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Bulletin of Computer Science Research
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 27743659     DOI : -
Core Subject : Science,
Computer Science & IT
Bulletin of Computer Science Research covers the whole spectrum of Computer Science, which includes, but is not limited to : • Artificial Immune Systems, Ant Colonies, and Swarm Intelligence • Bayesian Networks and Probabilistic Reasoning • Biologically Inspired Intelligence • Brain-Computer Interfacing • Business Intelligence • Chaos theory and intelligent control systems • Clustering and Data Analysis • Complex Systems and Applications • Computational Intelligence and Soft Computing • Distributed Intelligent Systems • Database Management and Information Retrieval • Evolutionary computation and DNA/cellular/molecular computing • Expert Systems • Fault detection, Fault analysis, and Diagnostics • Fusion of Neural Networks and Fuzzy Systems • Green and Renewable Energy Systems • Human Interface, Human-Computer Interaction, Human Information Processing • Hybrid and Distributed Algorithms • High-Performance Computing • Information storage, security, integrity, privacy, and trust • Image and Speech Signal Processing • Knowledge-Based Systems, Knowledge Networks • Knowledge discovery and ontology engineering • Machine Learning, Reinforcement Learning • Networked Control Systems • Neural Networks and Applications • Natural Language Processing • Optimization and Decision Making • Pattern Classification, Recognition, speech recognition, and synthesis • Robotic Intelligence • Rough sets and granular computing • Robustness Analysis • Self-Organizing Systems • Social Intelligence • Soft computing in P2P, Grid, Cloud and Internet Computing Technologies • Support Vector Machines • Ubiquitous, grid and high-performance computing • Virtual Reality in Engineering Applications • Web and mobile Intelligence, and Big Data • Cryptography • Model and Simulation • Image Processing
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 7 Documents
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Search results for , issue "Vol. 5 No. 2 (2025): February 2025" : 7 Documents clear
Perancangan UI/UX Aplikasi Untuk Meningkatkan Efisiensi Pemesanan Jasa Fotografi Terhadap Maka Studio Menggunakan Metode Design Thinking Febriansyah; Ruly Dwi Arista; Randi Rian Putra
Bulletin of Computer Science Research Vol. 5 No. 2 (2025): February 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i2.426

Abstract

As technology advances increasingly rapidly, especially in the field of e-commerce, Studios experience difficulties in handling orders for photography services. Ordering methods that still rely on WhatsApp (WA) show inefficiency and lack of optimization. This research focuses on designing the UI/UX of the application with the aim of increasing the efficiency of ordering photography services at Maka Studio. The testing process involves two methods, namely SUS (System Usability Scale) and analysis of data collected through questionnaires. The research subjects consisted of 10 respondents who were potential Maka Studio customers and 20 respondents among students. This research applies the Design Thinking method, through the stages of Empathize, Define, Ideate, Prototype, and Test. These stages aim to understand user needs, identify problems, come up with solution ideas, create prototypes, and test prototypes. The research results show that the application of design thinking was successful in creating the Maka Studio online booking system. This system is expected to be able to overcome various obstacles previously experienced by customers when placing orders at photo studios. Usability testing results shows that the UI/UX design of the photography services ordering application has achieved excellent results and meets user expectations. This can be seen from the majority of respondents who gave positive assessments of various aspects of the application, as well as the SUS test results with an average score of 94.3%.
Sistem Informasi Perencanaan Aplikasi Penjualan Buku Online Berbasis Android Prasetya, Rizki Nanda Winata; Muhammad Sukron; Rizki Hidayat Pane; Muhammad Hafiz Al Fazri; Muhammad Alda
Bulletin of Computer Science Research Vol. 5 No. 2 (2025): February 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i2.453

Abstract

The rapid development of the internet encourages people to live more practically and easily. Previously, the internet could only be enjoyed by certain people and its functions were limited. The internet currently greatly supports activities in all areas of life, for example, business and trade. At this time, business entities, both large companies, organizations and individuals have utilized the internet for their business, for example, business and trade in the food sector online. The popular term in the world of business and online trade is e-commerce. The Android application created by the author is a design for an online book sales system that uses e-commerce. This e-commerce book sales application is designed to make it easier for prospective buyers to make purchases and transactions through mobile devices and the internet. In addition, this application can save time and energy for prospective buyers. The process of this application was developed using the Rapid Application Development (RAD) method, which focuses on accelerating development through prototype literacy and direct user feedback. The main features offered by this application include book catalog management, ordering system, registration system, book upload system to be sold which is easily accessed via computer and mobile devices. The RAD method is the method used in designing this application, because RAD allows application development to be carried out more efficiently with user involvement from the early stages, ensuring that their needs can be met appropriately.
Pengaruh Hyperparameter Tuning Gradient Boosting Terhadap Prediksi Pemilihan Program Studi Mahasiswa Baru Harminto Mulyo; Akhmad Khanif Zyen
Bulletin of Computer Science Research Vol. 5 No. 2 (2025): February 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i2.454

Abstract

This study aims to improve the accuracy of predicting new student major selection using the Gradient Boosting algorithm optimized through hyperparameter tuning. Gradient Boosting was chosen for its ability to handle complex and diverse data, which is crucial in the context of major prediction. The data used was sourced from the new student admissions database of Universitas Islam Nahdlatul Ulama Jepara for the 2013–2023 period, with preprocessing including data cleaning, imputation of missing values, and transformation of categorical features. The initial accuracy of the Gradient Boosting model with default configuration reached 99.01%, indicating that the dataset had relatively clear and structured patterns, enabling the baseline model to perform highly. However, to ensure generalization and avoid the risk of overfitting, hyperparameter tuning was performed using Randomized Search CV. The tuning results showed an increase in accuracy to 99.84% with optimal configurations including a learning rate of 0.1, 300 estimators, and a maximum tree depth of 4. Feature analysis also revealed that attributes such as "school_type," "school_origin," and "gender" significantly influenced the prediction outcomes. This study demonstrates that hyperparameter tuning can significantly enhance model performance, providing a more accurate and relevant predictive solution for the major selection process. Nevertheless, the study's limitation lies in the scope of the dataset, which originated from a single institution, suggesting the need for further exploration with more diverse data and advanced tuning methods like Bayesian Optimization. These findings provide valuable contributions to educational institutions in developing data-driven systems to support strategic decision-making.
Perancangan UI/UX Aplikasi Kasir Inklusif untuk Penyandang Disabilitas di Coffee Shop Aldian Umbu Tamu Ama; Ricky Arnold Nggili; Deva Nita Mulya; Yashinta Putri Dwi Astuti
Bulletin of Computer Science Research Vol. 5 No. 2 (2025): February 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i2.470

Abstract

Kopi Hening is a coffee business in Salatiga City managed by individuals who are deaf or hard of hearing. Facing challenges in customer communication and manual bookkeeping processes, this study aims to design a prototype UI/UX for an inclusive cashier application to enhance operational efficiency and bookkeeping accuracy. Using the Design Science Research Methodology (DSRM) approach, the study involved direct observation of cashier activities, interviews with supervisors, and design evaluation through simulations using the Cognitive Walkthrough method. The Cognitive Walkthrough evaluation, which measured user success rates in completing specific tasks, showed good performance with transaction scenarios achieving 83-86% success rates (cash payment 83%, transfer 83%, QRIS 86%) and financial bookkeeping scenarios reaching 73%. Expert evaluations confirmed that the design adheres to inclusive UI/UX principles, though further adjustments, such as optimizing text size and element spacing, are recommended for better accessibility. This study serves as an initial step toward supporting digital inclusion and provides a foundation for the future development of inclusive cashier applications.
Analisis Sentimen Masyarakat di Twitter Mengenai Open AI CHATGPT Menggunakan Metode Support Vector Machine (SVM) Septini, Ayu; Susanto; Elmayati
Bulletin of Computer Science Research Vol. 5 No. 2 (2025): February 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i2.475

Abstract

This study aims to analyze public sentiment toward OpenAI ChatGPT technology on Twitter using the Support Vector Machine (SVM) method. The background of this research is based on the increasing global use of the internet and artificial intelligence (AI), as well as the role of social media as a platform for people to express their opinions. This study employs a qualitative research approach using the Support Vector Machine method, with data collection conducted through primary data obtained by crawling data from Twitter. The research uses data collected from 4,305 Indonesian-language tweets gathered between January and September 2023. These tweets were then classified into positive, neutral, and negative sentiments using the SVM method. The results indicate that out of the total collected data, 2,196 tweets had a neutral sentiment, 1,500 tweets had a positive sentiment, and 591 tweets had a negative sentiment. In the model performance evaluation, training data with an 80:20 ratio achieved the highest accuracy of 94.25%, while testing data with a 70:30 ratio achieved the highest accuracy of 93.16%. Additionally, the use of 10-fold cross-validation on training data resulted in an accuracy of 89.94%, while testing data achieved an average accuracy of 78.17%.
Analisis Sentimen Berita Online Terhadap Transportasi Online di Indonesia dengan Metode Naïve Bayes Classifier, Support Vector Machine dan K-Nearest Neighbor Selawati, Arina; Yan Rianto; Rachmawati Darma Astuti; Ainun Zumarniansyah; Deny Novianti
Bulletin of Computer Science Research Vol. 5 No. 2 (2025): February 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i2.477

Abstract

News about online transportation in Indonesia in 2019 until early 2020 has been published in various Indonesian online media, because there is enough information in the form of text without numerical scale, it is difficult to classify information information efficiently without reading the full text. Sentiment analysis is used to automate the process of assessing opinion whether it is positive or negative. Classifying sentiments on news from online news media with the Text Mining process and using the method of increasing the Classification Accuracy / Ensemble Method of Engineering by combining the classification algorithm naïve bayes method, classifier Supporting vector machines and k-nearest neighbors added with the Particle Swarm Optimization method and Vote method The next will be a comparative analysis. The results of the study above get an SVM exam accuracy value even after using the PSO selection feature with the ensemble. Select is still appropriate at 84.16%, Likewise for NB algorithm which gets 79.08% and KNN which gets approval 87.19%. These words will be used to see words related to sentiments that often appear and have the highest weight and can be used to find out positive news articles and negative news articles. And for this research the model that uses KNN algorithm gets the highest accuracy.
Rancangan UI/UX Aplikasi Pite Tenun Dengan Edukasi Budaya Menggunakan Metode Design Thinking Wilitama Tantosa; Lalu A Syamsul Irfan Akbar; Cipta Ramadhani
Bulletin of Computer Science Research Vol. 5 No. 2 (2025): February 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i2.482

Abstract

Woven fabric is an Indonesian cultural wealth that can be found in various regions, one of which is in Sukarara Village, Lombok. Sukarara woven fabric is known as "songket fabric" with strong religious and cultural values so that it becomes a preserved heritage and the main source of livelihood for the village community. However, currently many outsiders are taking advantage by making weaving motifs and then printed and sold at very cheap prices. So that it causes a decline in the existence of cultural values in woven fabrics. The purpose of the study is to produce a UI/UX design design of the Pite Tenun application with Cultural Education in Sukarara Village and to get measurable results from the design results of prospective users using the System Usability Scale. This app is made with an attractive design with UI/UX that is tailored to your needs. Therefore, the Pite Tenun application is designed to be able to carry out an informative process of selling woven fabrics from the materials used and more accurate product details, in addition to the addition of the story of Sukarara Village Weaving and its history is expected to be a trusted cultural education and can increase the existence of cultural values in it. The results of the research obtained show that the UI/UX design of the Pite Weaving application with Cultural Education in Sukarara Village was successfully implemented. The results obtained have been measured from the design of prospective users using the System Usability Scale with a score of 2197.5 and the average total number of respondent scores is 73.25%. The results are categorized as excellence (grade B) based on SUS scores.

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