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This research is motivated by the importance of understanding factors influencing employee performance, particularly at PT Air Minum Bandarmasih (PERSERODA) Banjarmasin. The study aims to analyze the effects of work behavior and workload on employee performance, both partially and simultaneously. This quantitative research employs a survey design with a population of 380 employees and a sample of 79 respondents selected using random sampling based on Slovin's formula. The data were analyzed using validity and reliability tests, classical assumption tests, linearity tests, multiple linear regression analysis, and hypothesis testing. The results reveal that work behavior and workload significantly affect employee performance, both individually and simultaneously. Positive work behavior enhances employee motivation, while a proportional workload supports employees in developing their potential. The implications of this study highlight the importance of organizational management in fostering productive work behavior and effectively managing workload to sustainably improve employee performance.

As cloud computing advances, organizations' IT infrastructure and application deployment processes are moving to the cloud because cloud computing provides everything as a service over the Internet. The performance of a cloud-based application is based on proper datacenter selection and workload distribution within the selected datacenter. Service broker policies are used for suitable datacenter selection, and load balancing algorithms(LBA) are applied to distribute workloads. This paper is to evaluate the effect of a proposed service broker policy (PSBR) on the performance of cloud-based applications with LBA. To achieve the objective, the behavior of the TikTok application was modeled using the worldwide users’ statistics on the cloud simulation framework, namely CloudAnalyst. As a result, the average response time and data center processing time are measured. Next, the PSBR provides better results than the existing service proximity-based policy. This paper supports cloud service providers' benefits, from coordination between data center configuration, data center selection, and workload distribution to cloud users' identification of the appropriate procedures for their organization or application. PSBR with Active Monitoring had the best average response time of 75.1 ms, while SPR consistently exhibited higher average times across all algorithms, with the highest being 84.5 ms for Round Robin. Under the PSBR policy, Throttled had the lowest average processing time (4.67), while Round Robin had the highest (5.72). Similarly, under the SPR policy, Throttled maintained its efficiency with the lowest average (4.8), while Round Robin showed the highest (5.79).