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Knowledge growth is currently experiencing a very exponential increase, through a digital transformation of knowledge in the organization and the emergence of various platforms through management system content such as blogs and social media that have encouraged such growth. An employee no longer only interacts in knowledge management (KM) in his organization but can communicate and collaborate to share knowledge through these platforms widely. Much of the spread of knowledge is a challenge for organizations to manage and use their knowledge and spread knowledge and become part of the expertise possessed by employees in their organizations. For this reason, an intelligent knowledge mapping approach is needed to facilitate finding, managing and identifying knowledge owned by an organization. This paper aims to see the use of smart knowledge mapping in organizations empirically.

This research was conducted empirically by conducting a literature study method to compile a questionnaire and conduct a survey through purposive sampling, sampling taken from the KM and Society Indonesia community. This survey limits only to respondents who have experience in conducting knowledge mapping in an organization.

The use of data sources that have been owned by the organization and also the consideration of the use of digital footprint employees spread across the internet can be a potential to explore the knowledge resources possessed by the organization. Of course, with the support of technology through the use of artificial intelligence (AI), it is expected to be able to present a comprehensive, adaptive and objective knowledge mapping for the organization.

The paper provides practical implications for knowledge mapping implementation in an organization by adopting AI with considerable digital footprint employees spread across the internet.

This paper provides empirical information about knowledge mapping implementation in Indonesian organization.

Study on knowledge-based systems for scientific publications is growing very broadly. However, most of these studies do not explicitly discuss the knowledge management (KM) component as knowledge management system (KMS) implementation. This background causes academic institutions to face challenges in developing KMS to support scholarly publication cycle (SPC). Therefore, this study aims to develop a new KMS conceptual model, Identify critical components and provide research gap opportunities for future KM studies on SPC.

This study used a systematic literature review (SLR) method with the procedure from Kitchenham et al. Then, the SLR results are compiled into a conceptual model design based on a framework on KM foundations and KM solutions. Finally, the model design was validated through interviews with related field experts.

The KMS for SPC focuses on the discovery, sharing and application of knowledge. The majority of KMS use recommendation systems technology with content-based filtering and collaborative filtering personalization approaches. The characteristics data used in KMS for SPC are structured and unstructured. Metadata and article abstracts are considered sufficiently representative of the entire article content to be used as a search tool and can provide recommendations. The KMS model for SPC has layers of KM infrastructure, processes, systems, strategies, outputs and outcomes.

This study has limitations in discussing tacit knowledge. In contrast, tacit knowledge for SPC is essential for scientific publication performance. The tacit knowledge includes experience in searching, writing, submitting, publishing and disseminating scientific publications. Tacit knowledge plays a vital role in the development of knowledge sharing system (KSS) and KCS. Therefore, KSS and KCS for SPC are still very challenging to be researched in the future. KMS opportunities that might be developed further are lessons learned databases and interactive forums that capture tacit knowledge about SPC. Future work potential could identify other types of KMS in academia and focus more on SPC.

This study proposes a novel comprehensive KMS model to support scientific publication performance. This model has a critical path as a KMS implementation solution for SPC. This model proposes and recommends appropriate components for SPC requirements (KM processes, technology, methods/techniques and data). This study also proposes novel research gaps as KMS research opportunities for SPC in the future.

The application of knowledge management (KM) in government agencies is one strategy to deal with government problems effectively and efficiently. This study aims to identify KM readiness critical success factors (CSFs), measure the level of readiness for KM implementation, identify improvement initiatives and develop KM readiness models for government agencies. This model plays a role in the implementation of KM successful.

The level of readiness is obtained by calculating the factor weights of the opinions of experts using the entropy method. The readiness value is calculated from the results of the questionnaire with average descriptive statistics. The method for analysis of improvement initiatives adopts the Asian Productivity Organization framework. The model was developed based on a systems approach and expert validation.

Reliability testing with a Cronbach’s alpha value for entropy is 0.861 and the questionnaire is 0.920. The result of measuring KM readiness in government agencies is 75.29% which is at level 3 (ready/needs improvement). The improvement in the level of readiness is divided into two parts: increasing the value of factors that are still less than ready (75%) and increasing the value of all factors to level 4 (84%). The model consists of three main sections: input (KMCSFs), process (KM readiness) and output (KM implementation).

The first suggestion is that the sample of employees used in this study is still in limited quantities, that is, 50% of the total population. The second limitation is determining KMCSFs. According to experts, combining this study with factor search and correlation computations would make it more complete. The expert’s advice aims to obtain factors that can be truly tested both subjectively and objectively. Finally, regarding literature selection for future research, it is recommended to use a systematic literature review such as the preferred reporting items for systematic reviews and meta-analyses and Kitchenham procedures.

The management must also prioritize KMCSF according to its level and make KMCSF a key performance indicator. For example, at the priority level, active leadership in KM is the leading performance indicator of a leader. Then at the second priority level, management can make a culture of sharing an indicator of employee performance through a gamification program. The last point that management must pay attention to in implementing all of these recommendations is to collaborate with relevant stakeholders, for example, those authorized to draft regulations and develop human resources.

This study proposes a novel comprehensive framework to measure and improve KM implementation readiness in government agencies. This study also proposes a KMCSF and novel KM readiness model with its improvement initiatives through this framework.

Fish quarantine is a measure to prevent the entry and spread of quarantine fish pests and diseases abroad and from one area to another within Indonesia's territory. Based on these backgrounds, this study aims to identify the knowledge, knowledge management (KM) processes and knowledge management system (KMS) priority needs for quarantine fish and other fishery products measures (QMFFP) and then develop a classification model and web-based decision support system (DSS) for QMFFP decisions.

This research methodology uses combination approaches, namely, contingency factor analysis (CFA), the cross-industry standard process for data mining (CRISP-DM) and knowledge management system development life cycle (KMSDLC). The CFA for KM solution design is performed by identifying KM processes and KMS priorities. The CRISP-DM for decision classification model is done by using a decision tree algorithm. The KMSDLC is used to develop a web-based DSS.

The highest priority requirements of KM technology for QMFFP are data mining and DSS with predictive features. The main finding of this study is to show that web-based DSS (functions and outputs) can support and accelerate QMFFP decisions by regulations and field practice needs. The DSS was developed using the CTree algorithm model, which has six main attributes and eight rules.

This study proposes a novel comprehensive framework for developing DSS (combination of CFA, CRISP-DM and KMSDLC), a novel classification model resulting from comparing two decision tree algorithms and a novel web-based DSS for QMFFP.

This study proposes to adopt joint application design (JAD) in the requirement gathering process on developing a knowledge management system (KMS) using Fernandez methodology. It is proposed that Fernandez methodology produces only a list of KMS features and the requirement of the feature is still unclear. This study aims to produce KMS that meets the needs and expectations of users based on features of Fernandez's methodology.

This study was conducted using a combination methodology that combines Fernandez methodology to identify the feature needs of the organization and JAD to identify user requirements of KMS. The system prototype is evaluated by measuring user satisfaction using the Post Study System Usability Questionnaire.

The results of this study indicate that with the adoption of JAD it is possible to get the requirement in accordance with the expectations of the user. In addition, this study also shows that the level of user satisfaction with the prototype developed with the requirement is high at 84% of the maximum score.

This study was used only in the education context, especially teaching assistant problems at the Faculty of Computer Science, University of Indonesia. For this reason, further research is needed for different contexts so that the implementation of this combination of methods can be generalized more broadly.

This paper provides practical implications for the development of KMS by identifying user requirements using JAD.

This paper provides a combination method to generate KMS that meets user requirements.

This paper aims to develop a framework for critical information infrastructure (CII) protection in smart government, an alternative measure for common cybersecurity frameworks such as NIST Cybersecurity Framework and ISO 27001. Smart government is defined as the government administration sector of CII due to its similarity as a core of smart technology.

To ensure the validity of the data, the research methodology used in this paper follows the predicting malfunctions in socio-technical systems (PreMiSTS) approach, a variation of the socio-technical system (STS) approach specifically designed to predict potential issues in the STS. In this study, PreMiSTS was enriched with observation and systematic literature review as its main data collection method, thematic analysis and validation by experts using fuzzy Delphi method (FDM).

The proposed CII protection framework comprises several dimensions: objectives, interdependency, functions, risk management, resources and governance. For all those dimensions, there are 20 elements and 41 variables.

This framework can be an alternative guideline for CII protection in smart government, particularly in government administration services.

The author uses PreMiSTS, a socio-technical approach combined with thematic analysis and FDM, to design a security framework for CII protection. This combination was designed as a mixed-method approach to improve the likelihood of success in an IT project.

This paper aims to recommend implementation of the knowledge management (KM) strategy for a mental health organisation, an area that has, to date, limited attention in literature based on the factors that influence KM success.

A mixed-methods research was conducted to identify the organisational culture, resources, enablers and the influential factors of mental health knowledge management (MHKM). The data were collected in five referral mental hospitals and were analysed using quantitative, qualitative and triangulation methods.

The organisational culture has become a great barrier. Forty-three influential factors were identified. Otherwise, based on culture, resources, enablers and strengthen, weakness, opportunities and threaten (SWOT) analysed were adopted to propose ten of the critical success factors and were recommended into an implementation strategy.

The paper has proven that KM is a new and emerging discipline in Indonesia, especially on mental health care. This will contribute to the governmental policy of KM implementation and enforce the quality of services.

This result has the potential to leverage interdisciplinary KM research. It supports a mental health organisation in applying KM.

This study is probably the first to analyse factors that are of influence in an MHKM initiative programme.