Data Monetization Service Development Using Iterative Lifecycle Framework, Quality Assurance, and Open Web Application Security Project: A Case Study of a Utility Company in Indonesia

The research aims to provide Data Monetization (DM) services for an Indonesian utility company as a pilot to generate additional revenue beyond the primary operation. The service is built using an iterative development lifecycle framework and evaluated based on five Quality Goals (QGs), including application and security testing activities. The framework includes methods for processing and modeling electricity usage data, testing application quality, checking infrastructure quality, and ensuring access security for front-end and back-end applications using the Open Web Application Security Project (OWASP). For data modeling, Support Vector Regression (SVR) is used, and it outperforms Polynomial Regression (PR) and Multi-Layer Perception (MLP) Neural Networks. Furthermore, QG shows strong performance with an Relative Root Mean Squared Error (RRMSE) value < 10%, high forecasting ability with Mean Average Probability Error (MAPE) < 10%, and a near-zero average error rate (Mean Squared Error (MSE)) square using minimal data from four months. The services go through functional and integration test to ensure product quality and application performance, which results in a minimum of 95% service response in throughput, 0.128 seconds for processing 2,000 requests, stability at 300–500 in one second per hour, and 7–21 seconds during peak hours. Additionally, the service passes nine penetration tests and ten vulnerability assessments using the OWASP top 10:2021 category. Based on the comprehensive testing and evaluation results, both the application and the service are considered ready and secured for deployment.

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Publication Details

Journal
CommIT (Communication and Information Technology) Journal
Published
2024-09-19
DOI
https://doi.org/10.21512/commit.v18i2.10293
Primary Topic
Information Retrieval and Data Mining
Type
article
Field-Weighted Citation Impact
0.00
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article

Data Monetization Service Development Using Iterative Lifecycle Framework, Quality Assurance, and Open Web Application Security Project: A Case Study of a Utility Company in Indonesia

Harco Leslie Hendric Spits Warnars, Benfano Soewito, Wahyu Haris Kusuma Atmaja, Ford Lumban Gaol
CommIT (Communication and Information Technology) Journal
Information Retrieval and Data Mining
article

Data Monetization Service Development Using Iterative Lifecycle Framework, Quality Assurance, and Open Web Application Security Project: A Case Study of a Utility Company in Indonesia

Harco Leslie Hendric Spits Warnars, Benfano Soewito, Wahyu Haris Kusuma Atmaja, Ford Lumban Gaol
article en

Abstract

The research aims to provide Data Monetization (DM) services for an Indonesian utility company as a pilot to generate additional revenue beyond the primary operation. The service is built using an iterative development lifecycle framework and evaluated based on five Quality Goals (QGs), including application and security testing activities. The framework includes methods for processing and modeling electricity usage data, testing application quality, checking infrastructure quality, and ensuring access security for front-end and back-end applications using the Open Web Application Security Project (OWASP). For data modeling, Support Vector Regression (SVR) is used, and it outperforms Polynomial Regression (PR) and Multi-Layer Perception (MLP) Neural Networks. Furthermore, QG shows strong performance with an Relative Root Mean Squared Error (RRMSE) value < 10%, high forecasting ability with Mean Average Probability Error (MAPE) < 10%, and a near-zero average error rate (Mean Squared Error (MSE)) square using minimal data from four months. The services go through functional and integration test to ensure product quality and application performance, which results in a minimum of 95% service response in throughput, 0.128 seconds for processing 2,000 requests, stability at 300–500 in one second per hour, and 7–21 seconds during peak hours. Additionally, the service passes nine penetration tests and ten vulnerability assessments using the OWASP top 10:2021 category. Based on the comprehensive testing and evaluation results, both the application and the service are considered ready and secured for deployment.

CommIT (Communication and Information Technology) JournalVol. 18(2)
Binus University (ID)
Openalex Percentile: Top 70%
Information Retrieval and Data Mining
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