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Attendance management is an essential component in educational institutions, companies, and organizations to monitor the presence and punctuality of participants. Traditional attendance systems, such as manual signatures or identification cards, are prone to various issues including human error, time inefficiency, and identity fraud. To address these challenges, this study aims to develop a smart attendance system using facial recognition technology based on Python and the OpenCV library. The system is designed to automatically detect and recognize faces in real time using a webcam or camera module. It employs computer vision techniques to capture facial images, extract unique features, and match them against a stored database of registered participants. Once the face is verified, the system records the attendance along with a timestamp, ensuring data accuracy and security. The development process involved several stages, including image acquisition, preprocessing, feature extraction, and classification. OpenCV was utilized for image processing tasks, while Python provided the programming framework to integrate all components. To enhance recognition accuracy, the system applied techniques such as histogram equalization for lighting normalization and Haar Cascade classifiers for initial face detection. An experimental evaluation was conducted under various conditions, including different lighting environments and facial orientations. The results demonstrated that the system achieved an accuracy rate of 96% under normal lighting conditions, with only a small decrease in performance under dim or uneven lighting. These findings indicate that the system is reliable for practical applications, especially in controlled environments. Conclusion: The Python-based facial recognition attendance system offers a more efficient, secure, and accurate alternative to conventional attendance methods. Future improvements may include the integration of deep learning models to enhance recognition robustness in diverse real-world scenarios.

Attendance management is an essential component in educational institutions, companies, and organizations to monitor the presence and punctuality of participants. Traditional attendance systems, such as manual signatures or identification cards, are prone to various issues including human error, time inefficiency, and identity fraud. To address these challenges, this study aims to develop a smart attendance system using facial recognition technology based on Python and the OpenCV library. The system is designed to automatically detect and recognize faces in real time using a webcam or camera module. It employs computer vision techniques to capture facial images, extract unique features, and match them against a stored database of registered participants. Once the face is verified, the system records the attendance along with a timestamp, ensuring data accuracy and security. The development process involved several stages, including image acquisition, preprocessing, feature extraction, and classification. OpenCV was utilized for image processing tasks, while Python provided the programming framework to integrate all components. To enhance recognition accuracy, the system applied techniques such as histogram equalization for lighting normalization and Haar Cascade classifiers for initial face detection. An experimental evaluation was conducted under various conditions, including different lighting environments and facial orientations. The results demonstrated that the system achieved an accuracy rate of 96% under normal lighting conditions, with only a small decrease in performance under dim or uneven lighting. These findings indicate that the system is reliable for practical applications, especially in controlled environments. Conclusion: The Python-based facial recognition attendance system offers a more efficient, secure, and accurate alternative to conventional attendance methods. Future improvements may include the integration of deep learning models to enhance recognition robustness in diverse real-world scenarios.

The implementation of digital medical records in Indonesian hospitals faces various challenges, especially in terms of technological readiness, inadequate regulations, and data security threats that need to be addressed to ensure efficient and safe healthcare services. This study aims to identify the challenges in Digital Medical Record Implementation from the perspective of technology, regulation, and data security. This study used a systematic literature review research approach guided by the Preferred Reposrting Items for Systematic Review and Meta-Analysis (PRISMA). The results showed that the implementation of digital medical records in Indonesian hospitals faces considerable challenges from three main perspectives, namely technology, regulation, and data security. The technology perspective includes several challenges such as 1) System Interoperability, 2) Privacy, 3) IT Infrastructure Limitations, 4) Implementation Costs and 5) Maintenance and Technology Adoption by Medical Staff. The regulatory perspective includes challenges such as 1) Regulatory Compliance, 2) Patient Data Protection, 3) Validity of Medical Records, 4) Long-term Data Retention and 5) System Interoperability. The data security perspective includes challenges such as 1) Infrastructure Security, 2) Data Encryption, 3) Access Control, 4) Incident Response and 5) Regular Security Audits.  Thus, collaborative efforts between the government, hospitals and technology providers are needed to address these challenges and drive safe and effective digital transformation in Indonesia's healthcare sector.

The implementation of digital medical records in Indonesian hospitals faces various challenges, especially in terms of technological readiness, inadequate regulations, and data security threats that need to be addressed to ensure efficient and safe healthcare services. This study aims to identify the challenges in Digital Medical Record Implementation from the perspective of technology, regulation, and data security. This study used a systematic literature review research approach guided by the Preferred Reposrting Items for Systematic Review and Meta-Analysis (PRISMA). The results showed that the implementation of digital medical records in Indonesian hospitals faces considerable challenges from three main perspectives, namely technology, regulation, and data security. The technology perspective includes several challenges such as 1) System Interoperability, 2) Privacy, 3) IT Infrastructure Limitations, 4) Implementation Costs and 5) Maintenance and Technology Adoption by Medical Staff. The regulatory perspective includes challenges such as 1) Regulatory Compliance, 2) Patient Data Protection, 3) Validity of Medical Records, 4) Long-term Data Retention and 5) System Interoperability. The data security perspective includes challenges such as 1) Infrastructure Security, 2) Data Encryption, 3) Access Control, 4) Incident Response and 5) Regular Security Audits.  Thus, collaborative efforts between the government, hospitals and technology providers are needed to address these challenges and drive safe and effective digital transformation in Indonesia's healthcare sector.

Introduction: Needle procedures are common actions that are often encountered in emergencies. Emergency Departement (ED) with high workloads sometimes needle procedures are performed by force, thus causing uncontrolled pain, long-term negative psychological disorder, impairing physical evaluation and clinical outcome. The purpose of this review is to identify nursing intervention to reduce pediatric pain in needle procedures in ED. Methods: The literature search used the PubMed database with the keywords: nursing intervention, pain, needle procedures or injection and emergency department. Article criteria: 1) full text, 2) published in the 2016-2020 period, 3) employing Randomized Controlled Trial (RCT) research design, and 4) respondents aged 3-13 years old. Analysis of the quality of articles using the Critical Appraisal Skills Programme (CASP) and Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA). Result: 171 articles identified. Based on criteria and quality assessment of articles as many as 6 articles reviewed with focus intervention: virtual reality, parental presence, buzzy aplication, ditto aplication, humanoid robot and listening music. Conclusion: Nurses can use these interventions in the nursing care to reduce pediatric pain during needle procedures in ED.

Introduction: Needle procedures are common actions that are often encountered in emergencies. Emergency Departement (ED) with high workloads sometimes needle procedures are performed by force, thus causing uncontrolled pain, long-term negative psychological disorder, impairing physical evaluation and clinical outcome. The purpose of this review is to identify nursing intervention to reduce pediatric pain in needle procedures in ED. Methods: The literature search used the PubMed database with the keywords: nursing intervention, pain, needle procedures or injection and emergency department. Article criteria: 1) full text, 2) published in the 2016-2020 period, 3) employing Randomized Controlled Trial (RCT) research design, and 4) respondents aged 3-13 years old. Analysis of the quality of articles using the Critical Appraisal Skills Programme (CASP) and Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA). Result: 171 articles identified. Based on criteria and quality assessment of articles as many as 6 articles reviewed with focus intervention: virtual reality, parental presence, buzzy aplication, ditto aplication, humanoid robot and listening music. Conclusion: Nurses can use these interventions in the nursing care to reduce pediatric pain during needle procedures in ED.

Cloud computing has revolutionized data storage and management; however, security and privacy concerns remain critical challenges. This paper explores the integration of blockchain technology to enhance data security in cloud environments. A decentralized approach ensures data integrity, authentication, and tamper resistance. The proposed framework leverages smart contracts to enforce access control policies efficiently. Simulation results indicate that our model significantly improves data security without compromising system performance.

Cloud computing has revolutionized data storage and management; however, security and privacy concerns remain critical challenges. This paper explores the integration of blockchain technology to enhance data security in cloud environments. A decentralized approach ensures data integrity, authentication, and tamper resistance. The proposed framework leverages smart contracts to enforce access control policies efficiently. Simulation results indicate that our model significantly improves data security without compromising system performance.

The COVID-19 pandemic is becoming an international threat. In order to overcome this, the Indonesian government has implemented a social distancing policy. However, the realization of the policies that exist to date has not run uniformly in relation to social distancing and social assistance that has not been received directly by the community. Therefore it is necessary to control the implementation process of policies that have been issued by the Government. This research is a normative legal research and empirical law with a normative juridical approach. The data obtained in this research is in the form of literature study and interviews. The data that has been collected is then presented in the form of descriptions which are arranged systematically following the flow of systematic discussion.

The COVID-19 pandemic is becoming an international threat. In order to overcome this, the Indonesian government has implemented a social distancing policy. However, the realization of the policies that exist to date has not run uniformly in relation to social distancing and social assistance that has not been received directly by the community. Therefore it is necessary to control the implementation process of policies that have been issued by the Government. This research is a normative legal research and empirical law with a normative juridical approach. The data obtained in this research is in the form of literature study and interviews. The data that has been collected is then presented in the form of descriptions which are arranged systematically following the flow of systematic discussion.