JUITA : Jurnal Informatika
UITA: Jurnal Informatika is a science journal and informatics field application that presents articles on thoughts and research of the latest developments. JUITA is a journal peer reviewed and open access. JUITA is published by the Informatics Engineering Study Program, Universitas Muhammadiyah Purwokerto. JUITA invites researchers, lecturers, and practitioners worldwide to exchange and advance knowledge in the field of Informatics. Documents submitted must be in Ms format. Word and written according to author guideline. JUITA is published twice a year in May and November. Currently, JUITA has been indexed by Google Scholar, IPI, DOAJ, and has been accredited by SINTA rank 2 through the Decree of the Director-General of Research and Development Strengthening of the Ministry of Research, Technology and Higher Education No. 36/E/KPT/2019. JUITA is intended as a media for informatics research among academics, practitioners, and society in general. JUITA covers the following topics of informatics research: Software engineering Artificial Intelligence Data Mining Computer network Multimedia Management Information System Digital forensics Game
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<![CDATA[Voting Scheme Nearest Neighbors by Difference Distance Metrics Measurement ]]>
<![CDATA[Gede Angga Pradipta]]>;
<![CDATA[Made Liandana]]>;
<![CDATA[Putu Desiana Wulaning Ayu]]>;
<![CDATA[Dandy Pramana Hostiadi]]>;
<![CDATA[Putu Sumardika Eka Putra]]>
<![CDATA[ JUITA: Jurnal Informatika JUITA Vol. 11 No. 2, November 2023 ]]>
Publisher : <![CDATA[Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto ]]>
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DOI: 10.30595/juita.v11i2.19298
<![CDATA[K-Nearest Neighbor (KNN) is a widely used method for both classification and regression cases. This algorithm, known for its simplicity and effectiveness, relies primarily on the Euclidean formula for distance metrics. Therefore, this study aimed to develop a voting model where observations were made using different distance calculation formulas. The nearest neighbors algorithm was divided based on differences in distance measurements, with each resulting model contributing a vote to determine the final class. Consequently, three methods were proposed, namely k-nearest neighbors (KNN), Local Mean-based KNN, and Distance-Weighted neighbor (DWKNN), with an inclusion of a voting scheme. The robustness of these models was tested using umbilical cord data characterized by imbalance and small dataset size. The results showed that the proposed voting model for nearest neighbors consistently improved performance by an average of 1-2% across accuracy, precision, recall, and F1 score when compared to the conventional non-voting method.]]>
<![CDATA[Comparison of Data Mining Classification Algorithms for Stroke Disease Prediction Using the SMOTE Upsampling Method ]]>
<![CDATA[Ronald Sebastian]]>;
<![CDATA[Christina Juliane]]>
<![CDATA[ JUITA: Jurnal Informatika JUITA Vol. 11 No. 2, November 2023 ]]>
Publisher : <![CDATA[Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto ]]>
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DOI: 10.30595/juita.v11i2.17348
<![CDATA[Stroke is a circulation disorder in the brain that can cause symptoms and signs related to the affected part of the brain and is the leading cause of death and disability in Indonesia. Everyone is at risk of experiencing a stroke, and it is important to recognize and manage risk factors. Data Mining techniques can help in the extraction and prediction of information, as well as finding hidden patterns in stroke medical data. The dataset used in this research comes from Kaggle and is imbalanced, so the SMOTE Upsampling technique is used to address this imbalance issue. The results of the study conclude that the use of SMOTE technique in the C4.5, NB, and KNN algorithms can increase precision, recall, and AUC. The C4.5 algorithm and SMOTE technique as the best performing algorithm were selected for testing new data, and the results show that the model created can predict stroke risk more accurately than the C4.5 model without SMOTE. However, it should be noted that based on the author's interview with one of the medical practitioners, the model cannot be directly used in medical practice because the observations in the medical field to determine factors related to stroke are highly complex. Thus, a new understanding revealed that predicting stroke in a practical setting is highly complex. While data mining can be used as a predictive tool in the initial stage for predictions in the general population, it is strongly recommended to undergo direct examination by doctors in a hospital to obtain more accurate and comprehensive medical evaluations.]]>
<![CDATA[Sentiment Analysis of Student Comment on the College Performance Evaluation Questionnaire Using Naïve Bayes and IndoBERT ]]>
<![CDATA[Wiga Maulana Baihaqi]]>;
<![CDATA[Arif Munandar]]>
<![CDATA[ JUITA: Jurnal Informatika JUITA Vol. 11 No. 2, November 2023 ]]>
Publisher : <![CDATA[Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto ]]>
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DOI: 10.30595/juita.v11i2.17336
<![CDATA[The development of the Internet has played a significant role in various aspects of life and has generated vast amounts of data, including student comments about universities. The challenge in analyzing comment data is the large number of students providing feedback, which makes manual analysis impractical. The purpose of this study is to analyze the performance evaluation of universities by students in terms of positive and negative sentiments, with the aim of assessing the level of student satisfaction with all elements and areas of university operations. This research utilized the Naïve Bayes algorithm and the IndoBERT model to build a classification model based on questionnaire data, starting from the data collection process, data preprocessing, feature extraction, modeling, and evaluation. The results of the IndoBERT model demonstrated the best performance, with an accuracy of 85%. The IndoBERT model effectively recognizes sentiments in text, distinguishing between positive and negative comments regarding university performance.]]>
<![CDATA[Multiplayer Game Guessing Sunda’s Proverb Using Socket.Io And Node.Js ]]>
<![CDATA[Leni Fitriani]]>;
<![CDATA[Dewi Tresnawati]]>;
<![CDATA[M. Iqbal Ismail Safei Pamungkas]]>
<![CDATA[ JUITA: Jurnal Informatika JUITA Vol. 11 No. 2, November 2023 ]]>
Publisher : <![CDATA[Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto ]]>
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DOI: 10.30595/juita.v11i2.16828
<![CDATA[Game development is currently quite rapid. Now games can be played by various groups, because many games now contain not just games, but there are also games with educational content. The educational game that will be made in this study is a website-based Sundanese proverb game, this type of game will be multiplayer so that players can compete with other players. The purpose of this research is to make a Sundanese proverb educational multiplayer game that can be played simultaneously with many players, so that it can introduce the regional language, namely Sundanese, to the wider community. The technology used in making this game is Socket.IO and Node.JS, using these technologies can make end users interact in real time. In making this game using the Game Development Life Cycle (GDLC) methodology with the stages of initialization, pre-production, production, testing, beta and release. The results obtained in this research are website-based Sundanese proverb educational games that can be used without taking up much space on the device.]]>
<![CDATA[Analysis of the Impact of Vectorization Methods on Machine Learning-Based Sentiment Analysis of Tweets Regarding Readiness for Offline Learning ]]>
<![CDATA[Yesi Novaria Kunang]]>;
<![CDATA[Widya Putri Mentari]]>
<![CDATA[ JUITA: Jurnal Informatika JUITA Vol. 11 No. 2, November 2023 ]]>
Publisher : <![CDATA[Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto ]]>
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DOI: 10.30595/juita.v11i2.17568
<![CDATA[Twitter users use social media to express emotions about something, whether it is criticism or praise. Analyzing the opinions or sentiments in the tweets that Twitter users send can identify their emotions for a particular topic. This study aims to determine the impact of vectorization methods on public sentiment analysis regarding the readiness for offline learning in Indonesia during the Covid-19 pandemic. The authors labeled sentiment using two different approaches: manually and automatically using the NLP TextBlob library. We compared the vectorization method used by employing count vectorization, TF-IDF, and a combination of both. The feature vectors were then classified using three classification methods: naïve Bayes, logistic regression, and k-nearest neighbor, for both manual and automatic labeling. To assess the performance of sentiment analysis models, we used accuracy, precision, recall, and F1-score for performance metrics. The best results showed that the Logistic regression classifier with the feature extraction technique that combines count vectorization and TF-IDF provided the best performance for both data with manual and automatic labeling.]]>
<![CDATA[Digital Twin and Blockchain Extension in Smart Buildings Platform as Cyber-Physical Systems ]]>
<![CDATA[Oktafian Sultan Hakim]]>;
<![CDATA[Muhammad Agus Zainuddin]]>;
<![CDATA[Sritrusta Sukaridhoto]]>;
<![CDATA[Agus Prayudi]]>
<![CDATA[ JUITA: Jurnal Informatika JUITA Vol. 11 No. 2, November 2023 ]]>
Publisher : <![CDATA[Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto ]]>
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DOI: 10.30595/juita.v11i2.18704
<![CDATA[Cyber-physical systems is integrated computation with the physical world. CPS increasing in a wide range of applications, from smart homes to smart buildings. Digital twins are promising way to solve challenges with combination of CPS, 3D technology, and IoT. The system provides users with immersive interfaces to control and interact with devices within the smart building environment. Blockchain was chosen to secure user data using cryptographic algorithms and ensure data protection against manipulation, spying, and theft. Average load testing data for digital twin platform implemented in smart buildings range from 1 to 11 floors. The results reveal a gradual increase in average test times as the buildings' size and complexity grow, with the following values: 5.663s for 1 floor until 11 floors 7.294s. The data obtained from of the blockchain test using Hyperledger Besu provide essential insights into the system's performance with several bandwidth that used in the system. Average time for each test trial ranged from 1.066 seconds to 2.006 seconds, showing slight variations based on the bandwidth used. However, transactions per second (TPS) values were relatively fast, ranging from 1.066 tps to 0.499 tps with positive aspect of the retention rate for all trials was 100% success.]]>
<![CDATA[Application of the Minkowski Distance Similarity Method in Case-Based Reasoning for Stroke Diagnosis ]]>
<![CDATA[Angelina Rumuy]]>;
<![CDATA[Rosa Delima]]>;
<![CDATA[Kuncoro Probo Saputra]]>;
<![CDATA[Joko Purwadi]]>
<![CDATA[ JUITA: Jurnal Informatika JUITA Vol. 11 No. 2, November 2023 ]]>
Publisher : <![CDATA[Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto ]]>
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DOI: 10.30595/juita.v11i2.18582
<![CDATA[A Stroke is a cerebrovascular disease characterized by impaired brain function due to damage or death of brain tissue caused by reduced or blocked blood and oxygen flow to the brain. Expert systems can be used as learning aids for medical students to diagnose stroke. Medical records of stroke cases can be reused as a reference for diagnosing stroke when there are new cases, known as the case-based reasoning (CBR) method. This study implements the Minkowski distance similarity method in CBR to calculate the similarity value between cases, where each similar case has the same solution. This study uses the Minkowski distance similarity method in CBR to obtain the most optimal value of r and the most appropriate threshold value in the expert system for stroke diagnosis. The diagnosis process is carried out by inputting the patient's condition, symptoms, and risk factors. Then the system will calculate the similarity value and take the case with the highest similarity value as the solution, providing that the similarity value must be greater than or equal to the threshold value. Based on system testing, the best accuracy value was achieved by applying a threshold value of 75 with an r value of 3 or 4, with an accuracy rate of 88,89%, a recall value of 88%, and a precision of 100%.]]>
<![CDATA[Leaderboard Application as A Ranking Media for Internet Users ]]>
<![CDATA[Hariadi Yutanto]]>;
<![CDATA[Gaguk Suprianto]]>;
<![CDATA[Yusuf Effendi]]>
<![CDATA[ JUITA: Jurnal Informatika JUITA Vol. 11 No. 2, November 2023 ]]>
Publisher : <![CDATA[Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto ]]>
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DOI: 10.30595/juita.v11i2.17094
<![CDATA[The technology of utilizing hotspot networks has developed quite rapidly. In its development, internet technology uses a more flexible Mikrotik hotspot because it provides convenience for administrators and users. The object of this study is the hotspot network of Hayam Wuruk University (UHW) Perbanas. The goal is to develop a leaderboard design as a medium for monitoring internet use through the UHW Perbanas hotspot. Its application is through the integration of mikrotik with the web service API as a ranking of internet users against three categories of activities, namely downloads, uploads and internet usage times on each day and month. Each of these categories has 20 users. The test method uses a black box. Hasil testing states that the system is successfully operating, so that it can be implemented in the context of decision making by the management of UHW Perbanas.]]>
<![CDATA[Implementation of RESHOT Method to Create a Good User Experience in an Application ]]>
<![CDATA[Ridwan Ahmad Ma'arif]]>;
<![CDATA[Fauziah Fauziah]]>
<![CDATA[ JUITA: Jurnal Informatika JUITA Vol. 11 No. 2, November 2023 ]]>
Publisher : <![CDATA[Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto ]]>
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DOI: 10.30595/juita.v11i2.17643
<![CDATA[In recent years User Experience (UX) has become something that must be implemented in making applications. Every application design practitioner has applied this discipline, but often they wonder how to simplify a user's journey flow by using applications and make it easier, faster, and simpler. This research aims to explain a method that can simplify the User Experience comprehensively. RESHOT is used (Refine the challenge, Remove, Shrink, Hide, Organize, Time). This method will make applications pay more attention to aspects that can increase user satisfaction. As a result, this study contributes to an explanation of simplifying the flow of uploading donor data files using the RESHOT method in the X blood donor data collection application. The results of streamlining the flow of uploading donor data files have been tested on five respondents and have a 100% user success rate in completing tasks with an average processing time of 14.5 seconds. In testing, there is a misclick rate of 10.7%. This is because the user wants to explore the designed application. And this is also a limitation of this study, namely not making the overall application design interaction.]]>
<![CDATA[Modified of Single Deepest Vertical Detection (SDVD) Algorithm for Amniotic Fluid Volume Classification ]]>
<![CDATA[Putu Desiana Wulaning Ayu]]>;
<![CDATA[Gede Angga Pradipta]]>;
<![CDATA[Roy Rudolf Huizen]]>;
<![CDATA[Kadek Eka Sapta W]]>;
<![CDATA[I Gede Edy Artana]]>
<![CDATA[ JUITA: Jurnal Informatika JUITA Vol. 11 No. 2, November 2023 ]]>
Publisher : <![CDATA[Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto ]]>
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DOI: 10.30595/juita.v11i2.18435
<![CDATA[Amniotic fluid a crucial role in ensuring the well-being of the fetus during pregnancy and is contained within the amnion cavity, which is surrounded by a membrane. Several studies have shown that volume of amniotic fluid can vary throughout pregnancy and is closely linked to the health and safety of the fetus. This indicates that it is essential to perform accurate measurement and identification of its volume. Obstetric specialist often use a manual method to identify amniotic fluid by visually determining the longest straight vertical line between the upper and lower boundaries. Therefore, this study aims to develop detection model, known as modified Single Deepest Vertical Detection (SDVD) algorithm to automatically measure the longest vertical line by following medical rules and regulations. SDVD algorithm was designed to measure the depth of amniotic fluid vertically by searching the column of pixels that comprised the image sample, excluding any intersection with the fetal body. Performance testing was carried out using 130 images by comparing the manual measurement results obtained by obstetric specialists and the proposed model. Based on the experimental results using modified SDVD, the average accuracy, precision, and recall achieved for amniotic fluid classification were 92.63%, 85.23%, and 95.6%, respectively.]]>
