Publication Search

The gap between academic curriculum content and modern industrial needs is often an obstacle for fresh graduates in the Information Technology field, particularly in the rapidly evolving Artificial Intelligence (AI) sector. This study aims to identify the relationship patterns among technical competencies (hard skills) most demanded by the global industry. The method employed is Association Rule Mining with the Apriori algorithm to discover association rules between skills, and Network Graph Analysis to visualize the topological map of these competencies. The research dataset covers 15,000 AI job vacancies from the 2024-2025 period, analyzed in depth using Support, Confidence, and Lift Ratio evaluation parameters to validate the strength of relationships between items. The results show that Python is the central competency with the highest frequency of occurrence. Strong association rules were found indicating that proficiency in TensorFlow has a high probability of requiring Python proficiency. The Network Graph visualization reveals three main competency clusters: Data Engineering Ecosystem, Deep Learning, and Infrastructure. These findings offer a strategic foundation for aligning curricula with the job market. Focusing on strengthening the identified competency clusters is expected to directly enhance the relevance and work readiness of graduates.

The shift in economic structure from a reliance on traditional agriculture to modern industrialization has yielded various competitive advantages for a region. The presence of leading sectors at the local level is a strong indicator of increased added value and high productivity, fueled by a healthy competitive climate among business actors. This phenomenon is closely related to the characteristics of the industrial sector, which possesses very strong forward and backward linkages, making it a primary driver of national economic growth. Progress in the manufacturing sector is not merely a measure of economic success but also serves as a driver of fiscal stability through massive employment absorption and increased foreign exchange earnings. Industrial growth is considered highly strategic because it holds significant potential for future expansion through technological innovation and production efficiency. This condition makes industrial cluster development an instrument for driving sustainable economic growth in Indonesia, while simultaneously strengthening the competitiveness of local products in the global market through the integration of a more organized production system.

This study investigates the strategic strengthening of the rambak cracker industry as an instrument for local economic development in Penanggulan Village, Pegandon District, Kendal Regency. Rural agro-processing enterprises have increasingly been recognized as territorially embedded production units capable of generating value-added outputs and absorbing surplus labor within localized economic systems. Field-based empirical observations reveal that rambak production in the village operates through household-managed processing systems characterized by traditional production techniques, informal managerial practices, and limited digital marketing adoption despite contributing significantly to community income generation. Data obtained from expert respondents were analyzed using the Analytical Hierarchy Process to identify strategic priority determinants influencing industrial competitiveness and sustainability. The results indicate that product innovation and quality improvement constitute the primary strategic priority, followed by digital marketing development and institutional partnership strengthening, while production capacity expansion remains comparatively less influential in enhancing market competitiveness. These findings suggest that adaptive innovation and digitally enabled commercialization pathways function as critical mechanisms for improving value-chain integration and expanding market accessibility among rural food-processing industries. Strengthening innovation ecosystems within the rambak sector may therefore contribute to employment creation, income diversification, and sustainable community-based economic transformation in rural production clusters.

The development of small and medium enterprises (SMEs) and household industries is often regarded as the economic foundation of a region. However, much of the existing research in Indonesia remains focused on quantitative descriptive analysis, while providing limited attention to spatial dynamics and interregional disparities. This study aims to critically evaluate the spatial distribution patterns of SMEs and household industries at the regency and city levels, with particular emphasis on clustering tendencies, unequal distribution, and their relationships with regional characteristics. A spatial analysis approach is employed to identify spatial autocorrelation and industrial clustering patterns, which is complemented by a structural analysis of infrastructure availability, market accessibility, and regional institutional capacity. The findings indicate that the distribution of SMEs and household industries is not geographically random, but rather forms clusters that are predominantly concentrated in areas with higher levels of accessibility and economic activity. This condition reflects spatial inequality that may exacerbate development disparities between regencies and cities. Furthermore, the results reveal that uniform industrial development policies are insufficient to accommodate the diverse spatial characteristics across regions. Therefore, this study underscores the importance of formulating spatially informed and context-sensitive policies for the development of SMEs and household industries in order to promote more balanced and sustainable regional industrial development.

Cilegon City, located in Banten Province, is recognized as a vital industrial hub contributing to Indonesia's economic growth. However, the city's investment competitiveness still requires substantial enhancement to attract both domestic and foreign investors. This study focuses on developing a strategy to strengthen the investment competitiveness of Cilegon City, primarily through optimizing its industrial sectors and innovating public services. The research adopts a descriptive qualitative approach, using literature reviews, interviews, and observations of local policies and conditions to gather data. The findings suggest that improving investment competitiveness can be achieved through the development of industrial clusters, providing necessary supporting infrastructure, and enhancing public service efficiency, particularly through digitalization and innovations in the licensing process. Additionally, fostering collaboration between local governments, businesses, and the community is essential for creating a competitive and sustainable investment environment. Public service innovation, especially in streamlining the licensing process, increases transparency and builds investor confidence. The study concludes that with an integrated strategy, Cilegon City can transform into a top industrial investment destination with the potential to compete effectively on both national and international levels. This research highlights the importance of strategic planning, innovation, and collaborative efforts in positioning Cilegon as a globally competitive industrial center, enhancing its attractiveness to investors and contributing to economic development.

Structural transformation is an important process in the economic development of a country. In Indonesia, the plan to move the National Capital City (IKN) from Jakarta to Nusantara in East Kalimantan is one of the strategic steps in accelerating structural transformationThe methodology used in this study is a qualitative and quantitative approach. The results of the study show that the acceleration of structural transformation through the development of IKN has a significant impact on the formation of a new economic base and increasing Indonesia's competitiveness. The formation of a new economic base in IKN can be seen from the emergence of technology and innovation-based industrial clusters. The impact on national competitiveness can be seen from the increase in productivity and innovation capacityThe analysis of the acceleration of structural transformation through the development of the IKN shows a fundamental change in Indonesia's economic base. The development of IKN as a smart forest city accelerates structural transformation through three main mechanisms. The impact on the formation of a new economic base can be seen from the shift in the economic structure in the IKN area and its surroundings. Structural transformation is also reflected in changes in the composition of the workforce and investment patterns. The impact analysis on Indonesia's competitiveness shows a significant increase in several dimensions

Structural transformation is an important process in the economic development of a country. In Indonesia, the plan to move the National Capital City (IKN) from Jakarta to Nusantara in East Kalimantan is one of the strategic steps in accelerating structural transformationThe methodology used in this study is a qualitative and quantitative approach. The results of the study show that the acceleration of structural transformation through the development of IKN has a significant impact on the formation of a new economic base and increasing Indonesia's competitiveness. The formation of a new economic base in IKN can be seen from the emergence of technology and innovation-based industrial clusters. The impact on national competitiveness can be seen from the increase in productivity and innovation capacityThe analysis of the acceleration of structural transformation through the development of the IKN shows a fundamental change in Indonesia's economic base. The development of IKN as a smart forest city accelerates structural transformation through three main mechanisms. The impact on the formation of a new economic base can be seen from the shift in the economic structure in the IKN area and its surroundings. Structural transformation is also reflected in changes in the composition of the workforce and investment patterns. The impact analysis on Indonesia's competitiveness shows a significant increase in several dimensions

Indonesia, based on natural resource potential, has great potential to achieve beef self-sufficiency. The contribution of this sector is not only limited to meeting food needs in the form of beef, but also includes economic aspects such as providing employment opportunities, industrial raw materials, and increasing the income of local farmers. This shows that the development of this sector has great potential in supporting food security and improving community welfare. Therefore, research was conducted on performance indicators that could influence the performance of the cattle farming sector in Indonesia in 2022 using cluster analysis. Cluster analysis is a statistical method that identifies groups of samples based on similar characteristics. Cluster analysis has two methods, namely hierarchical and non-hierarchical. This research focuses on classifying regions in Indonesia into groups based on similar characteristics. In this research, cluster analysis assumptions will be tested, namely the multivariate normal distribution test, conducting cluster analysis using hierarchical and non-hierarchical methods, characterizing the data in each cluster, then drawing conclusions and suggestions from the research results. Based on the research results obtained on data characteristics, it was found that variables tend to have a variety of data. Hierarchical cluster analysis uses the single linkage method which has an optimum number of clusters of 4. The highest number of cluster members is in cluster 1. Then cluster 1 shows the highest performance in the cattle farming sector. In non-hierarchical cluster analysis using the k-means method which has an optimum number of clusters of 5. The highest number of cluster members is in cluster 4. Then clusters 2, 3 and 4 show higher performance in the cattle farming sector compared to clusters 1 and 5 .

This research aims to analyze the structure of competitive forces and industrial clusters. Using Porter's five forces model framework, this research evaluates the key elements that influence competitiveness in a particular industry. This study also utilizes an industrial cluster approach to understand the dynamics of groups of companies operating in the same or related sectors. The research results show that factors such as the threat of new entrants, the bargaining power of suppliers, the bargaining power of buyers, the threat of substitute products, and competition between companies have a significant role in determining the structure of competition. In addition, industrial cluster analysis shows that synergy between companies in a cluster can increase operational efficiency and innovation, thereby strengthening competitive positions in the market. It is hoped that these findings will provide insight for companies and policy makers to formulate effective strategies in facing competition and exploiting the potential of industrial clusters.  

This research aims to analyze the performance structure and identify superior industrial clusters in Indonesia. Using secondary data from various sources, this research adopts a quantitative and qualitative approach to evaluate industrial performance based on key economic indicators such as production growth, productivity and contribution to GDP. Cluster analysis techniques are used to group industries that show superior performance. The analysis results show that several industrial clusters, such as high-tech manufacturing and financial services, perform much better than other sectors. These findings provide important insights for policy makers and industry players in formulating more effective and sustainable economic development strategies.  

The development of Small and Medium Enterprises (SMEs) is one of the government's priorities, especially in Tebing Tinggi City. Known as an industrial city, it becomes an opportunity for the development of SMEs, which are the majority of the workers. The development of SMEs, especially "Culinary Clusters" that have high added value to economic growth, needs to be given greater attention to developed. The purpose of this study is to analyze the factors that influence the business performance of SMEs in Batam City. The method used to determine the relationship between these factors uses partial least square- structural equation modeling (PLS-SEM) with SmartPLS 3.0 software. The results of data processing show that internal and external factors influence the performance of SMEs. External factors consist of government policies, socio-economic conditions, and culture, the role of related institutions has a significant influence on the condition of internal factors consisting of aspects of human resources, finance, technical production, and marketing. External and internal factors have a positive and significant influence on the performance of SMEs.

This study discusses the analysis of the power structure of leading industry clusters in Sidoarjo Regency. Sidoarjo Regency is one of the districts in East Java Province that has the potential and success in developing the local economy through the formation of industrial clusters. This study uses descriptive qualitative research methods by collecting secondary data through literature analysis. The results of the analysis show that factors such as superior natural resources, infrastructure availability, labor skills, research and innovation facilities, and government support policies affect the successful formation of leading industrial clusters in Sidoarjo Regency. Industrial clusters increase productivity, efficiency, innovation and commercialization. This study provides an understanding of the characteristics and dynamics of leading industry clusters in Sidoarjo Regency and the factors that influence efficiency. The results of this study can be the basis for further development to optimize the economic potential of the region with the help of industrial clusters.

Industry clusters, which consist of a group of companies related geographically and sectorally, have become the focus of attention in regional economic and business strategy studies. This study uses an industrial structure analysis approach to understand the strength of competition within an industry cluster. Some of the factors analyzed include the level of industry concentration, new entries, bargaining power of buyers and suppliers, as well as product or service substitution. The data used in this study includes information about the companies that are members of the industrial cluster studied. The research method used includes secondary data collection, such as company financial reports, industry data, and related publications. In addition, interviews with industry stakeholders were also conducted to gain deeper insights into the structure of competitive forces and the factors that influence industrial clusters. The results of the analysis show that the structure of competitive forces in industry clusters can vary depending on the industrial sector studied. This research contributes to our understanding of how the structure of competitive forces and industry clusters can shape a competitive business environment, as well as providing useful insights for the development of effective business strategies within industry clusters.