@article{Putra_Prasojo_Novfowan_Neelmani_2023, title={Dissolved Gas Analysis of Generator Step Up Transformer in Grati Power Plant Using Random Forest Based Method}, volume={13}, url={https://jartel.polinema.ac.id/index.php/jartel/article/view/583}, DOI={10.33795/jartel.v13i1.583}, abstractNote={<p>Transformers are one of the important electrical equipment in the power system. To prevent some electrical contact on the component in transformers, an insulator or dielectric material is needed likely insulating oil. DGA test is important for diagnosis and deciding the maintenance of transformers. Duval Triangle and Duval Pentagon methods are DGA identification methods with the highest of accuracy compared to other methods. The data used in this article is from the DGA measurement test of transformers GT 3.1 Steam and Gas Power Plant Grati. The DGA data was analyzed by Random Forest based-model of Duval Triangle and Pentagon method, in accordance to IEEE C57.104-2019 and IEC 60599-2015 guidelines. Random Forest based-model has the best performance in implemented Duval method than others. The result of DGA identification using Random Forest based-model showed PD and S for Duval Triangle, and S for Duval Pentagon and from the results of identification using the Duval Triangle and Pentagon it does not always show the same results on the same test sample, so it is necessary to identify the history of DGA testing to get accurate results. This article presents the use of the combined Duval Triangle and Pentagon for diagnosis transformers.</p>}, number={1}, journal={Journal of Telecommunication Network (Jurnal Jaringan Telekomunikasi)}, author={Putra, Muhammad Akmal Afibuddin and Prasojo, Rahman Azis and Novfowan, Anang Dasa and Neelmani, Neelmani}, year={2023}, month={Feb.}, pages={51-58} }