This study aims to analyze the effects of e-recruitment, company reputation, and expected compensation on the intention to apply for a job, both partially and simultaneously. This study employs a quantitative method with an associative-causal approach. The sampling technique used in this study is non- probability sampling with accidental sampling. Data were collected through the distribution of questionnaires to 348 Generation Z respondents in Bogor. The results of the study indicate that e-recruitment, company reputation, and expected compensation have a positive and significant partial effect on the intentionto apply for a job. Simultaneously, all three variables also have a positive and significant effect on the intention to apply for a job, indicating that the combination of these three factors can increase Generation Z’s interest in applying for jobs. This study concludes that companies need to optimize their e-recruitment systems, build a positive corporate reputation, and offer compensation that meets expectations in order to increase the company’s appeal to prospective Generation Z applicants.
This study analyzes the effect of Capital Adequacy Ratio (CAR), Net Interest Margin (NIM), and Operational Efficiency Ratio (BOPO) on Return on Assets (ROA) in 36 banks listed on the Indonesia Stock Exchange (IDX) in 2024. The analysis was conducted using multiple linear regression, including a simple robustness test through winsorizing to reduce the influence of outliers. The results show that BOPO has a significant negative effect on ROA in both the original model (β = –0.086; p < 0.001) and winsorized data (β = –0.090; p = 0.000), while NIM has a significant positive effect in the original model (β = 0.096; p = 0.031) but is not significant after winsorizing (β = 0.075; p = 0.070), and CAR has no significant effect in both models. Simultaneously, all three independent variables influenced ROA (F = 87.036; p < 0.001). The regression model explained 89.1% of the variation in ROA in the initial model and 91.0% after winsorizing, confirming the stability of the results. These findings emphasize that bank profitability is significantly influenced by operational efficiency and net interest margin management, while capital adequacy does not contribute significantly. Robustness tests confirmed the validity of the model, showing that conclusions remained consistent even when the data was smoothed to remove outliers.
This study aims to determine the influence of word of mouth and brand image on purchasing decisions for MS Glow products. This research is a quantitative and causal associative study. Data collection in this study was obtained from a survey using a questionnaire technique to MS Glow consumers. The data analysis technique used is Multiple Linear Regression. The results of the study indicate that partially word of mouth and brand image have a positive influence on purchasing decisions. Simultaneously, word of mouth and brand image together influence purchasing decisions.
This study aims to analyze the influence of TikTok social media promotion, influencers, and price perception on purchasing decisions for Tomoro Coffee in Bogor City, partially and simultaneously. This study uses a quantitative approach with a causal associative research type with a total of 141 respondents who purchase and consume Tomoro Coffee in Bogor City. Data analysis techniques include instrument testing, classical assumption testing, multiple linear regression analysis, coefficient of determination (R2), and hypothesis testing. The results of the study indicate that TikTok social media influencers and price perception partially and simultaneously have a positive and significant impact on purchasing decisions. The price perception variable was found to be the most dominant factor that strongly influences consumer purchasing decisions. These findings provide an understanding that digital-based marketing strategies, particularly through the TikTok platform and collaboration with influencers, as well as appropriate pricing, play a significant role in driving consumer purchasing decisions.
Community management in residential areas often relies on manual paper-based administration, leading to inefficiency, unclear financial records, data loss, and limited transparency, which undermine good governance and residents’ trust. This study aims to develop a web-based neighborhood (RT/RW) management information system to improve administrative effectiveness, financial transparency, and service quality. The system was built using CodeIgniter, PHP, MySQL, Bootstrap, and jQuery, applying the Agile development method to ensure flexibility and iterative improvement through continuous feedback between the developers and the community. The development process consisted of planning, design, coding, testing, and release stages, with flowcharts and wireframes supporting interface design and black box testing used for functional validation. The system was evaluated using a user-centered usability assessment (System Usability Scale – SUS), obtaining an average score of 82.5, which falls under the Excellent category. In addition, the financial reporting process time was reduced from three days to one hour, and data entry errors decreased by 90%, proving that the system significantly improves operational efficiency and transparency compared to manual methods. In conclusion, the combination of Agile methodology and lightweight frameworks such as CodeIgniter successfully delivers a responsive, transparent, and user-oriented information system that enhances trust and collaboration within the community. Future development will focus on integrating QRIS, e-wallets, and bank transfers to further streamline financial transactions and support sustainable digital transformation in community management.
