02935ntm a2200337 i 4500 0 0 lcc 0 6 10000 10000 2025-05-06 0 CD13593 T000003191 2025-05-06 00:00:00 2025-05-06 PSM 102504 102510 MY-KuUP 20251125111038.0 t||||fs|||| 000 0 ta 250506t20232023my a|||fs|||| 000 0 eng d THE0010038 (Local) Hardback UMPSA eng UMPSA rda PSM .A37 2023 r Bc. Nur Aishah Mohd Rahim, author. Supply chain dashboard accelerator (advanced visualization) / Nur Aishah Bt Mohd Rahim Kuantan Pahang : UMPSA, 2023 © 2023 xiii, 97 pages : illustrations ; 1 CD-ROM rdacontent text rdamedia unmediated rdacarrier volume rda text file PDF Center for Mathematical Sciences Bachelor of Applied Science In Data Analytics With Honour -- Universiti Malaysia Pahang – 2023 Includes bibliographical references The supply chain is the flow of products and services provided by the company to customers and suppliers from raw materials to the final products. Precisely, procurement is the main part in the supply chain that helps businesses to achieve their objectives especially in expenditure. However, only looking at the procurement dataset will not give an understanding of information for the businesses. Inability to identify the groups that impact spending in procurement also give some challenges to the businesses. Lastly, there are always problems that need to be solved in order to achieve the objectives of the businesses. Hence, this research aims to give better insight regarding the procurement to the businesses in order to enhance and improve the company. Therefore, the first aim is creating an informative dashboard regarding the procurement in supply chain. The goal of the procurement dashboard is to give better insight into the businesses. Thus, businesses are able to predict and achieve their goals to improve their company. Next aim that needs to be achieve is to cluster the spending in the procurement by using machine learning models which are DBSCAN and K-Means. In order to analyze the procurement analytics, spending is the key to improve procurement. K-Means has a higher accuracy in fitting the model compared to DBSCAN. K-Means give the best result in clustering the spending in procurement. Hence, by clustering spending, businesses are able to suggest the best recommendations based on the insight of dashboards to improve spending which will be the last objective that need to be achieved. Through this research, businesses are able to suggest better solutions for supply chain problems for the company’s growth. Center for Mathematical Sciences Dissertations Universities and colleges Dissertations Final Year Report Dissertations lcc PSM