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Gusfan Halik
Department of Civil Engineering, Faculty of Engineering, Jember University, Jember
Civil Engineering, Building, Construction & Architecture

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Prediction Of Project Schedule Performance Index for Trans South Java Road Project Lot 7 Blitar Regency Using Bayesian Network Kristya Hadi Wicaksono; Jojok Widodo Soetjipto; Gusfan Halik
UKaRsT Vol. 7 No. 1 (2023): APRIL
Publisher : Kadiri University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30737/ukarst.v7i1.3552

Abstract

The south coast of Indonesia has considerable potential and competitiveness in the field of tourism. This encourages the government to strive to improve tourism infrastructure through the construction of the South Coast Road. In its implementation, project reporting must be measured and controlled to assist project management in identifying problems and factors that affect project activities.  This research aims to identify the most influential factors on Schedule Performance Index and develop a prediction model using the Bayesian Network. 5 main factors that affect project performance, such as Heavy Equipment, materials, Implementation and Work Relations, Labor, and Environment are used to are set 13 scenarios to detect the behavior of each factor appropriately. The factor is confirmed to the respondent to ensure that the factor occurs in the project. The study's results obtained Bayesian Network approach can be used to assess the condition of the JLS Lot 7 Blitar  Schedule Performance Index (SPI) with an accuracy of around 80%. The dominant factor affecting SPI is the condition of the Heavy Equipment.  The condition of the Heavy Equipment will affect the condition of SPI so closely that the contractor must maintain the performance of the heavy equipment so that the project performance is always in good condition. The identification results are expected to help in better decision-making and project risk management.
Flood Susceptibility Mapping in Gending District by Comparison Frequency Ratio and Weight of Evidence for Mitigation Strategy Bachtiar Ilham Maulana; Entin Hidayah; Gusfan Halik
UKaRsT Vol. 7 No. 1 (2023): APRIL
Publisher : Kadiri University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30737/ukarst.v7i2.3999

Abstract

Floods are natural disasters that occur all over the world. Gending District in Probolinggo Regency, East Java, is an area that often experiences floods and causes various losses. A flood susceptibility map needed to prepare appropriate mitigation actions. Choosing the right method will produce a more accurate flood susceptibility map. The research aims to make a flood susceptibility map in Gending District by comparing the Frequency Ratio (FR) and Weight of Evidence (WofE) methods and providing appropriate mitigation recommendations. Six data factors that cause flooding are used: slope, elevation, land use, normalized difference vegetation index (NDVI), curvature, and rainfall. The data obtained were processed using the FR and WofE methods, which were then validated using the Receiver Operating Characteristics (ROC) method. The validation value is calculated using the ROC chart's Area Under Curve (AUC). The higher the AUC value, the better. The study's results revealed that the correct method for making a flood susceptibility map in Gending District was FR with an AUC value of 92.8%, while the WofE method was 90.4%. The flood susceptibility map illustrates that 14% of the area is in very high and high flood-prone zones, 23% is in the moderate zone, and 63% is in the safe zone. The appropriate mitigation strategy based on the highest FR value is creating drainage networks, and green open spaces, normalizing rivers in residential areas, and implementing selective logging and reforestation programs. The results of this study are used to reduce the impact and risk of future flood disasters.
Co-Authors Bachtiar Ilham Maulana Entin Hidayah Jojok Widodo Soetjipto Kristya Hadi Wicaksono