Publication Search

This study aims to analyze the implementation of performance management at the micro–enterprise AMANAH YOGURT, located in Candimulyo, Kiringan, Boyolali. The business employs 11 workers with specific task divisions: 7 in packaging, 1 in production, 2 in marketing responsible for promotion and advertising, and 1 supervisor who monitors the production process while also assisting in production ac,tivities. The daily production capacity reaches 500 packs during peak demand and 350 packs under normal conditions. This research applies a descriptive qualitative approach through observations and informal interviews with the owner and employees. The findings indicate that AMANAH YOGURT has implemented performance management through the application of production SOP, clear task distribution, informal evaluative communication between the owner and employees, as well as consistent adherence to hygiene standards and product quality. AMANAH YOGURT products have been distributed across Java Island, Bali, and even Mataram through bus logistics, travel services, and direct delivery for nearby areas. Halal certification and BPOM authorization further enhance consumer trust and strengthen the competitiveness of the business.

In the current era of digital transformation, organizations are increasingly turning to Artificial Intelligence (AI) to enhance the precision and agility of managerial decisions. This study investigates how AI adoption within management accounting systems influences decision-making efficiency and managerial performance. Using survey data collected from managers and accountants in medium-to-large firms across Central Java, the research applies Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the hypothesized relationships. The results reveal that AI adoption significantly improves decision-making efficiency, which in turn enhances managerial performance. Furthermore, leadership support strengthens the relationship between AI adoption and decision-making efficiency, indicating that human and organizational factors remain critical for realizing technological benefits. The findings contribute to management accounting literature by elucidating the mechanism through which AI technologies create managerial value specifically, by accelerating analytical processes and improving the quality of managerial judgments. Practically, the study suggests that firms should focus on leadership involvement, data governance, and employee training to ensure that AI systems complement, rather than replace, human judgment. Overall, this study highlights that successful AI adoption in management accounting is not merely a technical transition but a strategic and cultural evolution toward evidence-based decision-making.

CV Cielofood Pratama is a beverage processing business with nutmeg raw materials, located in Bogor City, West Java. The company produces syrups with varying sizes of packaging. The multi-stage production process does not rule out the possibility of irregularities that could cause the product to no longer meet the quality standards we set. In general, business units have a profit goal for business sustainability, by seeking efficiency in operations in order to obtain profitable profits. Analysis of the data shows the difference between corporate policy and the results of the EOQ method. The company usually orders 25 kg of raw materials with a frequency of 120 times per year. However, the EOQ method recommends ordering 144 kg with a frequency of 36 times per year. In addition, there is a significant difference in the total cost of supplies, which is IDR 30,900,000 according to company policy and IDR 10,392,000 according to EOQ method. This study aims to analyze strategies in raw material supply as an effort for supply chain efficiency. Using the Economic Orders Quantity (EOQ) method Reduce storage costs, save space on both storage and workspaces, resolve problems and reduce the risk that raw material supplies may pose.  

Divorce cases in West Java Province have increased every year. The profile map of divorce cases that occurred in each region is not yet known, so efforts to provide guidance to minimize divorce cases are not optimal. Divorce case data is also not equipped with a visualization feature that makes it easier for authorized officials to easily understand and analyze data. This study analyzes divorce cases in regencies/cities in West Java Province, using the K-Means Algorithm Clustering data mining method. The clustering method is grouping data based on the same characteristics. In determining the number of clusters, that is by using the value of the Davies Bouldin Index. The results of this study obtained the best cluster of grouping divorce cases, there were 2 clusters, namely cluster 0, there were 5 regencies and 9 cities, while in cluster 1 there were 13 regencies, with a Davies Bouldin index value of 0.168 and an avg.within centroid distance value of 5,870. Cluster 0 is the city/district with the lowest divorce cases and cluster 1 is the city/district with the highest divorce cases.