Tujuan penelitian ini adalah untuk menganalisis pengaruh faktor prosedur bongkar muat terhadap keselamatan  pekerja  bongkar  muat  di  Pelabuhan  Tanjung  Intan Cilacap; untuk menganalisis pengaruh faktor fasiltas keselamatan terhadap keselamatan  pekerja  bongkar  muat  di  Pelabuhan  Tanjung  Intan Cilacap; dan  menganalisis pengaruh faktor pelatihan kerja terhadap keselamatan  pekerja  bongkar  muat  di  Pelabuhan  Tanjung  Intan Cilacap. Metode pengumpulan data pada penelitian ini adalah dengan observasi dan kuesioner dan dianalisis dengan analisis regresi linier berganda. Berdasarkan hasil penelitian dan analisis berganda dihasilkan persamaan: Y = 0.614+0,483X1+ 0,323X2+ 0,148X3 + ?. Menunjukan bahwa, H1 diterima karena variabel Prosedur Bongkar Muat (X1) mempengaruhi Keselamatan Pekerja dengan t hitung  > t tabel (4.613 > 1.99547), dan signifikan 0,000 < 0,05; sedangkan H2 juga diterima karena variabel  Fasilitas  Keselamatan  (X2) mempengaruhi Keselamatan Pekerja dengan t hitung  > t tabel (3.914 > 1.99547), dan signifikan 0,000 < 0,05; dan variabel Pelatihan Kerja (X3) juga mempengaruhi Keselamatan Pekerja dengan t hitung > t tabel  (2.986 > 1.99547), dan signifikan 0,007 < 0,05. Dengan demikian hasil perhitungan statistik menunjukan bahwa secara persial variabel Pelatihan Kerja berpengaruh secara signifikan terhadap Keselamatan Pekerja. Dengan demikian Ha diterima yang berarti bahwa Pelatihan Kerja di Pelabuhan Tanjung Intan Cilacap.

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.

Ship waiting time is one issue that is always getting serious attention in every country. Marine transportation became the main made of transportation in trade. Nearly 90% of foreign trade is done by sea. Freight carried by sea to be very efficient due to large carring capacity and this the role of the port as a place where ships can carry out loading and unloading of goods becomes an important means of supporting adequate facilities and infrastructure. If the performance of the port is not optimal, it will have a direct impact on the service so that it will cause new problems, namely the ship’s waiting time gets higher, so that it  willlead to high costs, which have a direct impact on the price of goods on the market. This research has objective to know analysis the influence of factor ship scheduling, pilotage, and loading and unloading productivity to the waiting time. This research was conducted at the Port of Sei Kolak Kijang as a sample. The data collection done was through a method of observation, the literature study, interview, documentatuion and the questionnaires. Techique the analysis used is linear regression multiple with program assitance SPSS V.20. Based on the results of research and analysis produced equation: Y = 15.326 - 0,220 X1 - 0,178 X2 – 0,308 X3 + µ. Where the decision variable of waiting time (Y), ship scheduling (X1), pilotage (X2), loading and unloading productivity (X3) tested using t test show that the three independent variables significantly influence passenger decision as dependent variable. The Adjusted R Square number of 0,665 indicates that 66,5 percent of waiting time variables can be explained through the three independent variables in the regression equation. While the remaining 33,5 percent is explained by other variables outside the three variables used in this study.