This study aims to examine the mediating role of institutional trust (IT) between perceived corruption and subjective well-being (SWB) using data from 1566 households in a developing country. It deploys ordinary least square (OLS) and an ordered logit model within the generalized structural equation model. Results show that individuals who perceived no corruption in a country report more IT and higher levels of SWB. Furthermore, the direct effects of good governance, perceived IT, and the absence of corruption on SWB is also positive. Moreover, satisfaction with hospital services also improves happiness and life satisfaction levels. This study improves and validates how corruption is assessed to support future measures that reduce its harmful effects. Moreover, the masses must have widespread awareness about the critical nature of corruption and IT relative to well-being. This study also highlights the need to develop strong institutions to improve trust and minimize corruption.

Industrial zones require careful and meticulous planning because industry can have a major impact on the surrounding environment. The research location is the northern part of West Java Province which is a gold triangle area named Rebana Triangle Area. The purpose of this study is to measure the weight of the research variables in determining industrial zones from the results of fuzzy analytical hierarchy process (F-AHP) analysis, assessing the location of industrial zones in the research area based on important variables in determining industrial zones. The result of this study is the weight of the research variables in determining the industrial zone from the results of the fuzzy analytical hierarchy process (F-AHP) analysis obtained is the availability of electrical infrastructure with an influence weight of 15.00%. The second most influential factor is the availability of telecommunications infrastructure with an effect of 13.02%, the distance of land to roads and access of 11.76%, land use of 11.21%, distance of land to public facilities of 9.99%, labour cost work is 9.60%, the distance of land to the river is 8.19%, the price of land is 7.97%, the slope is 6.79%, and the type of soil is 6.43%. This GIS analysis model can be a reference model for the government in determining the potential of industrial zones in other regions in Indonesia. A total of 4822.41 Ha or the equivalent of 3.50% of the total area of 6 (six) regencies/cities research areas which are very suitable to be used as industrial zones. The district that has the largest area of potential industrial zone is Majalengka, while Cirebon does not have a location that has the potential for industrial zone locations. Based on the results of the analysis of 10 (ten) variables for determining industrial zones from expert opinion, a draft policy proposal for the government can be proposed, among others. These 10 (ten) variables are variables that are expected to be mandatory variables in planning and determining the location of potential industrial areas.

Amidst the COVID-19 pandemic, the imperative of physical distancing has underscored the necessity for telemedicine solutions. Traditionally, telemedicine systems have operated synchronously, requiring scheduled appointments. This study introduces an innovative telemedicine system integrating Artificial Intelligence (AI) to enable asynchronous communication between physicians and patients, eliminating the need for appointments and providing round-the-clock access from any location. The AI-Telemedicine system was developed utilizing Google Sheets and Google Forms. Patients can receive dietary recommendations from the AI acting as the physician and submit self-reports through the system. Physicians have access to patients’ submitted reports and can adjust AI settings to tailor recommendations accordingly. The AI-Telemedicine system for patients requiring daily dietary recommendations has been successfully developed, meeting all nine system requirements. System privacy and security are ensured through user account access controls within Google Sheets. This AI-Telemedicine system facilitates seamless communication between physicians and patients in situations requiring physical distancing, eliminating the need for appointments. Patients have round-the-clock access to the system, with AI serving as a physician surrogate whenever necessary. This system serves as a potential model for future telemedicine solutions.

To increase inter-region connectivity, the Indonesian government initiated infrastructure projects such as toll roads, airport, highways, as well as agriculture ones throughout the countries. One of the big projects in road infrastructure was the Cikampek–Palimanan (Cipali) toll road in West Java with a budget of more than USD1 billion which started to operate in July 2015. This paper is aimed to evaluate the impact of the toll road on accessibilities, trades, and investments in the region it traverses. To carry out the analysis, we used qualitative approach, difference-in-difference approach, and ANOVA, utilizing three kinds of data. The first data is collected from a survey of 331 small-medium enterprises (SMEs) in the logistics and the hotel and restaurant industries. The second one is bank loan data sourced from Bank Indonesia, while the third one is investment data from Investment Coordinating Board of Indonesia (BKPM).
After two years of its operation, Cipali toll road has increased accessibility, mobility, trade, and investment in the region it traverses. The travel time was reduced by 39%, while the cargo volume of the local businesses increased by 30% to 40%. These led to an improvement of wholesale trade volume in almost all regencies. However, SMEs in the hotel and restaurant industry along the traditional northern coastal highway in Subang, Indramayu, and Brebes experienced a decline due to the traffic shifting. Meanwhile, investments from national companies especially those of labor-intensive manufacturing industries flowed significantly especially to Subang and Majalengka, which reflected a “sorting effect”. However, investments from local and foreign businesses did not increase significantly yet after 2.5 years of toll operation.
To reap the benefit from the presence of Cipali toll road, the local governments should improve the ease of doing business to attract investments that boost employment in return. In addition, given a better accessibility from Greater Jakarta and a large number of potential visitors passing through the toll road, local businesses in the trade sector would benefit if they could promote the local attractions such as in tourism activities supported by the local government. The latter strategy should also be implemented by the local governments and local businesses in the northern coastal traditional route to minimize the negative impact of the toll road due to the traffic shifting. This strategy should be strengthened through increasing connectivity from the toll exits to local business areas and through increasing the ease of doing business.

This study evaluated the performance of several machine learning classifiers—Decision Tree, Random Forest, Logistic Regression, Gradient Boosting, SVM, KNN, and Naive Bayes—for adaptability classification in online and onsite learning environments. Decision Tree and Random Forest models achieved the highest accuracy of 0.833, with balanced precision, recall, and F1-scores, indicating strong, overall performance. In contrast, Naive Bayes, while having the lowest accuracy (0.625), exhibited high recall, making it potentially useful for identifying adaptable students despite lower precision. SHAP (SHapley Additive exPlanations) analysis further identified the most influential features on adaptability classification. IT Resources at the University emerged as the primary factor affecting adaptability, followed by Digital Tools Exposure and Class Scheduling Flexibility. Additionally, Psychological Readiness for Change and Technical Support Availability were impactful, underscoring their importance in engaging students in online learning. These findings illustrate the significance of IT infrastructure and flexible scheduling in fostering adaptability, with implications for enhancing online learning experiences.

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.