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Putu Agung Ananta Wijaya
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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Analysis and Design of Data Warehouse on Academic STMIK STIKOM Bali Komang Budiarta; Putu Agung Ananta Wijaya; Cokorde Gede Indra Partha
International Journal of Engineering and Emerging Technology Vol 2 No 1 (2017): January - June
Publisher : Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University

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Abstract

College accreditation by BAN-PT is one of the parameters in determining the quality of universities in Indonesia. As consideration to achieve the standard from BAN-PT, so they have an evaluation process itself in study program or college to be meet the standard universities when set by the BAN-PT. In carrying out the process of self evaluation, required data source that is used as the basis in assessing on a criteria. In most of the study program, all data spread on the system information and physical document that different, that is require more time and effort to integrate up to interpret. Data warehouse fight important in collecting data that spread and become an information. The process data warehouse with ETL used to integrate, extract, clean, transforming and reload into the data warehouse. With the existence of the data warehouse on Academic STIMIK STIKOM Bali can make it easier for executives to get the information to support the standard accreditation standart three and can be used as a reference in decision making.
Bussines Intelligent in Telemarketing Using SVM Putu Agung Ananta Wijaya; Komang Budiarta; Made Sudarma
International Journal of Engineering and Emerging Technology Vol 2 No 1 (2017): January - June
Publisher : Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University

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Abstract

Direct marketing provides an advantage in approaching consumers. Communication that happens allows us more closely, able to change the behavior and know the needs required by consumers accurately. But this technique has a lack of time. It takes a long time to convince consumers to buy the products offered. Bussines intelligent with data mining approach to consumer data is required. This process will analyze the potential possessed by a consumer. At the stage of the DSS used SVM method to predict whether consumers will buy products that have been offered. Bussines intelligent built proven able to predict consumers who have the potential to buy products. Tests show the greatest prediction accuracy rate is 89.5% with a combination of data traning of 70% of the dataset.
Co-Authors Komang Budiarta Made Sudarma Tjok Gede Indra Partha