Efficient resource allocation is a major challenge in various sectors, especially when faced with limitations in quantity, time, and cost. This study aims to examine the application of linear programming as an optimization method in solving assignment problems, where a number of resources must be optimally allocated to a number of specific tasks. Through a literature study approach, this study examines various relevant previous study results, especially in the Indonesian context. The results of the study indicate that linear programming is able to improve operational efficiency, reduce costs, and produce a more balanced task distribution. However, this model has limitations in dealing with non-linear conditions and data uncertainty, so integration with other methods such as fuzzy logic or genetic algorithms is needed. This study is expected to broaden the understanding of the benefits of linear programming and encourage its wider application in quantitative-based decision making.

This study aims to examine the application of the Hungarian method in solving assignment problems based on linear programming, particularly in optimizing work time allocation. Through a literature review of 15 research articles, it was found that the Hungarian method consistently proves effective in improving work efficiency, reducing time waste, and optimally matching resources with appropriate tasks. These studies reported reductions in work time ranging from 3 to 663 minutes after applying the method, depending on the complexity and context of each case. Additionally, integrating the Hungarian method with software tools such as POM-QM and LINGO further accelerates the optimization process. The findings indicate that the Hungarian method is a practical, flexible, and relevant mathematical approach across various sectors, supporting operational decision-making in an objective and efficient manner.

This study uses a qualitative method with a literature review approach to examine the effectiveness of the two-phase method in solving linear programming problems. The two-phase method is one of the techniques in linear programming used when the objective function does not have a feasible initial solution directly. Through the exploration and analysis of various scientific literature sources from 2019 onwards, this study finds that the two-phase method can systematically provide optimal solutions, especially in complex problems with multiple constraints. Previous research has shown that this method is effective in accelerating the identification of basic feasible solutions and minimizing unnecessary iterations compared to the standard simplex method. Additionally, the two-phase method offers better numerical stability and high reliability in both industrial and educational applications. However, its effectiveness largely depends on the understanding of the algorithm and the ability to design an appropriate mathematical model. The results of this study are expected to contribute theoretically to the development of efficient solution techniques for linear optimization problems.

In everyday life, decision making is an unavoidable activity, both in personal, organizational and societal contexts. Each individual or group is often faced with various alternative choices, where each choice has certain consequences. In your career, decision making is very important. In making a decision there are definitely factors that influence it. In this research, the author used the Systematic Literature Review (SLR) method This research uses a Systematic Literature Review (SLR) approach with data sources originating from previous journal literature.  Data collection was carried out by documenting all articles and journals that were relevant to this research. From 20 similar articles, researchers took 10 articles to analyze and summarize. The results of this research show that the factors that influence career decision making are internal factors which include self-efficacy, motivation, interests, skills and personal perceptions, which are the psychological and emotional basis for individuals in determining their career direction, as well as external factors such as family support, the environment. Social, economic opportunities, capital, and market conditions play a significant role in providing resources and external incentives that support career decision making.