Analisis Faktor Yang Mempengaruhi Idle Time (IT) Pada Proses Bongkar Muat Kapal di Terminal Petikemas Koja Pelabuhan Tanjung Priok Jakarta

been resolved in Indonesia. This research aims to determine the influence of Port Services, Loading and Unloading Performance, Loading and Unloading Equipment and Natural Factors on Idle Time at the Koja Container Terminal, Tanjung Priok Port, Jakarta. The population in this study were operational employees and ship crew from the deck department division. The sample used in this research was 80 respondents. And using a disproportionate stratified random sampling technique, then the data was analyzed using multiple linear regression with the help of (software) Statistical Package For Social Science (SPSS) Version 25. Based on the research results and data analysis, the regression equation was produced: Y= -1.176+ 0.334X1+ 0.181X2 + 0.318X3 + 0.302X4+ . From the equation it is known that the dominant variable influencing Idle Time is the Port Services variable with a regression coefficient of 0.334. The R2 (R square) test obtained a result of (67%), which means that Idle Time at the Koja Container Terminal, Tanjung Priok Port, Jakarta, is influenced by the variables Port Service, Loading and Unloading Performance, Loading and Unloading Equipment and Natural Factors, namely 67%. The conclusion is that the independent variables (port services, loading and unloading performance, loading and unloading equipment, and natural factors) have a negative and significant effect on the dependent variable Idle Time. This is because the results of the multiple linear regression equation show that t count > t table.

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Publication Details

Journal
Ocean Engineering Jurnal Ilmu Teknik dan Teknologi Maritim
Published
2025-02-19
DOI
https://doi.org/10.58192/ocean.v3i4.3053
Primary Topic
Management and Optimization Techniques
Type
article
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article

Analisis Faktor Yang Mempengaruhi Idle Time (IT) Pada Proses Bongkar Muat Kapal di Terminal Petikemas Koja Pelabuhan Tanjung Priok Jakarta

Iwan Weda, Purnomo Ari Wibowo, Gembong Satria Negara, Suryo Guritno et al.
Ocean Engineering Jurnal Ilmu Teknik dan Teknologi Maritim
Management and Optimization Techniques
article

Analisis Faktor Yang Mempengaruhi Idle Time (IT) Pada Proses Bongkar Muat Kapal di Terminal Petikemas Koja Pelabuhan Tanjung Priok Jakarta

Iwan Weda, Purnomo Ari Wibowo, Gembong Satria Negara, Suryo Guritno, Irwan Baharudin, Faresh Emha
article en

Abstract

been resolved in Indonesia. This research aims to determine the influence of Port Services, Loading and Unloading Performance, Loading and Unloading Equipment and Natural Factors on Idle Time at the Koja Container Terminal, Tanjung Priok Port, Jakarta. The population in this study were operational employees and ship crew from the deck department division. The sample used in this research was 80 respondents. And using a disproportionate stratified random sampling technique, then the data was analyzed using multiple linear regression with the help of (software) Statistical Package For Social Science (SPSS) Version 25. Based on the research results and data analysis, the regression equation was produced: Y= -1.176+ 0.334X1+ 0.181X2 + 0.318X3 + 0.302X4+ . From the equation it is known that the dominant variable influencing Idle Time is the Port Services variable with a regression coefficient of 0.334. The R2 (R square) test obtained a result of (67%), which means that Idle Time at the Koja Container Terminal, Tanjung Priok Port, Jakarta, is influenced by the variables Port Service, Loading and Unloading Performance, Loading and Unloading Equipment and Natural Factors, namely 67%. The conclusion is that the independent variables (port services, loading and unloading performance, loading and unloading equipment, and natural factors) have a negative and significant effect on the dependent variable Idle Time. This is because the results of the multiple linear regression equation show that t count > t table.

Ocean Engineering Jurnal Ilmu Teknik dan Teknologi MaritimVol. 3(4)
Openalex Percentile: Top 89%
Management and Optimization Techniques
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