scholarly journals IMPLEMENTASI OLAP (ON-LINE ANALYTICAL PROCESSING) UNTUK PENGOLAHAN TRANSAKSI PENJUALAN BERBASIS WEB (STUDI KASUS: LILOLA BOUTIQUE)

2018 ◽  
Vol 4 (1) ◽  
Author(s):  
Ni Putu Manik Ardiyanti ◽  
Aniek Suryanti Kusuma ◽  
I Kadek Budi Sandika
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Black Box ◽  
Web Based ◽  
Processing Application ◽  
Sales Data ◽  
Black Box Testing ◽  
On Line ◽  
Analytical Processing ◽  
On Line Analytical Processing

ABSTRACT<br />Information on sales data required by the owner at Lilola Boutique as a basis for decision making and strategy . On the other hand, the large amount of transactional sales data that occurs at any time causes problems in these analyze process. To solve these problem, an OLAP (On-Line Analytical Processing) application was built. OLAP application is designed using the CodeIgniter framework which produces a fast and reliable web-based application and data warehouse as its database. To produce a good data warehouse, the Nine Step Kimball method were used. Stages of this method produced a snowflake scheme as a storage place for data warehouse. The implementation of the system design could produced the OLAP report required by Lilola Boutique. Testing the system using black box testing method that showed the performance of applications that run well. From the results of this study can be concluded that OLAP application made the process of sales transaction data analysis to produce reports as the basis of the decision-making process.<br />Keywords: Sales, OLAP, Data Warehouse, Nine Step Kimball<br />ABSTRAK<br />Informasi mengenai data penjualan dibutuhkan oleh owner pada Lilola Boutique sebagai dasar untuk pengambilan keputusan dan penentuan strategi perusahaan. Di sisi lain, banyaknya data transaksi penjualan yang terjadi setiap harinya menyebabkan kesulitan dalam proses analisa dan pengambilan keputusan. Untuk mengatasi permasalahan tersebut, dibangun sebuah aplikasi OLAP (On-Line Analytical Processing). Perancangan aplikasi OLAP dirancang menggunakan framework CodeIgniter yang menghasilkan aplikasi berbasis web yang handal dan cepat dan data warehouse sebagai basis datanya. Untuk menghasilkan data warehouse yang baik, digunakan metode perancangan Nine Step Kimball. Tahapan metode ini menghasilkan rancangan snowflake schema sebagai tempat penampungan data warehouse. Implementasi rancangan sistem dapat menghasilkan laporan OLAP yang dibutuhkan oleh pihak Lilola Boutique. Pengujian sistem menggunakan metode black box testing yang menghasilkan unjuk kerja aplikasi yang berjalan dengan baik. Dari hasil penelitian ini dapat disimpulkan bahwa sistem aplikasi OLAP dapat membantu proses pengolahan data transaksi penjualan untuk menghasilkan laporan yang berkualitas sebagai dasar dalam pengambilan keputusan.<br />Kata Kunci: Penjualan, OLAP, Data Warehouse, Nine Step Kimball

Using OLAP Tools for e-HRM

2011 ◽  
pp. 252-265
Author(s):  
Alysson Bolognesi Prado ◽  
Carmen Freitas ◽  
Thiago Ricardo Sbrici
Keyword(s):  
Decision Making ◽  
Human Resources ◽  
Data Warehouse ◽  
End Users ◽  
Web Portal ◽  
Business Information ◽  
On Line ◽  
Analytical Processing ◽  
Resource Data ◽  
Support Decision Making

In the growing challenge of managing people, Human Resources need effective artifacts to support decision making. On Line Analytical Processing is intended to make business information available for managers, and HR departments can now encompass this technology. This paper describes a project in which the authors built a Data Warehouse containing actual Human Resource data. This paper provides data models and shows their use through OLAP software and their presentation to end-users using a web portal. The authors also discuss the progress, and some obstacles of the project, from the IT staff’s viewpoint.

scholarly journals Data Warehouse Schemas using Multidimensional Data Model for Retail

2017 ◽  
Vol 2 (1) ◽  
pp. 84
Author(s):  
Kheri Arionadi Shobirin ◽  
Adi Panca Saputra Iskandar ◽  
Ida Bagus Alit Swamardika
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Data Warehouse ◽  
Data Model ◽  
Transaction Processing ◽  
Multidimensional Data ◽  
Complex Query ◽  
On Line ◽  
Analytical Processing ◽  
Operational Data

A data warehouse are central repositories of integrated data from one or more disparate sources from operational data in On-Line Transaction Processing (OLTP) system to use in decision making strategy and business intelligent using On-Line Analytical Processing (OLAP) techniques. Data warehouses support OLAP applications by storing and maintaining data in multidimensional format. Multidimensional data models as an integral part of OLAP designed to solve complex query analysis in real time.

scholarly journals Perancangan Data Warehouse pada Laporan PDPT di Kopertis Wilayah V

2016 ◽  
Vol 3 (3) ◽  
pp. 255
Author(s):  
Sukarsono Windu Kumoro ◽  
Abidarin Rosidi ◽  
Armadyah Amborowati
Keyword(s):  
Higher Education ◽  
Data Warehouse ◽  
Teaching And Learning ◽  
Private Higher Education ◽  
Faculty Teaching ◽  
Star Schema ◽  
On Line ◽  
Analytical Processing ◽  
On Line Analytical Processing ◽  
Academic Year

Evaluasi terhadap Program Studi pada Perguruan Tinggi Swasta (PTS) yang memperoleh Ijin Penyelenggaraan dari Dirjen Dikti dibutuhkan oleh Koordinator Kopertis Wilayah V. Laporan PDPT telah terkumpul sejak tahun akademik 2002 semester ganjil (2002-1) sampai dengan tahun akademik 2013 semester genap (2013-2) yang terdiri dari data transaksi yang terkait dengan proses belajar mengajar di PTS. Laporan PDPT dari PTS dikerjakan atas dasar “Culture Trust”. Untuk mengatasi permasalahan tersebut dibangun sebuah data warehouse di Kopertis Wilayah V DIY. Data warehouse ini dikembangkan dengan menggunakan Foxpro dan Clipper dikarenakan data yang dilaporkan menggunakan file berekstendi DBF. Foxpro dan Clipper adalah sebuah paket basisdata dan dapat didistribusikan.Dalam pengerjaan pembangunan data warehouse ini akan melalui proses ETL dan pembuatan Star Schema (Skema Bintang) berupa dimensi-dimensi yang terhubung dengan tabel fakta berupa tabel aktifitas perkuliahan mahasiswa, evaluasi program studi dan aktifitas dosen mengajar di seluruh program studi pada PTS yang menjadi binaan Kopertis Wilayah V. Kemudian hasil data warehouse akan dianalisa melalui proses OLAP (On-line Analytical Processing).The evaluation of the Program on Private Higher Education (PTS) which derive from the Operating Licence required by the Coordinator General of Higher Education Kopertis Region V. PDPT reports have been collected since 2002 semester of the academic year (2002-1) until the second semester of academic year 2013 (2013-2), which consists of transaction data associated with the teaching and learning process in the PTS. PDPT reports of PTS is done on the basis of "Culture Trust".To overcome these problems built a data warehouse in Kopertis Region V DIY. The data warehouse was developed using FoxPro and Clipper because the data reported using a DBF file extension. FoxPro and Clipper is a package database and can be distributed. In the execution of data warehouse development is going through the ETL process and the making of Star Schema (Star Schema) in the form of dimensions that are connected with the fact table in the form of table activity lecturing students, evaluation of courses and activities throughout the faculty teaching courses at private universities being built Kopertis region V. Then the results will be analyzed data warehouse through a process of OLAP (On-line Analytical Processing).

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>

Some Issues in Design of Data Warehousing Systems

2011 ◽  
pp. 22-76
Author(s):  
Ladjel Bellatreche ◽  
Kamalakar Karlapalem ◽  
Mukesh Mohania
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Data Warehousing ◽  
Complex Data ◽  
Time Varying ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
On Line ◽  
Analytical Processing ◽  
Warehousing Systems

Information is one of the most valuable assets of an organization, and when used properly can assist intelligent decision-making that can significantly improve the functioning of an organization. Data warehousing is a recent technology that allows information to be easily and efficiently accessed for decision-making activities. On-line analytical processing (OLAP) tools are well studied for complex data analysis. A data warehouse is a set of subject-oriented, integrated, time varying and non-volatile databases used to support the decision-making activities (Inmon, 1992).

scholarly journals Analysis of Data Warehouse for Transactional Analysis Methods Online Analytical Processing (OLAP) at Company XYZ Silver

2017 ◽  
Vol 2 (1) ◽  
pp. 72
Author(s):  
Putu Widiadnyana ◽  
M. Azman Maricar ◽  
I Nyoman Arnawan ◽  
Sri Ariyani
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Data Warehouse ◽  
Production Costs ◽  
Transactional Analysis ◽  
Web Based ◽  
Analytical Processing ◽  
A Company ◽  
Processing Mechanisms ◽  
Sales Increase

Utilization of information technology is a necessity in looking at opportunities available for decision making by the management. With the ability of information technology to analyze existing used the data into useful information for a company. OLAP is Able to Overcome problems in the data processing mechanisms guided to know various information from different angles. By utilizing transactional analysis, then we know the reaction of customers in choosing the products that we will market. The result of Web-based sales has Decreased for the Gianyar and Denpasar regions but has Increased for the Ubud and online areas so as to give a benefit in terms of production costs. With the training for a sales increase of sales can evenly across locations and need input from customers related to minimize returns.

Enhancing the Diamond Document Warehouse Model

2020 ◽  
Vol 16 (4) ◽  
pp. 1-25
Author(s):  
Maha Azabou ◽  
Ameen Banjar ◽  
Jamel Omar Feki
Keyword(s):  
Data Warehouse ◽  
Decision Makers ◽  
Main Concern ◽  
Multidimensional Model ◽  
On Line ◽  
Analytical Processing ◽  
On Line Analytical Processing

The data warehouse community has paid particular attention to the document warehouse (DocW) paradigm during the last two decades. However, some important issues related to the semantics are still pending and therefore need a deep research investigation. Indeed, the semantic exploitation of the DocW is not yet mature despite it representing a main concern for decision-makers. This paper aims to enhancing the multidimensional model called Diamond Document Warehouse Model with semantics aspects; in particular, it suggests semantic OLAP (on-line analytical processing) operators for querying the DocW.

Some Issues in Design of Data Warehousing Systems

2001 ◽  
pp. 125-172 ◽  
Author(s):  
Ladjel Bellatreche ◽  
Kamalakar Karlapalem ◽  
Mukesh Mohania
Keyword(s):  
Decision Making ◽  
Data Warehouse ◽  
Data Warehousing ◽  
Complex Data ◽  
Time Varying ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
On Line ◽  
Analytical Processing ◽  
Warehousing Systems

Information is one of the most valuable assets of an organization, and when used properly can assist intelligent decision-making that can significantly improve the functioning of an organization. Data warehousing is a recent technology that allows information to be easily and efficiently accessed for decision-making activities. On-line analytical processing (OLAP) tools are well studied for complex data analysis. A data warehouse is a set of subject-oriented, integrated, time varying and non-volatile databases used to support the decision-making activities (Inmon, 1992).

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.

Sign in / Sign up

Export Citation Format

Share Document