scholarly journals The Implementation of Business Intelligence on Cost Accounting – Case Study of XYZ Company

2020 ◽  
Author(s):  
Ford Lumban Gaol ◽  
Lufty Abdillah ◽  
Tokuro Matsuo
Keyword(s):  
Real Time ◽  
Business Intelligence ◽  
Business Processes ◽  
Cost Accounting ◽  
Process Data ◽  
Monitoring Process ◽  
Accounting Report ◽  
Operational Activities ◽  
Access To Data ◽  
Accounting Reports

Abstract Introduction: XYZ is a company engaged in the port sector. XYZ is engaged in the business of loading and unloading terminal services and container buildup. To support the company's business processes. Case Description: XYZ uses two applications in carrying out operational activities, namely the CARTOS application to manage bills and the Finance application to record company costs and revenues. To produce a cost accounting report, PT XYZ is still processing and visualizing it manually using Microsoft Excel applications with data sources from the two applications previously mentioned. There are problems related to the process, where the processing time to process data into information is quite long. So that reporting to management cannot be done in real time. Discussion and Evaluation: The development of business competition is very rapid, the management of XYZ must be able to make decisions quickly and accurately, so company needs tools that can help the management to analyze and manage data into information in real time. The Business Intelligence (BI) method is one of the solutions to the company's needs, especially in analyzing and providing access to data to help make better decisions. Conclusion: This study discusses the design and implementation of business intelligence solutions ranging from architecture, data warehouse, ETL processes and visualization in the form of a dashboard in accordance with the needs of PT XYZ. The method used in developing the business intelligence dashboard refers to the executive information system lifecycle method which consists of justification, planning, business analysis, design, construction and deployment. The results of this research are dashboard visualization using Power BI tools that display information and knowledge needed in the monitoring process and become material for generating management decisions related to cost accounting reports.

scholarly journals Adoption of Business Intelligence to Support Cost Accounting Based Financial Systems — Case Study of XYZ Company

2020 ◽  
Vol 11 (1) ◽  
pp. 14-28
Author(s):  
Ford Lumban Gaol ◽  
Lufty Abdillah ◽  
Tokuro Matsuo
Keyword(s):  
Real Time ◽  
Business Intelligence ◽  
Business Processes ◽  
Cost Accounting ◽  
Accounting Report ◽  
Operational Activities ◽  
System Life ◽  
Access To Data ◽  
Accounting Reports ◽  
Support Cost

AbstractXYZ is a company engaged in the port sector. To support the company’s business processes, XYZ uses two applications to carry out operational activities, namely the CARTOS application to manage invoices and the Finance application to record company costs and revenues. To produce a cost accounting report, XYZ is still processing and visualizing it manually with data sources from the two applications mentioned earlier. This resulted in quite a long time processing data into information. So that reporting to management cannot be done in real time. Therefore XYZ needs a system that can help management to analyze and manage data into information in real time. The Business Intelligence (BI) method is one of the solutions for company needs, especially in analyzing and providing access to data to help make better decisions.This study discusses the design and implementation of business intelligence solutions ranging from architecture, data warehouse, ETL processes and visualization in the form of a dashboard in accordance with the needs of XYZ. The method used in developing business intelligence dashboards refers to the executive information system life cycle method which consists of justification, planning, business analysis, design, construction, and dissemination. The results of this research are dashboard visualization using the Power BI tool that displays information and knowledge needed in the monitoring process and becomes material to produce management decisions related to cost accounting reports.

Integrated Real-Time Information to Use in Commercial, Logistics and Operational Activities Provided by the National Control Center Operation of TRANSPETRO

2010 ◽  
Author(s):  
He´lio A. R. Aniceto
Keyword(s):  
Real Time ◽  
Information Quality ◽  
Process Data ◽  
Control Center ◽  
Oil Pipeline ◽  
Dynamic Representation ◽  
Global Movement ◽  
Information Management Systems ◽  
Operational Activities ◽  
National Control

The National Control Center Operation TRANSPETRO created an information site that allows obtaining in real-time, using a system PIMS (Plant Information Management Systems), the information of process plants involved in the operations of our pipelines. The site provides different views for different clients. It also indicates the logistics transportation schedule progress, pipelines operation rates, comparative graphs (like global movement historical by period), transportation summaries by product or regions, covering all pipeline operations in Brazil. We also have links to process data of some plants long and short oil pipeline and for transfer of custody, obtaining information on pumps, valves, control valves, pressure and flow of the operation in progress. The pipeline location maps have a dynamic representation using geographic maps and showing the pipeline status. We are still developing applications to improve the information quality for clients, what give us feedback about the site’s stage progress. When we created the site of the National Control Center Operation TRANSPETRO we seek the principal function of technology PIMS “collect data from all areas of a plant and provides them for any type of application and makes it a great diffuser of information across the various organizational levels” [1].The benefits obtained from deploying the site using the PIMS technology brings potential gains support for the “decision-making of strategic and tactical levels of the enterprise” [2].

scholarly journals Integration of business process and organizational data for evidence-based business intelligence

2021 ◽  
Vol 24 (2) ◽  
Author(s):  
Daniel Calegari ◽  
Andrea Delgado ◽  
Alexis Artus ◽  
Andrés Borges
Keyword(s):  
Business Process ◽  
Business Intelligence ◽  
Business Processes ◽  
Process Mining ◽  
Data Sources ◽  
Evidence Based ◽  
Process Data ◽  
Matching Problems ◽  
Data Matching ◽  
Unified View

Organizations require a unified view of business processes and organizational data for the improvement of their daily operations. However, it is infrequent for both kinds of data to be consistently unified. Organizational data (e.g., clients, orders, and payments) is usually stored in many different data sources. Process data (e.g., cases, activity in- stances, and variables) is generally handled manually or implicit in information systems and coupled with organizational data without clear separation. It impairs the combined application of process mining and data mining techniques for a complete evaluation of their business process execution. In this paper, we deal with the integration of both kinds of data into a unified view. First, we analyze data integration scenarios and data matching problems considering intra-organizational and inter-organizational collaborative business processes. We also propose a model-driven approach to integrate several data sources, generating a unified model for evidence-based business intelligence.

scholarly journals Near-real-time volcanic cloud monitoring: insights into global explosive volcanic eruptive activity through analysis of Volcanic Ash Advisories

2021 ◽  
Vol 83 (2) ◽  
Author(s):  
S. Engwell ◽  
L. Mastin ◽  
A. Tupper ◽  
J. Kibler ◽  
P. Acethorp ◽  
...  
Keyword(s):  
Real Time ◽  
Volcanic Activity ◽  
Volcanic Ash ◽  
Source Parameters ◽  
Volcanic Eruptions ◽  
Volcanic Hazards ◽  
Process Data ◽  
Cloud Monitoring ◽  
Satellite Sensors ◽  
Volcanic Cloud

AbstractUnderstanding the location, intensity, and likely duration of volcanic hazards is key to reducing risk from volcanic eruptions. Here, we use a novel near-real-time dataset comprising Volcanic Ash Advisories (VAAs) issued over 10 years to investigate global rates and durations of explosive volcanic activity. The VAAs were collected from the nine Volcanic Ash Advisory Centres (VAACs) worldwide. Information extracted allowed analysis of the frequency and type of explosive behaviour, including analysis of key eruption source parameters (ESPs) such as volcanic cloud height and duration. The results reflect changes in the VAA reporting process, data sources, and volcanic activity through time. The data show an increase in the number of VAAs issued since 2015 that cannot be directly correlated to an increase in volcanic activity. Instead, many represent increased observations, including improved capability to detect low- to mid-level volcanic clouds (FL101–FL200, 3–6 km asl), by higher temporal, spatial, and spectral resolution satellite sensors. Comparison of ESP data extracted from the VAAs with the Mastin et al. (J Volcanol Geotherm Res 186:10–21, 2009a) database shows that traditional assumptions used in the classification of volcanoes could be much simplified for operational use. The analysis highlights the VAA data as an exceptional resource documenting global volcanic activity on timescales that complement more widely used eruption datasets.

scholarly journals Real-time repair of business processes based on alternative operations in case of uncertainty

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Liwen Zhang ◽  
Xianwen Fang ◽  
Chifeng Shao ◽  
Lili Wang
Keyword(s):  
Real Time ◽  
Business Processes ◽  
Alternative Operations

scholarly journals Identification of Granule Growth Regimes in High Shear Wet Granulation Processes Using a Physics-Constrained Neural Network

Processes ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 737
Author(s):  
Chaitanya Sampat ◽  
Rohit Ramachandran
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Real Time ◽  
Data Driven ◽  
Wet Granulation ◽  
Manufacturing Processes ◽  
High Shear ◽  
Process Data ◽  
Physical Constraints ◽  
Granule Growth

The digitization of manufacturing processes has led to an increase in the availability of process data, which has enabled the use of data-driven models to predict the outcomes of these manufacturing processes. Data-driven models are instantaneous in simulate and can provide real-time predictions but lack any governing physics within their framework. When process data deviates from original conditions, the predictions from these models may not agree with physical boundaries. In such cases, the use of first-principle-based models to predict process outcomes have proven to be effective but computationally inefficient and cannot be solved in real time. Thus, there remains a need to develop efficient data-driven models with a physical understanding about the process. In this work, we have demonstrate the addition of physics-based boundary conditions constraints to a neural network to improve its predictability for granule density and granule size distribution (GSD) for a high shear granulation process. The physics-constrained neural network (PCNN) was better at predicting granule growth regimes when compared to other neural networks with no physical constraints. When input data that violated physics-based boundaries was provided, the PCNN identified these points more accurately compared to other non-physics constrained neural networks, with an error of <1%. A sensitivity analysis of the PCNN to the input variables was also performed to understand individual effects on the final outputs.

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