SEMICOLON: Computer Science Journal is an international peer-reviewed journal dedicated to advancing the field of Informatics. Published by the Cendekia Inovasi, Indonesia, SEMICOLON provides a platform for researchers, scientists, and academics worldwide to publish their research findings and share their knowledge with the broader scientific community. Focus Areas: Distributed Computing: Internet of Things (IoT) Technology, Cloud Computing, Smart System, Information Technology (IT) Automation, Virtualization, Network Security, Steganography, Cryptography, Blockchain, Ubiquitous Learning, Parallel and Distributed Systems Artificial Intelligence: Prompt Engineering, Digital Image Processing, Machine Learning, Decision Support System, Multimedia Data Processing, Knowledge Representation & Reasoning, Deep Learning, Data Mining, Natural Language Processing, Data Science, Artificial Intelligence Driven for IoT, Artificial Intelligence Driven for GameTech SEMICOLON welcomes submissions that contribute to these areas of research, fostering collaboration and knowledge exchange among informatics professionals worldwide. Thus, we invite Academics, Researchers, and Practitioners to participate in submitting their work to this journal.
Implementation of C45 Algorithm in Measuring the Level of Understanding of FIKOM UNIKA Santo Thomas Students on Courses
The objective of this research is to classify and quantify the level of understanding exhibited by students at the Faculty of Computer Science at Santo Thomas Catholic University. Santo Thomas Catholic University is one of the private universities in North Sumatra with a vision of becoming an innovative, humanist, cultured, internationally-oriented university that is based on the principles of Pancasila and Christian values. In order to successfully complete the course, students are required to demonstrate a comprehensive understanding of all the material presented by the instructor during lectures. There are a number of factors that can influence the level of comprehension exhibited by students in response to the material presented by the lecturer. The data were gathered from the responses of fifth-term students at the Faculty of Computer Science, Santo Thomas Catholic University, as recorded in a questionnaire. Five attributes were employed for analysis: communication, learning atmosphere, learning media, appearance, and teaching methods. The method employed in the investigation is the C4.5 algorithm, assisted by RapidMiner software for the construction of a decision tree. The results of the study yielded 14 rules for classifying levels of comprehension. Of these, nine rules exhibited the highest levels of understanding, while the other five demonstrated lower levels of comprehension. The C4.5 algorithm can be utilized to assess the level of comprehension among students at the Faculty of Computer Science at Santo Thomas Catholic University with an 87.10% accuracy rate. It is our hope that this analysis will encourage students to gain a deeper understanding of the course material.
Copyright (c) 2024 Johanes Kevin Malau, Dinda Roulita Simangunsong Simangunsong, Sardo Pardingotan Sipayung (Author) https://ejurnal.cendekiainovasi.org/index.php/semicolon/licenses
Performance Analysis of Parking System in FIKOM and KNN Environment: Efficiency and Effectiveness Approach
An efficient and effective parking system plays an important role in supporting the smooth running of activities in the academic environment, including at the Faculty of Computer Sciences (Fikom). This research aims to analyze the efficiency and effectiveness of the parking system in the Fikom environment by considering various factors, such as parking capacity, vehicle waiting time, inflow and outflow, and level of user satisfaction. The research methods applied include quantitative and qualitative descriptive approaches, through data collection through user surveys, direct observation, and data analysis related to the number of vehicles, arrival patterns, and parking space utilization. The research results show that the parking system at Fikom has several weaknesses, namely the small capacity causes a buildup of vehicles, and the parking flow management is less than optimal, resulting in longer waiting times. However, several customers appreciate the efforts to provide existing parking facilities. Based on this analysis, several improvement steps are recommended, such as optimizing parking spaces using smart parking technology, rearranging vehicle lanes, and adding parking areas to reduce density. This study brings important knowledge to the problems of parking systems in academic environments, while also presenting practical alternatives that may help improve the efficiency and effectiveness of parking systems. With proper implementation, it is hoped that the results obtained can increase user comfort and contribute to the smooth flow of activities in the campus environment.
Copyright (c) 2024 Aritmen Andreas L. Manurung, Lamdippos Hendry Parmadi Purba, Steven Ari Paradongan Silaban, Sardo Pardingotan Sipayung https://ejurnal.cendekiainovasi.org/index.php/semicolon/licenses
Data Mining as a Strategic Business Decision Prediction Tool
Data mining has become an important tool to support business strategy decisions. This process allows companies to use algorithms and statistical techniques to analyze previously unidentified big data patterns and trends. The purpose of this research is to determine the use of data mining in predicting business decisions that can increase the effectiveness of company strategy. The methods used in this research include classification and clustering techniques to identify main market segments and consumer behavior. Research shows that data mining provides valuable insights for sales forecasting, inventory optimization, personalization of customer experiences, and more, directly impacting more profitable and strategic business decisions. In conclusion, data mining can improve decision-making efficiency and help companies develop better business strategies.
Copyright (c) 2024 Histori Mei Selamat Gulo, Laurenzio Gratian Amati Daeli, Joy Silvia Siahaan, Sardo Sipayung, S.Kom., M.Kom (Translator); Laurenzio Gratian Amati Daeli, Joy Silvia Siahaan, Sardo P. Sipayung (Author) https://ejurnal.cendekiainovasi.org/index.php/semicolon/licenses
Prediction of The Impact of Social Environment on Students Academic Performance Using The K-Nearest Neighbor (KNN) Method
The research intends to examine the effect of the social ambience on student academic performance. The social environment here is operationalized through three dimensions: family support, peer interaction, and lecturer support. The same research will employ qualitative approach to replicate the reliability of the results among 200 students from different departments, usually conducting by linear regression analysis. Results from the research indicate that family support significantly and positively influences the students' academic achievement in that students who get material support from their parents are likely to have higher Grade Point Averages (GPA). In fact, positive interactions with peers and instructional support from lecturers would also create significant effects towards the students' motivation and learning engagement with a view to these factors. This research thus concluded that the creation of a very supportive social environment is critical towards enhancing students' academic performance, and therefore, the researchers recommend the educational institutions to develop such environments that are even better enabling improved student academic development.
Lingkungan Sosial, Prestasi Akademik, Dukungan Keluarga, Interaksi Sosial
Copyright (c) 2024 Sarah Sagala, San Benfri Saragih, Rifelson Sipayung https://ejurnal.cendekiainovasi.org/index.php/semicolon/licenses
Application Of Naïve Bayes To Analyze Learning Outcomes Through Social Media And Organizations
Media sosial dan keterlibatan organisasi berpengaruh signifikan terhadap hasil belajar mahasiswa.Penelitian ini menggunakan algoritma Naive Bayes untuk mengklasifikasi hasil belajar berdasarkan data survei yang di analisis RapidMiner. Dari 100 data yang digunakan, pembagian data menjadi 70 untuk pelatihan dan 30 untuk pengujian menghasilkan akurasi klasifikasi sebesar 100% menunjukan hubungan signifikan antara penggunaan media sosial, keterlibatan organisasi, dan pencapaian akademik. Temuan ini membuka peluang untuk mengoptimalkan peran media sosial dalam medukung hasil belajar mahasiswa.
Copyright (c) 2024 Jeni Nova Situmorang https://ejurnal.cendekiainovasi.org/index.php/semicolon/licenses
The Effect of Weather On Agricultural Results Using Naïve Bayes Calculation
This study aims to predict crop yields based on weather data using the Naive Bayes algorithm. Extreme weather factors such as high temperatures, low humidity, and unpredictable rainfall often affect crop yields in Indonesia. In this research, weather data, including temperature, humidity, and rainfall, were used to predict the yields of three types of crops: corn, chili, and tomatoes. The Naive Bayes algorithm was applied for classification, with the output being classified as low, medium, or high yield. The results showed that high temperatures and low rainfall significantly negatively impacted the yield of corn, while chili and tomato plants were more resistant to such extreme weather conditions. This research provides insights into the use of technology to enhance agricultural yields by planning planting and harvesting times based on weather predictions.
Copyright (c) 2024 Trihadi Trihadi Pinem https://ejurnal.cendekiainovasi.org/index.php/semicolon/licenses
Selecting a Major Based on Talent and Interest Using the Naive Bayes Algorithm in Python
Choosing the right major is an important step in education, which can influence a person's academic success and career. This study aims to develop a major recommendation system based on students' talents and interests using the Naive Bayes algorithm. The data used in this study includes demographic information, academic performance, as well as the results of students' talent and interest tests. The Naive Bayes algorithm is employed to group and analyze the data to provide the most suitable major recommendations for each student.
Copyright (c) 2024 Ganda Sari Tua Siregar, Sardo Pardingotan Sipayung https://ejurnal.cendekiainovasi.org/index.php/semicolon/licenses
Development of Cultural Picture Guessing Game through the QuickAppNinja Website to Strengthen the Love for the Homeland in the Young Generation in the Society 5.0 Era
This researcher developed a cultural guessing game application based on the QuickAppNinja platform to strengthen the love for the homeland in the younger generation in the era of society 5.0. Through research and development (R&D) research, this research involves the stages of analysis of needs, design, development, limited trials, field trials and there are evaluations and improvements. This limited trial involves teachers, lecturers, and students as assessors, and temporarily for field trials involving students as end users. The results of this study show that this application is easy to use, interesting, and effective in adding insight into local culture. Application users who show interest in the cultural elements presented and feel that they have become more familiar with Indonesian culture. This application has the potential to be an educational medium to introduce local culture to the younger generation. Further development of the development of this application includes the addition of game levels and a variety of cultural content.
Copyright (c) 2024 Pandu Rudy Widyatama, Ricky Widia Pratama, Suhartono, M. Syaifudin, Maya Mustika Kartika Sari https://ejurnal.cendekiainovasi.org/index.php/semicolon/licenses