This study aims to identify and the implementation of ASN Management policies on career development aspects based on the merit system in the West Java Provincial Government and 6 Regency/City Governments in West Java Province. The failure of the institutionalization of the meritocratic system in ASN career development is partly triggered by the symptoms of the appointment or selection of officials in the central and regional levels not based on their professionalism or competence except for subjective considerations, political ties, close relationships and even bribery. This study uses a qualitative method with a descriptive approach. The operationalization concept in this study uses Merilee S. Grindle’s Policy Implementation theory which consists of dimensions of policy content and its implementation context. The factors that cause the implementation of the policy to be less than optimal include: 1. Uneven understanding of meritocracy; 2. Slowness/unpreparedness in synchronizing central and regional rules/policies; 3. The information integration system between the center and regions has not yet been implemented; 4. Limited supporting infrastructure; 5. Limited permits for related officials; 6. Transparency; 7. Collaboration across units/agencies; 8. External intervention; 9. Use of information systems/technology. To optimize these factors, an Accelerator of Governmental Unit’s Success (AGUS) model was created, which is a development of the Grindle policy implementation model with the novelty of adding things that influence implementation, including top leader’s commitment and wisdom, effectiveness of talent placement, on-point human development, technology savvy, cross-unit/agency collaboration, and monitoring and evaluation processes.

Credit risk assessment is one of the most important aspects of financial decision-making processes. This study presents a systematic review of the literature on the application of Artificial Intelligence (AI) and Machine Learning (ML) techniques in credit risk assessment, offering insights into methodologies, outcomes, and prevalent analysis techniques. Covering studies from diverse regions and countries, the review focuses on AI/ML-based credit risk assessment from consumer and corporate perspectives. Employing the PRISMA framework, Antecedents, Decisions, and Outcomes (ADO) framework and stringent inclusion criteria, the review analyses geographic focus, methodologies, results, and analytical techniques. It examines a wide array of datasets and approaches, from traditional statistical methods to advanced AI/ML and deep learning techniques, emphasizing their impact on improving lending practices and ensuring fairness for borrowers. The discussion section critically evaluates the contributions and limitations of existing research papers, providing novel insights and comprehensive coverage. This review highlights the international scope of research in this field, with contributions from various countries providing diverse perspectives. This systematic review enhances understanding of the evolving landscape of credit risk assessment and offers valuable insights into the application, challenges, and opportunities of AI and ML in this critical financial domain. By comparing findings with existing survey papers, this review identifies novel insights and contributions, making it a valuable resource for researchers, practitioners, and policymakers in the financial industry.

The article highlights Malaysia’s multicultural history, the advancement of Internet technology, and the worldwide appeal of Chinese food, all of which serve as a good basis for the project. This study focuses on Malaysian Chinese takeout systems. The research’s primary goals include developing new business options for the Chinese food sector, as well as enhancing customer happiness and efficiency of takeout systems. As a result, the project intended to create a Web-based system for managing several tasks associated with meal ordering by users. For the system development, an Object-Oriented System Development (OOSD) methodology was used, mostly with the Java programming language. Model-View-Control (MVC) framework was employed throughout development to improve system administration. Redis and HTTP session technologies were included for user login to increase system security. For database operations, MyBatis and MyBatis Plus were also employed to enhance ease and security. The system adheres to design principles and leverages technologies like ElementUI and jQuery to further fulfill this criterion to provide a user-friendly interface. The results of this study demonstrate significant improvements in the overall efficiency of the takeout process, leading to enhanced user experiences and greater customer satisfaction. In addition to streamlining operations, the system opens new avenues for the Malaysian Chinese food industry to capitalize on the growing demand for online food ordering. This research provides a solid foundation for future innovations in takeout systems and serves as a reference point for enhancing the Chinese gastronomy sector in a rapidly digitizing world.