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Dea Sabrina; Syarifur Ridho; Fahmi Rinaldi; Fadiyah Hani Sabila

Jurnal Transformasi Bisnis Digital 2024 Asosiasi Riset Ilmu Manajemen Kewirausahaan dan Bisnis Indonesia

This paper explains the role of technology in optimizing container yard (CY) management at PT. Masaji Kargosentra Tama Belawan. PT. Masaji Kargosentra Tama Belawan is a shipping company that is a multimodal transport business entity, this company operates in the field of domestic warehousing services and import and export container Freight Station (CFS), with warehouse supply and distribution services. The container yard is one of PT's main facilities. Masaji Kargosentra Tama Belawan is used to form containers to minimize the risk of ship delays resulting in decreased loading and unloading production. In managing container yards, there are obstacles, including incompetent human resources and high implementation costs. For this reason, the purpose of writing this paper is to determine the role of technology in optimizing container yard (CY) management. The method used in this writing is field research (field research) where the author makes direct observations at the company and library research (library research) where the author obtains paper material from books in the library or other reading sources related to the main points. taken is the Role of Technology in Optimizing Container Yard (CY) Management at PT. Masaji Kargosentra Tama Belawan.

Radite Ranggi Ananta; Aura Aulia

Jurnal Manajemen dan Ekonomi Bisnis 2024 Pusat Riset dan Inovasi Nasional

Regional economic development is significant in improving the community's standard of living. The success of this development depends on formulating and implementing policies that prioritize sectors with substantial competitive advantages. This research aims to analyze the base and non-base sectors that comprise the economy and the typology of leading sectors to be developed further in Kebumen Regency. The method used in this research is quantitative descriptive to describe the characteristics of Kebumen Regency's economic sectors systematically. The data used is secondary data obtained from the Central Bureau of Statistics (BPS) in the form of Gross Regional Domestic Product (GRDP) data for Kebumen Regency and Central Java Province in 2023. Three analytical tools are used to analyze the leading sectors: Location Quotient (LQ), Dynamic Location Quotient, and Sectoral Klassen Typology. The research results show that five leading sectors in Kebumen Regency are classified as base and prospective sectors, namely (1) Agriculture, Forestry, and Fisheries, (2) Wholesale and Retail Trade, (3) Transportation and Warehousing, (4) Government Administration, Defense, and Mandatory Social Security, and (5) Health Services and Social Activities.

Asanka, PPG Dinesh; Mahanama, Thilini V.

Journal of Computing Theories and Applications 2024 Universitas Dian Nuswantoro

Bridging the gap between theoretical knowledge and practical application remains challenging in big data education. Our paper proposes a platform where students actively participate in a role-based learning (RBL) exercise designed to simulate real-world big data projects. This RBL exercise assigns each student participant to a business analyst role tasked with eliciting requirements or a customer role that provides those big data requirements. We conducted RBL sessions for postgraduate and undergraduate students learning big data analytics/data warehousing. Through role-playing in a collaborative environment, students face challenges such as unclear objectives, data privacy concerns, and evolving requirements. We evaluated the effectiveness of RBL simulations through brainstorming sessions, which verified that the students achieved the learning outcomes through RBL exercises. We also collected students’ feedback through a survey and found the RBL experience helped us understand the big data requirement elicitation skills, highlighting the significance of communication and collaboration skills. Further, we have evaluated students through a final exam question, and identified that students who participated in the RBL exercise outperformed in the big data requirement elicitation question. In summary, our research demonstrates that this RBL approach offers a valuable learning experience by enabling students to directly experience the complexities of big data requirement elicitation and identify the future requirements or challenges that encourage them to acquire the required skills.