Pada penelitian ini menganalisis faktor yang mempengaruhi ketepatan waktu keberangkatan pesawat di bandara internasional Raja Haji Fisabilillah Tanjungpinang. Metode penelitian ni menggunakan observasi dan kuesioner, sedangakan untuk metode analisis data adalah menggunakan analisis regresi linier berganda. Hasil penelitian ini menunjukkan bahwa variabel Maintenance, Scheduling dan Kapasitas Air Side berpengaruh psitif dan signig=fikan terhadap On Time Performance-nya dengan pembuktian uji t masing-masing variabel mendapatkan t hitung sebesar (0,385), (2,822), dan (5,176).

This study aims to determine the Analysis of Operational Factors, Tariffs, Facilities and Safety Against Guidance Services at PT. Port of Indonesia (Persero) Regional 4 pelabuhan Bitung This research was conducted on employees of the Shipping Agency working area of ??Tanjung Redeb as a population. Data was collected through the methods of Observation, Literature Study, Interview, Documentation and Questionnaire. The analytical technique used is based on the results of research and multiple analysis with the help of the SPSS V.26. Here’s the result from research of regression : Y = -0,219 + 0,308X1 + 0,200X2 + 0,192X3 + 0,349X4 + µ. The multiple linear regression equation can be seen that the most dominant variable influencing the guidance is the safety variable with a regression coefficient of 0.349. With the coefficient of determination (Adjusted R square) the results obtained are 0.837 or 83.7%, which means that the guidance at PT. Port of Indonesia (Persero) Regional 4 Pelabuhan Bitung is influenced by operational variables, tariffs, facilities and safety which is 83.7% and other factors that affect the guidance of PT. Port of Indonesia (Persero) Regional 4 Pelabuhan Bitung is 16.7%. Thus the results of the study indicate that Operations, Tariffs, Facilities and Safety have a positive and significant effect on the PT. Port of Indonesia (Persero) Regional 4 Pelabuhan Bitung.

The community service program to improve the tourism economy at Tirang Beach, Semarang aims to increase community income through developing tourism potential on the beach. This program will be implemented through tourism product development activities, improving the quality of tourism services, and skills training for the surrounding community. The method to be used in this program is data collection through a survey to find out the tourism potential in Tirang Beach, and the needs and expectations of tourists. Furthermore, tourism products will be developed in accordance with existing potential, such as developing culinary specialties from the beach, developing handicrafts, and developing natural tourism activities such as snorkeling and diving. In addition, there will be improvements to the quality of tourism services, such as developing tourism infrastructure, making information boards, and training the local community in good and friendly tourism services to tourists. In addition, skills training will be conducted for the surrounding community to improve the quality of tourism products and services provided. The expected results of this program are increasing people's income through developing tourism potential in Tirang Beach, as well as improving the quality of tourism products and services provided. This program is also expected to attract tourists to visit Tirang Beach, so as to increase tourism potential in the area. With this program, it is hoped that the surrounding community will become more independent and be able to improve the economy through existing tourism potential. Thus, a healthier and more sustainable environment can be created through sustainable economic development.

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.

In this study, loading and unloading productivity is influenced by several factors including : handling of the Covid-19 pandemic, operator performance, loading and unloading equipment and stacking field effectiveness. These factors have an important role in increasing loading and unloading productivity. The population in this study were employees of PT. Salam Pacific Indonesia Lines Medan Branch with a total sample of 109 respondents. The data analysis used in this research is descriptive analysis and quantitative analysis, the data is analyzed using multiple linear regression analysis using the Application (SPSS) Version 25. The results of the t-test hypothesis testing indicate that the Covid-19 Pandemic Handling, Operator Performance, Loading and Unloading Equipment and Stacking Field Effectiveness partially positive and significant effect on loading and unloading productivity. Based on the results of the study, it is known that the research model of the multiple linear regression equation resulted in the following equation : Y = 0,329 + 0,177X1 + 0,178X2 + 0,231X3 + 0,380X4 + µ. From the equation results show that the Covid-19 Pandemic Handling variable (X1) has (t count 2,004 > t table 1,983), Operator Performance variable (X2) has (t count 2,085 > t table 1,983), the Unloading Equipment variable (X3) has (t count 2,467 > t table 1,983) and the Stacking Field Effectiveness variable (X4) has (t count 4,243 > t table 1,983). As for the value of Adjusted R2 = 0.604. This means that 60.4% of the variation in the dependent variable (Y), namely the Unloading Productivity is explained by the independent variables, namely the Covid-19 Pandemic Handling (X1), Operator Performance (X2), Loading and Unloading Equipment (X3) and Stacking Field Effectiveness (X4). The remaining 100% - 60.4% = 39.6%, influenced by other variables outside the study.