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Customer satisfaction is a crucial indicator in assessing the quality of a company's products, services and overall experience. This research aims to identify the level of customer satisfaction and optimize the available data for effective use in sentiment analysis. In this study, we analyzed 4,353 customer reviews collected over the past year, with 3,481 reviews used as training data and 871 reviews as testing data. The analysis process was conducted using the Cross-Industry Standard Process for Data Mining (CRISP-DM) approach and leveraged the Logistic Regression algorithm to build a predictive model. Model evaluation using the confusion matrix yielded an accuracy of 94.60%, a precision of 94.26%, and a recall of 94.60%. The analysis was conducted using Jupyter Notebook and the Python programming language. The results indicate that sentiment analysis is effective in identifying and predicting customer satisfaction levels, which in turn can help a company’s products improve its service strategies. The optimization of previously underutilized data now provides deeper insights into customer perceptions and expectations, enabling the company to make more targeted decisions and enhance overall customer satisfaction.

PT Astra International BMW Semarang is a company operating in the automotive sector with 3 supporting pillars, namely Sales, Aftersales and Spare Parts for BMW car units. The availability of spare parts is one of the determining factors for consumer satisfaction with the company because if the spare parts stock is empty it will cause consumer disappointment with the company. By using spare parts sales transaction data for the period January 2019 – June 2023, totaling 52,162, it will be utilized using data mining association techniques with the a priori algorithm and the eclat algorithm. The problem in this research is how to find out consumer purchasing patterns so that there is no shortage or empty stock of spare parts in the warehouse. This research aims to determine the association of spare parts purchasing patterns in sales transactions so that partman get recommendations in making decisions about providing priority types of spare parts. This research methodology uses CRISP-DM (Cross-Industry Standard Process for Data Mining) and is implemented with the R programming language with R studio software. In 3 trials using the Apriori algorithm and 3 trials with the Eclat algorithm, The result with the highest confidence appears in a combination of 3 itemsets with minimum support 0.01 and confidence 0.9, namely if a customer buys B11.42.8.593.186 (Set oil-filter Mx) and B83.12.5.A1A.683 (Washer Cleaner) then they will also buy Z99000000333 ( BMW Engine Oil) with confidence 1.00 or 100%. From the results of this association's analysis, it can be used as advice for the management of PT Astra International BMW Semarang in managing spare parts stock.

The development of information technology has encouraged various educational institutions to switch from manual systems to more efficient and integrated digital systems. One important activity in school management is the process of scheduling teachers' lessons, which often takes a long time and has the potential to cause scheduling conflicts when done manually. Common problems that often arise include conflicts between teachers' teaching hours, incompatibility of classroom availability, and difficulties in adjusting schedules to teachers' preferences. Therefore, this study aims to design and develop a web-based teacher scheduling information system by applying the Greedy algorithm method as a solution to optimize automatic schedule compilation. This system was developed using the PHP programming language and MySQL database with a Waterfall development model approach. The implementation results show that the system is capable of producing teaching schedules quickly, accurately, and with minimal time conflicts. Thus, the application of the Greedy algorithm has proven to be effective in improving efficiency, accuracy, and flexibility in managing teacher schedules in a school environment.

This research uses a quantitative approach with the help of Python to solve infimum and supremum problems involving measurements, calculations and data analysis to draw conclusions. This research process consists of several stages: problem identification, modeling a set of numbers or functions, and implementing algorithms in Python to calculate the infimum and supremum. The calculation results are compared with manual analytical solutions to ensure accuracy and efficient use of Python. Sets as a basic concept in programming allow organizing data and logical operations more efficiently. These findings show that Python is not only effective in calculating supremum and infimum, but also speeds up the solution process compared to manual methods. The results of the program execution show that the analyzed set has an infimum fan supremum which is in accordance with the theory, where set 1 has an infimum of 2, set 2 has a supremum of 5, and set 3 has an infimum of 1 and a supremum of 4.

This study aims to explore the foundation of code in the C++ programming language with a focus on data structures. Data structures are a fundamental component in efficient and effective software development. This literature review explores various types of data structures implemented in C++, including arrays, linked lists, stacks, queues, hash tables, and trees. An analysis is conducted on the basic principles and implementation of these data structures in the context of C++, taking into account the strengths and weaknesses of each structure. In addition, this study also discusses the evolution and comparison of data structure implementations from the perspective of performance and algorithm complexity. The results of this study provide in-depth insights into how data structures can affect the design and efficiency of C++ applications, as well as provide guidance for software developers in choosing the most appropriate data structures for their specific needs. The conclusions of this study highlight the importance of a deep understanding of data structures in software development and their contribution to the success of software projects.

Employee Performance Assessment Decision Support System Using SAW Method at PT Hasta Bersama Prima Jaya Based on Java. The purpose of this study is to develop an existing employee performance assessment decision support system to facilitate data collection and employee performance assessment process. The research methodology used in the data processing system is the literature study method, namely data collection carried out by taking data from various books in the library, journals and other books that can be used as a basis for analyzing problems that can be discussed in the study, as well as the field study method, namely by conducting direct observations such as interviews and observations. The algorithm in solving the problem used is Simple Additive Weighting. The results of this study are the existence of an application device made with the Java programming language and data storage using a MySQL database so that the process of data collection and employee performance assessment at PT Hasta Bersama Prima Jaya becomes more effective, efficient and practical.

PT Astra International BMW Semarang operates in the automotive sector, focusing on sales, aftersales, and spare parts for BMW cars. The availability of spare parts is crucial for customer satisfaction, as stock shortages can lead to disappointment. Using data from 52,162 spare parts sales transactions from January 2019 to June 2023, the study applies data mining techniques with the a priori and eclat algorithms to identify consumer purchasing patterns and prevent stock shortages. The research aims to provide recommendations for prioritizing spare parts stock. Utilizing the CRISP-DM methodology and R programming, the study found that the highest confidence in purchasing patterns occurs with a combination of three itemsets: if a customer buys an oil filter set (B11.42.8.593.186) and washer cleaner (B83.12.5.A1A.683), they will also buy BMW engine oil (Z99000000333) with 100% confidence. These findings can help PT Astra International BMW Semarang manage spare parts stock more effectively.

Education in the digital era requires strong integration of computer programming in the educational curriculum. Programming algorithms are the main key in developing critical thinking and problem solving skills among students. The Merdeka Curriculum reinforces the importance of teaching programming algorithms as part of a curriculum that is flexible and adaptive to meet future demands. This research explores the benefits of programming algorithm strategies in the Merdeka Curriculum, including improving students' analytical, logical and systematic abilities, as well as their preparation for challenges in the digital era.

This study examines the use of dynamic programming in the context of container filling optimization, known as the knapsack problem. This problem requires selecting a number of goods with a certain volume and value to be loaded into a container with a certain capacity. We develop a knapsack-based algorithm using dynamic programming techniques to maximize container space utilization. By considering the volume and value of goods, our algorithm is able to achieve optimal results. Through a case study involving 25 items with predetermined volumes and values, we demonstrate the effectiveness of our algorithm in improving container space utilization. Our experimental results show significant improvements in container space utilization compared to naive filling methods. This research shows that the knapsack approach with dynamic programming can be an effective solution to the container filling problem in the context of logistics and optimization.

Computational thinking is the ability to solve problems and design systems using concepts and techniques generally associated with computers and computer programming. The aim of this research is to conduct a literature review, namely to determine the application of computational thinking in mathematics learning. The technique used is the Systematic Literature Review (SLR) strategy. SLR is a research method that aims to identify, study and interpret data in journals systematically with specified stages. The conclusion obtained from the research results is that the application of computational thinking in mathematics learning can be done using four foundations of computational thinking, namely: (1) Decomposition, namely the problem is divided into small parts, (2) Pattern recognition, namely the process of identifying patterns or sequences of problems, (3) Abstraction, namely consideration of the important parts of a problem, and (4) Algorithm, namely a series of instructions for solving the problem. Examples of its application include the use of interactive mathematics software, mathematical simulations, problem-based learning with technology, adaptive learning and the use of educational games.  

Universities' development hinges significantly on student admissions, necessitating accurate predictions for effective planning. This study applies the Monte Carlo simulation method to forecast new student arrivals at the Faculty of Mathematics and Natural Sciences (FMIPA) at Universitas Negeri Medan (UNIMED). Utilizing data from 2021 to 2023 sourced from the PDDikti website, the research employs PHP programming for implementation. The Monte Carlo algorithm's numerical prowess ensures precise statistical data simulation, comprising data collection, probabilistic distribution computations, cumulative distribution determinations, random number generation, and simulation analyses. Simulation results for 2022, 2023, and 2024 exhibit consistent trends, projecting an average of 860 to 930 new students per program. This methodology surpasses manual estimations, offering robust insights for university resource allocation and strategic management. Despite its effectiveness, study limitations, such as model assumptions, warrant continuous validation with actual data. This research advances predictive modeling in higher education, providing a foundation for future enhancements and comprehensive prediction integrations.

The Binjai District Court is a government agency that has the duty and authority to receive, examine and decide every case registered at the Binjai District Court. The Binjai District Court handles many gambling cases, but data management is still not fast and accurate because it still uses manual methods, so the agency needs to implement an application system. To solve this problem, you can use data mining applications, namely by utilizing existing data to dig up new information. One of the techniques in data mining is clustering. Clustering was chosen because it can group data according to the desired characteristics, in this research it means grouping gambling data in the Binjai City area. The clustering algorithm used is K-Means Clustering integrated into a desktop-based programming application. The conclusion obtained is that the system designed has proven successful in grouping gambling data into 3 clusters (groups). The process using MATLAB R2014a obtained results in group 1 which amounted to 276 data with a data centroid center (6.92; 2.41; 4.33) including the category of low levels of gambling, group 2 which amounted to 337 data with a data centroid center (7.56 ; 2.10; 14.48) is included in the category of moderate level of gambling and group 3 which amounts to 387 data with the centroid data (7.56; 2.10; 28.02) is included in the category of high level of gambling.    

This research aims to develop and apply a Convolutional Neural Network (CNN) algorithm to detect handwritten Roman numerals. Handwriting recognition is a classic challenge in the fields of image processing and machine learning, especially for less common characters such as Roman numerals. In this research, we use data augmentation techniques to increase the diversity and number of datasets used in model training, which is expected to increase model accuracy and generalization. The dataset used consists of 1,120 images for testing and 280 images for validation, each of which is divided into 14 classes of Roman numerals I, II, III, IV, V, VI, VII, VIII, IX, X, L, C, D , and M. Image data was created directly using simple software, namely Paint version 6.3. This research uses the Python programming language and Google Colab as a computing platform. Model training was carried out for 300 epochs and showed significant accuracy in the 150th to 300th iteration. The results at the 300th epoch show an accuracy of 0.9607 and a loss of 0.1162. The implementation of this algorithm shows significant potential in practical applications, such as in the fields of education and historical documentation. The conclusion of this research is that data augmentation is an effective technique to improve the performance of CNN models in detecting handwritten Roman numerals.

Computational Thinking skills are students' ability to use mathematical concepts to solve problems systematically using algorithms and programming. This research aims to measure the development of Computational Thinking skills of students at SMA N 3 Medan on algebraic function limits material. The research method used is survey research with data collection using tests and observations. The subjects of this research were class XI students from SMA N 3 Medan who were studying algebraic function limits. The research results show that there is significant development in students' Computational Thinking skills after studying the material. The implication of this research is the need for a learning approach that focuses more on developing Computational Thinking skills in mathematics learning in high school.

MSIB (Certified Independent Study and Internship) is one of the activity programs at the Merdeka Campus which aims to help students improve their skills and develop themselves. MSIB appointed Orbit Future Academy as one of the partners in the Independent Study program. Founded in 2016 with the aim of improving the quality of life through innovation, education and skills training. In accordance with its mission, namely "We curate and localize international programs and courses for upskilling, re-skilling youth, and the workforce towards jobs of the future". Partners provide opportunities for students to take Artificial Intelligence programs and study online. Learning consists of eight material courses including Python Programming, AI Technology Logic and Concepts, AI Project Cycle, AI Research Methods, ChatGPT, Professional and Company Ethics, Financial Literacy and ending with a Final Project. The final project scope carried out is the Occupancy Detection in Parking Lot project. This project uses the Computer Vision domain with the selection of the YOLO model in detecting objects and pixel segmentation. The project begins with selecting a dataset using roboflow which then goes through data pre-processing for cloning, annotation and augmentation. Then the model is trained using machine learning and deep learning algorithms to understand patterns and characteristics related to parking spaces. Once trained, the AI model will be validated using test data. This aims to ensure that the model truly recognizes the presence of the vehicle. Next, form the application design in creating an informative interface using wireframes. Then enter the deployment stage so that the system can be accessed widely and easily via the web. Lastly, field testing is to find out the performance of the application that has been designed.      

Learning using media based on the Canva application has the advantage that the learning material is made more interesting. As support for direct learning, the use of the Canva application which has a variety of saved file formats, according to Rahmatullahet al (2020), the use of Canva-based audio visual learning media can improve students' informatics learning outcomes. There are also research results from Vivi et al (2021) which state that using the Canva application can help students fulfill online learning assignments at school. According to Yanti in Assidiqi (2020), learning using Canva-based learning media can help students understand learning even though they are at home because there are obstacles in the form of not having textbooks. This is known from the lack of student data recapitulation of the low learning outcomes of students who reach the KKM, namely 14 students out of a total of 38 students in class X.9

household industry or usually known quantity when UMKM  is an arising chance. Rephrase. This happens because there are very few job break. However, some UMKMs still have adversity determining the optimal  production abundance broad- based on accessible expedient, so  these troop cannot amplify. One of them is Bu Ida fruit juice, which consistently produces fruit juice according to crowd-pleasing orders of average consumer credit. admittedly utilize capital and basic materials enough, Ms. Ida's business is growing day by day. From this research, problems were distinguish and answer live needed, comprehend the employment of linear programming to determine the  sales abundance that absence to be optimized to attain maximum earnings from juice sales Ida's fruit. There are 6 (six) juices and 6 (six) ingredients. In this study, a simple method linear programming algorithm is applied to obtain an optimization model to maximize the  juice production quantity and obtain optimal profits. The POM-QM Windows application provides fast, accurate and precise  calculation results.

Many rivers in Indonesia had very poor water clarity due to a mixture of dirt and mud in the  water.  Polluted  rivers were  often  found  in  areas  near  settlements,  where  household  waste that flowing into rivers made the water look dirty and turbid. Pollutants dissolved in water will bind to small particles and settle at the bottom of the river, due to sedimentation. This research designed a device to detect sediment volume in the rivers. This device used an ultrasonic sensor type DYP-L04 and a rotary encoder for calculating volume, with Arduino Mega 2560 R3 as a processor. There is a PG45 motor that was used to set the motor speed to be constant. This ultrasonic sensor works based on the Arduino programming algorithm that has been designed,  so that the device can measure sediment volume optimally. The results of this research showed that the device could determine the volume of sediment with the average error score less than 10 %.

Thel purposel of thils relselarch ils to ilmprovel thel elffilcilelncy of solvilng trilgonomeltrilc problelms by applyilng programmilng algorilthms iln Maplel softwarel. Iln thel contelxt of trilgonomeltry, you willl elncountelr complelx problelms such as workilng wilth trilgonomeltrilc functilons, solvilng trilgonomeltrilc elquatilons, and othelr trilgonomeltrilc analysils. Pelrformilng trilgonomeltrilc calculatilons iln Maplel softwarel usels an algorilthmilc programmilng approach to crelatel fastelr and morel accuratel solutilons. Thils melthod ilnvolvels delsilgnilng algorilthms that arel useld to handlel varilous trilgonomeltrilc casels. Elxpelrilmelnts welrel conducteld to melasurel thel elxelcutilon speleld and accuracy of thel relsultilng solutilons. Thel relsults show that thel applilcatilon of algorilthmilc programmilng to Maplel softwarel silgnilfilcantly spelelds up thel solutilon of trilgonomeltrilc problelms whillel mailntailnilng a hilgh lelvell of accuracy.    

Over time, the progress of science, technology and information is growing very rapidly. One of the things related to this problem is that the children of the nation must now master and study the developing science and technology. Utilizing science technology is now very important. The computer is one example of a technological tool that can be used. Regarding computers, we must first study in detail about programming algorithms that have applications and functions for us in education and everyday life. The purpose  of writing this article is to examine the application and function of programming algorithms. Then the writing of this article use the literature study method and library research, namely by studying systematically and structured about programming algorithms. Data collection is done by online books or offline books, reputable scientific journals and sources from Google Scholar, Digital Library, website research and so on. The result of writing this article is that the application or presentation of programming algorithms can be seen in examples of application in mathematics. Writing an algorithm is not bound by a certain rule, but it must be clear what it means for each step of the algorithm. Many functions are very important in programming algorithms. The main function of programming algorithms is to solve a problem. This algorithm is an important thing in the activity of making a program.