scholarly journals Desain Data Warehouse pada Sistem Informasi Sumber Daya Manusia Sub-Sistem Rekrutmen

2012 ◽  
Vol 3 (1) ◽  
pp. 307
Author(s):  
Eka Miranda
Keyword(s):  
Decision Making ◽  
Resource Management ◽  
Data Warehouse ◽  
High Performance ◽  
Ad Hoc ◽  
Process Efficiency ◽  
Literature Study ◽  
Recruitment Activities ◽  
Warehouse Design ◽  
Transactional Data

Employees as a resource management are essential to improve the effectiveness of company’s performance and process efficiency. This paper discusses the implementation of data warehouse and its role in assisting the decision making related to recruitment activities undertaken by Human Resources Department. In this research built a data warehouse design to store large amounts of data and to gain potentially a new perspective of data distribution as well as to provide reports and solutions for users the ad hoc question and to analyze the transactional data. This study aims to design a data warehouse to support accurate decision making related to human resource management in order to create high performance productivity. The method used in this paper consists of: (1) data collection using interview and literature study related to employee recruitment and (2) data warehouse design derived from Teh Ying Wah et al. This research results in a data warehouse design and its implementation to analyze transactional data from the related activities of recruitment and employee management to support decision making.

scholarly journals Implemetasi Data Warehouse pada Bagian Pemasaran Perguruan Tinggi

2012 ◽  
Vol 3 (1) ◽  
pp. 315
Author(s):  
Eka Miranda ◽  
Rudy Rudy ◽  
Eli Suryani
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Data Warehouse ◽  
Ad Hoc ◽  
External Data ◽  
Study Results ◽  
Marketing Activities ◽  
Warehouse Design ◽  
Transactional Data ◽  
Support Decision Making

Transactional data are widely owned by higher education institutes, but the utilization of the data to support decision making has not functioned maximally. Therefore, higher education institutes need analysis tools to maximize decision making processes. Based on the issue, then data warehouse design was created to: (1) store large-amount data; (2) potentially gain new perspectives of distributed data; (3) provide reports and answers to users’ ad hoc questions; (4) perform data analysis of external conditions and transactional data from the marketing activities of universities, since marketing is one supporting field as well as the cutting edge of higher education institutes. The methods used to design and implement data warehouse are analysis of records related to the marketing activities of higher education institutes and data warehouse design. This study results in a data warehouse design and its implementation to analyze the external data and transactional data from the marketing activities of universities to support decision making.

scholarly journals Perancangan Model Data Warehouse dan Perangkat Analitik untuk Memaksimalkan Proses Pemasaran Hotel: Studi Kasus pada Hotel Abc

2013 ◽  
Vol 4 (1) ◽  
pp. 230
Author(s):  
Eka Miranda
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Business Processes ◽  
Ad Hoc ◽  
Raw Material ◽  
Decision Making Process ◽  
Literature Study ◽  
Analysis Process ◽  
Marketing Area ◽  
New Perspective

The increasing competition in hotel business forces every hotel to be equiped with analysis tools that can maximize its marketing performance. This paper discusses the development of a data warehouse model and analytic tools to enhance the company's competitive advantage through the utilization of a variety of data, information and knowledge held by the company as a raw material in the decision making process. A study is done at ABC Hotel which uses a database to save the transactional record. However, the database cannot be directly used to support analysis and decision making process. Based on this issue, the company needs a data warehouse model and analytic tools that can be used to store large amounts of data and also potentially to gain a new perspective of data distribution which allows to provide reporting and answers of ad hoc users questions and assist managers in making decisions. Further data warehouse model and analytic tools can be used to help manager to formulate planning and marketing strategies. Data are collected through interviews and literature study, followed by data analysis to analyze business processes, to identify the problems and the information to support analysis process. Furthermore, data warehouse is designed using analysis of records related to the activities in hotel's marketing area and data warehouse model. The result of this paper is data warehouse model and analytic tools to analyze the external and transactional data and to support decision making process in marketing area.

scholarly journals Data Warehouse, Data Mining Dan Konsep Cross-Selling Pada Analisis Penjualan Produk

2010 ◽  
Vol 1 (2) ◽  
pp. 344
Author(s):  
Eka Miranda ◽  
Natalya Elfreida
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Data Warehouse ◽  
Ad Hoc ◽  
Data Warehousing ◽  
Problem Analysis ◽  
Literature Study ◽  
Product Analysis ◽  
Huge Amount ◽  
Design And Testing

This paper is about designing and implementing data warehousing and data mining, along with their roles in supporting decision-making related to sales product analysis in cross-selling concept of PT XYZ. The database the company used is not supporting data analysis and decision-making. Therefore, it made a data warehousing design that could be used to keep data in a huge amount and could give report and answer from user’s questions in ad hoc. The method is used to design and implement data warehousing and data mining which consists of literature study, company problem analysis, and data warehousing design, and testing result. The writing results are a data warehousing design and data mining and also the implementation of cross-selling concept to analysis the sales, purchases, and customers’ cancellation data. The data could be showed and analyzed from some point of views that could help managers to analyse and acknowledge more information. 

A New Architecture for Large Data Warehouse

2011 ◽  
Vol 55-57 ◽  
pp. 87-90
Author(s):  
Gang Li ◽  
Xing San Qian ◽  
Chun Ming Ye
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Business Intelligence ◽  
High Performance ◽  
Lower Cost ◽  
Large Data ◽  
Current Data

Data warehouse is playing a more and more important role in company’s decision making; it is the basis for a typical business intelligence solution. The paper points out the reasons why data warehouse projects failed and by analyzing the current data warehouse architectures, as well as technologies used in industry, a new data warehouse architecture is proposed which has many advantages over current ones, for example, it is extensible, reusable, flexible and with high performance and lower cost.

scholarly journals Warehouse Data System Analysis PT. Kanaan Global Indonesia

2020 ◽  
Vol 1 (3) ◽  
pp. 70-73
Author(s):  
Tino Feri Efendi ◽  
Mutiya Krisanty
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Inventory Control ◽  
Research Method ◽  
System Analysis ◽  
Historical Data ◽  
Decision Making Process ◽  
Literature Study ◽  
Precise Information ◽  
Operational Systems

Data Warehouse is a computer system for archiving and analyzing historical data of an organization. An organization copies information from its operational systems to a warehouse. The purpose of this research is to help provide information in supporting the decision-making process in the field of sales, purchasing and material inventory control at PT Kanaan Global Indonesia. PT Kanaan Global Indonesia previously presented the data warehouse manually. By designing a data warehouse system, company leaders can be more assisted in making decisions that are faster and more precise. The research method used includes analysis of observations, interviews, documentation and literature study. The result of this research is the availability of a data warehouse that can produce fast and precise information, thus helping the company in making decisions.Keywords— Data, Information, Warehouse

scholarly journals A development framework for decision support systems in high-performance sport

2020 ◽  
Vol 19 (1) ◽  
pp. 1-23 ◽  
Author(s):  
Xavier Schelling ◽  
Sam Robertson
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
High Performance ◽  
Injury Risk ◽  
Support Systems ◽  
System Development ◽  
Process Efficiency ◽  
Cognitive Limitations ◽  
Development Framework

AbstractDecision making in sport involves forecasting and selecting choices from different options of action, care, or management. These processes are conditioned by the available information (sometimes limited, fallible, or excessive), the cognitive limitations of the decision-maker (heuristics and biases), the finite amount of available time to make the decision, and the levels of risk and reward. Decision support systems have become increasingly common in sporting contexts such as scheduling optimization, skills evaluation and classification, decision-making assessment, talent identification and team selection, or injury risk assessment. However no specific, formalised framework exists to help guide either the development or evaluation of these systems. Drawing on a variety of literature, this paper proposes a decision support system development framework for specific use in high-performance sport. It proposes three separate criteria for this purpose: 1) Context Satisfaction, 2) Output Quality, and 3) Process Efficiency. Underpinning these criteria there are six specific components: Feasibility, Delivered knowledge, Decisional guidance, Data quality, System error, and System complexity. The proposed framework offers a systematic approach for users to ensure that each of the six components are considered and optimised before, during, and after developing the system. A DSS development framework for high-performance sport should help to improve both short and long term decision-making in a variety of sporting contexts.

scholarly journals Implementasi Pengembangan Sistem Model Water Fall Untuk Data Warehouse Akademik

2017 ◽  
Vol 1 (2) ◽  
pp. 108
Author(s):  
Arik Sofan Tohir Sofan Tohir ◽  
Kusrini Kusrini ◽  
Sudarmawan Sudarmawan
Keyword(s):  
Data Warehouse ◽  
Flow System ◽  
Step Method ◽  
Good Data ◽  
Analysis Process ◽  
Warehouse Design ◽  
Waterfall Model ◽  
Transactional Data ◽  
Model Water ◽  
Selection Of

  Data warehouse is a concept and a technology to store transactional data from several sources that have been through the process of filtering and selection of data. By using the Ectract, Transform and Load (ETL) process in the data warehouse, OLTP data is processed to produce good data and ready for use for the analysis process. For the design of this warehouse data will be built by using the Nine Step Method from Kimbal, so that the resulting warhouse data can be as expected. For the development of life flow system (SDLC) with waterfall model. By using the wate fall model will be built a prototype to implement the data warehouse design results.

scholarly journals Implementasi Data Warehouse dan Data Mining: Studi Kasus Analisis Peminatan Studi Siswa

2011 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Eka Miranda
Keyword(s):  
Data Mining ◽  
Academic Achievement ◽  
Decision Making ◽  
Data Analysis ◽  
Data Warehouse ◽  
Ad Hoc ◽  
Data Distribution ◽  
Program Selection ◽  
Mining Design ◽  
The University

This paper discusses the implementation of data mining and their role in helping decision-making related to students’ specialization program selection. Currently, the university uses a database to store records of transactions which can not directly be used to assist analysis and decision making. Based on these issues then made the data warehouse design used to store large amounts of data and also has the potential to gain new data distribution perspectives and allows to answer the ad hoc question as well as to perform data analysis. The method used consists of: record analysis related to students’ academic achievement, designing data warehouse and data mining. The paper’s results are in a form of data warehouse and data mining design and its implementation with the classification techniques and association rules. From these results can be seen the students’ tendency and pattern background in choosing the specialization, to help them make decisions. 

scholarly journals RANCANGAN DATA WAREHOUSE AKADEMIK POLITEKNIK PARIWISATA BALI BERBASIS LINUX OPENSUSE

2021 ◽  
Vol 4 (1) ◽  
pp. 18-25
Author(s):  
I Gusti Agung Made Wirautama ◽  
I Made Candiasa ◽  
Gede Rasben Dantes ◽  
I Putu Agus Eka Pratama
Keyword(s):  
Information System ◽  
Information Systems ◽  
Open Source ◽  
Data Warehouse ◽  
Literature Study ◽  
Research Information ◽  
Warehouse Design ◽  
Academic Information ◽  
The Right ◽  
Open Source Hardware

This study aims to design an academic data warehouse at Politeknik Pariwisata Bali because there are several information systems that require a system capable of handling databases of several existing information system applications and perform analysis. A data warehouse is the right solution for handling databases of several information systems that are not yet integrated. The research method begins with literature study, identification of problems, determining research objectives, designing solutions, namely designing an academic data warehouse, determining the hardware and software specifications needed, and ending with discussions and drawing conclusions. The result of this research is an academic data warehouse design that can be implemented properly. Besides, the results of this study are also accompanied by specifications for open-source hardware and software to save costs. The data warehouse design produced in this study uses a database of 3 information systems which is the main business process of a college, namely: Academic Information System, Information System for New Student Admissions, Research Information System. The three databases of the information system are internal data sources using the MySQL DBMS. The resulting academic data warehouse design uses open source software, namely: openSUSE, Pentaho Data Integration, MySQL DBMS.

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