SEMICOLON: Computer Science Journal
type: channel
description: 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. <img src="[binary]" />
publisher: Cendekia Inovasi
language: en
publication name: SEMICOLON: Computer Science Journal
issn: 2985-9999
items: Implementation of C45 Algorithm in Measuring the Level of Understanding of FIKOM UNIKA Santo Thomas Students on Courses
items: Performance Analysis of Parking System in FIKOM and KNN Environment: Efficiency and Effectiveness Approach
items: Data Mining as a Strategic Business Decision Prediction Tool
items: Prediction of The Impact of Social Environment on Students Academic Performance Using The K-Nearest Neighbor (KNN) Method
items: Application Of Naïve Bayes To Analyze Learning Outcomes Through Social Media And Organizations
items: The Effect of Weather On Agricultural Results Using Naïve Bayes Calculation
items: Selecting a Major Based on Talent and Interest Using the Naive Bayes Algorithm in Python
items: 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

Implementation of C45 Algorithm in Measuring the Level of Understanding of FIKOM UNIKA Santo Thomas Students on Courses
type: item
description: 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.
subject: Articles
  topic: section
subject: C45 Algorithm
  topic: keywords
subject: Level of understanding
  topic: keywords
subject: Decision tree
  topic: keywords
subject: RapidMiner
  topic: keywords
subject: Data Mining
  topic: keywords
creator: Johanes Kevin Malau
creator: Dinda Roulita Simangunsong Simangunsong
creator: Sardo Pardingotan Sipayung Sipayung
rights: Copyright (c) 2024 Johanes Kevin Malau, Dinda Roulita Simangunsong Simangunsong, Sardo Pardingotan Sipayung (Author) https://ejurnal.cendekiainovasi.org/index.php/semicolon/licenses
date: 2024-12-08
publication date: 2024-12-08
starting page: 48
ending page: 55
doi: 10.99999/

Performance Analysis of Parking System in FIKOM and KNN Environment: Efficiency and Effectiveness Approach
type: item
description: 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.
subject: Articles
  topic: section
subject: Parking system
  topic: keywords
subject: parking space optimization
  topic: keywords
subject: intelligent parking system
  topic: keywords
subject: customer satisfaction,
  topic: keywords
subject: parking management
  topic: keywords
subject: parking space availability
  topic: keywords
creator: Aritmen Andreas L Manurung
creator: Lamdippos Hendry Parmadi Purba
creator: Steven Ari Paradongan Silaban
creator: Sardo Pardingotan Sipayung
rights: 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
date: 2024-12-08
publication date: 2024-12-08
starting page: 17
ending page: 28
doi: 10.99999/

Data Mining as a Strategic Business Decision Prediction Tool
type: item
description: 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.
subject: Articles
  topic: section
subject: Data Mining
  topic: keywords
subject: Business Decisions
  topic: keywords
subject: Classification
  topic: keywords
subject: Clustering
  topic: keywords
subject: Business Strategy
  topic: keywords
creator: Histori Mei Selamat Gulo
creator: Laurenzio Gratian Amati Daeli
creator: Joy Silvia Siahaan
creator: Sardo P. Sipayung
rights: 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
date: 2024-12-20
publication date: 2024-12-20
starting page: 56
ending page: 60
doi: 10.99999/

Prediction of The Impact of Social Environment on Students Academic Performance Using The K-Nearest Neighbor (KNN) Method
type: item
description: 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.
subject: Articles
  topic: section
subject: Lingkungan Sosial, Prestasi Akademik, Dukungan Keluarga, Interaksi Sosial
  topic: keywords
creator: Sarah Sagala
creator: San Benfri Saragih
creator: Rifelson Sipayung
rights: Copyright (c) 2024 Sarah Sagala, San Benfri Saragih, Rifelson Sipayung https://ejurnal.cendekiainovasi.org/index.php/semicolon/licenses
date: 2024-12-08
publication date: 2024-12-08
starting page: 29
ending page: 33
doi: 10.99999/

Application Of Naïve Bayes To Analyze Learning Outcomes Through Social Media And Organizations
type: item
description: 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.
subject: Articles
  topic: section
subject: Naïve Bayes
  topic: keywords
subject: Analisis Data Pembelajaran Mesin
  topic: keywords
subject: Predeksi
  topic: keywords
subject: Media sosial
  topic: keywords
creator: Jeni Nova Situmorang Situmorang
creator: Fera Sihotang
creator: Joy Sofater Purba
creator: Sardo Pardiongotan Sipayung
rights: Copyright (c) 2024 Jeni Nova Situmorang https://ejurnal.cendekiainovasi.org/index.php/semicolon/licenses
date: 2024-12-08
publication date: 2024-12-08
starting page: 42
ending page: 47
doi: 10.99999/

The Effect of Weather On Agricultural Results Using Naïve Bayes Calculation
type: item
description: 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.
subject: Articles
  topic: section
subject: Prediksi Hasil Panen
  topic: keywords
subject: Cuaca Ekstrem
  topic: keywords
subject: Pertanian
  topic: keywords
subject: Tanaman Pangan
  topic: keywords
subject: Naive Bayes
  topic: keywords
creator: Trihadi Trihadi Pinem
creator: Sardo Sardo Sipayung
rights: Copyright (c) 2024 Trihadi Trihadi Pinem https://ejurnal.cendekiainovasi.org/index.php/semicolon/licenses
date: 2024-12-08
publication date: 2024-12-08
starting page: 34
ending page: 41
doi: 10.99999/

Selecting a Major Based on Talent and Interest Using the Naive Bayes Algorithm in Python
type: item
description: 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.
subject: Articles
  topic: section
subject: Naïve Bayes
  topic: keywords
subject: Talents and Interests
  topic: keywords
subject: Pemilihan Jurusan
  topic: keywords
subject: Machine Learning
  topic: keywords
creator: Ganda Sari Tua Siregar
creator: Sardo Sipayung
rights: Copyright (c) 2024 Ganda Sari Tua Siregar, Sardo Pardingotan Sipayung https://ejurnal.cendekiainovasi.org/index.php/semicolon/licenses
date: 2024-12-08
publication date: 2024-12-08
starting page: 1
ending page: 7
doi: 10.99999/

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
type: item
description: 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.
subject: Articles
  topic: section
subject: Guess the Culture Picture
  topic: keywords
subject: Website QuickAppNinja
  topic: keywords
subject: Love for the Motherland
  topic: keywords
subject: The Younger Generation
  topic: keywords
subject: Era Society 5.0
  topic: keywords
creator: Pandu Rudy Widyatama
creator: Ricky Widia Pratama
creator: Suhartono
creator: M. Syaifudin
creator: Maya Mustika Kartika Sari
rights: Copyright (c) 2024 Pandu Rudy Widyatama, Ricky Widia Pratama, Suhartono, M. Syaifudin, Maya Mustika Kartika Sari https://ejurnal.cendekiainovasi.org/index.php/semicolon/licenses
date: 2024-12-08
publication date: 2024-12-08
starting page: 8
ending page: 16
doi: 10.99999/