The Influence of Programming Algorithm Understanding

Study Case The Influence of Programming Algorithm Understanding on the Effectiveness of Technical and Non-Technical Problem Solving Michael Kurniawan (2018123456) University of Cincinnati, 2600 Clifton Ave, Cincinnati, OH 45221, United States kurniaml@mail.uc.edu Abstract An algorithm is a series of logical steps used to solve problems systematically and efficiently. In the era of modern computing in the United States, programming has become an important skill in various fields, so the ability to solve technical and nontechnical problems is greatly influenced by an understanding of programming algorithms. This article explores the basic concepts of algorithms, effective teaching approaches, and case studies that show how algorithmic competence can strengthen an individual's ability to solve problems in both software development and real-world situations. The research uses the library research method through analysis of literature and related written sources. The findings show that understanding algorithms provides various benefits in improving logical thinking skills, problem-solving efficiency, and computational process optimization. Keywords: Algorithm, Programming, Problem Solving, Benefits INTRODUCTION The term algorithm has a long linguistic history. Linguists initially had difficulty tracing its origins, until mathematicians finally discovered that the word came from the name of a famous Arab scientist, Abu Ja'far Muhammad Ibn Musa Al-Khwarizmi. In Western tradition, the name Al-Khwarizmi evolved into Algorism, which then changed to Algorithm after the suffix -sm was often misinterpreted as a term related to arithmetic. From this linguistic evolution, the term “algorithm” came to be used in Indonesian as well as in global scientific studies. MICHAEL KURNIAWAN 1 Study Case Conceptually, an algorithm is a structured series of steps designed to solve a problem logically and systematically. Algorithms play an important role in producing fast, accurate, and consistent solutions. Computers can understand and execute instructions effectively because they follow well-defined sequential algorithms. According to classical literature [1], programming capabilities and computational effectiveness are closely related to how an algorithm is designed and executed. Other literature [2] mentions that the basic structure of an algorithm includes input, process, and output. In computer science in the United States, algorithms are seen as central to almost all subfields of computing. However, algorithms are not limited to the realm of technology. Many everyday activities are practically forms of algorithms, such as cooking instructions that follow a specific logical sequence. If the steps are not performed correctly, the end result will not meet expectations. In this era of rapidly developing modern technology, programming skills have become essential in various sectors, including business, education, and the technology industry. An individual's success in solving technical and analytical challenges often depends on the extent to which they understand algorithmic principles. A strong understanding of algorithms enables individuals to optimize processes, improve efficiency, and produce innovative solutions. This study aims to identify the benefits individuals gain in improving their problem-solving abilities through an understanding of programming algorithms. Understanding algorithms focuses not only on the ability to write code but also includes logical thinking, optimization strategies, and the ability to design effective solutions in computational contexts and real-world situations. This article covers a discussion of basic algorithm concepts, pedagogical approaches that have proven effective in educational environments such as the University of Cincinnati, and case studies that demonstrate the significant influence of algorithm understanding on problem-solving abilities. RESEARCH METHODOLOGY This article was compiled using library research methods by collecting and analyzing literature sources such as books, scientific articles, academic documents, and other written references relevant to the topic of algorithms and problem solving. The MICHAEL KURNIAWAN 2 Study Case analysis was conducted to describe the concept of programming algorithms, identify the benefits of understanding them, and evaluate their relevance to individual problemsolving abilities. Primary and secondary data sources were used to strengthen the study of the contribution of understanding algorithms in improving problem-solving capacity, both in the context of software development and real-world applications. RESULTS AND DISCUSSION Table 1. Summary of Articles Reviewed From the eight pieces of literature analyzed over the last five years (2019–2023), it was found that in 2019 there were two publications, in 2020 there was one publication, in 2021 there was one publication, in 2022 there were two publications, and in 2023 there were two publications. Application of Scratch in Algorithm Learning In the first article, the use of the Scratch application showed a significant increase in student understanding. Of the 15 students studied, none had a basic understanding of algorithms before the activity, but after training, 80% of students showed an increase in understanding. These results confirm that interactive media such as Scratch are effective in teaching algorithmic concepts to elementary school children [1]. MICHAEL KURNIAWAN 3 Study Case In the second article, the use of the same method resulted in a 100% satisfaction rate, with 78.9% of participants feeling satisfied and 21.1% feeling very satisfied with the learning process. This data shows that Scratch can be an engaging and easily accepted teaching medium in the context of technology education in the United States [2]. The Effectiveness of Bubble Sort in Basic Algorithm Learning The third study discusses the Bubble Sort algorithm, which is known to be simple but inefficient for large datasets. The study confirms that Bubble Sort is more appropriate as a teaching tool to introduce basic sorting concepts than as a practical solution in the real world [3]. This is in line with US computing literature that emphasizes the use of basic algorithms for the formation of computational thinking. Implementation of Neural Networks for Energy Classification The fourth study applies the Backpropagation Neural Network algorithm to classify electrical energy usage data. The results show an accuracy of 96.67% with the following training parameters: • Learning Rate = 0.5 • Number of Hidden Neurons = 25 • Iterations = 6870 • Mean Squared Error = 0.03333 • Training Duration = 4 minutes 17 seconds Of the 30 test data, 29 were correctly classified into four categories: highly efficient (9 data), efficient (6), moderately efficient (5), and wasteful (9). These findings indicate that neural network models can provide useful information in energy consumption monitoring [4]. Brute Force-Based Programming Terminology Dictionary Application The fifth article develops a PHP terminology dictionary application using the brute force algorithm as a word search method. The use of this algorithm increases search speed compared to conventional dictionaries, making it easier for programmers to access programming terminology definitions quickly and efficiently [5]. Programming Training in Student Creativity Programs In the sixth and seventh studies, algorithm training in student development programs at the University of Cincinnati had a positive effect on participants' understanding. Researchers emphasized the need for ongoing programs to ensure participants can learn programming topics gradually, from basic concepts to advanced MICHAEL KURNIAWAN 4 Study Case material [6][7]. This type of training has been proven to improve learning outcomes compared to conventional learning. Use of Pascal N-IDE as a Learning Medium The eighth study shows that the Pascal N-IDE application can be used as an alternative learning medium for computer science subjects, especially for material on algorithms and programming. This application allows students to understand basic syntax practically through Android devices—although its use is not yet widespread in the US educational environment [8]. The Role of Algorithm Understanding in Problem-Solving Skills Overall, these studies show that understanding algorithms: 1. Strengthens logical and systematic thinking skills 2. Improving the ability to design efficient solutions 3. Assisting in the selection of appropriate data structures and methods 4. Optimizing code performance 5. Building mental resilience and confidence in solving complex problems 6. Relevant in both technology and everyday situations Understanding algorithms is an important foundation in modern computing and supports cross-disciplinary problem-solving skills. CONCLUSION Algorithms are a series of logical steps to solve problems in a structured, fast, and accurate manner. Understanding algorithms is not only related to the ability to write code, but also includes process optimization, the application of computational logic, and the ability to design efficient solutions. Based on the eight literature reviews, programming algorithms have proven to provide significant benefits both in software development and in solving real-world problems. Thus, mastering algorithms is a crucial skill that supports learning effectiveness, programming quality, and improved problem-solving abilities in general. MICHAEL KURNIAWAN 5 Study Case REFERENCE MICHAEL KURNIAWAN 6