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Scientific Journal of Informatics
Published by Universitas Negeri Semarang
ISSN : 24077658     EISSN : 24600040     DOI : -
Core Subject : Science,
Computer Science & IT
Scientific Journal of Informatics published by the Department of Computer Science, Semarang State University, a scientific journal of Information Systems and Information Technology which includes scholarly writings on pure research and applied research in the field of information systems and information technology as well as a review-general review of the development of the theory, methods, and related applied sciences.
Arjuna Subject : -
Articles 564 Documents
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Performance Analysis for Classification of Malnourished Toddlers Using K-Nearest Neighbor Lonang, Syahrani; Yudhana, Anton; Biddinika, Muhammad Kunta
Scientific Journal of Informatics Vol 10, No 3 (2023): August 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i3.45196

Abstract

Purpose: Malnutrition in toddlers is a nutritional issue that Indonesia is still dealing with. Toddlers can suffer from decreasing cognitive and physical abilities, as well as being categorized as having a high risk of death. Early detection is crucial for preventing this and providing appropriate treatment if malnutrition is detected. Classification is a machine-learning technique widely used in disease detection. Because it is simple and easy to implement, K-Nearest Neighbor is the most used classification algorithm. Detecting malnutrition can be done automatically and more quickly by utilizing classification and machine learning algorithms. The aim of this study was to analyze performance to find out which model is best for detecting malnutrition by evaluating the performance of classification using KNN with the Euclidean distance function.Methods: The dataset used in this study is the nutritional status of toddlers from Puskesmas Ubung. The classification method proposed in this research is the KNN algorithm with Euclidean distance. There are three scenarios for the classification model that will be used. Performance classification will compare each model in terms of accuracy, precision, recall, f1-score, and mean absolute error.Results: The experimental results show that KNN k = 15 using the first model generates excellent classification when classifying malnourished toddlers using the Euclidean distance function. The model obtains 91% accuracy, 86.6% precision, 83.8% recall, 85.2% recall, and a mean absolute error of 0.09.Novelty: In this experiment, we analyzed the performance of the KNN to classify malnourished children using a nutritional status dataset, which resulted in an excellent classification that could be used for early detection.
YOLOv8 Based on Data Augmentation for MRI Brain Tumor Detection Passa, Rahma Satila; Nurmaini, Siti; Rini, Dian Palupi
Scientific Journal of Informatics Vol 10, No 3 (2023): August 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i3.45361

Abstract

Purpose: This research aimed to detect meningioma, glioma, and pituitary brain tumors using the YOLOv8 architecture and data augmentations.Methods: This research employed the YOLOv8 architecture with data augmentation techniques to detect meningioma, glioma, and pituitary brain tumors. The study collected a dataset of T1-weighted contrast-enhanced images. The dataset is used for training, validation, and testing. Preprocessing and augmentation are applied to enhance the training data.Result: After applying data augmentation techniques, the performance of all tumor types improves significantly. Meningioma, Glioma, and Pituitary tumors demonstrate increased Precision, Recall, and mAP50 scores compared to the results before augmentation. The findings highlight the effectiveness of the proposed method in enhancing the model's ability to accurately detect brain tumors in MRI scans. The research conducted both with and without augmentation followed a similar procedure: data collection was first undertaken, followed by preprocessing and with or without augmentation. Subsequently, the collected data was partitioned into training and validation subsets for training with the YOLOv8 architecture. Finally, the model's performance was evaluated through testing to assess its effectiveness in detecting brain tumors.Novelty: The novelty of this research lies in the YOLOv8 architecture and data augmentation techniques for MRI brain tumor detection. The study contributes to the existing knowledge by demonstrating the effectiveness of deep learning-based approaches in automating the detection process and improving the model's performance. By combining YOLOv8 with data augmentation, the proposed method enhances the model's accuracy and efficiency. The research findings emphasize the potential of this approach in facilitating early diagnosis and treatment planning, thereby improving patient care in the context of brain tumor detection. 
UTAUT and WebQual Models for Measuring User Acceptance of Text Minutes from Video Conferencing Services Ningsih, Dewi Handayani Untari; Nurdin, Alya aulia; Muslim, Much Aziz
Scientific Journal of Informatics Vol 10, No 3 (2023): August 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i3.46651

Abstract

One of the issues encountered during the post-COVID-19 and new normal period is in the field of higher education and employment that require education and online or virtual meetings. Automatic speech recognition (ASR) is one of the technologies used to simplify recording through speech recognition into text minutes for the effectiveness of online meetings. This study aims to determine user acceptance in adopting text minutes on the Zoom Meeting video conference service for online meetings so that it can provide insights for video conferencing service provider companies in developing text minutes on their platforms. In this study, a total of 156 respondents participated in the study. The obtained data were analyzed using PLS-SEM. As a result, the construct of information, interaction, and performance expectancy has been shown to affect user satisfaction with text minutes in video conferencing services with an R square value of satisfaction of 0.516 (moderate). The quality of information is an important factor, information from the text minutes on video conferencing services must be accurate, reliable, timely, relevant, easy to understand, and presented in the appropriate format.Purpose: This observes ambitions to determine consumer popularity in adopting text minutes at the Zoom assembly video conference provider for online meetings in order that it could offer insights for video conferencing carrier company organizations in developing text minutes on their structures.Methods/Study design/approach: This study uses a mixture of UTAUT and WebQual. A studies instrument becomes prepared inside the shape of a web questionnaire containing query objects. All the items had been adapted from previous research. Then, data became amassed by way of administering an online questionnaire through diverse social media structures, along with WhatsApp and Telegram to respondents with several demographic questions and a five-factor Likert scale from strongly disagree to strongly agree (scored from 1 to 5) from eleven constructs. The obtained facts had been analyzed the usage of PLS-SEM.Result/Findings: The existence of text minutes on the Zoom Meeting video conference service has not been fully adopted by users in carrying out learning activities or online meetings. Primarily based on the studies that have been executed, there are four hypotheses accepted, namely H2, H3, H5, and H10. Meanwhile, six different hypotheses, namely H1, H4, H6, H7, H8, and H9, have been rejected. Elements influencing person adoption of the text of the Zoom assembly video conferencing carrier depend on the nice of the information generated from the text minutes from video conferencing in which the statistics ought to be accurate, reliable, well timed, relevant, easy to apprehend, and provided in the right format. Novelty/Originality/Value: As a result, the construct of information, interaction, and performance expectancy has been shown to affect user satisfaction with text minutes in video conferencing services with an R square value of satisfaction of 0.516 (moderate). From the outcomes of the research conducted, video conferencing service providers can improve and expand text mins capabilities extra sophisticatedly but nonetheless easy in order that overall customers sense greater satisfied with video conference textual content mins and could reuse and endorse others to apply the same era. In the next look at, its miles predicted that the scope of the survey will be wider globally with the growth within the wide variety of respondents, in addition to including a few constructs that have now not been used
Arabica Coffee Price Prediction Using the Long Short Term Memory Network (LSTM) Algorithm Setiyani, Lila; Utomo, Wiranto Herry
Scientific Journal of Informatics Vol 10, No 3 (2023): August 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i3.44162

Abstract

Purpose:  Arabica coffee beans have been widely cultivated in various parts of the world. The need for coffee beans is estimated to increase every year. This was followed by the rapid growth of franchised coffee shops and cafes, therefore Arabica coffee beans have been traded legally in the world, thus making the price of these Arabica coffee beans a public concern. This prediction of the price of Arabica coffee beans can be input for business actors in the coffee shop, café franchises, and farmers in the decision-making process. This study aims to predict the price of Arabica coffee beans in 2023 and 2024 using the long short-term memory (LSTM) Algorithm.Methods:  The research procedure is carried out by collecting data, data analysis, and preprocessing, and building a forecasting model using the Long Short-Term Memory Network (LSTM) algorithm. Arabica coffee bean price datasets in this study were taken from The Pink Sheet World Bank Commodity Price Data, which presents Arabica coffee bean prices from 1960 to February 2023.Results:  The results of this study indicate the predicted price of Arabica coffee beans in 2023 and 2024 with Error (MAE), which is the average absolute difference between the actual value and the predicted value.Novelty:  What is most important and what differentiates it from previous research is in the preprocessing using two algorithms namely MinMaxScaler and Sliding Window. Meanwhile, for the training model, GridSearchCV is used. The model is evaluated using the lost function using Mean Squared Error (MSE) and Mean Absolute Error (MAE) thereby making it easy to evaluate the performance of the model. 
Social Media Marketing and Brand Loyalty, The Mediating Role of Brand Trust: a Partial Least Square Algorithm (PLS) Approach Umar, Fadhil; Raharja, Edy; Mahardika, Jihaddul Akbar; Arkhiansyah, M. Topan Bastari
Scientific Journal of Informatics Vol 10, No 3 (2023): August 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i3.45486

Abstract

Purpose: Brand loyalty is a very important aspect along with technological growth, market saturation, globalization, and intense competition. This research seeks to analyze how social media marketing and brand experience impact brand loyalty among students who use XL in Semarang City, with brand trust serving as an intermediary factor.Methods: The research approach is quantitative, with sampling using a purposive sampling technique and the research sample is 133 university students in Semarang. This research establishes a structural equation modeling (SEM) analysis with Smart PLS.Result: The results of this research indicate that both social media marketing and brand experience factors exhibit a favorable and substantial impact on brand loyalty. Moreover, brand trust displays a positive and notable effect on brand loyalty while also acting as a mediator for the positive influence that social media marketing and brand experience have on brand loyalty.Novelty: Analysis and testing of variables that influence user brand loyalty of XL using the Partial Least Square (PLS) algorithm and the Customer Relationship Marketing (CRM) approach. This study examines the telecommunications sector on the advice of previous studies.
Impact of Online Gaming on the Academic Performance of DEBESMSCAT-Cawayan Campus Students Ricky Capinig Gabrito; Roger Yatan Ibañez Jr.; Jacob Frederick Palabiano Velza
Scientific Journal of Informatics Vol 10, No 4 (2023): November 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v%vi%i.45007

Abstract

Purpose: This study investigated the effects of online gaming on the academic performance of students of DEBESMSCAT-Cawayan Campus.Methods: A descriptive research design was employed, and a survey questionnaire was distributed to 75 student online gamers who were selected through a census approach. Statistical analysis techniques such as frequency and percentage were used to analyze the data.Result: Mobile Legends was found to be the most popular game among the respondents. The majority of students spent 1-2 hours playing online games per day and incurred costs associated with gaming. However, most respondents believed that their gaming activities did not significantly hinder their ability to perform tasks in school or at home. The effects of online games on academic performance were perceived positively by the respondents. They believed that online gaming had a positive impact on test scores, overall grades, submission of school activities, time in studying, concentration in studies, participation in learning activities, interaction with people, interest in class discussions, willingness to go to school, and interest in school activities.Novelty: This study provided a comprehensive overview of the perceptions of students regarding the effects of online games on their academic performance. The study suggested that online gaming could have both positive and negative effects on academic performance, depending on how it was managed by students. The study also contributed to the existing body of knowledge on the subject and may have informed future research and interventions aimed at supporting students in managing their gaming activities while maintaining their academic performance.
Comparison of Discriminant Analysis and Support Vector Machine on Mixed Categorical and Continuous Independent Variables for COVID-19 Patients Data Haikal, Husnul Aris; Wigena, Aji Hamim; Sadik, Kusman; Efriwati, Efriwati
Scientific Journal of Informatics Vol 11, No 1 (2024): February 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i1.48565

Abstract

Purpose: Numerous factors can affect the duration of COVID-19 recovery. One method involves utilizing natural herbal medication. This study seeks to determine the variables influencing the duration of COVID-19 recovery and to compare discriminant analysis and support vector machine models using COVID-19 patient data from West Sumatra.Methods: Two data mining methods, Discriminant Analysis and Support Vector Machine with different types of kernels (linear, polynomial, and radial basis function), were employed to categorize the time of COVID-19 recovery in this work. The study utilized 428 data points, with 75% allocated for training data and 25% for testing data. The independent factors were evaluated by determining the selection variables' information value (IV) to gauge their influence on the dependent variable. Data resampling techniques were employed to tackle the problem of data imbalance. This study employs data resampling techniques, including undersampling, oversampling, and SMOTE. The balancing accuracy of Discriminant Analysis and Support Vector Machine was examined.Result: The Discriminant Analysis with SMOTE achieved a balanced accuracy of 66.50%, outperforming the linear kernel Support Vector Machine with SMOTE, which had a balanced accuracy of 63.20% in this dataset.Novelty: This study assessed the novelty, originality, and value by comparing Discriminant Analysis and SVM algorithms with categorical and continuous independent variables. This research explores techniques for managing imbalanced data using undersampling, oversampling, and SMOTE, with variable selection based on information value assessment. 
Analysis Impact of Rapid Application Development Method on Development Cycle and User Satisfaction: A Case Study on Web-Based Registration Service Riadi, Imam; Yudhana, Anton; Elvina, Ade
Scientific Journal of Informatics Vol 11, No 1 (2024): February 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i1.49590

Abstract

Purpose: This research was conducted to respond to obstacles and inefficiencies in the new student registration system at RA Plus Rabbani. Currently, the conventional method of using physical documents for registration is vulnerable to damage and data loss. Therefore, the proposed solution is implementing a website-based online registration system using the Rapid Application Development (RAD) method. This aims to simplify the process, increase accessibility for prospective students, and reduce the costs and time required.Methods: This research commenced by identifying constraints within the conventional student registration system at RA Plus Rabbani through observations and interviews. The development, following the RAD methodology, involved testing with PHPUnit and Blackbox Testing to ensure the functionality of the system aligned with specifications. In addition, usability evaluation was conducted based on the ISO 9126 standard.Result: The research results show that testing on MVC indicated a 100% success rate for each architectural feature. Referring to expectations with a “valid” conclusion on functionality using Blackbox testing, based on ISO 9126 percentage displayed, it is known that the criterion with the most significant value is the understandability characteristic with a value of 83%. Novelty: This research makes a significant contribution by improving student registration services at RA Plus Rabbani through the implementation of various testing techniques, following the research flow offered by RAD. The study also provides substantial references for further research in web-based system development.
Real-Time Web-Based Monitoring System for Temperature, Humidity, and Solar Panels in Ramie Drying Facilities Hidayat, Sidiq Syamsul; Shabiya, Kiara Izzatus; Kadiran, Sri Anggraeni; Mujahidin, Irfan; Prabowo, M. Cahyo Ardi; Nursyahid, Arif; Wasito, Endro; Helmy, Helmy
Scientific Journal of Informatics Vol 11, No 1 (2024): February 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i1.47234

Abstract

Purpose: To address the manual monitoring challenges in processing ramie fibers, especially during drying. The purpose is to create a monitoring system that oversees room temperature, humidity, and the status of solar panels, crucial factors in ramie productivity.Methods: Real-time web-based system development that monitors room temperature, humidity, and the performance of solar panels in a ramie drying room using the Internet of Things architecture ESP32 with communication through GSM SIM 800L in rural areas.Results: The system can display real-time information such as temperature data, humidity, and electrical energy parameters derived from the solar panel's utilization in the ramie drying room. By doing so, users gain efficiency and effectiveness in obtaining information, significantly enhancing ramie fiber productivity.Novelty:  Integration of sensor instruments, low-power ESP32 microcontrollers, GSM Telecommunication, Solar Cell Energy as a power source, and a real-time web-based Monitoring Information System implemented in a ramie drying dome. This simplifies the monitoring process and optimizes limited resources such as space, energy, telecommunications, and human resources, which are typically constrained infrastructure in the ramie fiber agricultural system.
Examination of the Factors Impacting the Interest of Residents in Semarang City in Mobile Health Applications: An UTAUT Analysis Perdana, Muhamad Putra; Abidin, Zaenal
Scientific Journal of Informatics Vol 11, No 1 (2024): February 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i1.48130

Abstract

Purpose: The study aims is to examine the determinants that impact the level of public interest in utilizing mobile health (m-health) applications in Semarang City, Indonesia. Our specific objective is to identify the critical factors that facilitate or impede the public's adoption of these applications.Methods: This study objective was pursued using a comprehensive approach. A study model was developed utilizing the Unified Theory of Acceptance and Use of Technology (UTAUT) as its foundation. This model encompasses essential variables including performance expectancy, effort expectancy, social influence, facilitating conditions, price value, and perceived trust. The process of data collecting was carried out by means of a survey that was disseminated across widely used social media channels. The study was conducted using a sample size of 257 participants who are residents of Semarang City. The data that was collected underwent a thorough analysis utilizing the Partial Least Squares - Structural Equation Model (PLS-SEM) approach.Results: The research conducted in our study resulted in several significant findings. The study revealed that several factors, namely performance expectancy, social influence, price value, and perceived trust, had a notable and beneficial impact on users' inclination towards using m-health applications. On the other hand, the variables of effort expectancy and facilitating conditions did not exhibit a statistically significant influence on the level of public interest in these applications. Furthermore, a substantial correlation was found between the behavioral intention and the actual usage behavior of inhabitants of Semarang City in their adoption of m-health applications.Novelty: The research presented in this study is distinguished by its comprehensive analysis of the various factors that impact the adoption of mobile health (m-health) applications in Semarang City. Through the incorporation and expansion of variables such as price value and perceived trust, our study provides a comprehensive and nuanced comprehension of this particular occurrence by adapting and extending the UTAUT model. Our work emphasizes the importance of performance expectancy and social influence, while also suggesting the need for additional investigation into the roles of effort expectancy and facilitating conditions. Additionally, our study offers valuable information regarding the influence of age and gender as moderators in these associations. The results of this study have significant practical implications for healthcare professionals and policymakers who are interested in promoting the use of mobile health (m-health) technologies among the public. Additionally, these findings can serve as a valuable guide for future research endeavors in this particular area of study. 

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