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.

Damage that occurs to manufactured goods can occur due to several things, such as in the manufacturing process, in the packaging process or during the delivery process. To find out where when the goods were damaged and the factors causing the damage to the goods as well as the efforts made to reduce the damage to the goods, an investigation was carried out at the time of unloading the goods, to find out where the damage to the goods occurred so as not to harm the recipient of the goods if they received the goods in damage condition.Based on multiple linear regression analysis, the results obtained are Y = 3.133 + 0.044 X1, + 0.402 X2 + 0.299 X3 + . Partial test results of machine (X1), material (X2), man power (X3) have a positive and significant effect on damage goods. It is proven by the results of the comparison of the value of t count with t table and with a significant level comparison of 5% (0.05) where the machine variable t count (0.413) < t table (1.98609), material variable t count (3.142) > t table (1.98609), variable man power t count (2.990) > t table (1.98609). The R2 test of machines, materials and man power gave a significant effect on damage goods by 43.6%, while the remaining 56.4% was explained by other causes outside the model variables that were not examined.

There are so many companies nowadays, some are large companies and some are small companies. Every company certainly hopes to continue to exist in an era of intense competition. Without realizing it, technology is also experiencing rapid development too. The problem faced by companies is how to improve employee performance with current technology. The company realizes that employee performance is very important so that the company can compete with other companies. One way to improve company performance is by digitalizing the company. Steps that companies can take in implementing company digitalization are: creating a business website, carrying out digital marketing, implementing cloud computing, utilizing big data, implementing AI technology, and participating in digital training for their employees.

Ship KM. Egon is one of PT Indoneisan National Shiiping fleets that seves the Indonesian people for smooth sea transportation. This ship is a ship made in Germany in 1991 with a length of 94,30 meters and a windth of 16 meters which is one of the means of transportation that crosses various islands. In one voyage this ship is capable of transportation 500 pax of vehicles, loads of goods passengers with a capacity of 500 passengers with the destination of KM ship. Egon it self is Sheet Harbor, Waingapu Port, Surabaya Port, Batulicin Port, and Pare-pare Port. This study aims to determine the effect of Quality/Service Quality, Corporate Image, Safety Assurance on Passenger’s Decisions to Use the KM Ship Egon especially at PT. Pelni Surabaya Branch, the population in this study were passengers on the KM Egon ship owned by PT. Pelni Surabaya Branch and the sampels used in this study were 92 respondents. Data collection methods used are observation (Observation), interviews, and distribution of questionnaires. The sampling technique used is non-probability sampling purposive sampling type, then the data is analyzed using multiple linear regression with the help of (software) Statistical Package For Social Science (SPSS) Version 26. The regression formulation in this study is as follows:     Y = 1.785 + 0,310X1 + 0,202X2 + 0,220X3 + µ. From this equation, it is known that the most dominant variable influencing passenger decisions is the corporate image variable with a regression coefficient of 0.202. The R2 (R Square) test obtained results of 0.517 or 51,7% which means that Passenger Decisions are influenced by the variables of Quality/Service Quality, Corporate Image, Safety Assurance which are 51,7% and other factors that affect Shipping Safety at PT. Pelni Surabaya Branch, which is 48,3%.

The purpose of this study was to determine whether or not the influence of customer experience, consumer confidence, prices and flight ticket purchasing decisions on the Traveloka application for UNIMAR AMNI Semarang Students. The sample in this study amounted to 52 respondents who used airline ticket services in the Traveloka application. By using probability sampling technique, namely by random sampling. Analysis of the data used in this study is descriptive analysis and quantitative analysis, the data were analyzed using multiple linear regression analysis with the help of (software) Statistical Package For Social Science (SPSS) version 26. The results of the study by partially testing the t-test hypothesis showed that Customer experience, consumer trust, and price have a positive and significant effect on purchasing decisions. Based on the research results, it can be seen that the research model of the multiple linear regression equation is Y= 0.095 + 0.484.X1 + 0.195.X2 +0.295.X3 + . From the regression equation, it can be seen that the most dominant variable affecting the increase in the number of passengers is the price variable with a regression coefficient of 0.095. And the R2 test (Adjusted R Square) obtained results of 0.780 or 78.0% which means that purchasing decisions are influenced by customer experience, consumer confidence and price variables which are 63.8% and other factors that influence passenger decisions are 36.2 % or 0.362.