PENERAPAN PEMROGRAMAN PYTHON DALAM MENENTUKAN WAKTU OVERHOUL KONDENSOR TURBIN UAP

Application of Python Programming in Determining the Overhoul Steam Turbine Condenser

Authors

  • Raihan Muhammad Universitas Muhammadiyah Jakarta
  • Sulis Yulianto Universitas Muhammadiyah Jakarta

DOI:

https://doi.org/10.21009/JKEM.8.1.6

Keywords:

Cleanliness Condenser, Linear Regression, Python

Abstract

Condensers as the main equipment and heat exchangers in a combined cycle power plant have a major effect to determine combined cycle efficiency. The condenser is used to transform saturated steam into water which will be reused in a combined cycle power plant. To acquire high performance, the condenser requires an overhaul plan and calculated performance. In this research, to determine a good overhaul plan, the python programming language with the linear regression method is used. The python programming language aims to predict the condenser when it must be overhauled. From the results of the research, it was found that there was an increase in the value of the cleanliness factor condenser before the overhaul. From 56.69% to 57.45% after the overhaul. After using linear regression in python programming on the distribution data from 2018 which was divided into three groups of analysis, it was found that the condenser must be overhauled on August 24, 2023.

References

[1] Akmal, "Lebih Dekat Dengan Industri 4.0," Sleman: Deepublish, 2019.
[2] N. Fonna, "Pengembangan Revolusi Industri 4.0 dalam Berbagai Bidang," Medan: Guepedia, 2019.
[3] G. N. Ayuni, “Penerapan Metode Regresi Linear Untuk Predisi Penjualan Properti pada PT XYZ,” Jurnal Telematika, vol. 14 no. 2, pp. 79-86, 2019.
[4] A. Sukarno and B. Prasetyo, “Analisis Perubahan Tekanan Vakum Kondensor Terhadap Kinerja Kondensor di PLTU Tanjung Jati B Unit 1,” EKSERGI Jurnal Teknik Energi, vol. 10, no. 2, pp. 65-71, 2014.
[5] N. N. P. Pinata, I. M. Sukarsa, and N. K. D. Rusjayanthi, “Prediksi Kecelakaan Lalu Lintas di Bali dengan XGBoost pada Python,” Jurnal Ilmiah Merpati , vol. 8, no. 3, pp. 188-196, 2020.
[6] R. Rajesh and P. S. Kishore, “Thermal Efficiency of Combined Cycle Power Plant,” International Journal of Engineering and Management Research, vol. 8, no. 3, pp. 229-234, 2018.
[7] J. Litwin, M. Olech, and A. Szymusik, “Applying Python’s Time Series Forecasting Method in Microsoft Excel – Integration as a Business Process Supporting Tool for Small Enterprises,” Technical Sciences, vol. 24, pp. 115-133, 2021.
[8] G. Prihandini and M. T. Sinarta, “Analisa Cleanliness Factor Sebagai Nilai Performasi Kondenser,” Jurnal Migasian, vol. 1, no. 2, pp. 36-39, 2017.
[9] T. L. Bergman, A. S. Lavine, F. P. Incropera, and D. P. Dewitt, "Fundamentals of Heat Transfer 7th Edition," United States of America: John Wiley & Sons, Inc., 2011.
[10] J. J. F. E. A. Hair, "Multivariate Data Analysis-Fifth Edition," New Jersey: PrenticeHall, Inc, 2011.
[11] B. Abraham, "The Regression Model," in Statistical Methods for Forecasting, United States of America, John Wiley & Sons, Inc., pp. 8-77, 2005.
[12] A. S. Saabith, M. Farez, and T. Vinothraj, “Python Current Trend Applications-An Overview,” International Journal of Advance Engineering and Research Development, vol. 6 , no. 10, pp. 6-12, 2019.
[13] Chandan07, “GeeksforGeeks,” 16 Agustus 2021. [Online]. Available: https://www.geeksforgeeks.org/python-for-data-science/#:~:text=It%20provides%20great%20libraries%20to,not%20have%20an%20engineering%20background.

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Published

2023-01-07

How to Cite

[1]
Raihan Muhammad and S. Yulianto, “PENERAPAN PEMROGRAMAN PYTHON DALAM MENENTUKAN WAKTU OVERHOUL KONDENSOR TURBIN UAP: Application of Python Programming in Determining the Overhoul Steam Turbine Condenser”, J. Konversi Energi dan Manufaktur, vol. 8, no. 1, pp. 49–57, Jan. 2023.

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