Smart Material Test: Optimalisasi Pengujian Bahan Bangunan Berbasis Web
Abstract
In designing material requirements, it is very important to do so that the use of materials becomes effective and efficient. Building materials are an important component in producing a reliable quality building structure. One of the efforts made to ensure the quality of building materials is to carry out material tests in the laboratory. The Palembang Aviation Polytechnic materials laboratory performs the testing procedure manually using a calculator or Microsoft Excel. Manual test calculations pose potential problems (error calculation) and must be well-documented. A materials testing calculation application is made for data processing to get better results and more efficient and effective calculations. The research aims to optimize the data processing of building materials testing using an application so that it is more efficient and effective and the data can be well documented. The material was used to calculate fine aggregate and coarse aggregate tests. The research has implemented a web-based Smart Material Test application using the programming language PHP Version 7, Laravel 8 Framework, and MySQL Database to optimize material testing that is more accurate and well-documented. The results show of testing the application, as many as 50 trials for each test found no application errors, and the average calculation difference was 0.0005 or 0.01744%. Thus, the application is very useful in assisting the calculation of building material testing.
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Allen, E. and Iano, J. (2019) Fundamentals of building construction: materials and methods. John Wiley & Sons.
ASTM C33 (1985) ‘Kadar Air Agregat Kasar’, 2(1), pp. 1–7.
Hsu, T.-C., Chang, S.-C. and Hung, Y.-T. (2018) ‘How to learn and how to teach computational thinking: Suggestions based on a review of the literature’, Computers & Education, 126, pp. 296–310.
Huang, Y. and Fu, J. (2019) ‘Review on application of artificial intelligence in civil engineering’, Computer Modeling in Engineering & Sciences, 121(3), pp. 845–875.
Jiang, F. et al. (2021) ‘Digital twin and its implementations in the civil engineering sector’, Automation in Construction, 130, p. 103838.
Klahr, D. and Wallace, J.G. (2022) Cognitive development: An information-processing view. Routledge.
Li, Z. et al. (2022) Advanced concrete technology. John Wiley & Sons.
Muqorobin, M. and Rais, N.A.R. (2022) ‘Comparison of PHP Programming Language with Codeigniter Framework in Project CRUD’, International Journal of Computer and Information System (IJCIS), 3(3), pp. 94–98.
Nasional, B.S. (1990a) ‘SNI 03-1968-1990’, Metode Pengujian Analisis Saringan Agregat Halus dan Kasar [Preprint].
Nasional, B.S. (1990b) SNI 03-1970-1990, Metode Pengujian Berat Jenis dan Penyerapan Air Agregat Halus. Jakarta.
Nasional, B.S. (2008) ‘SNI 2417: 2008’, Cara Uji Keausan Agregat Dengan Mesin Abrasi Los Angeles [Preprint].
Robert L Peurifoy et al. (2018) Construction planning, equipment, and methods. McGraw-Hill Education.
Setiawan, D. (2019) ‘Kompterisasi Perhitungan Parameter Marshall Untuk Rancangan Campuran Beton Aspal’, Jurnal Teknik Sipil, 4(1), pp. 9–27. Available at: https://doi.org/10.28932/jts.v4i1.1293.
Tang, C.-W., Cheng, C.-K. and Ean, L.-W. (2022) ‘Mix design and engineering properties of fiber-reinforced pervious concrete using lightweight aggregates’, Applied Sciences, 12(1), p. 524.
Vögele, C. et al. (2018) ‘WESSBAS: extraction of probabilistic workload specifications for load testing and performance prediction—a model-driven approach for session-based application systems’, Software and Systems Modeling, 17(2), pp. 443–477. Available at: https://doi.org/10.1007/s10270-016-0566-5.
DOI: http://dx.doi.org/10.33087/talentasipil.v6i2.295
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