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JUITA : Jurnal Informatika
Published by Universitas Muhammadiyah Purwokerto
ISSN : 20869398     EISSN : 25798901     DOI : 10.30595/JUITA
Core Subject : Science,
Computer Science & IT
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
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 316 Documents
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Selection of TikTok Content Based on User Engagement Criteria Using the Analytic Hierarchy Process Citra Wiguna; Sri Mulyana; Retantyo Wardoyo
JUITA: Jurnal Informatika JUITA Vol. 11 No. 1, May 2023
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v11i1.16314

Abstract

Indonesia has 106.9 million active TikTok users aged 18 and above. TikTok is designed for engagement in many ways, as it actively encourages two-way communication and eye-catching content. Uploaded content must have its uniqueness variable. In increasing the engagement of a TikTok account, criteria are chosen based on the COBRA concept (consuming, contributing, and creating) and alternatives based on social media content trends in Indonesia (tutorial, educational, a day in my life, behind the scene dan tips and trick). This research was conducted by implementing the Analytic Hierarchy Process (AHP) method to select the content that must be prioritized to get engagement from the wider community. From the data processing results obtained, tutorial content is the best content in increasing engagement results, especially TikTok. Content that has the lowest engagement is behind the scene content. Further research can be carried out through a group decision support system with various related experts. It can also be combined with the BORDA, TOPSIS, and Profile Matching methods to optimize ranking results.
Monitoring the Performance of Lecturers Using Behaviorally Anchor Rating Scale and Management by Objectives Method Muhammad Sabiq Dzakwan; Sunardi Sunardi; Anton Yudhana
JUITA: Jurnal Informatika JUITA Vol. 11 No. 1, May 2023
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v11i1.15354

Abstract

Mutiara Mahakam Samarinda Institute of Health Sciences (STIKES-MM Samarinda) has a system for monitoring and evaluating the performance of lecturers or education staff. This system measures performance achievements in terms of teaching, research, and community service. . Nevertheless, since every segment of the system is not yet fully computerized, this then raises several obstacles in the process of monitoring and evaluating the performance, length of time to obtain the final assessment results and the low accuracy level of the assessment. This study aims to seeks solutions to these obstacles and offers an educator performance monitoring system that combines the Behaviorally Anchor Rating Scale (BARS) and Management by Objectives (MBO) methods to be assessed quantitatively based on the rating scores in measuring the two methods. The BARS method was focused on evaluating behaviour that would affect overall performance with an average score of 4.14%, while the MBO method was focused on evaluating according to Tri Dharma of higher education, namely teaching, research and community service.  The assessment system was then implemented to evaluate the performance of lecturers and education staff. Subsequently, the data obtained were analyzed to get the final result of the assessment. In particular for data from the MBO method, the analysis was carried out using step with and without KRA. This exploratory research succeeded in presenting the final results of the performance assessment of each lecturer who was assessed for both the value of the BARS and MBO methods. Data analysis from the MBO method ,  when calculated with and without KRA and KRA, showed some significant differences in MBO. For all lecturers, the difference in scores, if the average was 3.48%, then this assessment was more inclined to the BARS assessment, which had a better rating than MBO.
Information System Strategic Planning at Institut Agama Islam Negeri Ternate Sudarman Sudarman; Asmarani Pratama Y. Hadad; Abd. Haris Abbas
JUITA: Jurnal Informatika JUITA Vol. 11 No. 1, May 2023
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v11i1.15506

Abstract

Institut Agama Islam Ternate (IAIN) is one of the universities that run business processes in terms of educational services. IAIN Ternate has implemented information systems and information technology (IS/IT) to support its business processes. However, the implementation of IS/IT has not been equipped with strategic planning, so all forms of procurement, development, and maintenance of IS/IT are only available upon request and are not yet aligned with the organization's strategic plan. This research was conducted to design organizational needs into an IS/IT strategic plan at IAIN Ternate using the Ward and Peppard Framework. This research was conducted using interviews and focus group discussions (FGD) with the leaders and staff of the units at IAIN Ternate. The tools used for the analysis of the organization's internal environment are SWOT and value chain; for the analysis of the organization's external environment, PESTLE and McFarlan Grid are used to map the application portfolio. Based on the results of the study, IAIN Ternate has utilized IS and IT. To achieve the vision, mission, and objectives of IAIN Ternate, it is recommended that IS/IT become a priority for development. The IT Strategic Plan consists of an IS strategy, an IT strategy, and an IS/IT management strategy.
The Automatic Classification System for Academic Performance Evaluation at the Faculty of Information Technology Atma Jaya University of Makassar Erick Alfons Lisangan; Dwi Marisa Midyanti; Chairul Mukmin; Astrid Lestari Tungadi
JUITA: Jurnal Informatika JUITA Vol. 11 No. 1, May 2023
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v11i1.14116

Abstract

Abstract - The Faculty of Information Technology currently carries out performance evaluations at the end of each semester and involves students as sources of data evaluation. The evaluation activity took place online on the website ss.fti.uajm.ac.id. With the number of active students, the number of evaluations that need to be read and the number read by faculty stakeholders also increases. This is inversely proportional to the time that stakeholders need time to read, evaluate, and categorize comments entered by students as part of the performance evaluation. In this study, a multi-classification of student comments related to evaluations at the Faculty of Information Technology UAJM will be carried out. Text pre-processing will use the Sastrawi library which includes stopword removal, stemming, and transformation of text into TFIDF form. The results of the pre-processing text will be used as input on Naive Bayes and using three scenarios to evaluate the classifier model. The average accuracy values of the Naive Bayes algorithm for category and sentiment labels are 79% and 81%, respectively. Furthermore, the expected result of this research is to reduce the time for FTI UAJM stakeholders to read and comment/suggest faster because the evaluation results are obtained in real-time.
Decision Support System for Suitability of Horticultural Agricultural Plant Types with Land Conditions Using Interpolation Profile Matching Petrus Wolo; Sri Mulyana; Retantyo Wardoyo
JUITA: Jurnal Informatika JUITA Vol. 11 No. 1, May 2023
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v11i1.16546

Abstract

Horticultural crops are the most produced by farmers in the Napugera Village area because they are more profitable to cultivate because they are short in life and from an economic point of view they are obtained faster. However, has often experienced obstacles, one of which is determining the suitability of agricultural land for horticultural crops.  Determining the selection of horticultural crops for the types of red onion, red red chili, and tomato crops on a field based on land conditions is very necessary for farmers in the Napugera Village area as a support for decision-making. There are 8 criteria assessed including temperature, rainfall, air humidity, soil type, soil texture, soil ph, land slope and topography. In this study, a profile-matching interpolation method was developed for a decision-making system that can be used as a tool in providing decisions on plants that are suitable for planting in a field easily, quickly, and accurately. The profile-matching interpolation method is one of the methods of scoring data. The results showed that the type of onion horticultural crop with a final value of 3,764 is suitable for cultivation in the Napugera Village area.
Artificial Intelligent for Human Emotion Detection with the Mel-Frequency Cepstral Coefficient (MFCC) Anita Ahmad Kasim; Muhammad Bakri; Irwan Mahmudi; Rahmawati Rahmawati; Zulnabil Zulnabil
JUITA: Jurnal Informatika JUITA Vol. 11 No. 1, May 2023
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v11i1.15435

Abstract

Emotions are an important aspect of human communication. Expression of human emotions can be identified through sound. The development of voice detection or speech recognition is a technology that has developed rapidly to help improve human-machine interaction. This study aims to classify emotions through the detection of human voices. One of the most frequently used methods for sound detection is the Mel-Frequency Cepstrum Coefficient (MFCC) where sound waves are converted into several types of representation. Mel-frequency cepstral coefficients (MFCCs) are the coefficients that collectively represent the short-term power spectrum of a sound, based on a linear cosine transform of a log power spectrum on a nonlinear mel scale of frequency. The primary data used in this research is the data recorded by the author. The secondary data used is data from the "Berlin Database of Emotional Speech" in the amount of 500 voice recording data. The use of MFCC can extract implied information from the human voice, especially to recognize the feelings experienced by humans when pronouncing the sound. In this study, the highest accuracy was obtained when training with epochs of 10000 times, which was 85% accuracy.
Voting Scheme Nearest Neighbors by Difference Distance Metrics Measurement Gede Angga Pradipta; Made Liandana; Putu Desiana Wulaning Ayu; Dandy Pramana Hostiadi; Putu Sumardika Eka Putra
JUITA: Jurnal Informatika JUITA Vol. 11 No. 2, November 2023
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v11i2.19298

Abstract

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.
Comparison of Data Mining Classification Algorithms for Stroke Disease Prediction Using the SMOTE Upsampling Method Ronald Sebastian; Christina Juliane
JUITA: Jurnal Informatika JUITA Vol. 11 No. 2, November 2023
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v11i2.17348

Abstract

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.
Sentiment Analysis of Student Comment on the College Performance Evaluation Questionnaire Using Naïve Bayes and IndoBERT Wiga Maulana Baihaqi; Arif Munandar
JUITA: Jurnal Informatika JUITA Vol. 11 No. 2, November 2023
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v11i2.17336

Abstract

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.
Multiplayer Game Guessing Sunda’s Proverb Using Socket.Io And Node.Js Leni Fitriani; Dewi Tresnawati; M. Iqbal Ismail Safei Pamungkas
JUITA: Jurnal Informatika JUITA Vol. 11 No. 2, November 2023
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v11i2.16828

Abstract

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.

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