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All Journal International Journal of Engineering and Emerging Technology
Komang Sri Utami
Department of Electrical and Computer Engineering, Post Graduate Program, Udayana University
Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Mechanical Engineering

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Stock management using K-means method and Time Series method as Stock Order Komang Sri Utami; I Gede Wira Dharma; Ni Wayan Sri Aryani
International Journal of Engineering and Emerging Technology Vol 4 No 1 (2019): January - June
Publisher : Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University

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Abstract

Good stock management is one of the keys to success for sales businesses. A stable stock flow will affect the cost of purchasing goods and income. This condition can be achieved when the prediction of the required stock is right, so there is no accumulation of stock or empty stock. The case to be taken is for drug management of a pharmacy. This study uses the K-means method and time series method. The K-means method is a grouping method that is very easy to use and implement. Drug groupings will be made into 3 types, namely the best-selling, selling, and less-selling groups. While the regression time series method is used to predict the stock to be purchased that will be used in two weeks so that there is no stock buildup. Both of these methods are used to provide a grouping of drugs and the right amount of medicine to buy so that the management of drug stocks can be done well. The results of the tests carried out using 1000 test data, in which the K-means grouping test was C1 = 13, C2 = 29, C3 = 958 which was obtained from 11 iterations that had been done. In addition, each drug item has been predicted for the number of drugs to be purchased according to the sales performance of the last 3 months. From both of these results, it can be a reference in making order decisions to better manage stocks
Data Warehouse Analysis to Support UMKM Decisions using the Nine-step Kimball Method I Gede Wira Darma; Komang Sri Utami; Ni Wayan Sri Aryani
International Journal of Engineering and Emerging Technology Vol 4 No 1 (2019): January - June
Publisher : Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University

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Abstract

Micro, small and medium enterprises are one of the drivers of the economy. In the current technological era, companies have supported information systems to process business transactions. Naris Mart is one of the MSMEs engaged in retail with a business that has been running for 6 years. During the span of 6 years, of course, many buying and selling transactions were carried out. To help analyze how the business work, will be designed a data warehouse. Data warehouses need to be made so that they can receive information, reports, and can carry out multi-dimensional analysis that can ultimately help business owners. The design of the data warehouse uses the Nine-step Kimball methodology. Results obtained in the form of star schema and retail data warehouse analysis. The data warehouse can provide fast, accurate and continuous information that can help management in making policies for the future to come. In general, the benefit of this research is that additional references in building a data warehouse use the Nine-step Kimball methodology
Co-Authors I Gede Wira Darma I Gede Wira Dharma Ni Wayan Sri Aryani Ni Wayan Sri Aryani