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Classification system model for project sustainability Hendra, S; Ngemba, H R; Azhar, R; Laila, R; Domingo, N P; Nur, R
Applied Engineering and Technology Vol 1, No 3 (2022): December 2022
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (305.312 KB) | DOI: 10.31763/aet.v1i3.689

Abstract

One of the problems faced by the state-owned electricity company (PT. PLN) in Indonesia is the difficulty of monitoring the progress of an ongoing project so that it requires a technology that can help project managers in monitoring project implementation. The data in this study consisted of 117 Win project data and 89 Lose project data with a total of 206 data. The system development used extreme programming with algorithmic testing, namely the configuration matrix. The result of this research showed that the model could produce an accuracy of 92.68% with an error percentage of 7.32%, which means that the model produced good accuracy in implementing the C4.5 algorithm in recognizing patterns of project development. The first implication of the proposed approach is that it can establish project work monitoring services. The second implication is that project managers can improve company performance