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Transaction on Informatics and Data Science
Published by Universitas Islam Negeri Profesor Kiai Haji Saifuddin Zuhri Purwokerto
ISSN : -     EISSN : 30641772     DOI : https://doi.org/10.24090/tids
Core Subject : Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Engineering
Transactions on Informatics and Data Science (TIDS), with ISSN: 3064-1772 (online), is a scientific journal that publishes the latest research in the fields of informatics and data science, focusing on both theoretical advances and practical applications. Published by the Department of Informatics, Universitas Islam Negeri Prof. K.H. Saifuddin Zuhri Purwokerto, Purwokerto, this journal serves as a platform for researchers, academics, and practitioners to share new ideas and innovations in data science, artificial intelligence, natural language processing, cloud computing, and information technology applications across various domains. It promotes collaboration and deep knowledge exchange within the scientific community, bridging the gap between theory and practice in the rapidly evolving fields of informatics and data science. Aims Transaction on Informatics and Data Science aims to advance the frontiers of informatics and data science knowledge by publishing high-quality research that encompasses theoretical advancements and practical applications. The journal seeks to contribute significantly to the understanding and developing of innovative approaches, methodologies, and technologies in these domains. Scopes The scope of "Transaction on Informatics and Data Science" covers a wide range of topics related to informatics and data science, including but not limited to: - Data analysis and mining - Artificial intelligence and machine learning - Natural language processing and understanding - Cloud computing and big data technologies - Information retrieval and knowledge management - Data-driven decision-making and predictive modelling - Internet of Things (IoT) and data analytics - Cybersecurity and privacy in data science - Informatics and data science applications in various healthcare, finance, education, and other domains. The journal welcomes original research articles, reviews, case studies, and technical notes that contribute significantly to advancing knowledge and practice in informatics and data science. Submissions should demonstrate novelty, tightness, and relevance to the rapidly evolving landscape of information technology and data-driven decision-making processes.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 5 Documents
 1 
Search results for , issue "Vol. 1 No. 2 (2024)" : 5 Documents clear
Monitoring Application for Student Activity Units Administration Data of Nurul Jadid University Based on Android Syafiih, M; Nadiyah; Khairi, Matlubul
Transactions on Informatics and Data Science Vol. 1 No. 2 (2024)
Publisher : Department of Informatics, Faculty of Da'wah, UIN Saizu Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24090/tids.v1i2.12233

Abstract

Nurul Jadid University (UNUJA) at Probolinggo, Indonesia, is one of the universities located in Karanganyar, Paiton District, Probolinggo Regency, which is based in Pesantren, as a place for students who want to gain knowledge not only in the religious field- but also technology and health. Administrative data monitoring activities from 17 Student Activity Units owned by Nurul Jadid University are still run manually or face-to-face directly between the student affairs section and the head of the student affairs section starts monitoring from submission of decision letters, budgets, work programs, proposals, and activity reports of each student activity units. Several problems arise in this way; the busyness of students with a tight lecture schedule causes a slow process of depositing files and others, impacting the predetermined time- Therefore, an application is needed to monitor administrative data at Nurul Jadid University. The RAD method was chosen in this study to achieve the expected goals. An Android-based student activity unit (SAU) of Nurul Jadid University of administration data monitoring application has been produced.
Prediction of Customer Switching Using Support Vector Machine Method Tholib, Abu; Sholeha, Selfia Hafidatus; Aini, Qurrotu
Transactions on Informatics and Data Science Vol. 1 No. 2 (2024)
Publisher : Department of Informatics, Faculty of Da'wah, UIN Saizu Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24090/tids.v1i2.12277

Abstract

Several studies on predicting customer switching focus on the telecommunications industry and online stores. This research aims to predict customer switching to get the best results; customers are the most critical mass; some companies must provide satisfying services so customer flow decreases. The support vector machine (SVM) method uses machine learning to find a hyperplane based on the SRM principle. A hyperplane is a decision boundary that helps classify data points. SVM stands out for its ability to take input data and make predictions based on its characteristics. This study uses data from Kaggle, structured it, cleaned it, identified patterns and inconsistencies (such as skewness, outliers, and missing values), and built and validated hypotheses. From the data processing, the plot shows the imbalance of data classes between churners and non-churners. This research applies several models where the most significant or best performance value is in the SVM model of 0.7996. The Neural Network model can be trained with better patterns to detect data and achieve high accuracy.
Analysis of Tahfidz Program Entrance Examination Using C4.5 Method for Classification of Learning Groups in The Al-Mawaddah Region of Nurul Jadid Islamic Boarding School, Probolinggo, Indonesia Sya'roni, Wahab; Devi, Yulia Sri; Ilmansyah, Yanuar
Transactions on Informatics and Data Science Vol. 1 No. 2 (2024)
Publisher : Department of Informatics, Faculty of Da'wah, UIN Saizu Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24090/tids.v1i2.12278

Abstract

The tahfidz program aims to improve understanding and memorization of the Al-Quran in the Al-Mawaddah Region, Probolinggo, Indonesia, including those who organize the Tahfid Qur'an program. This research aims to increase the efficiency and accuracy of analyzing the Tahfid program entrance test results using the C4.5 Algorithm for study group classification and visualizing the results through a web-based interactive application using Streamlit. The C4.5 algorithm is used to build a classification model based on the results of the entrance test criteria. The application of Streamlit as a framework for creating interactive web applications makes it easier for users to enter entrance test data and study group classification results, making it easier to make decisions and plan to learn for Tahfid program administrators. The research results show that the use of the C4.5 Algorithm method and the streamlit application is practical in analyzing the results of the Tahfidz program entrance test and determining study groups, the C4.5 Algorithm succeeded in achieving a high level of accuracy with an accuracy of 94%, then it was implemented using streamlit. With the interactive application, tahfid program managers can carry out the selection and grouping process more quickly and precisely and provide a more targeted learning approach according to the student's ability level.
Implementation of Simple Additive Weighting Method for Biomass Selection in IoT-Based Smart Stove Tijaniyah
Transactions on Informatics and Data Science Vol. 1 No. 2 (2024)
Publisher : Department of Informatics, Faculty of Da'wah, UIN Saizu Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24090/tids.v1i2.12280

Abstract

Technology is now needed most in everyday society. Many things have changed to become modern and sophisticated because of the role of technology. It helps with cooking food or drinks at home. The stove is one of the most critical components in the kitchen. A furnace can help cook food or beverages. The use of gas stoves is cost-intensive. Liquid petroleum gas (LPG) is a stove fuel often used by people for cooking. As cooking demands increase, gas consumption increases, causing gas expenses to become more and more costly. We make an intelligent or innovative stove with advantages. This smart stove is medium and portable so that it can be taken anywhere; besides that, this tool uses a supercapacitor to store the electric voltage generated in the heat of biomass combustion; this tool can generate electricity from biomass and solar cells. The selection of biomass types using the Simple Additive Weighting (SAW) method, namely wood or waste. The Internet of Things (IoT) is an information medium for the innovative stove process. In addition to cooking, this tool can turn on 1 LED lamp measuring 5-10 watts as a cellphone charger with as much as 5 volts or 60 minutes of charge time. The advantages of this intelligent stove are that it is beneficial to the community to reduce gas prices.
Validation of New Student Registration Documents at Nurul Jadid University Using Convolutional Neural Network Fajri, Fathorazi Nur; Pratamasunu, Gulpi Qorik Oktagalu; Malik, Kamil
Transactions on Informatics and Data Science Vol. 1 No. 2 (2024)
Publisher : Department of Informatics, Faculty of Da'wah, UIN Saizu Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24090/tids.v1i2.12281

Abstract

Every year, Nurul Jadid University admits new students by registering them using the website. Each prospective new student can fill in data independently and upload documents such as Deeds, Family Register, Identity Cards, Diplomas, and SKHU. Often, prospective new students need clarification in uploading documents; for example, the place for uploading ID cards is filled with uploading diplomas and vice versa. It causes the uploaded data not to match the place or group. Today, no document validation technique can match these types of documents. Therefore, a way is needed to overcome this problem. One way to recognize the document type is by its visual form or image. There are several methods for identifying an image, namely deep learning and neural network models. Where the convolutional neural network is known to be fast in processing data in images, this research aims to validate documents on new student registration data with a deep learning method, namely convolutional neural network (CNN). The experimental results show that the proposed method can classify the Nurul Jadid University new student registration documents with an accuracy rate of 0.91, such as the birth certificate at 0.97, diploma documents at 0.88, Family card documents at 0.88, identity cards at 0.84, exam result certificate with an accuracy 0.94.

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