considering the rate of the currency channel, this study aims to analyze the effect of government foreign debt on labour demand in Indonesia. The Real Effective Exchange Rate (REER) is used to quantify the exchange rate, while estimates of the labour force participation rate characterize labour demand. this study expands upon the cobb-Douglass production function by including public debt as an integral element of the statistical model. The current study examines time series data from 1994 to 2022 and uses the Vector Error Correction Model (VECM) for estimation. in conclusion, the results suggest that an increase in government external debt would result in a decline in labour demand, especially during economic shock associated with an expansion of the government deficit. Moreover, the Real Effective Exchange Rate has a beneficial long-term impact on labour demand. enhancing the purchasing power and stimulating investment through the appreciation of the domestic currency against foreign currencies will consequently increase economic productivity.

Indonesia, an emerging archipelagic nation, possesses abundant natural resources spanning marine, land (including forests and water sources), and diverse biological riches. The agricultural sector emerges as a pivotal driver of growth across the country, exhibiting extensive distribution. Consequently, there is an urgent imperative for comprehensive research to bolster and optimize the performance of this sector. This study aims to meticulously analyze and scrutinize macroeconomic variables aimed at enhancing Indonesia’s agricultural sector. Through the utilization of a dynamic panel model, the study zeroes in on crucial variables: economic growth in the agricultural sector, farmer terms of exchange, human development index, population density, inflation, average daily wages, and lagged economic growth data from each province in Indonesia. The best model for dynamic panel testing, employing both First Difference Generalized Method of Moments (FD-GMM) and Generalized Method of Moments System (SYS-GMM) approaches, is identified as the SYS-GMM model. This model exhibits unbiased and consistent estimation, as evidenced by the Arellano-Bond (AB) test and Sargan test results. The analysis conducted using this selected model reveals notable findings. Lagging agricultural sector performance, human capital measured by the Human Development Index (HDI), and farmers’ exchange rates are found to significantly and positively influence the economic growth of the agricultural sector. Conversely, inflation exerts a significant and negative impact on sectoral growth. However, wage levels and population density do not demonstrate a significant partial effect on the economic growth of the agricultural sector.

Infectious diseases often occur, especially as diseases such as COVID-19 have claimed many lives in the years between 2019–2021. That’s why it’s called COVID-19, considering that this infectious disease outbreak started in 2019, and its consequences and effects are devastating. Like other countries’ governments, the Indonesian government always announces the latest data on this infectious disease, such as death rates and recoveries. Infectious diseases are transmitted directly through disease carriers to humans through infections such as fungi, bacteria, viruses and parasites. In this research, we offer a contagious illness monitoring application to help the public and government know the zone’s status so that people are more alert when travelling between regions. This application was created based on Web Application Programming Interface (API) data and configured on the Google Map API to determine a person’s or user’s coordinates in a particular zone. We made it using the prototype method to help users understand this application well. This research is part of the Automatic Identification System (AIS) research, where the use of mobile technology is an example of implementation options that can be made to implement this system.

This study aims to explore the implications of imported electrical equipment in Indonesia, analysing both short-term and long-term impacts using a quantitative approach. The research focuses on understanding how various economic factors, such as domestic production, international pricing, national income, and exchange rates, influence the country’s import dynamics in the electrical equipment sector. Employing an Error Correction Model (ECM) for regression analysis, the study utilises time-series data from 2007 to 2021 to delve into the complex interplay of these variables. The methodology involves a comprehensive analysis using the Augmented Dickey-Fuller and Phillips-Perron tests to assess the stationarity of the data. This approach ensures the robustness of the ECM, which is employed to analyse the short-term and long-term effects of the identified variables on electrical equipment imports in Indonesia. The results reveal significant relationships between these economic factors and import levels. In the short term, imports are shown to be sensitive to changes in domestic economic conditions and international market prices, while in the long term, the country’s economic growth, reflected through GDP, emerges as a significant determinant. The findings suggest that Indonesia’s electrical equipment import policies must adapt highly to domestic and international economic changes. In the short term, a responsive approach is required to manage the immediate impacts of market fluctuations. The study highlights the importance of aligning import strategies with broader economic growth and environmental sustainability goals for long-term sustainability. Policymakers are advised to focus on enhancing domestic production capabilities, reducing import dependency, and ensuring that environmental considerations are integral to import policies. This study contributes to understanding import dynamics in a developing country context, offering valuable insights for policymakers and industry stakeholders in shaping strategies for economic growth and sustainability in the electrical equipment sector. The findings underscore the need for a balanced, data-driven approach to managing imports, aligning short-term responses with long-term strategic objectives for Indonesia’s ongoing development and industrial advancement.

Most airport development projects entail disputes due to the features that are distinctive and complicated. Disputes can be minimized through creative problem-solving by implementing knowledge management practices into the system. This study investigates the direct influence of knowledge management (KM) on dispute minimization (DM) along with the key factors for developing a strategy that can enhance KM success. A mixed method was adopted including statistical data analysis based on the PLS-SEM and descriptive analysis with the SECI (Socialization, Externalization, Combination, Internalization) model approach for strategy development. These findings show that KM has a positive and significant direct influence on DM, while the factors that are considered to have a significant influence on KM success are human resources management (HR) and learning & training (LT) on airport development projects in state-owned airport companies. This research supports the importance of a well-developed HR system accompanied by regular LT to all members of the organization to optimize and encourage the spread of knowledge in the organization.