The Effect of Internal and External Project Factors on the Performance of Road Improvement Projects in Papua Province - Arnes Richard Kreeuw; Bernathius Julison; Mujiati; Bahtiar; Dewi Ana Rusim (Jurnal Ekonomi Teknologi dan Bisnis (JETBIS), 2026)
This study aimed to analyze the influence of Internal Project Factors and External Project Factors on the performance of road improvement projects in Papua Province. The research was motivated by the importance of successful road construction projects in supporting regional connectivity, particularly in Papua Province, which faces complex geographical, logistical, and project implementation challenges. Internal factors, including project management, human resource competence, heavy equipment availability, and contractor financial capacity, as well as external factors, such as weather conditions, social factors, and bureaucratic processes, were assumed to influence project performance. The research employed a qualitative approach using a survey method through questionnaires distributed to parties directly involved in road construction projects, including Commitment-Making Officials (Pejabat Pembuat Komitmen or PPK), Technical Activity Implementation Officers (Pejabat Pelaksana Teknis Kegiatan or PPTK), supervisory consultants, and contractors. A total of 196 respondents participated in this study. The data were analyzed using IBM SPSS Statistics 26 through validity testing, reliability testing, classical assumption testing, multiple linear regression analysis, partial significance testing (t-test), simultaneous significance testing (F-test), and coefficient of determination (R²) analysis. The results showed that Internal Project Factors (X1) had a positive and significant effect on Project Performance (Y), whereas External Project Factors (X2) did not have a partially significant effect. Simultaneously, both independent variables significantly influenced project performance. The coefficient of determination (R²) value of 0.434 indicated that the two independent variables explained 43.4% of the variation in project performance, while the remaining 56.6% was influenced by other factors outside the research model.