scholarly journals KAJIAN TERHADAP STRUKTUR MIKRO PASAR VALAS ANTAR BANK DOMESTIK

2004 ◽  
Vol 7 (1) ◽  
Author(s):  
Aida S. Budiman ◽  
Nanang Hendarsah ◽  
M. Noor Nugroho ◽  
Evy Silviani
Keyword(s):  
Foreign Exchange ◽  
Business Intelligence ◽  
High Frequency ◽  
Foreign Bank ◽  
Short Term ◽  
Credit Line ◽  
National Bank ◽  
On Line ◽  
Analytical Processing ◽  
Intelligence Application

Price fluctuation on foreign exchange induces a complex consequences on financial market. Understanding micro structure of forex market and their linkage to other market will help central bank to maintain ‘targeted’ value of Rupiah and to ensure the economy recovery post crisis. We apply business intelligence application namely On-Line Analytical Processing (OLAP) to deal with huge and high frequency data from Pusat Informasi Pasar Uang (PIPU) during period of January 2003 up to 20 June 2003. Using this tool, we can analyze characteristic of any observable market blocks including market clearance status and their inter-linkage (flow of transactions). The result shows that swap transaction dominates foreign exchange transaction, followed by spot and forward. The swap transaction is mostly used to maintain short term liquidity in inter bank market. From all of the three types of transaction, foreign bank plays important role because they have ‘greater’ access on Pasar Uang Antar Bank (PUAB), meanwhile national bank face credit line policy hence 90% of foreign exchange placement is directed to foreign bank.

Evolutionary Intelligent Data Warehousing Approach to Knowledge Discovery Systems: Dynamic Cubing

2019 ◽  
Vol 13 ◽  
Author(s):  
Harkiran Kaur ◽  
Kawaljeet Singh ◽  
Tejinder Kaur
Keyword(s):  
Knowledge Discovery ◽  
Data Warehouse ◽  
Business Intelligence ◽  
End Users ◽  
Processing Stage ◽  
Information Update ◽  
On Line ◽  
Analytical Processing ◽  
Warehouse Operations ◽  
Made In

Background: Numerous E – Migrants databases assist the migrants to locate their peers in various countries; hence contributing largely in communication of migrants, staying overseas. Presently, these traditional E – Migrants databases face the issues of non – scalability, difficult search mechanisms and burdensome information update routines. Furthermore, analysis of migrants’ profiles in these databases has remained unhandled till date and hence do not generate any knowledge. Objective: To design and develop an efficient and multidimensional knowledge discovery framework for E - Migrants databases. Method: In the proposed technique, results of complex calculations related to most probable On-Line Analytical Processing operations required by end users, are stored in the form of Decision Trees, at the pre- processing stage of data analysis. While browsing the Cube, these pre-computed results are called; thus offering Dynamic Cubing feature to end users at runtime. This data-tuning step reduces the query processing time and increases efficiency of required data warehouse operations. Results: Experiments conducted with Data Warehouse of around 1000 migrants’ profiles confirm the knowledge discovery power of this proposal. Using the proposed methodology, authors have designed a framework efficient enough to incorporate the amendments made in the E – Migrants Data Warehouse systems on regular intervals, which was totally missing in the traditional E – Migrants databases. Conclusion: The proposed methodology facilitate migrants to generate dynamic knowledge and visualize it in the form of dynamic cubes. Applying Business Intelligence mechanisms, blending it with tuned OLAP operations, the authors have managed to transform traditional datasets into intelligent migrants Data Warehouse.

scholarly journals Pengembangan Business Intelligence Dashboard untuk Monitoring Aktivitas Pariwisata (Studi Kasus: Dinas Pariwisata Provinsi Bali)

2021 ◽  
Vol 8 (6) ◽  
pp. 1159
Author(s):  
Evan Himawan Saragih ◽  
I Putu Agung Bayupati ◽  
Gusti Agung Ayu Putri
Keyword(s):  
Business Intelligence ◽  
System Development ◽  
Black Box ◽  
Percentage Error ◽  
Double Exponential ◽  
Black Box Testing ◽  
On Line ◽  
Analytical Processing ◽  
Double Exponential Smoothing ◽  
Model View

<p class="Judul2">Bali merupakan satu dari beberapa destinasi wisata yang mendatangkan wisatawan nusantara dan mancanegara di Indonesia. Pada tahun 2017, wisatawan mancanegara yang berkunjung ke Bali adalah sebesar 5,6 juta orang dan didominasi oleh wisatawan dari negara Cina. Jumlah kunjungan pada seluruh objek wisata yang ada di Bali tahun 2017 mencapai 17,8 juta kunjungan. Berdasarkan hal tersebut, pemerintah daerah membutuhkan strategi dan keputusan dalam pembangunan sarana dan prasarana yang dapat mendukung pengembangan dan kemajuan pariwisata di Bali. Pemanfaatan teknologi <em>business intelligence</em> dalam menganalisa data dalam jumlah yang besar akan membantu. Penelitian ini mengembangkan sistem informasi memakai pendekatan BI dalam menganalisis data pariwisata Bali dan manajemen data dengan menggantikan pemakaian kertas menjadi media komputer sehingga data tidak hilang begitu saja, namun digunakan sebagai acuan saat menentukan keputusan. Dalam pengembangan sistem digunakan beberapa metode diantaranya <em>framework </em>Codeigniter dengan arsitektur <em>web</em> MVC (<em>Model, View, </em>Controller), OLAP (<em>On-line Analytical Processing</em>) untuk menampilkan visualisasi data, dan <em>double exponential smoothing</em> menampilkan hasil peramalan data pada periode berikutnya. Nilai <em>error </em>dari metode peramalan tersebut dapat dihitung menggunakan algoritma <em>Mean Absolute Percentage Error</em>. Agar dapat mengetahui tingkat pemanfaatan terhadap pengembangan sistem ini, maka digunakan metode <em>black box testing</em>, <em>usability testing</em>, dan <em>user acceptance test</em> untuk mengetahui kualitas dan fungsionalitas sistem dari segi input, output, dan penilaian oleh pengguna sistem. Penelitian ini memperlihatkan bahwa pemakaian teknologi BI tidak hanya mendukung pada perusahaan namun juga mendukung pada bidang pariwisata, pemerintahan dan layanan. Sistem yang dikembangkan dapat membantu proses pemantauan pariwisata dan pendukung dalam pengambilan keputusan.</p><p class="Judul2"> </p><p class="Judul2"><strong><em>Abstract</em></strong></p><p class="Judul2"><em><em>Bali is one of several tourist destinations that bring domestic and foreign tourists to Indonesia. In 2017, there were 5.6 million foreign tourists visiting Bali and dominated by tourists from China. The number of visits to all tourist objects in Bali in 2017 reached 17.8 million visits. Based on this, local governments need strategies and decisions in the development of facilities and infrastructure that can support the development and progress of tourism in Bali. The use of business intelligence technology in analyzing large amounts of data will help. This study develops an information system using the BI approach in analyzing Bali tourism data and data management by replacing paper use as computer media so that data does not just disappear, but is used as a reference when making decisions. In system development, several methods are used including the Codeigniter framework with the MVC web architecture (Model, View, Controller), OLAP (On-line Analytical Processing) to display data visualization, and double exponential smoothing to display the results of forecasting data in the next period. The error value of this forecasting method can be calculated using the Mean Absolute Percentage Error algorithm. In order to determine the level of utilization of this system development, black box testing, usability testing and user acceptance tests are used to determine the quality and functionality of the system in terms of input, output, and assessment by system users. This study shows that the use of BI technology is not only supportive of companies but also supports tourism, government and services. The system developed can assist the tourism monitoring process and support decision making.</em></em></p>

scholarly journals A Survey of Open Source Tools for Business Intelligence

2011 ◽  
pp. 237-257
Keyword(s):  
Open Source ◽  
Business Intelligence ◽  
Database Management ◽  
Database Management Systems ◽  
Management Systems ◽  
Survey Article ◽  
On Line ◽  
Analytical Processing ◽  
Industrial Use ◽  
On Line Analytical Processing

The industrial use of open source Business Intelligence (BI) tools is becoming more common, but is still not as widespread as for other types of software. It is therefore of interest to explore which possibilities are available for open source BI and compare the tools. In this survey article, we consider the capabilities of a number of open source tools for BI. In the article, we consider a number of Extract- Transform-Load (ETL) tools, database management systems (DBMSs), On-Line Analytical Processing (OLAP) servers, and OLAP clients. We find that, unlike the situation a few years ago, there now exist mature and powerful tools in all these categories. However, the functionality still falls somewhat short of that found in commercial tools.

scholarly journals A Survey of Open Source Tools for Business Intelligence

2010 ◽  
pp. 624-644
Author(s):  
Christian Thomsen ◽  
Torben Bach Pedersen
Keyword(s):  
Open Source ◽  
Business Intelligence ◽  
Database Management ◽  
Database Management Systems ◽  
Management Systems ◽  
Survey Article ◽  
On Line ◽  
Analytical Processing ◽  
Industrial Use ◽  
On Line Analytical Processing

The industrial use of open source Business Intelligence (BI) tools is becoming more common, but is still not as widespread as for other types of software. It is therefore of interest to explore which possibilities are available for open source BI and compare the tools. In this survey article, we consider the capabilities of a number of open source tools for BI. In the article, we consider a number of Extract-Transform-Load (ETL) tools, database management systems (DBMSs), On-Line Analytical Processing (OLAP) servers, and OLAP clients. We find that, unlike the situation a few years ago, there now exist mature and powerful tools in all these categories. However, the functionality still falls somewhat short of that found in commercial tools.

BI4IPM

2018 ◽  
Vol 9 (1) ◽  
pp. 16-38 ◽  
Author(s):  
Claudio Zaza ◽  
Sandro Bimonte ◽  
Nicola Faccilongo ◽  
Piermichele La Sala ◽  
Francesco Contò ◽  
...  
Keyword(s):  
Business Intelligence ◽  
Crop Protection ◽  
Production Performance ◽  
Environmental Cost ◽  
Food Chains ◽  
World Population ◽  
Food Sector ◽  
On Line ◽  
Technical Specifications ◽  
Analytical Processing

The Agri-Food sector is facing global challenges. The first challenge is feeding a world population that will reach 9.3 billion people in 2050, according to UN projections. The second challenge is the demand from consumers for high-quality products obtained through more sustainable, safe and clear agri-food chains. Integrated pest management (IPM) could be an important instrument for helping farmers face these challenges. IPM requires the simultaneous use of different crop protection techniques to control pests through an ecological and economic approach. This work explores the possibility of developing a framework that combines business intelligence (BI) technologies with IPM principles to support farmers in the decisional process, thereby decreasing environmental cost and improving production performance. The proposed BI system is called BI4IPM, and it combines on-line transaction processing (OLTP) with on-line analytical processing (OLAP) to verify adherence to the IPM technical specifications.

scholarly journals Uma proposta de aplicação de business intelligence no chão-de-fábrica

2005 ◽  
Vol 12 (1) ◽  
pp. 55-66 ◽  
Author(s):  
Marcos Roberto Fortulan ◽  
Eduardo Vila Gonçalves Filho
Keyword(s):  
Data Warehouse ◽  
Business Intelligence ◽  
On Line ◽  
Analytical Processing ◽  
On Line Analytical Processing

A evolução do chão-de-fábrica tem sido significativa nas últimas décadas, quando grandes investimentos têm sido realizados em infra-estrutura, automação, treinamento e sistemas de informação, transformando-o numa área estratégica para as empresas. O chão-de-fábrica gera hoje grande quantidade de dados que, por estarem dispersos ou desorganizados, não são utilizados em todo o seu potencial como fonte de informação. Com vistas nessa deficiência, este trabalho propõe a implantação de um sistema de Business Intelligence por meio do uso de ferramentas de Data Warehouse e OLAP (On-Line Analytical Processing), aplicadas especificamente ao chão-de-fábrica. O objetivo é desenvolver um sistema que utilize os dados resultantes do processo produtivo e os transforme em informações que auxiliem o gerente na tomada de decisões, de forma a garantir a competitividade da empresa. Um protótipo foi construído com dados simulados para testar a proposta.

scholarly journals On-line Analytical Processing (OLAP) Operation for Outpatient Healthcare

2021 ◽  
pp. 225-231
Author(s):  
Talib M. J. Al Taleb ◽  
Sami Hasan ◽  
Yaqoob Yousif Mahd
Keyword(s):  
Data Warehouse ◽  
Business Intelligence ◽  
Decision Makers ◽  
Data Repository ◽  
Managerial Decision ◽  
High Quality Information ◽  
On Line ◽  
Analytical Processing ◽  
On Line Analytical Processing ◽  
Different Sources

This paper presents an architecture for the data warehouse of outpatient healthcare (DWOP) as a data repository collects data from two different sources (Databases of outpatient healthcare and Excel files from hospitals) and provides storage, functionality and responsiveness to queries to meet decision makers requirements.Successfully supporting managerial decision-making is critically dependent upon the availability of integrated, high quality information organized and presented in a timely and easily understood manner. “On-Line Analytical Processing (OLAP) is utilized for decision support to get interesting information” from the data warehouse with a rapid execution time. OLAP is considered one of Business Intelligence tools.

Validation of On-line Respiration Meter and its Applications by Computer Simulation

1992 ◽  
Vol 26 (5-6) ◽  
pp. 1355-1363 ◽  
Author(s):  
C-W. Kim ◽  
H. Spanjers ◽  
A. Klapwijk
Keyword(s):  
Steady State ◽  
Activated Sludge ◽  
Respiration Rate ◽  
Oxygen Demand ◽  
Operating Conditions ◽  
Mass Balances ◽  
Short Term ◽  
Respiration Rates ◽  
On Line ◽  
Made In

An on-line respiration meter is presented to monitor three types of respiration rates of activated sludge and to calculate effluent and influent short term biochemical oxygen demand (BODst) in the continuous activated sludge process. This work is to verify if the calculated BODst is reliable and the assumptions made in the course of developing the proposed procedure were acceptable. A mathematical model and a dynamic simulation program are written for an activated sludge model plant along with the respiration meter based on mass balances of BODst and DO. The simulation results show that the three types of respiration rate reach steady state within 15 minutes under reasonable operating conditions. As long as the respiration rate reaches steady state the proposed procedure calculates the respiration rate that is equal to the simulated. Under constant and dynamic BODst loading, the proposed procedure is capable of calculating the effluent and influent BODst with reasonable accuracy.

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