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This study aims to analyze the implementation of good governance principles in digital population administration services in Medan Marelan Subdistrict from the perspective of Administrative Law. The background of this research is based on the importance of digital transformation in public services through the Electronic-Based Government System (SPBE) to enhance transparency, accountability, effectiveness, and efficiency. However, in practice, several obstacles are still encountered, such as limited infrastructure, network disruptions, and limited human resources. This research employs an empirical legal research method with both empirical and statutory approaches. Data were collected through field research, including interviews with subdistrict officials and the community, as well as library research involving laws, regulations, and relevant literature. The data were analyzed qualitatively to examine the conformity between the implementation of services and the principles of good governance and general principles of good administration (AUPB). The results show that the implementation of good governance principles in digital population services in Medan Marelan Subdistrict has not been fully optimal. This is indicated by challenges in information transparency, system effectiveness, and limitations in human resources and infrastructure. Nevertheless, digital services have provided convenience for the community in accessing population administration services. In conclusion, improvements in human resources quality, technological infrastructure, and the strengthening of supervision and evaluation mechanisms are necessary to achieve public services that align with good governance principles.

Magelang City faces the challenge of limited land availability, with a total area of only 18.58 km2 and a high population density. Consequently, telecommunications infrastructure development requires a precise strategy. This study aims to analyze the business model and investment feasibility of Pole and Greenfield type telecommunication towers in Magelang City. Using a descriptive quantitative approach, this research processes secondary data from PT Dayamitra Telekomunikasi Indonesia by applying feasibility analysis based on Life Cycle Costing (LCC), Net Present Value (NPV), Internal Rate of Return (IRR), Break-Even Point (BEP), Payback Period (PP), and Benefit-Cost Ratio (BCR). The results indicate significant differences in cost structures; Pole towers proved to be more efficient, requiring an initial capital outlay of only 28.8% of the total capital required for Greenfield towers. Greenfield towers generated an NPV of Rp13.07 billion with an IRR of 20%, while Pole towers generated an NPV of Rp2.46 billion with a higher IRR of 23%. Pole towers have proven to offer a faster return on investment and better operational cost efficiency, making them the most strategic option to support network densification and the implementation of 5G technology in urban areas with spatial constraints like Magelang City.

Post-disaster settlement recovery requires more than the provision of permanent housing; it demands an integrated approach covering social, economic, institutional, environmental, and disaster risk reduction dimensions. This study analyzes the Settlement Planning Document (RPP) of the Sibalaya Selatan Satellite Permanent Resettlement Area (Huntap) in Sigi Regency, Central Sulawesi, which accommodates 118 households displaced by the 2018 Palu liquefaction disaster. The research examines the RPP as a participatory planning instrument for sustainable post-disaster recovery. A qualitative participatory approach using the Community Action Plan (CAP) method was conducted from July to November 2024 through focus group discussions, participatory workshops, formation of a Core Planning Team (TIP), field observations, document reviews, and public consultations. Data were analyzed using descriptive, infrastructure, spatial, and strengths-problems-opportunities-challenges frameworks. The findings reveal that community social capital, reflected in active organizations, social networks, and digital communication infrastructure, has been transformed into economic capital. In addition, four dimensions of community resilience economic, social, communication, and competence capacities were identified at varying levels of development. The TIP also played a strategic role in integrating the RPP into village and regional development planning. The resulting RPP contains 39 priority programs valued at approximately IDR 340.6 million for 2024-2028 across infrastructure, economic, social-environmental, and disaster risk reduction sectors. The study demonstrates that the CAP approach effectively supports sustainable settlement development and offers a replicable model for post-disaster resettlement areas in Indonesia.

This study investigates the performance of Internet of Things (IoT)-based monitoring systems using a mobile hotspot and IoT sensors for temperature and humidity data transmission. The research is based on the IoT concept, which enables electronic devices to communicate and exchange data through internet networks without direct human intervention. System performance was evaluated using standard Quality of Service (QoS) parameters, including throughput, packet loss, delay, and jitter. The experimental setup utilized a NodeMCU ESP32 microcontroller and a DHT22 sensor, with measurements conducted at various transmission distances through wireless communication media. The objective was to determine the reliability of hotspot connectivity and sensor communication in supporting IoT applications. The results indicate that the optimal performance was achieved at a distance of 20 meters using a 40-lambda variation. Furthermore, the communication signal between the ESP32 device and the mobile hotspot remained detectable up to a maximum distance of 32 meters. These findings demonstrate the effectiveness of the proposed IoT system for environmental monitoring applications within specific transmission ranges.

This study discusses a student concentration detection system using Convolutional Neural Network (CNN) with the MobileNetV2 architecture. The dataset was adapted from Classroom Student Behaviors and mapped into four concentration categories: highly focused, focused, less focused, and unfocused. The system was tested with a 720p webcam and produced real-time detection data. The evaluation results show an overall accuracy of 75.85%, with the highest precision achieved in the focused class (0.9859) and the highest recall in the highly focused (0.9739) and unfocused (0.9811) classes. The confusion matrix indicates that the focused class was detected most consistently, while highly focused and unfocused classes were often misclassified as focused, resulting in lower precision. In real-time testing, the system operated at an average of 7 FPS and worked optimally when students faced the camera directly with sufficient lighting, but its performance decreased significantly at face angles greater than 45°. User evaluation shows that 75% of students rated the detection results as accurate/very accurate with an average satisfaction score of 3.6 out of 5, and 75% felt assisted in recognizing their concentration level. From the teachers’ perspective, most stated that the results were consistent with classroom observations, and all expressed willingness to reuse the system.

SR12 Herbal Cosmetics is a company engaged in the field of herbal and skin care. Founded in 2015 byToni Firmansyah, S. Farm., Apt. and Asrianty Salam, Farm. This company has a vision to provide benefits to many people through the herbal and skin care products they produce. SR12 Herbal Cosmetics products are formulated based on research from certified scientists, and have been tested at the Sucofindo Laboratory, are free of mercury and hydroquinone, and have been registered with the Indonesian Food and Drug Supervisory Agency (BPOM RI). SR12 Herbal Cosmetics has several factories in West Java Province and has an extensive distribution network with hundreds of distributors and tens of thousands of partners throughout Indonesia. The goal to be achieved is to produce a management information system model including a management information system for PT SR12 Herbal Cosmetics. The research object chosen is a company in the field of cosmetics and skin care which has its head office in Gunung Sindur, West Java. This selection aims to form a management information system design model that is able to produce relevant and timely information for planning, controlling, decision making and evaluating the performance of activities. For the Web-Based Instagram Content Management Information System Design project to Support SR12 Herbal Cosmetics' Brand Awareness, I used Agile (Scrum) due to the dynamic nature of digital marketing and potential changes to the Instagram API or business needs. This allowed SR12 to get core functionality faster and provide iterative feedback, ensuring the system built was truly relevant to their brand awareness needs.

Computers in one of the network companies at PT. Estrada uses the Fortinet operating system. The final result expected through this implementation is to comprehensively see the capabilities of the firewall on Fortinet in overcoming the problem of blocking social media applications and streaming platforms during working hours. Blocking the application in question is the ability to filter web processes such as Facebook, Instagram, YouTube, etc. In the tests carried out, web filtering was able to block applications on social media and streaming platforms, which proves that the performance of web filtering is quite good. In analyzing web filtering performance, use the office hour rule tool by carrying out the rule schedule in the Fortinet network and displaying all the information in detail. The final result obtained in the network application filtering simulation process using Fortinet is that every network sent cannot be entered (blocked) on both social media applications and streaming platforms.

Data security in Electronic Medical Records (EMR) is a crucial issue in health information governance in Indonesia. This study evaluates the compliance of health facility information security systems with Ministry of Health Regulation (PERMENKES) No. 24 of 2022 and Personal Data Protection Law (UU PDP) No. 27 of 2022, and analyzes the impact of non-compliance on service quality and patient trust. The method employed is a systematic narrative literature review on the Google Scholar database (2023–2026) using the keywords "data security and privacy," "electronic medical records," and "CIA Triad," focusing on the implementation of Confidentiality, Integrity, and Availability. The four healthcare facilities examined have implemented controls such as role-based access control, Electronic Signatures (TTE), Virtual Private Networks (VPN), data encryption, and SSL/TLS protocols in accordance with PERMENKES provisions and Article 35 of the UU PDP. However, the effectiveness of implementation is hindered by weak authentication due to the use of simple passwords and excessively long auto-logout durations, the absence of comprehensive written standard operating procedures (SOPs), low staff compliance with security protocols, and minimal patient awareness regarding personal data protection rights. These weaknesses heighten the risk of patient data breaches as well as potential administrative sanctions and fines, and carry negative implications for service quality and public trust. Recommendations include strengthening internal security policies, developing written SOPs, providing continuous training for healthcare workers, implementing stronger authentication mechanisms (e.g., multi-factor authentication/MFA), and conducting patient awareness programs to ensure regulatory compliance and maintain public confidence.

This study aims to analyze the Cambodian government's efforts to address human trafficking from a human security perspective. It employs a qualitative descriptive approach, utilizing secondary data from relevant journals, reports, and academic publications. The findings indicate that human trafficking in Cambodia has evolved into a hub for digital-based fraud linked to transnational cybercrime networks. Victims face not only labor exploitation but are also coerced into participating in online fraudulent activities, such as romance scams. This surge in human trafficking is driven by weak law enforcement, high levels of corruption, low public digital literacy, and the rapid expansion of the online gambling industry and special economic zones, which serve as operational bases for criminal activities. The Cambodian government has implemented various measures regarding prevention, protection, and law enforcement through regulations, international cooperation, victim rescue operations, and anti-fraud campaigns. However, the effectiveness of these policies remains limited due to the state's constrained capacity and the ability of criminal networks to continuously adapt to advancements in digital technology. The study concludes that addressing human trafficking in Cambodia requires strengthened governance, more intensive international cooperation, and improved public digital literacy.

This study aims to implement Business Intelligence using Microsoft Power BI to support network disturbance monitoring based on trend analysis. The main problem addressed in this research is that network disturbance data has only been used as documentation, resulting in suboptimal monitoring and data analysis processes. The data used in this study consists of historical network disturbance data, including information on disturbance location, type of disturbance, occurrence time, and resolution duration. The research methodology includes data collection, data preprocessing, implementation of a Business Intelligence dashboard, and trend analysis using interactive visualizations in Microsoft Power BI. The developed dashboard consists of Key Performance Indicators (KPI), interactive filters, line charts, pie charts, bar charts, and table visuals to support a more effective and structured network monitoring process. The results show that the implementation of the Business Intelligence dashboard is capable of supporting real-time, interactive, and user-friendly monitoring of network disturbances. The trend analysis results indicate that the number of network disturbances fluctuated each month, with the highest number occurring in August and the lowest in November. In addition, the dominant types of disturbances were identified as Supporting Facilities and Electrical Problems. Based on functional testing and user testing results, all dashboard features performed successfully and were considered effective in supporting monitoring activities and data-driven decision making.  

Librarians, as information specialists, play a vital role in managing and providing access to digital libraries. Despite the availability of digital information through repositories and digital libraries, a gap remains between users and their effective utilization. This underscores the importance of librarians in facilitating access and supporting users. This study analyzes the role, competencies, and challenges faced by librarians at the UPA Library of the University of Bengkulu in the digital knowledge ecosystem. A qualitative descriptive approach was used, with data collected through semi-structured interviews with four librarians and two users, direct observation, and documentation. Data were analyzed using data reduction, presentation, and conclusion drawing. The findings show that librarians act as information specialists by providing access through the OPAC system, repositories, digital libraries, e-journals, Springer Digital References, Instagram, and the library website. They evaluate and ensure credible digital information sources, preserve and back up collections, and assist users in information searches. However, librarians face challenges such as budget constraints, low user awareness, limited human resources, network issues, restricted access, and inadequate collections. These findings contribute to understanding the role of librarians as information specialists.

Unpredictable changes in weather conditions have increased the need for real-time weather monitoring systems. This study aims to implement an Internet of Things (IoT)-based adaptive weather monitoring and alarm system by utilizing JSON Web API as a weather data source. This system is built using NodeMCU ESP8266 as the main microcontroller connected to the OpenWeatherMap API service via an internet network. The weather data obtained includes temperature, humidity, and weather conditions which are then displayed on the MAX7219 Matrix monitoring and display website in real-time. In addition, this system is equipped with an adaptive alarm feature that can be controlled through the website so that users can set alarms according to their needs. The research method used is an experimental method with a descriptive approach through the stages of system design, hardware and software implementation, and system testing. Based on the test results, the system successfully displays weather information in real-time and runs automatic alarms according to user settings. With this system, users can obtain weather information and time reminders more effectively, practically, and efficiently.

This study aims to examine how nepotism can manifest through the role of informal institutions and its influence on administrative integrity within the bureaucracy. The method used is literature analysis by examining various related scientific references, such as books, journal articles, and research, which are then analyzed descriptively and analytically through identification, classification, and data integration. The research findings indicate that nepotism does not only arise from weaknesses in the official system, but is also strongly influenced by the existence of informal institutions such as personal networks, social norms, and organizational culture. This practice tends to persist within a system because it gains social recognition, making it difficult to overcome solely with regulations. The consequences include a decline in employee professionalism, weak accountability, and erosion of administrative integrity, which impacts on reduced public trust in government institutions. The implications of this study indicate that a comprehensive approach is crucial in bureaucratic reform, through strengthening the official system and changing organizational cultural values ​​to produce transparent, accountable, and dignified government management.

Public Wi-Fi services (Wifi_STAKat) at the State Catholic College of Pontianak continue to face technical issues, such as network speed and connection stability, as well as non-technical challenges, including the responsiveness of administrators to user complaints. This study aims to analyze user satisfaction based on the five Servqual dimensions and to map improvement priorities using the Importance–Performance Analysis (IPA) method. The relationship between Servqual and IPA is explained by mapping GAP values (perception–expectation) into the four IPA quadrants to determine the urgency level of service improvements. A 4-point Likert scale was used to avoid neutral responses and strengthen the clarity of respondents’ perceptions. The results show that all dimensions have negative GAP scores, particularly responsiveness and reliability, which are directly related to technical indicators (speed, stability, coverage) and non-technical factors (responsiveness to complaints, ease of access. The study recommends integrating an IT-based monitoring system and increasing network capacity to improve service quality.

The increasing complexity of urban transportation systems demands intelligent and measurable navigation methods. Medan City, the capital of North Sumatra Province, has a dense road network with multiple route options that often confuse road users. Dijkstra's Algorithm, developed by Edsger Wybe Dijkstra in 1959, is a greedy-based computational approach proven effective for solving the shortest path problem on non-negative weighted graphs. This study applies Dijkstra's Algorithm to determine the shortest route from Medan Railway Station to Universitas Negeri Medan (UNIMED). The road network was modeled as an undirected weighted graph with 15 nodes and 16 edges, where edge weights represent actual road distances measured via Google Maps. The graph has a density of 0.152, confirming its sparse graph characteristic. Three alternative routes were identified and analyzed. The algorithm was implemented in Python 3 using the heapq module as a priority queue. Results show that the optimal route is A → B → C → E → F → M → N → O via Jl. M.T. Haryono, Jl. Aipda KS Tubun, Jl. Madong Lubis, and Jl. Prof. H.M. Yamin, with a total distance of 6.64 km. This achieves 99.1% accuracy compared to Google Maps, with a deviation of only 0.06 km. The optimal route is 6.25% more efficient than Alternative Route 1 (7.30 km) and 11.9% more efficient than Alternative Route 2 (7.54 km). The algorithm executes in under 1 millisecond with time complexity O((V+E) log V). These findings confirm Dijkstra's Algorithm as highly effective for medium-scale urban road network optimization.

Recent Internet of Things (IoT) intrusion detection studies have reported near-perfect benchmark performance for Distributed Denial of Service (DDoS) detection, yet limited attention has been given to understanding how different traffic representations contribute to the detection process under highly imbalanced traffic conditions. This study presents an ablation-driven analysis to investigate the contribution of statistical and temporal representations for large-scale IoT DDoS detection using the CICIoT2023 dataset. Three experimental scenarios are evaluated, including statistical representation, temporal sequence representation, and hybrid statistical–temporal representation. Temporal representations are learned using a one-dimensional Convolutional Neural Network (1D-CNN) with lag-based traffic sequences, while ensemble tree-based classifiers are employed for final classification and representation analysis. In addition, multiple ablation configurations are designed to evaluate the impact of temporal dependency modeling and feature engineering strategies on detection performance. Experimental results show that statistical traffic representations remain highly effective for DDoS detection on CICIoT2023, achieving 99.36% accuracy and 99.31% weighted F1-score in the statistical representation scenario. Feature importance analysis further indicates that engineered statistical features contribute substantially more to the classification process than CNN-based temporal representations. Although temporal modeling captures sequential traffic behavior, its contribution is relatively limited and mainly acts as a complementary representation. Furthermore, the hybrid configuration produces only marginal improvements over the statistical representation alone. These findings highlight the importance of representation-level analysis for understanding the actual contribution of statistical and temporal modeling in modern IoT intrusion detection systems beyond relying solely on benchmark accuracy.

Purpose Research on digitalization in Human Resource Management (HRM) has grown significantly alongside rapid digital transformation and organizational change. However, studies integrating systematic literature review and bibliometric analysis remain limited. This study aims to examine research trends and thematic developments related to digitalization in HRM through a hybrid systematic literature review and bibliometric analysis approach. Method This study employed a Systematic Literature Review based on PRISMA 2020 guidelines using data from the Scopus database with keywords related to digitalization and Human Resource Management. The initial search identified 2,497 documents, and after the screening process, 108 relevant articles were selected. Data were analyzed using VOSviewer to identify publication trends, keyword relationships, collaboration networks, and thematic clusters. Findings The findings indicate that research on digitalization in HRM increased significantly during 2018–2026. Dominant themes include digital transformation, artificial intelligence, e-HRM, innovation, Industry 4.0, sustainability, and organizational performance. Digitalization in HRM has evolved from administrative automation toward strategic organizational transformation supported by technology and data-driven decision making. Originality/value This study integrates systematic literature review and bibliometric analysis to provide a comprehensive understanding of digitalization in HRM.  

This study aims to analyze trends in scientific publications related to the application of green banking in financing products within Islamic banking in Indonesia during the 2019–2024 period. Using a bibliometric analysis method based on Google Scholar data and mapping via VOSviewer software, this study evaluates 60 selected articles. The study results indicate a significant annual increase in publications, with a primary focus on integrating green banking principles into Islamic financing policies, their impact on profitability, and the role of technology in supporting green banking. Additionally, the study found that environmental sustainability, green financing, and digital transformation are the most dominant themes in the development of green banking research within Islamic banking. Bibliometric network analysis indicates a strong interconnection between the concepts of green finance, sustainable banking, and Islamic banking in supporting sustainable economic development. This study also identifies opportunities for further research related to the effectiveness of green banking implementation on the financial performance and social responsibility of Islamic banking. These findings contribute to the development of green finance literature in the Islamic finance sector and serve as a strategic reference for regulators and practitioners in implementing sustainable banking policies in the future.

This study explores the urgency of halal certification for food and beverage Micro, Small, and Medium Enterprises (UMKM) in Indonesia following the implementation of Law Number 33 of 2014. Despite the enactment of regulations, various obstacles such as low halal literacy and bureaucratic complexity remain major challenges. This study aims to analyze the strategic role of Islamic religious instructors as agents of empowerment and da'wah (Islamic outreach) in assisting UMKM in their halal certification process. Using qualitative methods with a library research approach, data was collected through a search of relevant literature and regulations, then analyzed using content analysis techniques. The study results indicate that Islamic religious instructors perform four crucial functions: literacy educators, access facilitators, motivators of Islamic economics, and policy mediators. Optimizing these roles can be achieved through capacity building, digitalization of mentoring, and integration of community networks. The study concludes that strengthening the role of instructors is essential to accelerate the implementation of mandatory halal certification and strengthen the Islamic economic ecosystem in Indonesia.

Ntobo Specta is a community service program implemented by students of the Community Service Program (KKN) of the Bima College of Economics (STIE) as an effort to support the development of a creative economy based on local potential in Ntobo Village. Ntobo Village is known as one of the centers of traditional weaving craftsmen who are the main source of income for most of the community. However, promotion and marketing of woven products are still limited, so innovative activities are needed to increase the attractiveness and economic value of local weaving. Ntobo Specta activities are packaged in the form of a bazaar for weaving MSMEs and a fashion show made from typical Ntobo woven fabrics involving elementary, middle, and high school students. This activity aims to introduce Ntobo weaving to the wider community, increase the interest of the younger generation in local culture, and open marketing opportunities for weaving MSMEs. The implementation method is carried out through the stages of coordination, activity preparation, event implementation, and evaluation. The results of the activity show that Ntobo Specta is able to be an effective medium for promoting culture and the creative economy. The enthusiasm of the community and participants has a positive impact on increasing the existence of Ntobo weaving as a superior regional product. Furthermore, this activity also stimulates economic growth in the community by increasing awareness of local woven products and expanding the marketing network for MSMEs. Thus, Ntobo Specta is a form of community empowerment that integrates cultural preservation with strengthening the creative economy based on local wisdom.