The Analysis of Data Preparation to Validate Model Values of Information Technology

Currently, there are some methods of preparing data for validating an IT value model correctly. One challenge in applying data mining to validate model values is to convert data into an appropriate form for this activity. Data mining algorithms can then be applied using the prepared data. The adequa...

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Main Authors: Taufik Hidayat, Rahutomo Mahardiko, Ali Miftakhu Rosyad
Format: Article
Language:English
Published: Institute for International Cooperation Development 2023-06-01
Series:Virtual Economics
Subjects:
Online Access:https://www.virtual-economics.eu/index.php/VE/article/view/259/129
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author Taufik Hidayat
Rahutomo Mahardiko
Ali Miftakhu Rosyad
author_facet Taufik Hidayat
Rahutomo Mahardiko
Ali Miftakhu Rosyad
author_sort Taufik Hidayat
collection DOAJ
description Currently, there are some methods of preparing data for validating an IT value model correctly. One challenge in applying data mining to validate model values is to convert data into an appropriate form for this activity. Data mining algorithms can then be applied using the prepared data. The adequacy of data preparation often determines whether this data mining is successful or not. This study aims at creating a method for preparing the data during validation. The basic method used for data preparation is the Returns to Scale (RTS) method because it is easy to use and can be combined with further validation results. This method was applied by employing two models: two-factor and three-factor models. Both models are then compared to see the difference between them. The developed model is then tested on Branchless Banking (BB) and Downstream Petroleum (DP) industries. The results show that the method is applicable to prepare the data for validation. In addition, the results also demonstrate that both industries, DP and BB, have different result on data preparation, meaning that DP and BB have different ITs. This research contributes not only to a technique of preparing data for validating an IT value model by the RTS method but also can be a basis to work for data validation because it can give a result with the behaviour of the industry.
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spelling doaj.art-02d246a5d1a24a0ea47aa342df21a8c02023-09-17T10:27:20ZengInstitute for International Cooperation DevelopmentVirtual Economics2657-40472023-06-0162233410.34021/ve.2023.06.02(2)The Analysis of Data Preparation to Validate Model Values of Information TechnologyTaufik Hidayat0https://orcid.org/0000-0003-0230-9872Rahutomo Mahardiko1https://orcid.org/0000-0001-7324-0556Ali Miftakhu Rosyad2https://orcid.org/0000-0002-8845-2364Department of Electrical Engineering, Universitas Indonesia, Depok, IndonesiaDepartment of Data Management, PT.BFI Finance Indonesia Tbk, IndonesiaDepartment of Islamic Education, Universitas Wiralodra, Indramayu, IndonesiaCurrently, there are some methods of preparing data for validating an IT value model correctly. One challenge in applying data mining to validate model values is to convert data into an appropriate form for this activity. Data mining algorithms can then be applied using the prepared data. The adequacy of data preparation often determines whether this data mining is successful or not. This study aims at creating a method for preparing the data during validation. The basic method used for data preparation is the Returns to Scale (RTS) method because it is easy to use and can be combined with further validation results. This method was applied by employing two models: two-factor and three-factor models. Both models are then compared to see the difference between them. The developed model is then tested on Branchless Banking (BB) and Downstream Petroleum (DP) industries. The results show that the method is applicable to prepare the data for validation. In addition, the results also demonstrate that both industries, DP and BB, have different result on data preparation, meaning that DP and BB have different ITs. This research contributes not only to a technique of preparing data for validating an IT value model by the RTS method but also can be a basis to work for data validation because it can give a result with the behaviour of the industry.https://www.virtual-economics.eu/index.php/VE/article/view/259/129it valueit value modelreturns to scale methoddata preparationvalidation
spellingShingle Taufik Hidayat
Rahutomo Mahardiko
Ali Miftakhu Rosyad
The Analysis of Data Preparation to Validate Model Values of Information Technology
Virtual Economics
it value
it value model
returns to scale method
data preparation
validation
title The Analysis of Data Preparation to Validate Model Values of Information Technology
title_full The Analysis of Data Preparation to Validate Model Values of Information Technology
title_fullStr The Analysis of Data Preparation to Validate Model Values of Information Technology
title_full_unstemmed The Analysis of Data Preparation to Validate Model Values of Information Technology
title_short The Analysis of Data Preparation to Validate Model Values of Information Technology
title_sort analysis of data preparation to validate model values of information technology
topic it value
it value model
returns to scale method
data preparation
validation
url https://www.virtual-economics.eu/index.php/VE/article/view/259/129
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