Application of fuzzy logic method to determine the level of damage to buildings in elementary schools
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Published:
Mar 30, 2024
Keywords:
Decision Support Systems, Fuzzy Logic Methods
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Abstract
This study aims to provide information effectively and efficiently about the condition of damage to elementary school buildings to assist schools in determining decisions about buildings in schools that must be repaired immediately. In research, the application of fuzzy logic methods to assess the extent of damage to elementary school buildings will depend heavily on the research design, processes, and data used to develop and test fuzzy logic models. This approach involves reviewing, synthesizing, and evaluating a variety of literature sources, including scientific journals, books, conference papers, articles, and other written sources. It is important to consider that the value and novelty of a study can be assessed by the scientific community and practitioners in related fields, and the results will depend on the ability of that research to make a meaningful contribution. The value of applying fuzzy logic methods to determine the extent of damage to elementary school buildings will provide a more complete picture of the contribution of such research to science and practice in the field concerned.
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Fahirah, D. F. ., Anandaianskha, S. ., & Gunawan, G. (2024). Application of fuzzy logic method to determine the level of damage to buildings in elementary schools. Journal of Intelligent Decision Support System (IDSS), 7(1), 49-56. https://doi.org/10.35335/idss.v7i1.208
References
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Rizki, A. M., &; Marina, N. (2019). Classification of damage to school buildings using the Convolutional Neural Network method with a pre-trained model Vgg-16. Scientific Journal of Technology and Engineering, 24(3), 197–206. https://doi.org/10.35760/tr.2019.v24i3.2396
Rosani, D. P., Dhokhikah, Y., &; Trisiana, A. (2020). Technical Risk Analysis of Construction Project Using Fuzzy Logic Method (Case Study of Grand Sungkono Lagoon Project, Surabaya). Journal of Civil and Environmental Engineering, 4(1), 40–50.
Faithful, B. (2019). Application of fuzzy logic to intelligent systems. 02, 61–66.
Tundo, T., Akbar, R., &; Sela, E. I. (2020). Comparative analysis of Fuzzy Tsukamoto and Sugeno in determining the amount of woven fabric production using a base rule decision tree. In Journal of Information Technology and Computer Science (Vol. 7, Issue 1, p. 171). https://doi.org/10.25126/jtiik.2020701751
Wiyanto, H., &; Justin, E. (2019). Determination of criteria for assessing concrete damage to buildings based on priority scales. Estuary Journal of Science, Technology, Medicine and Health Sciences, 3(1), 153. https://doi.org/10.24912/jmstkik.v3i1.5192
Yulia, & Mardiah, A. (2018). Fuzzy Logic to determine student satisfaction with school facilities and infrastructure using the Sugeno method. Scientific Journal of Informatics, 6(01), 32.
Ahsanandi, M. F., &; Awaludin, L. (2022). IMU Sensor-Based Building Vulnerability Warning System with Fuzzy Method. IJEIS (Indonesian Journal of Electronic and Instrumentation Systems), 12(1), 93. https://doi.org/10.22146/ijeis.70141
Arifin, S., Muslim, M. A., &; Sugiman, S. (2016). Implementation of Fuzzy Mamdani logic to detect the vulnerability of flooded areas in North Semarang. Scientific Journal of Informatics, 2(2), 179. https://doi.org/10.15294/sji.v2i2.5086
Arjuna, A., Shauqi, A., &; Nabyla, F. (2021). Decision Support System in Scholarship Determination using Fuzzy Logic Method (Case Study of University of Civilization). Journal of Information Systems and ..., 2(1), 1–5. https://103.122.98.12/index.php/jsitp/article/view/752
Batvian, K., &; Manullang, S. R. (2022). Grouping Types of Building Damage to SD Inpres 22 Sorong Regency. Journal of Symmetry, 12(1), 531–536. https://doi.org/10.31959/js.v12i1.1067
Daniel, Diba, F., &; Husni, H. (2014). Identification of damage to elementary school buildings in Pontianak City based on wood damage factors. Journal of Sustainable Forests, 365–372.
Goddess, AR (2020). Implementation of Disaster Preparedness School Policy at the Elementary School Level in Yogyakarta. HIGEIA Journal, 4(1), 286–295. http://journal.unnes.ac.id/sju/index.php/higeia
Director General, S. K., Research, P., Development, D., Higher Education, R., Hamdi, K., Information, S., & Padang, J. (2017). SINTA Accredited Rank 2 Geographic Information System (RTLH) Data Analysis of Uninhabitable Houses Using Fuzzy Logic Method. Validity period from, 1(3), 1179–1189.
Fibriani, C., &; Wijayanto, G. A. (2020). Modeling recommendations for temporary landfills using fuzzy overlays in Semarang Regency. Systemation, 9(1), 27. https://doi.org/10.32520/stmsi.v9i1.571
Logic, F., Gudiato, C., Cahyaningtyas, C., &; Noviyanti, P. (2024). G-Tech : Journal of Applied Technology. 8(1), 186–195.
Mathematics, J. (2018). Application of Fuzzy Linear Programming in Optimizing the Construction of Flats (Flats) in the Pondok Cina Area of West Java Province. 4(1), 79–89.
Muharomeita Aulia, Ekawati Prihatini, &; Nyayu Latifah Husni. (2020). Design of Fuzzy Logic-Based Blind Aids Control. Sriwijaya Journal of Electrical Engineering, 1(2), 62–70. https://doi.org/10.36706/jres.v1i2.15
Muhtadi, N. S., Rahman, D. M., &; Surianto, D. F. (2024). Forest Fire Risk Analysis with Fuzzy Mamdani Logic. Journal of Electrical Informatics and Applied Engineering, 12(1). https://doi.org/10.23960/jitet.v12i1.3902
Muttaqin, Z., Jubaedi, A.D., Kom, M., &; Kom, M. (2021). DSLR cameras use the Fuzzy Logic method. 8(1), 13–16.
Nasution, V. M., &; Prakarsa, G. (2021). Designing a fuzzy logic application for the prediction of positive Covid-19 cases using the Tsukamoto method. Journal of Media Informatics Budidarma, 5(4), 1642. https://doi.org/10.30865/mib.v5i4.3338
Oktavia, H. F., Suyoso, H., &; Nursing, N. (2020). Analysis of the Level of Damage and Estimated Cost of Building Maintenance of the Faculty of Nursing, Jember University. Journal of Civil and Environmental Engineering, 4(1), 22–30.
Parningotan, S., &; Mulyanto, T. (2020). Using the Sugeno method in fuzzy Logic. Journal of Manufacturing Technology, 12(01).
Pujianto, A., Faizah, R., Monika, F., &; Prayuda, H. (2019). Rapid assessment of school buildings after the Palu earthquake. Bulletin of Professional Engineers, 2(2), 81–85. https://doi.org/10.20527/bpi.v2i2.46
Retired, H. A., Ratnaningsih, A., &; Irawan, J. F. (2022). Green Building Assessment in the Lecture Building of the Faculty of Medicine, University of Jember using the Greenship assessment tool for the new building version 1.2. Journal of Civil and Environmental Engineering, 5(2), 166. https://doi.org/10.19184/jrsl.v5i2.18936
Puspaningrum, A. S. (2022). Implementation of Disaster Resilient Schools at Smk Bina TTrain Karya. Journal of Social Sciences and Technology for Community Service (JSSTCS), 3(2), 224. https://doi.org/10.33365/jsstcs.v3i2.2091
Rizki, A. M., &; Marina, N. (2019). Classification of damage to school buildings using the Convolutional Neural Network method with a pre-trained model Vgg-16. Scientific Journal of Technology and Engineering, 24(3), 197–206. https://doi.org/10.35760/tr.2019.v24i3.2396
Rosani, D. P., Dhokhikah, Y., &; Trisiana, A. (2020). Technical Risk Analysis of Construction Project Using Fuzzy Logic Method (Case Study of Grand Sungkono Lagoon Project, Surabaya). Journal of Civil and Environmental Engineering, 4(1), 40–50.
Faithful, B. (2019). Application of fuzzy logic to intelligent systems. 02, 61–66.
Tundo, T., Akbar, R., &; Sela, E. I. (2020). Comparative analysis of Fuzzy Tsukamoto and Sugeno in determining the amount of woven fabric production using a base rule decision tree. In Journal of Information Technology and Computer Science (Vol. 7, Issue 1, p. 171). https://doi.org/10.25126/jtiik.2020701751
Wiyanto, H., &; Justin, E. (2019). Determination of criteria for assessing concrete damage to buildings based on priority scales. Estuary Journal of Science, Technology, Medicine and Health Sciences, 3(1), 153. https://doi.org/10.24912/jmstkik.v3i1.5192
Yulia, & Mardiah, A. (2018). Fuzzy Logic to determine student satisfaction with school facilities and infrastructure using the Sugeno method. Scientific Journal of Informatics, 6(01), 32.
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