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[1] Budya, H., Arofat, M.Y. (2011). Providing cleaner energy access in Indonesia through the megaproject of kerosene conversion to LPG. Energy Policy, 39, 7575-7586. https://doi.org/10.1016/j.enpol.2011.02.06110.1016/j.enpol.2011.02.061 Search in Google Scholar

[2] Badan Standarisasi Nasional. (2018). Kompor gas LPG dan LNG/NG tekanan rendah untuk rumah tangga (Gas stove with low pressure of LPG and LNG/NG for household). SNI 8660:2018. Search in Google Scholar

[3] Badan Standarisasi Nasional. (2019). Kompor gas LPG dan LNG/NG untuk komersil (Gas stove with LPG and LNG/NG for commercial). SNI 7613:2019. Search in Google Scholar

[4] Stant, L.T., Aaen, P.H., Ridler, N.M. (2016). Comparing methods for evaluating measurement uncertainty given in the JCGM ‘evaluation of measurement data’ documents. Measurement, 94, 847-851. https://doi.org/10.1016/j.measurement.2016.08.01510.1016/j.measurement.2016.08.015 Search in Google Scholar

[5] ISO. (2008). Uncertainty of measurement — Part 3: Guide to the expression of uncertainty in measurement (GUM:1995) — Supplement 1: Propagation of distributions using a Monte Carlo method. ISO/IEC Guide 98-3:2008 Supplement 1. Search in Google Scholar

[6] Yeung, H., Papadopoulos, C.E. (2000). Natural gas energy flow (quality) uncertainty estimation using Monte Carlo simulation method. In 10th IMEKO TC9 Conference on Flow Measurement (FLOMEKO 2000). IMEKO. Search in Google Scholar

[7] Sediva, S., Uher, M., Havlikova, M. (2015). Application of the Monte Carlo method to estimate the uncertainty of air flow measurement. In Proceedings of the 2015 16th International Carpathian Control Conference (ICCC). IEEE, 465-469, DOI: 10.1109/CarpathianCC.2015.7145124.10.1109/CarpathianCC.2015.7145124 Search in Google Scholar

[8] Castrup, S. (2010). Comparison of methods for establishing confidence limits and expanded Uncertainties. In Measurement Science Conference, Pasadena, USA. Search in Google Scholar

[9] Acko, B., Godina, A. (2005). Verification of the conventional measuring uncertainty evaluation model with Monte Carlo simulation. International Journal of Simulation Modelling, 4 (2), 76-84. http://dx.doi.org/10.2507/IJSIMM04(2)3.03910.2507/IJSIMM04(2)3.039 Search in Google Scholar

[10] Castro, H. (2021). Validation of the GUM using the Monte Carlo method when applied in the calculation of the measurement uncertainty of a compact prover calibration. Flow Measurement and Instrumentation, 72, 101877. https://doi.org/10.1016/j.flowmeasinst.2020.10187710.1016/j.flowmeasinst.2020.101877 Search in Google Scholar

[11] Bahassou, K., Salih, Oubrek, M., Jalid, A. (2019). Measurement uncertainty on the correction matrix of the coordinate measuring machine. International Journal of Advanced Research in Engineering and Technology, 10 (2), 669-676.10.34218/IJARET.10.2.2019.064 Search in Google Scholar

[12] Theodorou, D., Meligotsidou, L., Karavoltsos, S., Burnetas, A., Dassenakis, M., Scoullos, M. (2011). Comparison of ISO-GUM and Monte Carlo methods for the evaluation of measurement uncertainty: Application to direct cadmium measurement in water by GFAAS. Talanta, 83 (5), 1568-1574. https://doi.org/10.1016/j.talanta.2010.11.05910.1016/j.talanta.2010.11.05921238753 Search in Google Scholar

[13] Theodorou, D., Zannikou, Y., Anastopoulos, G., Zannikos, F. (2011). Coverage interval estimation of the measurement of gross heat of combustion of fuel by bomb calorimetry: Comparison of ISO GUM and adaptive Monte Carlo method. Thermochimica Acta, 526 (1-2), 122-129. https://doi.org/10.1016/j.tca.2011.09.00410.1016/j.tca.2011.09.004 Search in Google Scholar

[14] Couto, P.R.G., Damasceno, J.C., Borges, R.M.H. (2006). Uncertainty estimation of mechanical assays by ISO GUM 95 and Monte Carlo simulation – case study: Tensile strength, torque and brinell hardness measurements. In XVIII IMEKO World Congress: Metrology for a Sustainable Development. IMEKO. Search in Google Scholar

[15] Mahmoud, G.M., Hegazy, R.S. (2017). Comparison of GUM and Monte Carlo methods for the uncertainty estimation in hardness measurements. International Journal of Metrology and Quality Engineering, 8, 14. https://doi.org/10.1051/ijmqe/201701410.1051/ijmqe/2017014 Search in Google Scholar

[16] Jalid, A., Hariri, S., El Gharad, A., Senelaer, J.P. (2016). Comparison of the GUM and Monte Carlo methods on the flatness uncertainty estimation in coordinate measuring machine. International Journal of Metrology and Quality Engineering, 7 (3), 302. https://doi.org/10.1051/ijmqe/201601310.1051/ijmqe/2016013 Search in Google Scholar

[17] Navacerrada, M.A., Sanchidrián, C.D., Pedrero, A., Martínez, L.I. (2008). Calculus of the uncertainty in acoustic field measurements: Comparative study between the uncertainty propagation method and the distribution propagation method. In V Congreso Ibérico de Acústica, Coimbra, Portugal. Search in Google Scholar

[18] Junga, R., Chudy, P., Pospolita, J. (2017). Uncertainty estimation of the efficiency of small-scale boilers. Measurement, 97, 186-194. http://dx.doi.org/10.1016/j.measurement.2016.11.01110.1016/j.measurement.2016.11.011 Search in Google Scholar

[19] Ramnath, V. (2010). Comparison of the GUM and Monte Carlo measurement uncertainty techniques with application to effective area determination in pressure standards. International Journal of Metrology and Quality Engineering, 1 (1) 51-57. https://doi.org/10.1051/ijmqe/201001310.1051/ijmqe/2010013 Search in Google Scholar

[20] Wen, X., Zhao, Y., Wang, D., Pan, J. (2013). Adaptive Monte Carlo and GUM methods for the evaluation of measurement uncertainty of cylindricity error. Precision Engineering, 37 (4), 856-864. http://dx.doi.org/10.1016/j.precisioneng.2013.05.00210.1016/j.precisioneng.2013.05.002 Search in Google Scholar

[21] Ling, M., Li, H., Li, Q. (2014). Measurement uncertainty evaluation method considering correlation and its application to precision pentrifuge. Measurement Science Review, 14 (6), 308-316. https://doi.org/10.2478/msr-2014-004210.2478/msr-2014-0042 Search in Google Scholar

[22] Kusnandar, N. (2015). Metode pengukuran asupan panas kompor gas berdasarkan SNI 7368:2011 dan SNI 7469:2013 (The method of measuring gas stove heat input based on SNI 7368:2011 and SNI 7469:2013). Jurnal Standarisasi, 17 (3), 233-240, DOI: 10.31153/js.v17i3.323.10.31153/js.v17i3.323 Search in Google Scholar

[23] Utomo, B., Kusnandar, N., Lailiyah, Q., Ramadhani, W.S. (2019). An evaluation of heat input and efficiency test method based on SNI 7368:2011 – single burner LPG gas stove with igniter system. Jurnal Standarisasi, 21 (3), 193-201, DOI: 10.31153/js.v21i3.773.10.31153/js.v21i3.773 Search in Google Scholar

[24] Badan Standarisasi Nasional. (2010). Kompor gas bahan bakar LPG satu tungku dengan sistem pemantik (Single burner LPG gas stove with ignition system). SNI 7368:2011. Search in Google Scholar

[25] IEC - IECEE. (2004). Laboratory procedure for preparation, attachment, extension and use of thermocouples. CTL-OP 108-Ed.1. Search in Google Scholar

[26] JCGM. (2008). Evaluation of measurement data - Guide to the expression of uncertainty in measurement. JCGM 100:2008. Search in Google Scholar

[27] ISO. (2008). Uncertainty of measurement - Part 3: Guide to the expression of uncertainty in measurement (GUM:1995). ISO/IEC Guide 98-3:2008. Search in Google Scholar

[28] ISO. (2009). Uncertainty of measurement - Part 1: Introduction to the expression of uncertainty in measurement. ISO/IEC Guide 98-1:2009. Search in Google Scholar

[29] Beckert, S.F., Domeneghetti, G., Bond, D. (2013). Use of pooled standard deviation of paired samples in calculating the measurement uncertainty by the Monte Carlo Method. In 16th International Congress of Metrology. EDP Sciences, 03003. https://doi.org/10.1051/metrology/20130300310.1051/metrology/201303003 Search in Google Scholar

[30] Sediva, S., Havlikova, M. (2013). Comparison of GUM and Monte Carlo method for evaluation measurement uncertainty of indirect measurements. In Proceedings of the 14th International Carpathian Control Conference. IEEE, DOI: 10.1109/CarpathianCC.2013.6560563.10.1109/CarpathianCC.2013.6560563 Search in Google Scholar

[31] Solaguren-Beascoa Fernandez, M., Alegre Calderon, J.M., Bravo Diez, P.M. (2009). Implementation in MATLAB of the adaptive Monte Carlo method for the evaluation of measurement uncertainties. Accreditation and Quality Assurance, 14, 95-106. https://doi.org/10.1007/s00769-008-0475-610.1007/s00769-008-0475-6 Search in Google Scholar

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Sujets de la revue:
Engineering, Electrical Engineering, Control Engineering, Metrology and Testing