The application of smart campuses (SC), especially at higher education institutions (HEI) in Indonesia, is very diverse, and does not yet have standards. As a result, SC practice is spread across various areas in an unstructured and uneven manner. KM is one of the critical components of SC. However, the use of KM to support SC is less clearly discussed. Most implementations and assumptions still consider the latest IT application as the SC component. As such, this study aims to identify the components of the KM model for SC. This study used a systematic literature review (SLR) technique with PRISMA procedures, an analytical hierarchy process, and expert interviews. SLR is used to identify the components of the conceptual model, and AHP is used for model priority component analysis. Interviews were used for validation and model development. The results show that KM, IoT, and big data have the highest trends. Governance, people, and smart education have the highest trends. IT is the highest priority component. The KM model for SC has five main layers grouped in phases of the system cycle. This cycle describes the organization’s intellectual ability to adapt in achieving SC indicators. The knowledge cycle at HEIs focuses on education, research, and community service.

This study aimed to propose a tool for measuring the research performance of researchers, institutions, and journals in Indonesia based on bibliometrics. Specifically, the output of this measurement tool, referred to as the S-score, is described, as well as its implementation on the main database portal in Indonesia. The S-score was developed by a focus group discussion. The following 8 evaluation items for journal accreditation were analyzed in the development process: journal title, aims and scope; publisher; editorial and journal management; quality of articles; writing style; format of PDF and e-journal; regularity; and dissemination. The elements of the S-score are as follows: number of journal article documents in Scopus, number of non-journalarticle in Scopus, number of citations in Scopus, number of citations in Google Scholar, the hindex in Scopus, and the h-index in Google Scholar. The S-score yields results ranging from S1 to S6. The above metrics were implemented on the Science and Technology Index, a database portal in Indonesia. The measurement tool developed through the focus group discussion was successfully implemented on the database portal. Its validity and reliability should be monitored consistently through regular assessments of S-scores. The S-score may be a good example of a metric for measuring the performance of researchers, institutions, and journals in countries where most journals are not indexed by Scopus.

Background: Human Resource Management System (HRMS) is an important aspect of managing organizations. However, the successful integration of the system into respective roles is often associated with diverse technological challenges and trends. Some major obstacles identified in recent research include reluctance to change, lack of training, fragmented Human Resource (HR) data, rigid processes, and continuous changes in organizational needs. Exciting technology trends offer promise for next-generation HRMS solutions, including artificial intelligence (AI), machine learning, predictive analytics, and mobile accessibility. This shows the need for a systematic literature review to comprehensively map the challenges and technology trends shaping the implementation of HRMS. Objective: This research aimed to conduct a comprehensive review of existing literature to identify the main challenges faced during HRMS implementation and the latest technology trends in the space. Methods: A systematic literature review was adopted through the Kitchenham method with a focus on five databases including Scopus, Emerald, IEEE, Science Direct, and ProQuest. Results: The result was in the form of a table mapping of the challenges faced by each stakeholder in HRMS, including resistance to change, lack of management support, and limited technology infrastructure. Meanwhile, the most common technology challenges found were system integration issues, data security, and lack of technical capabilities or skills. The potential opportunities from technology trends to address the issues included training and skills development, enhanced cybersecurity, and effective change management methods. These recommendations were designed to support organizations in further optimizing HRMS utilization and leveraging the latest technologies such as AI and blockchain. Conclusion: The review used a structured method to develop a rich overview through tabular presentations summarizing problem identification and technology trend compilation of HRMS. The systematic exploration aimed to contribute valuable insights into the complexities of HRMS implementation and offer a comprehensive perspective on the emergence of relevant technology trends. The results were expected to contribute to future research directions in this important area at the nexus of Human Resource Management (HRM) and technological innovation. Keywords: Human Resource Management System, Challenges, Technology Trends, Systematic Literature Review

Citation frequency is an important factor for estimating the quality of a scientific journal, and the number of citations that an academic paper receives is often used as a measure of its scientific impact. This study aimed to characterize the citation performance of scientific journals published by Indonesian publishers that have been indexed in Scopus by analyzing the number of citations available in the Scopus database and Google Scholar. The results of the study identified 30 Indonesian journals that have been Scopus-indexed, of which 22 were listed in SCImago Journal Rank up to October 2017. Journals in the engineering field were the most cited, with 2,427 citations, including 930 self-citations. A large proportion of the citations were of recently-founded journals. The mean proportional difference in the citation frequency between Scopus and Google Scholar was 14.71%.

Open innovation is a concept of collaboration of ideas, knowledge, and resources that originates from within the organization and involves external organizations. University-industry collaboration is a factor driving innovation and competitiveness. Most research on interactions between universities and industry concentrated on the industrial side meanwhile, universities, as knowledge producers, play a vital role in creating an open innovation ecosystem that encourages realizing innovations that benefit society. Therefore, the problem raised in this research is how university collaboration can support open innovation. This research aims to identify research trends, the latest technologies, and inter-university collaboration frameworks that can support open innovation. The methodology used is Kitchenham's Systematic Literature Review (SLR) and bibliometric. SLR consists of Identification Study, Selection Studies, Quality Assessment, Data Extraction and Study Synthesis. From the SLR stages, 21 papers published between 2019 and 2023 were obtained. Synthesis and additional literature review were carried out to identify trends, technologies, and frameworks related to the topic comprehensively. In terms of trend, based on the application bibliometric, it was found that there was an increase in the number of publications and the top list of open innovation journals. University collaboration in open innovation more frequently takes place in the UK, and the industries mostly involved are small-medium enterprises. Quantitative research methodology and data analyses, comprising of hypothesis test, regression test, and descriptive statistics, are mostly preferred. Meanwhile, descriptive data analysis is the most common means of qualitative data analysis. Numerous suggestions on topics for future research were also identified. In addition, data analysis using machine learning survival data is identified as a novelty among data analysis methods. Technology transfer and the use of digital platforms may support open innovation processes, and the use of blockchain technology may promote digital platforms development. Seven domains form the framework for university collaboration in open innovation, namely Social Behavior, People, Process, Organization, Environment, Technology, and Performance. The findings of trends, technologies, and frameworks in this research may serve as a foundation for research on similar topics, and the identified framework domains could serve as framework components that might be used by universities to collaborate with partners in implementing open innovation processes. The research have contributes to knowledge management theoretically and practically. Theoretically, open innovation can expand the knowledge base by supporting the concept that knowledge and expertise can be found outside organizational boundaries. Practically, it can enrich knowledge management practices by emphasizing the importance of utilizing digital platform technology in supporting knowledge management sourced from external knowledge and collaboration services in the open innovation process.

Background: Amidst a rapidly evolving digital landscape that accelerates the flow of information, higher education institutions face the unique challenge of managing vast and dynamic knowledge resources. This research delves into the motivations and innovative solutions for developing Knowledge Management Systems (KMS), which is key to optimizing knowledge resource utilization and enhancing academic collaboration. Objective: This research provides a comprehensive mapping of problems and solutions for developing university knowledge management systems based on previous research. Not only that, but the results of this study also suggest three future research studies that can be adopted. Methods: This study used the Kitchenham systematic literature review method. The author uses literature in the form of journals and conference proceedings published from 2019 to 2023. Twenty-three articles were used for this study from 5 databases, such as ACM, ProQuest, Scopus, Taylor & Francis, and IEEE Xplore. Results: This study reveals research trends in knowledge management systems within higher education, examining aspects such as country, data collection methods, research methodologies, and theoretical frameworks. The main problems motivating the development of KMS are identified and categorized based on the people, process, and technology framework. In overcoming these problems in the university business process, there are several alternative solutions, both in the form of requirements and systems. Thus, the results of this study seek to provide guidelines for future research to adopt alternative solutions from this research and develop KMS to provide new solutions. Conclusion: This study advances knowledge about various trends, motivations, requirements, and system solutions to address KMS problems in higher education. The authors' research results can add valuable insights to improve our understanding of the development of KMS in universities in various countries. Future research can identify new potential in KMS in business processes currently running in a university with appropriate methodologies. Keywords: Knowledge management system, higher education, systematic literature review, problem, solution