Optimasi Penjadwalan Proyek Kantor PT.X dengan Konsep Finance-Based Scheduling dan Metode Metaheuristik

Ambrosius Matthew Junius Reynaldo; Doddy Prayogo; Richard Christian Thendean; Imannuel Michraga Freando

doi:10.28932/jts.v20i2.8445

Authors

Ambrosius Matthew Junius Reynaldo Program Studi Teknik Sipil, Universitas Kristen Petra, Surabaya, 60236, Indonesia
Doddy Prayogo Program Studi Teknik Sipil, Universitas Kristen Petra, Surabaya, 60236, Indonesia
Richard Christian Thendean Program Studi Teknik Sipil, Universitas Kristen Petra, Surabaya, 60236, Indonesia
Imannuel Michraga Freando Program Studi Teknik Sipil, Universitas Kristen Petra, Surabaya, 60236, Indonesia

DOI:

https://doi.org/10.28932/jts.v20i2.8445

Keywords:

Scheduling, Finance, Finance-Based Scheduling, Optimization, Symbiotic Organisms Search

Abstract

Contractors need to pay attention to the financial condition of the company so that the availability of funds to carry out profitable construction operations can be fulfilled. Construction projects require substantial funds, so contractors often utilize bank loan systems. A finance-based scheduling concept is needed to combine scheduling and funding in construction projects. This research seeks to optimize finance-based scheduling with the goal of minimizing interest on contractor loans. The optimization method used is the metaheuristic algorithm Symbiotic Organisms Search (SOS), and the case study used is the construction project of PT.X office building in Surabaya with the aim of providing alternative scheduling scenarios to contractors. The optimization process involves shifting the start time of activities (shift value) to generate new schedules. The results of the optimization process in three payment scenarios were able to produce smaller interest burdens on contractor loans. Additionally, after the optimization process, the contractor's largest loan also decreased, meeting the credit limit set by the bank. The best alternative scenario choices are scenarios 1 and 3, which result in the highest decrease in loan interest burden and the largest decrease in loan amount.

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