Infrastructure Management of the Smart and Green Learning Center Building Using the Analytical Hierarchy Process (AHP)

Ratu Irmi Balqis; Henricus Priyosulistyo; Inggar Septhia Irawati

doi:10.21831/inersia.v20i1.67639

Infrastructure Management of the Smart and Green Learning Center Building Using the Analytical Hierarchy Process (AHP)

Ratu Irmi Balqis, Department of Civil and Environmental Engineering, Faculty of Engineering, Gadjah Mada University, Yogyakarta 55281, Indonesia
Henricus Priyosulistyo, Department of Civil and Environmental Engineering, Faculty of Engineering, Gadjah Mada University, Yogyakarta 55281, Indonesia
Inggar Septhia Irawati, Department of Civil and Environmental Engineering, Faculty of Engineering, Gadjah Mada University, Yogyakarta 55281, Indonesia

10.21831/inersia.v20i1.67639

Abstract

Building infrastructure management is a key element in maintaining and improving the efficiency, sustainability, and quality of a building. The Smart and Green Learning Center (SGLC) building at Gadjah Mada University is a modern building that functions as both an administrative office and a lecture hall. The building boasts a modern design featuring extensive use of glass and stands 11 stories tall. It embodies the concept of a green and smart building. Hence, it requires serious attention in terms of effective maintenance and proper maintenance to ensure the building can function properly. This research uses the Analytical Hierarchy Process (AHP) method to obtain weighting values for room components/elements. This weighting value is then used to calculate the SGLC building component condition index, which can provide information of whether the component is damaged or not. The weighting values are obtained by distributing questionnaires, while the condition index is determined through observation. The components observed include structural, architectural, and utility components. The results show that weighting values for structure, architecture and utilities were 46.3%, 33.9% and 19.8%, respectively. In the structural components, it is found that the column, beam, and plate weighting values are 48.3%, 42.7% and 8.9%, respectively. In the architectural components, the weighting values for ceilings, walls, floors & ceramics, doors & windows are 11.7%, 36.6%, 8.8%, 42.9% respectively. In the utility components, the weighting values for electricity, electronics, elevators, building sensor systems, and plumbing are 30%, 22.3%, 4.9%, 19.1%, and 23.7%, respectively. After searching floors 1 to 11, it was seen that the structural components were still in exceptionally good condition. There is only minor damage to utility and architectural components that require maintenance such as repair or replacement of components that are no longer suitable for use.

Keywords

Maintenance; Condition Index; and Analytical Hierarchy Process

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References

S. Kim, S. Lee, and Y. H. Ahn, “Evaluating Housing Maintenance Costs with Loss-Distribution Approach in South Korean Apartment Housing,” J. Manag. Eng., vol. 35, Mar. 2019, doi: 10.1061/(ASCE)ME.1943-5479.0000672.

C. P. Au-Yong, S. Chua, A. Ali, and M. Tucker, “Optimising maintenance cost by prioritising maintenance of facilities services in residential buildings,” Eng. Constr. Archit. Manag., vol. 26, pp. 1593–1607, May 2019, doi: 10.1108/ECAM-07-2018-0265.

S.-W. Whang, R. Flanagan, S. Kim, and S. Kim, “Contractor-Led Critical Design Management Factors in High-Rise Building Projects Involving Multinational Design Teams,” J. Constr. Eng. Manag., vol. 143, no. 5, p. 06016009, May 2017, doi: 10.1061/(ASCE)CO.1943-7862.0001242

S.J.L. Chua, N.B. Zubbir, A.S. Ali,C.P. Au-Yong, “Maintenance of high-rise resindential buildings,” pp. 137-151, (2018).

R. da Silva, A. Melani, M. Michalski, G. Souza, S. Nabeta, and F. Hamaji, “Defining Maintenance Performance Indicators for asset management based on ISO 55000 and Balanced Scorecard: A hydropower plant case study,” Jun. 2020. doi: 10.3850/978-981-14-8593-0_3820-cd.

P. Benítez, E. Rocha, H. Varum, and F. Rodrigues, “A dynamic multi-criteria decision-making model for the maintenance planning of reinforced concrete structures,” J. Build. Eng., vol. 27, p. 100971, Jan. 2020, doi:10.1016/j.jobe.2019.100 971.

R. Ahmed, F. Nasiri, and T. Zayed, “A novel Neutrosophic-based machine learning approach for maintenance prioritization in healthcare facilities,” J. Build. Eng., vol. 42, p. 102480, Oct. 2021, doi: 10.1016/j.jobe.2021.102480.

M. A. Anshebo, W. J. Mengesha, and D. L. Sokido, “Developing a Green Building Assessment Tool for Ethiopia,” Heliyon, vol. 8, no. 9,p. el0569, Sep.2022,doi: 10.1016/j.heliyon.2022.e10569.

T. L. Saaty and L. G. Vargas, “A Model of Neural Impulse Firing and Synthesis,” J. Math. Psychol., vol. 37, no. 2, pp. 200–219, Jun. 1993, doi: 10.1006/jmps.1993.1013

T. L. Saaty, “How to make a decision: The analytic hierarchy process,” Eur. J. Oper. Res., vol. 48, no. 1, pp. 9–26, Sep. 1990, doi: 10.1016/0377-2217(90)90057-I.

N. Munier, E. Hontoria, "Uses and limitations of the AHP method: A non-mathematical and rational analysis," in Management for Professionals, Springer, Berlin, Germany, 2021. [Google Scholar].

T. L. Saaty, “How to make a decision: The analytic hierarchy process,” Eur. J. Oper. Res., vol. 48, no. 1, pp. 9–26, Sep. 1990, doi: 10.1016/0377-2217(90)90057-I.

Hudson, W.R., Haas, R., Uddin, 1997. “Infrastructure management,” [WWW Document]. Univ. Indones. Libr. URL https://lib.ui.ac.id

N. Hazem, M. Abdelraouf, I. Fahim, and S. El-Omari, “A Novel Green Rating System for Existing Buildings,” Sustainability, vol. 12, p. 7143, Sep. 2020, doi: 10.3390/su12177143

DOI: https://doi.org/10.21831/inersia.v20i1.67639