ENERGY AUDIT ANALYSIS BY BUSINESS INTELLIGENCE APPLICATION
<em>Energy audit is one of the first tasks to be performed in the accomplishment of an effective energy cost control program. To obtain the best information for a successful energy audit, the auditor must make some measurements during the audit visit. One of the tools that primarily used in au...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Universitas Mercu Buana
2015-12-01
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| Series: | Jurnal Ilmiah SINERGI |
| Online Access: | http://publikasi.mercubuana.ac.id/index.php/sinergi/article/view/213 |
| _version_ | 1797764091511570432 |
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| author | Alfa Firdaus Uly Amrina |
| author_facet | Alfa Firdaus Uly Amrina |
| author_sort | Alfa Firdaus |
| collection | DOAJ |
| description | <em>Energy audit is one of the first tasks to be performed in the accomplishment of an effective energy cost control program. To obtain the best information for a successful energy audit, the auditor must make some measurements during the audit visit. One of the tools that primarily used in audit visit is the portable Power Quality Analyzers (PQA) for measuring single to three-phase lines with a high degree of precision and accuracy. It is utilized for monitoring and recording power supply anomalies. For most survey applications, changing currents makes it mandatory for data to be compiled over a period of time with enormous amount of electricity data. Hence, this paper proposed a Business Intelligence approach that can facilitate the auditor to quickly analyze the PQA data. There are five Key Performance Indicators (KPI) to be displayed for analyze in form of dashboard. The method that uses to construct the dashboard is classification and association rules with the help of orange dataminer tools. Classification method is utilized to display the data distributions by frequency on a bar chart. Once we got the frequent sets, they allow us to extract association rules among the item sets, where we make some statement about how likely are two sets of items to co-occur or to conditionally occur. The result of this paper is a dashboard of five scorecards, namely unbalanced voltage, unbalanced currents, voltage harmonic, currents harmonic, and power factor. </em> |
| first_indexed | 2024-03-12T19:50:48Z |
| format | Article |
| id | doaj.art-293361f4da234081a96654e6be271f8b |
| institution | Directory Open Access Journal |
| issn | 1410-2331 2460-1217 |
| language | English |
| last_indexed | 2024-03-12T19:50:48Z |
| publishDate | 2015-12-01 |
| publisher | Universitas Mercu Buana |
| record_format | Article |
| series | Jurnal Ilmiah SINERGI |
| spelling | doaj.art-293361f4da234081a96654e6be271f8b2023-08-02T03:10:42ZengUniversitas Mercu BuanaJurnal Ilmiah SINERGI1410-23312460-12172015-12-01193175180235ENERGY AUDIT ANALYSIS BY BUSINESS INTELLIGENCE APPLICATIONAlfa Firdaus0Uly Amrina1Faculty of Engineering, Mercu Buana Universityaculty of Engineering, Mercu Buana University<em>Energy audit is one of the first tasks to be performed in the accomplishment of an effective energy cost control program. To obtain the best information for a successful energy audit, the auditor must make some measurements during the audit visit. One of the tools that primarily used in audit visit is the portable Power Quality Analyzers (PQA) for measuring single to three-phase lines with a high degree of precision and accuracy. It is utilized for monitoring and recording power supply anomalies. For most survey applications, changing currents makes it mandatory for data to be compiled over a period of time with enormous amount of electricity data. Hence, this paper proposed a Business Intelligence approach that can facilitate the auditor to quickly analyze the PQA data. There are five Key Performance Indicators (KPI) to be displayed for analyze in form of dashboard. The method that uses to construct the dashboard is classification and association rules with the help of orange dataminer tools. Classification method is utilized to display the data distributions by frequency on a bar chart. Once we got the frequent sets, they allow us to extract association rules among the item sets, where we make some statement about how likely are two sets of items to co-occur or to conditionally occur. The result of this paper is a dashboard of five scorecards, namely unbalanced voltage, unbalanced currents, voltage harmonic, currents harmonic, and power factor. </em>http://publikasi.mercubuana.ac.id/index.php/sinergi/article/view/213 |
| spellingShingle | Alfa Firdaus Uly Amrina ENERGY AUDIT ANALYSIS BY BUSINESS INTELLIGENCE APPLICATION Jurnal Ilmiah SINERGI |
| title | ENERGY AUDIT ANALYSIS BY BUSINESS INTELLIGENCE APPLICATION |
| title_full | ENERGY AUDIT ANALYSIS BY BUSINESS INTELLIGENCE APPLICATION |
| title_fullStr | ENERGY AUDIT ANALYSIS BY BUSINESS INTELLIGENCE APPLICATION |
| title_full_unstemmed | ENERGY AUDIT ANALYSIS BY BUSINESS INTELLIGENCE APPLICATION |
| title_short | ENERGY AUDIT ANALYSIS BY BUSINESS INTELLIGENCE APPLICATION |
| title_sort | energy audit analysis by business intelligence application |
| url | http://publikasi.mercubuana.ac.id/index.php/sinergi/article/view/213 |
| work_keys_str_mv | AT alfafirdaus energyauditanalysisbybusinessintelligenceapplication AT ulyamrina energyauditanalysisbybusinessintelligenceapplication |