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All Journal Instal : Jurnal Komputer International Journal of Economics, Management and Accounting
Yasri, Afif
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Analysis of the Influence of Competency and Workload on Employee Performance with Presenteism as An Intervening Variable in the Distribution Regulation Implementing Unit (UP2D) PT. PLN (Persero) North Sumatera Distribution Main Unit Yasri, Afif; Syahrizal, Syahrizal
International Journal of Economics, Management and Accounting (IJEMA) Vol. 2 No. 9 (2025): February
Publisher : Lafadz Jaya Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47353/ijema.v2i9.242

Abstract

This study aims to analyze the influence of competence and workload on employee performance with presenteeism as an intervening variable at the Distribution Management Implementation Unit (UP2D) of PT. PLN (Persero) North Sumatra Distribution Main Unit. Competence and workload are important factors that influence employee performance in achieving organizational goals, while presenteeism, which refers to the physical presence of employees without optimal productivity, can be a barrier to performance. This study uses a quantitative approach with an explanatory research design. Data were collected through questionnaires distributed to employees of UP2D PT. PLN (Persero), and analyzed using the path analysis method to measure the direct and indirect relationships between the variables studied. The results of this study are that Workload has a negative and significant effect on Employee Performance with an original sample value of -0.264 and p values 0.006. Workload has a positive and significant effect on Presenteeism with an original value of 0.379 and p values 0.000. Competence has a positive and significant effect on Employee Performance with an original sample value of 0.300 and p values of 0.001. Competence has a negative and significant effect on Presenteeism with an original sample value of -0.579 and p values of 0.000. Presenteeism has a negative and significant effect on Employee Performance with an original sample value of -0.397 and p values of 0.002. Workload has a negative and significant effect on Employee Performance through Presenteeism with an original sample value of -0.151 and p values of 0.004. Competence has a positive and significant effect on Employee Performance through Presenteeism with an original sample value of 0.230 and p values of 0.008.
Development of a distribution network electricity supply regulation system using machine learning at PT. PLN (Persero) UP2D North Sumatra Yasri, Afif; Zulham Sitorus
Bahasa Indonesia Vol 18 No 02 (2026): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v18i02.491

Abstract

The regulation of efficient energy supply within the distribution network is a significant difficulty for PT. PLN (Persero) UP2D North Sumatra in delivering dependable and stable services. This project seeks to create an automated system for regulating power supply in the distribution network through machine learning techniques. This system aims to forecast and enhance the allocation of electrical energy utilising historical data and current network circumstances. The dataset is partitioned into training data (training set) and testing data (testing/validation set) in specific ratios, such as 70%:30% or 80%:20%. The division is executed to preserve the temporal sequence (in time series scenarios) or to ensure a balanced representation (in classification scenarios). The employed machine learning approach is K-Means Clustering, utilised to analyse electricity consumption patterns and identify probable problems in the distribution network. The new centroid computation is based on the fact that each cluster contains a single data point, specifically C1 = (193, 205, 213), C2 = (153, 167, 170), and C3 = (179, 196, 200). This study's findings are anticipated to enhance the efficiency of energy distribution management, minimise downtime, and elevate the quality of service for consumers. By using a machine learning-driven automation system, PT. PLN UP2D North Sumatra can enhance its adaptability to load fluctuations and optimise the utilisation of current power supplies. The division is executed to preserve the temporal sequence (in the case of time series) or to ensure a balanced representation (in the case of classification).
Co-Authors Sitorus, Zulham Syahrizal Syahrizal