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Job analysis is a key component of human resource management that plays a role in determining the tasks, responsibilities, and competencies required for a particular job. In various organizations, job analysis serves as the foundation for HR planning, recruitment, selection, employee placement, and performance evaluation. However, research on job analysis remains scattered across various studies focused on specific organizational contexts, necessitating a literature synthesis to gain a more comprehensive understanding of research developments in this field. Therefore, this study aims to analyze the development of research on job analysis and identify its role and contributions to human resource management. This study employed a literature review method by searching for scientific articles in the Google Scholar database using the Publish or Perish (PoP) application with the keyword “job analysis.” The initial search yielded 30 scientific articles, which were then screened based on topic relevance, open access, and publication years ranging from 2020-2026, resulting in 16 articles selected for further analysis. The findings indicate that the literature on job analysis can be grouped into three main themes: the role of job analysis in human resource management, its contribution to improving employee performance and productivity, and its implementation in employee placement and organizational governance. Overall, job analysis has proven to be a strategic tool for enhancing the effectiveness of human resource management. Further research is recommended to examine the implementation of job analysis in greater depth across various organizational contexts to enrich the development of human resource management theory and practice.

This study aims to improve subcontractor safety performance through strengthening governance systems, leading safety indicators, capability building, and performance monitoring at PT Putra Perkasa Abadi (PPA) Jobsite Borneo Indobara (BIB). The research was motivated by the increasing trend of subcontractor incidents during Quarter 1 to Quarter 3 of 2025, where seven incidents occurred and exceeded the company threshold. In addition, subcontractor performance evaluation scores remained below the target threshold of 70, while customer satisfaction scores in subcontractor management decreased from 8.45 to 7.58. The study applied a continuous improvement approach using Quality Control Circle (QCC), Pareto analysis, Nominal Group Technique (NGT), and root cause analysis with the Ishikawa method. Improvement initiatives were implemented through four strategic pillars: strengthening governance, reinforcing leading indicators, capability building, and integrated dashboard monitoring. The implementation results showed significant improvements in subcontractor safety management. The subcontractor incident frequency rate was reduced to zero incidents in Quarter 4 of 2025, subcontractor performance evaluation increased above the threshold to 70.81, and customer satisfaction scores improved to 8.55. The findings indicate that structured governance strengthening combined with real-time monitoring and subcontractor engagement can significantly improve mining safety performance and stakeholder trust.

Libraries play a crucial role in broadening the public's knowledge horizons by improving literacy skills. However, the reality at the Samaturu Library in Jambu Malea Village shows that manual management still dominates, leading to various administrative obstacles such as data irregularities, the risk of losing important information, and inefficiencies in tracking daily activities. This condition demands digital transformation to optimize public services at the village level comprehensively and sustainably. This research focuses on the development of a web-based library information system specifically designed to modernize administrative processes to be more systematic, fast, and organized. Built using the PHP programming language and MySQL database, this platform offers an intuitive interface for both staff and members. Its superior features include book data management, membership, activity agendas, announcements, and digitizing the borrowing and return process. Furthermore, the system is capable of automatically generating periodic reports to facilitate library performance evaluation. Based on the results of comprehensive testing using the Black Box Testing method, all system functionality was proven to operate optimally according to the required specifications. Direct user trials also showed very positive responses regarding aspects of ease of navigation and operational time efficiency. The implementation of this system is expected to improve the effectiveness of internal management, accelerate the quality of services to library users, and become a major catalyst in realizing superior digital literacy governance in rural areas.

Libraries play a crucial role in broadening the public's knowledge horizons by improving literacy skills. However, the reality at the Samaturu Library in Jambu Malea Village shows that manual management still dominates, leading to various administrative obstacles such as data irregularities, the risk of losing important information, and inefficiencies in tracking daily activities. This condition demands digital transformation to optimize public services at the village level comprehensively and sustainably. This research focuses on the development of a web-based library information system specifically designed to modernize administrative processes to be more systematic, fast, and organized. Built using the PHP programming language and MySQL database, this platform offers an intuitive interface for both staff and members. Its superior features include book data management, membership, activity agendas, announcements, and digitizing the borrowing and return process. Furthermore, the system is capable of automatically generating periodic reports to facilitate library performance evaluation. Based on the results of comprehensive testing using the Black Box Testing method, all system functionality was proven to operate optimally according to the required specifications. Direct user trials also showed very positive responses regarding aspects of ease of navigation and operational time efficiency. The implementation of this system is expected to improve the effectiveness of internal management, accelerate the quality of services to library users, and become a major catalyst in realizing superior digital literacy governance in rural areas

Micro, Small, and Medium Enterprises (MSMEs) play a crucial role in supporting local and national economic development, particularly through employment generation and income distribution. Seasonal religious events such as Ramadan significantly influence consumption patterns and market dynamics, creating both opportunities and challenges for MSMEs. This study aims to analyze the implementation of the “Seri Ramadhan” phenomenon within the strategic management practices of MSMEs in Martapura, focusing on the periods before and after Ramadan. The research employed a qualitative descriptive approach with field study methods. Data were collected through in-depth interviews, direct observation, and documentation involving selected MSME actors in the culinary, fashion, and retail sectors. The findings indicate that prior to Ramadan, MSMEs emphasize strategic planning through product innovation, stock preparation, promotional intensification, and operational adjustments. After Ramadan, they conduct performance evaluations, inventory control, and strategic realignment to maintain business sustainability. The study highlights that Ramadan is not merely a short-term sales opportunity but also a strategic momentum integrated into broader business planning cycles. The implications suggest that adaptive and cyclical strategic management enhances MSME resilience and competitive advantage in seasonal markets.

This research is motivated by the importance of strengthening a professional public service culture through the integration of public administration values, norms, and ethics. Although various regulations and codes of ethics have been established in public organizations, gaps remain between formal norms and service practices in the field, such as low levels of responsiveness and professionalism among civil servants. This study aims to analyze the relationship between values, norms, and ethics in shaping public service culture, and to examine the role of organizational ethics and codes of ethics in strengthening public administration professionalism. The research employed a qualitative approach with a descriptive-analytical design through a literature review of relevant journals, books, and policy documents. Content analysis techniques were used to identify patterns of relationships between concepts. The results indicate that the internalization of ethical values ​​such as integrity, accountability, and transparency significantly influences the quality of public services. An organizational code of ethics serves as a formal instrument that clarifies standards of conduct for civil servants and strengthens a professional work culture. Consequently, public organizations need to strengthen ethics training, oversight mechanisms, and the integration of ethical values ​​into performance evaluation systems to build responsive and public-interest-oriented services.

Public service performance serves as a crucial measure of how effectively government agencies provide services to the public. Rising expectations from the public compel governments to ensure that services are delivered in an efficient, open, responsible, and responsive manner. Within the realm of public administration reform, the standard of public services has emerged as a key issue for governments looking to enhance public confidence and governance. The Indonesian government has created the Public Service Index (Indeks Pelayanan Publik/IPP) as a tool to assess the performance of public services. The IPP functions as an all-encompassing measurement system to evaluate the quality, efficiency, and responsibility associated with public service provision across government entities. This research intends to explore the definition of public service performance, the legal framework that regulates public services in Indonesia, and the metrics employed for calculating the Public Service Index. The study uses a qualitative descriptive method and a literature review approach, evaluating various pertinent books, regulations, and scholarly articles concentrating on public service management and performance evaluation. The results indicate that the Public Service Index plays a vital role in assessing service quality, institutional effectiveness, and the degree of public satisfaction. Additionally, the application of the IPP measurements fosters transparency, bolsters accountability, and encourages ongoing enhancements in public service delivery. Therefore, enhancing public service performance necessitates robust regulatory backing, institutional dedication, and the utilization of clear and quantifiable performance metrics to guarantee enduring improvements in service quality.

Object detection plays a crucial role in intelligent transportation systems, particularly for outdoor traffic monitoring applications that require accurate and real-time performance under limited computational resources. Recent developments in YOLO-based architectures have introduced multiple model variants; however, their practical performance under constrained training conditions remains insufficiently explored. This study presents a comparative evaluation of YOLOv5, YOLOv7, and YOLOv8 for outdoor traffic object detection using a real-world dataset and identical experimental settings. The main objective of this research is to analyze the robustness and detection quality of different YOLO variants when trained with a limited number of epochs, reflecting practical deployment scenarios. All models were trained and evaluated using the same dataset, preprocessing pipeline, and hardware configuration to ensure a fair comparison. Performance evaluation was conducted using multiple metrics, including precision, recall, mAP@50, Precision–Recall curves, area under the curve (AUC), and peak F1-score. Experimental results indicate that YOLOv5 outperformed YOLOv7 and YOLOv8 in terms of overall detection stability and robustness. The merged Precision–Recall analysis shows that YOLOv5 achieved a higher effective AUC and superior mAP@50, reflecting better global detection performance. In addition, YOLOv5 exhibited a higher peak F1-score, indicating a more balanced trade-off between precision and recall. In contrast, YOLOv7 and YOLOv8 showed performance degradation under limited training conditions despite their more advanced architectures. These findings suggest that YOLOv5 remains a reliable and efficient solution for outdoor traffic object detection, particularly in resource-constrained environments. The study highlights the importance of comprehensive evaluation metrics and practical experimental settings when selecting object detection models for real-world applications.

Object detection plays a crucial role in intelligent transportation systems, particularly for outdoor traffic monitoring applications that require accurate and real-time performance under limited computational resources. Recent developments in YOLO-based architectures have introduced multiple model variants; however, their practical performance under constrained training conditions remains insufficiently explored. This study presents a comparative evaluation of YOLOv5, YOLOv7, and YOLOv8 for outdoor traffic object detection using a real-world dataset and identical experimental settings. The main objective of this research is to analyze the robustness and detection quality of different YOLO variants when trained with a limited number of epochs, reflecting practical deployment scenarios. All models were trained and evaluated using the same dataset, preprocessing pipeline, and hardware configuration to ensure a fair comparison. Performance evaluation was conducted using multiple metrics, including precision, recall, mAP@50, Precision–Recall curves, area under the curve (AUC), and peak F1-score. Experimental results indicate that YOLOv5 outperformed YOLOv7 and YOLOv8 in terms of overall detection stability and robustness. The merged Precision–Recall analysis shows that YOLOv5 achieved a higher effective AUC and superior mAP@50, reflecting better global detection performance. In addition, YOLOv5 exhibited a higher peak F1-score, indicating a more balanced trade-off between precision and recall. In contrast, YOLOv7 and YOLOv8 showed performance degradation under limited training conditions despite their more advanced architectures. These findings suggest that YOLOv5 remains a reliable and efficient solution for outdoor traffic object detection, particularly in resource-constrained environments. The study highlights the importance of comprehensive evaluation metrics and practical experimental settings when selecting object detection models for real-world applications.

Good governance has become a crucial framework for improving public sector effectiveness, accountability, and responsiveness to citizens’ needs. In Indonesia, decentralization policies since 1999 have devolved significant authority and resources to local governments, creating both opportunities and challenges in implementing good governance principles. This study examines administrative reform efforts in Indonesian local governments, focusing on progress, challenges, and key success factors. Using a multiple case study design, the research analyzed reform initiatives in six district/city governments with diverse contexts. Data were collected through document analysis, semi-structured interviews with government officials, civil society representatives, and citizens, as well as direct observation of administrative processes conducted between March and November 2024. The study assessed six core principles of good governance: participation, transparency, accountability, effectiveness and efficiency, equity and inclusiveness, and rule of law. The findings reveal variations in implementation across regions, with high-performing governments demonstrating strong leadership commitment, systematic planning, active citizen engagement, and effective monitoring mechanisms. However, challenges persist, including limited capacity, bureaucratic resistance, weak accountability enforcement, and low public participation. Key success factors include visionary leadership, capacity development, strategic partnerships, and institutional strengthening. Policy recommendations emphasize enhancing local capacity, accountability systems, citizen participation, and performance evaluation. Good governance has become a crucial framework for improving public sector effectiveness, accountability, and responsiveness to citizens’ needs. In Indonesia, decentralization policies since 1999 have devolved significant authority and resources to local governments, creating both opportunities and challenges in implementing good governance principles. This study examines administrative reform efforts in Indonesian local governments, focusing on progress, challenges, and key success factors. Using a multiple case study design, the research analyzed reform initiatives in six district/city governments with diverse contexts. Data were collected through document analysis, semi-structured interviews with government officials, civil society representatives, and citizens, as well as direct observation of administrative processes conducted between March and November 2024. The study assessed six core principles of good governance: participation, transparency, accountability, effectiveness and efficiency, equity and inclusiveness, and rule of law. The findings reveal variations in implementation across regions, with high-performing governments demonstrating strong leadership commitment, systematic planning, active citizen engagement, and effective monitoring mechanisms. However, challenges persist, including limited capacity, bureaucratic resistance, weak accountability enforcement, and low public participation. Key success factors include visionary leadership, capacity development, strategic partnerships, and institutional strengthening. Policy recommendations emphasize enhancing local capacity, accountability systems, citizen participation, and performance evaluation.

Information technology advancements have sparked a digital revolution in village government operations, especially in tracking and assessing village officials' performance. Performance evaluation is still done by hand in many village government organizations, which frequently causes reporting delays, ineffective data processing, and a lack of transparency in the evaluation process. In order to facilitate a more efficient and organized monitoring and performance evaluation process, an information system therefore required. In order to support the management village apparatus data, performance assessment procedures, and integrated reporting, this study intends design and develop a web-based monitoring system for assessing the performance village officials. To represent the system processes in an organized way, the system design is modeled using the Unified Modeling Language (UML), which includes use case diagrams, activity diagrams, and sequence diagrams. To make sure that every system function performs in accordance with user requirements, system testing is carried out using the Black Box Testing method. The findings demonstrate the system's ability handle village apparatus data, carry out automated performance evaluation procedures, compute final scores using assessment indicators, and produce precise performance reports. It is anticipated that the system's implementation will enhance the village officials' performance monitoring procedure's efficacy, efficiency, transparency, and structure.

Stunting remains a significant public health challenge in Indonesia, including in Paser Regency, East Kalimantan. Effective human resource (HR) management among community cadres is a critical factor in stunting prevention and intervention programs. This community service activity aimed to enhance the knowledge and skills of 33 Stunting Companion Cadres under the auspices of the Office of Population Control, Family Planning, Women's Empowerment and Child Protection (DPPKBPPPA) of Paser Regency through counseling and training on HR management principles applied to stunting mitigation. The activity was conducted using a participatory lecture method supplemented by discussion and question-and-answer sessions. Pre-test and post-test evaluations were administered to measure improvements in participants' knowledge. Results indicated a significant increase in participants' understanding of HR management concepts—including planning, recruitment, training, and performance evaluation—as applied to stunting intervention programs. The mean pre-test score was 58.3, which increased to 82.7 after the intervention (improvement of 41.8%). These findings underscore the importance of HR management capacity-building for cadres as a foundational strategy for achieving optimal stunting reduction outcomes at the community level.

This study examines the effectiveness of public service management in Ponorogo Regency's transport sector, focusing on the performance gap between traffic asset conditions (signs, traffic lights) and formal maintenance policies. This gap indicates a non-proactive maintenance cycle, exacerbated by limited resources and low organisational responsiveness to public complaints. Employing a qualitative case study grounded in a synthesis of Edwards III's Policy Implementation Theory and the New Public Service (NPS) perspective, the core findings confirm that frontline officials' low proactive disposition mediates policy implementation failure. Instead of proactive responsiveness (anticipating minor damage), officials often exhibit passive responsiveness (acting only after major incidents or reports), leading to a critical breakdown in which administrative procedures are completed but the public outcome remains poor. The novelty of this research lies in proposing a Proactive and Participatory Governance Model. This model necessitates the institutionalisation of Public Involvement (Participation) to enhance transparency and shift asset performance evaluation from output-oriented to outcome-oriented. The study concludes that the optimal model for the Ponorogo Transportation Department is the synergy between agile asset management and NPS principles (proactive and participatory) to enhance public service effectiveness.

Public accountability is a key principle in the implementation of good governance, particularly in fulfilling the responsibilities of local governments. One instrument of this accountability is the Regional Government Administration Report (Laporan Penyelenggaraan Pemerintahan Daerah / LPPD), which is prepared annually by regional heads and submitted to the central government. This study aims to analyze public accountability in the preparation of the LPPD in Ponorogo Regency. The research employs a descriptive qualitative approach using interviews, observations, and documentation for data collection. Informants include the LPPD preparation team at the Regional Secretariat of Ponorogo Regency and Regional Apparatus Organizations (OPD) involved in providing data. The analysis uses accountability indicators including responsiveness, debate forums, coordination, autonomy, clarity of performance evaluation standards, negotiation, accountability campaigns, evaluation and feedback, and participation and responsiveness to environmental changes. The results indicate that the preparation of the LPPD in Ponorogo Regency has followed administrative procedures and is supported by the involvement of regional agencies and a digital-based reporting system. However, its implementation remains less than optimal, particularly in terms of responsiveness of regional agencies, cross-sector coordination, public accountability campaigns, and mechanisms for public participation.

This study aims to analyze bureaucratic transformation and public service innovation in the dynamics of the administrative capacity of the Dili City government, specifically at the Cristo Rei District Office, in realizing responsive, accountable, and quality public services. The research approach employed a mixed methods approach, collecting quantitative data through questionnaires from 12 respondents and qualitative data through in-depth interviews with four key informants: Fernando Araujo (District Head), Marciana de Jesus Soares (Head of Administration and Finance), Jose Sarmento (Head of Program Planning), and Ernesto Mendonça (Head of Public Relations). Statistical analysis showed that institutional capacity had a very strong influence on public accountability (r = 0.806; p = 0.002), while bureaucratic responsiveness had a very strong influence on the quality of public services (r = 0.727; p = 0.007). The interviews revealed concrete practices of bureaucratic transformation, such as effective internal coordination, orderly administrative procedures, one-stop service, and responsiveness to citizen needs. This study indicates that institutional capacity and bureaucratic responsiveness are the dominant factors in improving service quality, while formal accountability needs to be made more open and participatory. The findings support the Theory of Administrative Capacity and the New Public Service, and offer recommendations to strengthen participatory mechanisms and make performance evaluation more transparent.  

In Surabaya City, the City Government through the Transportation Agency developed the Suroboyo Bus and Trans Semanggi programs to address traffic congestion, limited public transportation, and the need for safe, comfortable, and environmentally friendly transportation. However, complaints are still found regarding limited facilities, irregular schedules, and suboptimal communication services, so that service performance evaluation is needed from the user's perspective. This study aims to analyze the performance of Suroboyo Bus and Trans Semanggi public transportation services at the Surabaya City Transportation Agency using five public service performance indicators according to Dwiyanto et al. (2021), namely productivity, service quality, responsiveness, responsibility, and accountability. The approach used is quantitative with the Importance Performance Analysis (IPA) method. The results of the study show an average expectation score (importance) of 4.18 and a reality score (performance) of 3.86 with an overall gap of -0.32, which means that the performance of Suroboyo Bus and Trans Semanggi services still does not meet public expectations. Through the IPA mapping, three attributes are in Quadrant I (high priority): the friendly and professional attitude of staff, the adequacy of on-board facilities, and the transparency of official information regarding schedules and service changes. A total of 13 attributes are in Quadrant II (maintained), 13 attributes in Quadrant III (low priority), and one attribute in Quadrant IV (excessive).

This study is motivated by the increasing need for accurate modeling and classification of one-dimensional signal data in intelligent systems. The rapid development of deep learning has led to the adoption of more adaptive and complex neural network architectures capable of capturing both temporal dependencies and local patterns in sequential data. This research aims to analyze and compare the performance of several deep learning models, namely Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and a hybrid Convolutional Neural Network–GRU (CNN–GRU) model for signal data classification. The research method employs a quantitative experimental approach involving data preprocessing, windowing, model training, and performance evaluation. Model performance is evaluated using accuracy, precision, recall, and F1-score metrics. The results indicate that the hybrid CNN–GRU model outperforms the other models, particularly in capturing local features and long-term temporal dependencies within signal data. These findings suggest that the integration of convolutional layers and recurrent mechanisms enhances feature representation and learning stability. This study is expected to contribute both theoretically and practically to the development of deep learning models for signal processing and time-series-based intelligent applications.

This study aims to conduct a pilot evaluation of employee performance in the Raw Material Warehouse Section at PT. IKPP Serang Mill using a checklist-based performance appraisal model. Performance evaluation is a crucial aspect in ensuring the smooth operation of raw material warehouses, which involve a high level of occupational risk and have a direct impact on the continuity of the production process. The checklist method is applied because it integrates quantitative assessment through scoring results with qualitative evaluation in the form of behavioral feedback. This study employs a qualitative descriptive approach supported by quantitative data obtained from performance assessments of ten employees holding various positions, including forklift operators, checkers, shift administrators, and shift supervisors. The results indicate that employee performance falls within a diverse spectrum, categorized as “performance” and “need to improve,” influenced by compliance with standard operating procedures (SOPs), work discipline, communication, and awareness of occupational health and safety (OHS). The findings also demonstrate that the checklist-based model is effective in identifying performance gaps and serves as a basis for formulating improvement actions such as coaching, OHS training, promotions, and administrative sanctions. This study concludes that the checklist model functions not only as an administrative evaluation tool but also as a strategic instrument for human resource development and sustainable organizational performance improvement.

Digital transformation in public service delivery encourages government to implement service innovations that are effective, efficient, transparent, and accountable. This transformations is realized through the adoption of innovations capable of responding to public needs in a timely and accurate manner to improve service quality. The Regional Civil Service Agency of East Java Province developed the Rumah ASN Application as a digital-based personnel service innovation to support the needs of civil servants of the East Java Provincial Government and the general public. This study aims to analyze and describe the implementation of the Rumah ASN Application as an innovation in personnel services at the Regional Civil Service Agency of East Java Province. This research employs a qualitative descriptive. The analytical framework is based on the public sector process innovation theory proposed by Khodadad-Saryazdi (2022), which consists of seven key success factors: strategic alignment, governance, leadership, culture, information technology and information system, process actors, and performance evaluation. Data were collected through interviews, observations, and documentation. The findings indicate that the implementation of the Rumah ASN Application has generally been conducted well, but it has not yet reached optimal. Challenges identified for optimizing this service including the needs for continuous user socialization during system updates, optimization of service features for civil servant capacity building, strengthening administrative capacity and cross-sectoral coordination, and the developing the application into a mobile application version.

This study develops a computational-based system to identify individual potential through the analysis of signature patterns using Artificial Neural Networks (ANN) and the Backpropagation algorithm. The research aims to explore and examine the effectiveness of applying ANN in recognizing and identifying signature patterns that are assumed to be related to an individual’s potential. In the data processing stage, Principal Component Analysis (PCA) is employed as a dimensionality reduction and feature extraction technique to optimally obtain the main characteristics of signature images. The system performance evaluation is conducted using a total of 80 signature images, consisting of 60 training data and 20 testing data. This study analyzes two network architecture configurations, namely a model with one hidden layer and a model with two hidden layers. The experimental results show that both network configurations achieve the same accuracy level of 92.5%. These findings indicate that the use of Artificial Neural Networks with the Backpropagation algorithm is effective in producing high accuracy in the signature pattern recognition process. Furthermore, the developed system has broad potential applications in the field of personal identification, such as employee evaluation, selection systems, and other applications across various organizational and industrial sectors.