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General Information
ISSN:
2377-2891(Print); 2377-2905(Online)
Frequency:
Bimonthly
Editor-in-Chief:
Prof. Eric C. K. Cheng
Associate Executive Editor:
Ms. Jenny Jiang
DOI:
10.18178/ijlt
Abstracting/Indexing:
Google Scholar; Crossref, CNKI,
etc.
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questions or comments to
IJLT Editorial Office
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Editor-in-Chief
Prof. Eric C. K. Cheng
Professor & Vice President (Academic)
Yew Chung College of Early Childhood Education, Hong Kong, China
As the Editor-in-Chief of IJLT, I invite you to contribute your scholarly work to our esteemed publication. IJLT serves as a beacon for original and impactful academic contributions in the realm of education, fostering multidisciplinary research and development to enhance teaching-learning processes globally. We welcome submissions spanning a wide spectrum of topics, from innovative program development to the integration of digital tools in education. Our scope encompasses areas such as student leadership, diversity in education, and collaborative initiatives, reflecting our commitment to a sustainable and inclusive society. [
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What's New
2024-02-29
Vol. 10, No. 1, 2024 has been published!
2024-02-07
Welcome Prof. Eric C. K. Cheng from Yew Chung College of Early Childhood Education, Hong Kong, China to join IJLT Editorial Board as Editor-in-Chief!
2023-12-13
IJLT will adopt Article-by-Article Work Flow from 2024. For the Bimonthly journal, each issue will be released at the end of the issue month.
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2017
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Volume 3, No. 4, December 2017
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Application of Improved Initialization of K-means Algorithm for Monitoring of Fixed Asset
Aleta C. Fabregas
1
, Ruji P. Medina
1
, and Bobby D. Gerardo
2
1. Technological Institute of the Philippines, Graduate Programs, Quezon City, Philippines
2. West Visayas State University, Institute of Information and Communication Technology, La Paz, Iloilo City, Philippines
Abstract
—A new method of initializing centroids for K-means algorithm is developed in fixed asset monitoring application. The new method utilizing improved utilization of K-means using weighted average was found to be more efficient than the standard K-means owing to its simplicity and having no need for complex computation. The Depreciation was calculated with the use of the new method through the implementation of Age and Usage factors as the major attributes. The clustering output was able to determine the level of maintenance. This paper shows that the developed algorithm is highly applicable to accounting application.
Index Terms
—initialization of centroids, fixed asset, depreciation, level of maintenance
Cite: Aleta C. Fabregas, Ruji P. Medina, and Bobby D. Gerardo, "Application of Improved Initialization of K-means Algorithm for Monitoring of Fixed Asset," International Journal of Learning and Teaching, Vol. 3, No. 4, pp. 336-341, December 2017. doi: 10.18178/ijlt.3.4.336-341
16-AC026
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