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. 

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 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 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.

Data Science

2018 ◽  
pp. 141-151
Author(s):  
Sabitha Rajagopal
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Research And Development ◽  
Real Time ◽  
Data Science ◽  
Data Warehousing ◽  
Holistic Approach ◽  
Digital Data ◽  
Data Application ◽  
Development Analysis

Data Science employs techniques and theories to create data products. Data product is merely a data application that acquires its value from the data itself, and creates more data as a result; it's not just an application with data. Data science involves the methodical study of digital data employing techniques of observation, development, analysis, testing and validation. It tackles the real time challenges by adopting a holistic approach. It ‘creates' knowledge about large and dynamic bases, ‘develops' methods to manage data and ‘optimizes' processes to improve its performance. The goal includes vital investigation and innovation in conjunction with functional exploration intended to notify decision-making for individuals, businesses, and governments. This paper discusses the emergence of Data Science and its subsequent developments in the fields of Data Mining and Data Warehousing. The research focuses on need, challenges, impact, ethics and progress of Data Science. Finally the insights of the subsequent phases in research and development of Data Science is provided.

Physical Data Warehousing Design

2011 ◽  
pp. 906-911 ◽  
Author(s):  
Ladjel Bellatreche ◽  
Mukesh Mohania
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Historical Data ◽  
Data Warehousing ◽  
Management Decision ◽  
Materialized Views ◽  
Performance Goal ◽  
Interactive Nature ◽  
Management Decision Making ◽  
Using Data

Recently, organizations have increasingly emphasized applications in which current and historical data are analyzed and explored comprehensively, identifying useful trends and creating summaries of the data in order to support high-level decision making. Every organization keeps accumulating data from different functional units, so that they can be analyzed (after integration), and important decisions can be made from the analytical results. Conceptually, a data warehouse is extremely simple. As popularized by Inmon (1992), it is a “subject-oriented, integrated, time-invariant, non-updatable collection of data used to support management decision-making processes and business intelligence”. A data warehouse is a repository into which are placed all data relevant to the management of an organization and from which emerge the information and knowledge needed to effectively manage the organization. This management can be done using data-mining techniques, comparisons of historical data, and trend analysis. For such analysis, it is vital that (1) data should be accurate, complete, consistent, well defined, and time-stamped for informational purposes; and (2) data should follow business rules and satisfy integrity constraints. Designing a data warehouse is a lengthy, time-consuming, and iterative process. Due to the interactive nature of a data warehouse application, having fast query response time is a critical performance goal. Therefore, the physical design of a warehouse gets the lion’s part of research done in the data warehousing area. Several techniques have been developed to meet the performance requirement of such an application, including materialized views, indexing techniques, partitioning and parallel processing, and so forth. Next, we briefly outline the architecture of a data warehousing system.

Data mining solutions and the establishment of a data warehouse: Corporate nirvana for the 21st Century

First Monday ◽  
1997 ◽  
Author(s):  
Christine Maxwell ◽  
Howard Gutowitz
Keyword(s):  
Data Mining ◽  
Data Warehouse ◽  
21St Century ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Data Warehousing ◽  
Knowledge Retrieval ◽  
End User ◽  
Information Mining ◽  
Complex Adaptive

Addresses the need to broaden the meaning of data mining and data warehousing to encompass information mining and knowledge retrieval into complex adaptive systems with the business end user in mind.

scholarly journals SISTEM DATA WAREHOUSE DAN DATA MINING SEBAGAI PENGUKUR KINERJA ENTERPRISE

CCIT Journal ◽  
2011 ◽  
Vol 4 (2) ◽  
pp. 172-184
Author(s):  
Henderi Henderi ◽  
Untung Rahardja ◽  
Muhammad Yusup
Keyword(s):  
Data Mining ◽  
Life Cycle ◽  
Data Warehouse ◽  
Ad Hoc ◽  
System Development ◽  
Transaction Processing ◽  
Design System ◽  
Study Analysis ◽  
System Study ◽  
Analysis Design

Sistem informasi pada organisasi sebagian besar digunakan untuk membantu pelaksanaan business process enterprise. Sistem tersebut pada umumnya belum dapat menyediakan informasi strategis dan membantu manajemen dalam melakukan evaluasi kinerja enterprise. Hal ini terjadi karena sistem informasi sebagian besar dibangun menggunakan konsep database OLTP (online transaction processing) dan bersifat ad hoc. Permasalahan ini terjadi pula pada sistem informasi di sebagian besar Perguruan Tinggi di Kota Tangerang sebagai sampel penelitian. Alternatif pemecahan masalah tersebut adalah membangun sistem informasi yang menerapkan konsep dan cara kerja data warehouse dan data mining yang dapat dijasikan sebagai tools pengukur kinerja enterprise. Metodologi pengembangan sistemnya menggunakan metode system developmnet life cycle (SDLC). Metode SDLC terdiri dari tahapan: system study, analysis design, system development, dan implementation. Melalui pendekatan ini diciptakan sebuah sistem informasi dengan konsep data warehouse dan data mining yang dapat menghasilkan informasi yang bersifat strategis, sesuai kebutuhan, dan sebagai tools melaksanakan pengukuran kinerja enterprise. Hasil akhir penelitian adalah sebuah sistem data warehouse dan data mining sebagai tools pengukur kinerja enterprise pada Perguruan Tinggi Raharja sebagai prototipe penerapannya.

Data Mining for Human Resource Information Systems

Data Mining ◽  
2011 ◽  
pp. 366-381 ◽  
Author(s):  
Lori K. Long ◽  
Mavin D. Troutt
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Information Systems ◽  
Human Resource ◽  
Data Warehousing ◽  
Organizational Decision Making ◽  
Resource Information ◽  
Potential Applications ◽  
Statistical Studies ◽  
Hr Function

This chapter focuses on the potential contributions that Data Mining (DM) could make within the Human Resource (HR) function in organizations. We first provide a basic introduction to DM techniques and processes and a survey of the literature on the steps involved in successfully mining this information. We also discuss the importance of data warehousing and datamart considerations. An examination of the contrast between DM and more routine statistical studies is given, and the value of HR information to support a firm’s competitive position and organizational decision-making is considered. Examples of potential applications are outlined in terms of data that is ordinarily captured in HR information systems.

The Research of Intelligence Data Mining Oriented to Battlefield Situation Assessment

2013 ◽  
Vol 427-429 ◽  
pp. 1662-1665
Author(s):  
Jing Xue Liu ◽  
Wei Tang
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Data Warehouse ◽  
Data Warehouses ◽  
Situation Assessment ◽  
Basic Construction ◽  
Holistic Conception

Battlefield situation assessment has a positive significance on improving the efficiency of commanding decision-making; moreover, battlefield situation assessment cannot be made successfully without the support of some integrated and exact intelligence data. In this paper, basing on the demand of identifying the battlefield situation, the corresponding knowledge context database was first discussed; on this basic, construction of the intelligence data warehouses framework was explored. Then, the study of data mining based on the intelligence data warehouse was made from the view of a holistic conception, and a detailed arithmetic was presented by making use of the tactic from data mining driven fishbone.

Marketing Decision and Decision Support System Design Based on Web

2013 ◽  
Vol 850-851 ◽  
pp. 1048-1051
Author(s):  
Guang Yu Peng
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Data Warehouse ◽  
Support System ◽  
Logical Structure ◽  
The Internet ◽  
Marketing Decision ◽  
Online Analysis Processing

This paper analyzes the DSS characteristics about the marketing under the internet as well as the influencing factors of the market decisions, Studying the decision-making functions of marketing decision support system DSS. It proposed the marketing DSS design, logical structure and its implementation based on a data warehouse as the center, online analysis processing and data mining as a means.

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