Business Intelligence Design Research Articles

BUILDING A DATAMART FOR DASHBOARD DESIGN TO DECISION SUPPORT SYSTEM OF LEGAL DIVISION

The goal of development and implementation is to identify, analyze needs, design datamart and making a dashboard for Decision Support System, especially in the data analysis process of the legal division at PT.XYZ. The design of business intelligence uses a Business Intelligence Roadmap approach that refers to justification, planning, and application prototyping. The analysis is carried out on ongoing business processes, then the results of the analysis are used as a reference in the design of the datamart and dashboard for Legal division consisting of a contract dashboard, brand dashboard, opinion dashboard, licensing dashboard, SPSK dashboard, and produce legal reports that meet the provisions of PT.XYZ. The resulting datamart and dashboard can help the Legal division of PT.XYZ perform data analysis and facilitate the decision-making process.

A Proposed Menu Engineering-Based Business Intelligence Design Using K-Means Algorithm

A Proposed Menu Engineering-Based Business Intelligence Design Using K-Means Algorithm

Design of a Sales Performance System for SMEs based on Business Intelligence and Data Warehouse

The influence of information technology today is powerful. It impacts people's lives because technological changes are running so fast and affect the way of thinking and behaving in competition in the business world and organizations. Small and Medium Enterprises (SMEs) must be able to adapt to this technology to maintain their business. It means that digitizing SMEs means integrating technology into all business activities. In this study, Toko Cerme is the object of research. The Toko Cerme is a SMEs in the form of a minimarket located in Central Java, Indonesia. The Toko Cerme takes advantage of technology to help run business processes so that they can be managed optimally. In running its business, The Toko Cerme is currently using an information system to input product data and transaction activities. The purpose of this research is to propose a Design of a Sales Performance System based on Business Intelligence and a Data Warehouse to support business processes at the Toko Cerme so that it can efficiently process data and information in the future. From the research that the authors conducted, it can be concluded that the results of this study are the creation of a data warehouse and business intelligence design using the nine steps Kimbal method. At the same time, Pentaho Data Integration (PDI) is a tool. The design is used as a reference in producing information relating to sales transactions.
 
 

Business Intelligence Design for Data Visualization and Drug Stock Forecasting

Klinik Pratama is one form of service provided by the Ministry of Communication and Information of the Republic of Indonesia in protect employees from health disorders that could affect employee productivity. In its development, the clinic often finds problems, one of them is often a shortage or excess the drug stock on a running period. Therefore, it be required a design of an Business Intelligence that manages complex data into a data visualization forecasting of the future stock of drugs. Historical data processing of the drug is done with process of Extract, Transform and Load (ETL) using the Spoon Pentaho Data Integration tools. While the visualization of drug stock data and forecast results is done using Microsoft Power BI (Business Intelligence) tools and for forecasting is done with Artificial Neural Network method by RStudio tools. The results of forecasting the amount of stock out of drug samples using the Artificial Neural Network method obtained an MSE value of 67.72 and RMSE 8.22 which means that this forecast has a good ability with the resulting error rate is relatively small. From this research, the Klinik Pratama of the Ministry of Communication and Information can easily understand and analyze drug stock data and can support operational decision making The results of forecasting the amount of stock out of drug samples using the Artificial Neural Network method obtained an MSE value of 67.72 and RMSE 8.22 which means that this forecast has a good ability because the resulting error rate is relatively small. From this research, Klinik Pratama of the Ministry of Communication and Information can easily understand and analyze drug stock data and can support operational decision making The results of forecasting the amount of stock out of drug samples using the Artificial Neural Network method obtained an MSE value of 67.72 and RMSE 8.22 which means that this forecast has a good ability with the resulting error rate is relatively small. From this research, Klinik Pratama of the Ministry of Communication and Information can easily understand and analyze drug stock data and can support operational decision making.

BUSINESS INTELLIGENCE GUNA MENDUKUNG KEPUTUSAN STRATEGIS KETUA PROGRAM STUDI DENGAN MODEL FAST

Strategic decisions taken by the head of study programs related to lecturers and students are very decisive direction of campus policy. Constraints are often faced is the absence of data and information available well to make decisions. Business Intelligence has the function of collecting and analyzing organizational data in the form of knowledge in order to produce future and medium term and long term university decisions. Business intelligence to support the study program's strategic decisions is designed based on the FAST (Framework for the Application of System Thingking) model of using UML (Unified Modelling Languange) tools. The result of this research will get business intelligence design to produce information for the head of study program in STMIK Atma Luhur to take strategic decision. Key words: Business Inteligence, FAST, Unified Modelling Languange.Â

Design of Business Intelligence in Learning Systems Using iLearning Media

In the era of modern learning, e-Learning system utilized the school as a media institution of learning that can control the effectiveness of student learning. Some of your existing online learning system is not yet able to support teaching and learning activities based on student (student oriented). This research aims to harness and develop a system that is running by adding the concept of Business Intelligence in order to measure interest and activity of students in learning system application wear online. The methods used in this research are with the method of OLAP by utilizing data mart and user needs analysis. Design of business intelligence using user interface components namely the dashboard so that the information displayed in real time and accurate. The next of this research will be known how much interest and the liveliness of the students in the following learning interactively and communicative.

Business Intelligence Design Model (BIDM) for University

ABSTRACT Information and knowledge are the backbone of any organization’s development because they are used in decision making processes. In addition, the management level of any organization is looking forward to ensure the quality and the effectiveness of the work performances depending on the knowledge to make the right decisions. But by the increased amount of information produced by the organizations the decision making processes becomes more complex and needs lots of time to be taken. Therefore, they have to upgrade their work and the way of decision making processes by using new technologies like the Business Intelligence (BI). BI can help the organizations to make the best use of information and creating a knowledge base which supports the decision making processes. Therefore, the universities as any organizations are looking forward to improve their work performances to keep pace with the world’s development and manage the increase of the volume of the information needed for the decision making process. Therefore, this research paper is to introduce a Business Intelligence Design Model (BIDM). BIDM is a model that is going to help university to use the business intelligence systems to produce the reports which achieve the accuracy, reliability and the effectiveness to support the decision making processes.

Augmenting Analytical CRM Strategies with Social BI

Large communities built around social media on the Internet offer an opportunity to augment analytical customer relationship management (CRM) strategies. The purpose of this paper is to provide direction to advance the conceptual design of business intelligence (BI) systems for implementing CRM strategies. After introducing social CRM and social BI as emerging fields of research, the authors match CRM strategies with a re-engineered conceptual data model of Facebook in order to illustrate the strategic value of these data. Subsequently, the authors design a multi-dimensional data model for social BI and demonstrate its applicability by designing management reports in a retail scenario. Building on the service blueprinting framework, the authors propose a structured research agenda for the emerging field of social BI.

Decision Support as Knowledge Creation

The primary purpose of decision support systems (DSS) is to improve the quality of decisions. Since decisions are based on an individual’s mental model, improving decision quality is a function of discovering the decision maker’s mental model, and updating and/or enhancing it with new knowledge; that is, the purpose of decision support is knowledge creation. This article suggests that BI techniques can be applied to knowledge creation as an enabling technology. Specifically, the authors propose a business intelligence design theory for DSS as knowledge creation, a prescriptive theory based on Nonaka’s knowledge spiral that indicates how BI can be focused internally on the decision maker to discover and enhance his/her mental model and improve the quality of decisions.