As a newly built city and the new capital of Indonesia, Ibu Kota Nusantara (IKN), is expected to become known worldwide as an economic driver, a symbol of national identity, and a sustainable city. As the nation’s capital, IKN will become the location for running central government activities and hosting representatives of foreign countries and international organizations or institutions. However, there is no concept of cybersecurity in IKN associated with existing functions and expectations of the city. This study identifies the initial cybersecurity framework in the new capital city of Indonesia, IKN. A PRISMA systematic review was used to identify variables and design an initial framework. The initial framework was then validated by cybersecurity and smart city experts. The results show that the recommended cybersecurity framework involved IKN’s factors as a livable city, a smart city, and a city with critical infrastructure. We applied five security objectives supported by risk management, governance, security awareness, and the latest security technology to these factors.

In the digital era, transforming public services through the application of innovative technologies to form a Smart Government has become a priority for governments at various levels. This study presents a systematic review of smart government frameworks and architectures, focusing on identifying and analyzing the key components and features that enhance public service delivery. Specifically, the study examines the impact of smart government initiatives on public services, the challenges and barriers faced, and the solutions implemented across different regions. The findings highlight the importance of integrating advanced information technology, ensuring system interoperability, and fostering stakeholder engagement and collaboration. Major challenges include data security issues, technological infrastructure limitations, and resistance to change within government organizations. This study also identifies gaps in the current literature and provides recommendations for future research, aimed at improving the efficiency and responsiveness of public services through smart government innovations. The insights from this research are intended to assist policymakers, IT practitioners, and academics in designing and implementing effective smart government frameworks and architectures for the transformation of public services.

Moving the capital of Indonesia from the Jakarta area to the island of Kalimantan is an inevitable necessity due to economic, political, socio-cultural and environmental factors, which require other areas of the archipelago to be developed. It has been decided that the green city and smart city concepts will be applied in the development of the new capital, using a state-of-the-art approach, including metaverse technology. The methodology employed in this study includes in-depth interviews, focus group discussions, direct field observations, and documentation. The findings of this research consist of an analysis of the readiness of IKN and its surrounding area for the implementation of metaverse technology in IKN. This paper examines whether metaverse technology is needed in the construction of the new capital city. If so, what are the needs for the development of the new capital's metaverse, and what are the advantages (and disadvantages) of using the metaverse. The results are expected to provide a more comprehensive view of the use of metaverse technology in the new capital.

Effort estimation is one of the most important activities in the software development project, because the project managers need to bea able to estimate the amount of cost and time for developing software. There are several techniques and models that can be used to estimate effort such as COCOMO, COCOMO II, SLIM, SEER-SEM. One method that is widely used for effort estimation is COCOMO II. COCOMO II model is an improvement of COCOMO '81 model. However, COCOMO II estimation results are still not satisfying in terms of accuracy. To improve the accuracy of COCOMO II, many researchers are trying to combine COCOMO II with other methods. In this paper, we propose to combine COCOMO II with K-Means clustering method to improve the accuracy. K-Means clustering is used to determine the data that will be used in the COCOMO II calibration process. The COCOMO II calibration aims to determine the new A and B constant values based on software project dataset. Based on the results of the study, it can be concluded that the accuracy of the proposed method generally increased compared to the original COCOMO II model. The value of accuracy depends on the preprocessing technique performed and the number of clusters. The best accuracy is achieved when the preprocessing technique used is to multiply cost driver attributes by 100 and number of clusters is 5. This proposed method can reduce the value of MRE COCOMO II from 1.32 to 0.85 and increase the value of PRED (0.3) from 32% to 54% for COCOMO NASA 2 dataset and Turkish Software Industry.

e-Government can be divided into several models, such as, Government-to-Citizen or Government-to-Customer (G2C), Government-to-Business (G2B), Government-to-Government (G2G), or Government-to-employees (G2E). Based on previous study, research on G2B model was not as many as the research on the other areas such as on G2C [12]. G2B faces business organization with complex rules. Many software applications have been developed however their utilization is low because most the applications could not meet the needs and expectation of the users or stakeholders. Therefore, it is necessary to build a specific assessment model to further assess the suitability of software with the needs and expectations from users, so that the quality of the software applications can be guaranteed, and their utilization can be increased. Our study proposes a software assessment model using the development and improvement of metrics products from ISO/IEC 9126 for e-Government in the G2B model. The model includes the assessments on functionality, reliability, usability and efficiency. The model is expected to help a government to assess the quality of a software application for a G2B model. A case study in a local government office was performed to validate the model. Our model has been executed systematically, and the results has evaluated. The results demonstrate that our model can be used to assess a software application for G2B model. However more application of the model should be performed to give results for further analysis.

Open Government Data (OGD) is data produced or commissioned by the government, which can be publicly published. These data can be accessed freely by anyone, in order to increase public participation and enable government agencies to report their performance transparently. Indonesia is one of many countries that has been applying open government data concept, by establishing Open Government Indonesia (OGI). With the establishment of the OGI, many Indonesian government agencies have developed open government data. However, many of them have low data quality. One standard that can assess open government data quality is Five Star Open Data. This standard uses 5-step concept, with each data requires particular quality to achieve those steps. This paper proposed a solution to enhance the data quality of Indonesian government data and develop a data publishing tool. This data publishing tool accepts data with 2-star and 3-star quality and enhances the quality of input data to 5-star quality respectively. This tool also publishes the data and generates several types of data visualization according to the data. This tool uses data from Hasan Sadikin General Public Hospital (RSHS) as test data. Based on the evaluation conducted, this tool can enhance the data quality of five datasets, from 2-star to 5-star quality. In addition, the tool publishes the datasets and generates data visualization based on the datasets' contents.