[Cardiac arrhythmias pose significant health risks, and current detection systems often suffer from high costs and limited accessibility, particularly in resource-constrained settings. This research aimed to develop a portable, cost-effective Holter monitoring device for accurate arrhythmia detection using machine learning. By combining an inexpensive ESP32 microcontroller with an AD8232 ECG sensor, a data acquisition system was built. Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Multilayer Perceptron (MLP) models were trained and evaluated for arrhythmia classification. The SVM model achieved the highest accuracy (78.53%) using a linear kernel and features selected by a random forest algorithm. While KNN and MLP also showed promise, the results emphasized the importance of hyperparameter tuning and feature selection. This research demonstrated the feasibility of creating an affordable and intelligent Holter device capable of effective arrhythmia detection, potentially increasing access to cardiac monitoring and enabling early diagnosis in resource-limited environments.]]>
<![CDATA[ANALYSIS OF THE DISTRIBUTION PATTERN OF TUBERCULOSIS (TB) INCIDENCE IN THE WORKING AREA OF MUARA BELITI HEALTH CENTER, MUSI RAWAS DISTRICT, 2025 ]]>
<![CDATA[Chandra, Pendana]]>;
<![CDATA[Wahyudi, Arie]]>;
<![CDATA[Prima Cakra, Muhammad]]>
<![CDATA[ Jurnal Teknokes Vol. 18 No. 2 (2025): June ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia ]]>
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<![CDATA[Tuberculosis (TB) impacts not only physical health but also psychological and economic aspects of individuals and their families. In 2020, global TB-related deaths reached 1.3 million, marking the first annual increase since 2005. Indonesia ranks third globally with a high TB burden, with cases increasing from 724,309 in 2022 to 821,200 in 2023. Similar trends are observed in South Sumatra and the Muara Beliti Health Center's working area, with cases rising from 27 in 2022 to 42 in 2024, highlighting the urgent need for effective TB control strategies. This study aims to analyze the spatial patterns of TB risk in Muara Beliti District, Musi Rawas Regency in 2025 using the Analytic Hierarchy Process (AHP) and Inverse Distance Weighting (IDW) spatial interpolation methods. A key contribution is the integration of behavioral and environmental factors with spatial analysis, allowing for more targeted intervention planning. Using Geographic Information Systems (GIS), this analysis provides accurate insights into high-risk areas, enabling efficient mitigation. The descriptive quantitative method used includes patient characteristic data and coordinates, AHP risk variable weighting, and TB risk pattern visualization using IDW. Results indicate that areas with low contour values (0.5–0.5912) represent high TB risk zones, particularly around Air Lesing, Ketuan Jaya, south of Durian Remuk, and Muara Beliti Baru. Areas with higher contour values (0.786–1) are at lower risk, mostly located in agricultural or sparsely populated regions. Risk maps supported by satellite imagery show TB concentrations in residential areas with poor ventilation and sanitation. In conclusion, the combination of AHP and IDW is effective in identifying spatial TB risk patterns and aiding in the design of focused interventions. Adjusting strategies based on local contexts is crucial. Further studies with broader coverage and additional variables are recommended to enhance the validity and effectiveness of TB control efforts.]]>
<![CDATA[An IoT-Based Framework for Real-Time Monitoring and Evaluation of Child Growth to Support Indonesia’s Stunting Reduction Initiative ]]>
<![CDATA[Andri Ulus Rahayu]]>;
<![CDATA[Taufiqurrahman, Imam]]>;
<![CDATA[Arie Gustaman, Rian]]>;
<![CDATA[Fittur Farabi Sanaz]]>
<![CDATA[ Jurnal Teknokes Vol. 18 No. 2 (2025): June ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia ]]>
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<![CDATA[Stunting remains a significant public health concern in Indonesia, leading to lifelong developmental and economic disadvantages. This study aims to address limitations in conventional child growth monitoring by developing and validating an IoT-based system that integrates ultrasonic and load cell sensors, an ESP32 microcontroller, RFID identification, and cloud-based data management. The system enables automated, real-time measurement and digital record-keeping, accessible via a user-friendly dashboard. Empirical validation was conducted on 35 children at local Integrated Health Service Post (Posyandu), showing high measurement accuracy (±0.53 cm for height, ±0.08 kg for weight), rapid average data transmission (2.05 seconds), and strong agreement with manual gold standards (p > 0.05). Usability evaluations indicated high satisfaction among health cadres, with streamlined workflows reducing time and staff requirements. The findings demonstrate that the proposed IoT-based system offers an effective, scalable, and economically viable solution for improving child growth monitoring and supporting stunting prevention programs in community health settings.]]>
