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Paradigma
Published by Universitas Bina Sarana Informatika
ISSN : 14105063     EISSN : 25793500     DOI : http://dx.doi.org/10.31294/paradigma
Core Subject : Science,
Computer Science & IT
The Paradigma Journal is intended as a medium for scientific studies of research, thought and analysis-critical issues on Computer Science, Information Systems, and Information Technology, both nationally and internationally. The scientific article refers to theoretical reviews and empirical studies of related sciences, which can be accounted for and disseminated nationally and internationally. Paradigma Journal accepts scientific articles research at Expert Systems, Information Systems, Web Programming, Mobile Programming, Games Programming, Data Mining, and Decision Support Systems.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 136 Documents
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Information System for Internship Applications in the Yogyakarta City Communication, Informatics, and Encoding Office Pradana, Bimo; Kesuma, Sara Puja; Darmanto, Darmanto; Meyliana, Anastasia; Pradiatiningtyas, Diah
Paradigma - Jurnal Komputer dan Informatika Vol. 25 No. 2 (2023): September 2023 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v25i2.2328

Abstract

The Office of Communication, Informatics and Encoding (DISKOMINFOSAN) is a Yogyakarta City government agency tasked with carrying out government affairs in the field of Communication, Informatics and Encoding to meet the needs of society in the current digital era. Needs regarding registration and internship activities or field work practices for Yogyakarta City students, DISKOMINFOSAN is needed to provide better service. Based on the data obtained from interviews with the Sub Coordinator of the Information System Planning and Implementation Substance Group explained that the apprentice registration system and apprentice activities that are currently running are not computerized so that the data cannot be managed optimally. Research is also carried out by direct observation as an active participant in internship activities so that it can analyze deficiencies and constraints on the running system. In the early stages, students must submit documents for the requirements to register for an apprenticeship directly to the agency so that it will take time. Next, students fill in the required data on the Google Form. If an internship has been accepted, students must fill in the progress and final report on the Google Form. This activity is considered inefficient for students because they have to access many Google Form links during registration and internship activities. The software development method used in this study is the Waterfall method, the framework used for application development uses the CodeIgniter framework while the software testing used is the black-box method. With the design of this website application system, it can be a solution to problems that occur in the running system for the registration process and internship activities at the Yogyakarta City Informatics and Encryption Communication Service.
Information Systems to Enhance Focus in the Learning Process Using Design Thinking Methodology Rahayu, Wahyu; Primajaya, Aji
Paradigma - Jurnal Komputer dan Informatika Vol. 25 No. 2 (2023): September 2023 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v25i2.2331

Abstract

This study adopts the Design Thinking methodology to investigate the habits, needs, and challenges faced by students when attempting to maintain focus during activities that require concentration. The research surveyed students, with a significant proportion (approximately 53% of all participants) reporting frequent loss of focus during tasks. External disturbances, such as an unconducive environment, gadget notifications, and enticing distractions, were identified as the primary triggers for this lack of focus, resulting in procrastination and hindrance in achieving their main goals. In response to these findings, this research proposes a User Interface / User Experience (UI/UX) design approach to develop an application aimed at enhancing focus and learning performance to boost overall productivity. The design aims to ensure the application's interface is user-friendly and easily comprehensible. By designing an application interface that can organize focused sessions for the activities to be carried out by the users. The UI/UX design of this application holds the potential to empower students in elevating their learning experience, thereby fostering higher productivity and goal achievement. The results of this research show that the use of the Design Thinking methodology achieved a score of 70% from the overall users who tested the application design using the Maze tool.
The Method User Experience Questionnaire Analysis of Identitas Kependudukan Digital Application Farlian, Galang Fachrul; Ridwansyah, Ridwansyah
Paradigma - Jurnal Komputer dan Informatika Vol. 25 No. 2 (2023): September 2023 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v25i2.2353

Abstract

User Experience (UX) becomes important to explore and fulfill the needs for developing user-focused applications or products. The problems that exist to measure the level of user experience in the Digital Resident Identity (IKD) application and complaints submitted by users tend to lead to system and service quality problems in the IKD application. Then research purposes are assessed to evaluate the extent to which users can utilize and interact with the application. The method used by researchers is the User Experience Questionnaire (UEQ). UEQ is a widely used scoring methodology used to quantitatively measure user experience by administering a questionnaire to individuals that measures their subjective experiences and perceptions. Variables in UEQ, namely: efficiency, perspicuity, dependability, novelty, stimulation, and interestingness. The evaluation results of user experience in IKD applications using UEQ showed that there were 5 variables that received positive evaluation results, including attractiveness variables (mean 2.14), clarity variables (perspicuity) (mean 1.725), efficiency variables (efficiency) ( mean 1.725), accuracy variable (mean 1.525), and stimulation variable (mean 1.475). Whereas the novelty variable (mean 0.602) gets neutral evaluation results. From these results it can be used by IKD application developers to improve the user experience (user experience) of IKD applications on novelty variables by improving the appearance of applications that are more creative, inventive, and also cutting edge. The developer can pay attention to the recommendations that have been presented in this study. Parties who wish to conduct further research can use other evaluation methods such as Heuristic Evaluation.
Internet Network Analysis with Hierarchy Token Bucket Method at Dhyana Pura University Rina, Trywanto; Aryanto, Kadek Yota Ernanda; Sunarya, I Made Gede
Paradigma - Jurnal Komputer dan Informatika Vol. 25 No. 2 (2023): September 2023 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v25i2.2354

Abstract

Bandwidth management is indispensable in computer networks. Not only to manage the needs of each individual, but also to keep the data traffic running smoothly. Dhyana Pura University is a private university that utilizes information technology in achieving optimal performance. Observation results with throughput, delay, packet loss and jitter parameters show that bandwidth management has not been done properly. Implementation of bandwidth management is done on Mikrotik Cloud Core Router and PC Router based on Ubuntu server version 16.04. One way to reduce performance degradation is to manage bandwidth. Good bandwidth management is expected to provide the right Quality of Service (QoS) for each internet service. The Hierarchy Token Bucket (HTB) method as a queuing method that regulates bandwidth usage to be given to each internet user shows more optimal results and is easier to use according to the desired needs. This is because the bandwidth is divided evenly and prevents one user from spending excessive bandwidth, so that it can increase employee satisfaction in using internet services. The results of the analysis of measuring the level of employee satisfaction with the Customer Satisfaction Index (CSI) method show that the HTB method has a total satisfaction index of 66.154% in the very satisfied category, while for troughput variables of 65.32%, delay of 67.14%, packet loss of 66.50% and jitter of 65.40%. Thus the implementation on the internet network at Dhyana Pura University using the Hierarchy Token Bucket (HTB) method is feasible to implement with a satisfied predicate.
Comparative Analysis of Email Spam Detection Using SVM with TF-IDF and Word2Vec on Multilingual Datasets Katamsyi, Kaifa Ahlal; Akbar, Ahmad Taufiq; Nurkholis, Andi; Prapcoyo, Hari; Akbar, Bagus Muhammad; Saifullah, Shoffan
Paradigma - Jurnal Komputer dan Informatika Vol. 28 No. 1 (2026): March 2026 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v28i1.12339

Abstract

The rapid growth of email communication has increased the prevalence of spam emails, which can disrupt productivity and compromise information security. This study presents a comparative analysis of two text representation methods—TF-IDF and Word2Vec—for spam email classification using a Support Vector Machine (SVM) with a Radial Basis Function kernel. The experiments utilized Indonesian and English email datasets totaling 5,421 emails, split into 75% training and 25% testing sets. Two scenarios were evaluated: baseline with default parameters and after hyperparameter optimization using Grid Search combined with K-Fold Cross Validation. The results indicate that TF-IDF consistently outperformed Word2Vec across both languages, achieving the highest accuracy of 0.9562 on the English dataset after tuning. Word2Vec showed substantial improvement following parameter adjustment, reducing the performance gap with TF-IDF. The findings highlight the importance of hyperparameter optimization for enhancing the quality of feature representations and improving classification performance. This study also demonstrates that TF-IDF provides more stable results across different linguistic contexts, while Word2Vec benefits significantly from careful tuning. The results provide practical insights for implementing efficient spam email detection systems in multilingual environments. Future research could explore additional classifiers, deep learning approaches, and contextual embeddings to further improve classification accuracy and robustness.
Facial Skin Disease Classification Using Swin Transformer V2 and ResNet-50 in a Flask-Based System Imaniyah, Shinta Arum; Murti Dewanto, Febrian; Sari, Nur Latifah Dwi Mutiara
Paradigma - Jurnal Komputer dan Informatika Vol. 28 No. 1 (2026): March 2026 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v28i1.12381

Abstract

Facial skin diseases are common health conditions that can significantly affect both physical and psychological well-being. Early identification is essential to minimize the risk of disease progression. However, in many areas, there is still a lack of access to dermatological care. Although deep learning algorithms have been widely used in medical image categorization, few studies offer a direct comparison between convolutional neural networks (CNN) and transformer-based architectures within a cohesive experimental framework, especially concerning the classification of facial skin diseases. This study compares the effectiveness of ResNet-50 with Swin Transformer V2 and develops a deep learning system to classify six different types of skin problems on the face. The models were evaluated using accuracy, precision, recall, and F1-score after the dataset was divided into subsets for testing, validation, and training. According to the trial results, Swin Transformer V2 achieves an astounding accuracy of 97.54%, outperforming ResNet-50, which achieves 94.44%. The training curves indicate stable learning behavior with minimal overfitting. Grad-CAM visualization is applied to improve interpretability by highlighting relevant regions in the images. The best-performing model is implemented in a Flask-based web application as a prototype system for early detection. These results demonstrate how transformer-based architectures can improve classification performance and highlight their potential applications in practical diagnostic support systems

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