cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Edi Sutoyo
Contact Email
journalijadis@gmail.com
Phone
+62895410194922
Journal Mail Official
info@ijadis.org
Editorial Address
Indonesian Scientific Journal (Jurnal Ilmiah Indonesia) Jl. Pasar Atas No 3, Kompleks Setramas Kota Cimahi, Bandung
Location
Unknown,
Unknown
INDONESIA
International Journal of Advances in Data and Information Systems
Published by Indonesian Scientific Journal
ISSN : -     EISSN : 27213056     DOI : https://doi.org/10.25008/ijadis
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal of Advances in Data and Information Systems (IJADIS) (e-ISSN: 2721-3056) is a peer-reviewed journal in the field of data science and information system that is published twice a year; scheduled in April and October. The journal is published for those who wish to share information about their research and innovations and for those who want to know the latest results in the field of Data Science and Information System. The Journal is published by the Indonesian Scientific Journal. Accepted paper will be available online (free access), and there will be no publication fee. The author will get their own personal copy of the paperwork. IJADIS welcomes all topics that are relevant to data science, and information system. The listed topics of interest are as follows: Data clustering and classifications Statistical model in data science Artificial intelligence and machine learning in data science Data visualization Data mining Data intelligence Business intelligence and data warehousing Cloud computing for Big Data Data processing and analytics in IoT Tools and applications in data science Vision and future directions of data science Computational Linguistics Text Classification Language resources Information retrieval Information extraction Information security Machine translation Sentiment analysis Semantics Summarization Speech processing Mathematical linguistics NLP applications Information Science Cryptography and steganography Digital Forensic Social media and social network Crowdsourcing Computational intelligence Collective intelligence Graph theory and computation Network science Modeling and simulation Parallel and distributed computing High-performance computing Information architecture
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 168 Documents
 3   4   5   6   7 
Developing an Augmented Reality Application as Instruction Media to Help in Learning the Solar System Muhammad Sholeh; Erfanti Fatkhiyah; Heru Aprianto
International Journal of Advances in Data and Information Systems Vol. 4 No. 1 (2023): April 2023 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i2.1264

Abstract

This study aimed to develop an application to help in learning the solar system using Augmented Reality (AR) technology. In an era where technology is very developed, learning about the solar system can be made more interactive by providing 3D illustrations to the students. One of the technologies that can be applied to support the development of educational applications to help in learning about the solar system is AR technology. It can create 3D illustrations. The study is the Research and Development (R&D). The research produced an AR-based solar system introduction application. This application can be used as a learning media for students. The developed AR application was tested using alpha and beta testing. The alpha testing was the marker accuracy testing and black-box testing, while the beta testing was done by distributing questionnaires to 30 respondents and then doing validity and reliability test. This study produced an AR application to help in learning the solar system. The black-box testing showed that the AR application generally was functioning well. The marker accuracy testing showed that the AR camera succeeded in scanning markers up to 25% of the marker area. The data obtained from distributing questionnaires were processed to know the validity in terms of attractiveness and effectiveness, and the results showed the data was valid. Moreover, the reliability testing was carried out with Cronbach's alpha, and the result was 0.771 for the attractiveness aspect and 0.742 for the effectiveness aspect. These values mean that most beta testers agree that the AR application was attractive and effective.
Prediction of Service Level Agreement Time of Delivery of Goods and Documents at PT Pos Indonesia Using the Random Forest Method Muhammad Isa Ansori; Ririen Kusumawati; M. Amin Hariyadi
International Journal of Advances in Data and Information Systems Vol. 4 No. 1 (2023): April 2023 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i2.1281

Abstract

This study aimed to predict the service level agreement travel time for goods and document shipments at PT Pos Indonesia (Persero) from the island of Java to the islands of Kalimantan, Sulawesi, Maluku and Papua. This is very important because of the high competition between the logistics industry which is getting faster and faster. The random forest method was chosen because this method is easy to use and flexible for various kinds of data. The prediction results with Random Forest in this study have a good level of accuracy, namely 83.86% of the average 4 trials. This shows that the Random Forest method is the right choice for managing the existing data model at PT Pos Indonesia.
Aspect-Based Sentiment Analysis of Hotels in Bali on Tripadvisor Using BERT Algorithm Dimas Samodra Bimaputra; Edi Sutoyo
International Journal of Advances in Data and Information Systems Vol. 4 No. 1 (2023): April 2023 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i2.1284

Abstract

The covid pandemic that began in 2020 has caused enormous losses worldwide, including in Indonesia. Human-to-human contact is the source of the transmission of the covid virus, so the government urges people to maintain cleanliness when interacting. Bali is a popular destination for foreign and domestic visitors in Indonesia. Hospitality businesses in Bali unquestionably face a high risk of covid transmission; consequently, changes in hotel business processes are unavoidable; the implementation of new business processes can have a negative effect on business performance. In order to maintain Bali's reputation as the most popular tourist destination in Indonesia, the government must evaluate the performance of several hotel services that have implemented new business processes. The Aspect-Based Sentiment Analysis (ABSA) methodology can be utilized for performance evaluation. One of the finest algorithms for analyzing text, Bidirectional Encoder Representations from Transformer (BERT), is required for sentiment analysis. The data consists of textual customer evaluations of hotels in Bali that have implemented a new protocol or Standard Operational Procedure (SOP), retrieved from the Tripadvisor website. In the form of a number of evaluations of various aspects of the hotel, the research results can assist the government in analyzing the performance of hotels in Bali based on predetermined criteria.
Prediction of Planning Value School Shopping Income Budget with Multiple Linear Regression Cahyani Hana Bestari; Faisal Fajri Rahani
International Journal of Advances in Data and Information Systems Vol. 4 No. 1 (2023): April 2023 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i1.1285

Abstract

The School Expenditure Budget Plan or RAPBS is the pillar of school management for allocating the revenue budget and use of school funds to meet all school needs for one year. However, there are problems that occur in the management of the RAPBS, namely the difficulty of grouping the RAPBS data annually, making it difficult to predict the budget for the coming year. This research was conducted to study and implement the Multiple Linear Regression algorithm in predicting the value of data on income and expenditure budget plans which are a reference in planning future budgets. To support predictions of planned school budgets and income, BUMS data, Aid data, School Program Cost data, Original School Revenue data, Other Sources data, and Total Budget data are used. The prediction system method used consists of the planning stage, the analysis stage, the modeling stage, interface design, and implementation using the PHP and MySQL programming languages for database management and system testing and analysis. The results of testing the data analysis using the multiple linear regression method with SPSS software have a 100% result according to the manual calculations performed.
Web-Based Counseling Skills Evaluation Information System Using Design Science Research Methodology (DSRM) Approach Rangga Gelar Guntara; Muhammad Rizki Nugraha; Muhammad Dzikri Ar Ridlo
International Journal of Advances in Data and Information Systems Vol. 4 No. 2 (2023): October 2023 - International Journal of Advances in Data and Information System
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i2.1288

Abstract

This research presents the development of a web-based counseling skills evaluation information system using the Design Science Research Methodology (DSRM) approach. The DSRM approach was utilized to design and develop an effective and efficient information system that meets the requirements of the counseling profession. The research discusses the six stages of DSRM, which include problem identification, solution design, construction, evaluation, communication, and reflection, and how they were used to develop the system. The evaluation stage involved conducting empirical studies to assess the system's effectiveness in supporting counseling skills evaluation. The article concludes that the DSRM approach was effective in developing a web-based counseling skills evaluation information system that meets the needs of the counseling profession. This web using PHP, MySQL and Youtube API. The testing software using blackbox and beta testing. the final results of the study show the level of success of the system in facilitating the process of assessing and evaluating basic counseling skills.
Optimization of the Random Forest Method Using Principal Component Analysis to Predict House Prices: A Case Study of House Prices in Malang City Emha Ahdan Fahmi Elmuna; Totok Chamidy; Fresy Nugroho
International Journal of Advances in Data and Information Systems Vol. 4 No. 2 (2023): October 2023 - International Journal of Advances in Data and Information System
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i2.1290

Abstract

Investment is an interesting thing, especially property investment. The developer must also be careful in determining the price of the property. It should be noted that every year, both short-term and long-term, property prices increase and rarely go down. In determining the price, it is often also based on the features of the house such as the concept, location, bedrooms, etc. To predict house prices based on their features, the random forest has a good performance for predicting house prices. However, the random forest method has the disadvantage that if you use too many variables, the training process will take longer and feature selection tends to select features that are not informative. One way to reduce features without removing other features is to use Principal Component Analysis. In this research, the method used is Principal Component Analysis (PCA) and Random Forest. From the results of model training, it can be concluded that the use of model evaluation results using PCA has a smaller error rate and more consistent values, with an average of 0.018. While the results of the evaluation without PCA and using only Random Forest have a higher error value with an average of 0.03125. The training time using the PCA model has a faster time, with an average of 7918 milliseconds, while those using only random forest without PCA have an average time of 8975 milliseconds.
Pay Later Risk Management: A Review of FMECA and Potential Customer Prediction Frameworks Through the Application of Machine Learning Arif Furqon Nugraha Adz Zikri; Wiwin Suwarningsih
International Journal of Advances in Data and Information Systems Vol. 4 No. 2 (2023): October 2023 - International Journal of Advances in Data and Information System
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i2.1293

Abstract

The development of technology continues to develop and gradually change the way people buy such as on online shopping sites. The increase in internet use, especially in the use of E Commerce, has given birth to great potential in the market, especially in Indonesia. These changes prompted the birth of various payment methods. One of them is Pay Later. 27% of the 3560 samples decided to use Pay Later with all the conveniences offered. However, the development of Pay Later is not synchronized with good risk management. The use of Pay Later, which is not targeted at the right consumers, causes PT. XYZ suffered losses due to 22.37% of users defaulting on Pay Later installments. The purpose of this study is to reduce Pay Later default users by answering what factors cause consumers to default. To support this study, the authors used FMECA, Cause Effect Diagrams and conducted tests using Machine Learning to improve company efficiency. Through critical matrix analysis, the author gets 3 priority failure modes, Users default, users disappear, and users experience payment delays. In solving the problems in this study, the authors provide recommendations in the form of a new framework in the form of analyzing the best Pay Later offers by analyzing consumer behavior patterns in an E Commerce by utilizing Machine Learning. However, future research will need to be conducted correlation analysis and static testing in testing attribute correlation before testing algorithms when building machine learning models. The authors also suggested comparing using other methods to improve risk management in this study.
Prediction of Apartment Price Considering Socio Economic and Crime Rates Factors in DKI Jakarta David Noorcahya; Achmad Pratama Rifai; Agus Darmawan; Wangi Pandan Sari
International Journal of Advances in Data and Information Systems Vol. 4 No. 2 (2023): October 2023 - International Journal of Advances in Data and Information System
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i2.1294

Abstract

Investing in real estate properties in Indonesia is highly lucrative due to their consistent appreciation in value. Amongst the various property types, apartments are particularly favored for investment in limited land space. However, determining the value of apartments is often subjective and lacks quantitative measures. To address this issue, this study develops prediction models to predict rental prices and asset value based on apartment specifications, socio-economic factors, and crime rates. Machine learning models employed include Random Forest, Decision Tree, and Gradient Boosting Machine. The findings show Gradient Boosting Machine exhibits the highest accuracy in predicting apartment rental and sale prices, achieving R² values of 0.9230 and 0.8460, respectively. The study also highlights the significant influence of socio-economic factors and crime rates on the performance of the models, contributing between 0.09 and 0.22 with an average of 0.14, as indicated by the improved R² values. This study demonstrate that these models can be valuable tools for real estate investors and professionals seeking quantitative measures to determine the value of apartments. By incorporating apartment specifications, socio-economic factors, and crime rates, the models can provide objective insights into the potential rental income and asset value of apartments.
Comparative Analysis of Software Development Lifecycle Methods in Software Development: A Systematic Literature Review Ahmad Febri Diansyah; Muhammad Rusdi Rahman; Rizky Handayani; D. Diffran Nur Cahyo; Ema Utami
International Journal of Advances in Data and Information Systems Vol. 4 No. 2 (2023): October 2023 - International Journal of Advances in Data and Information System
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i2.1295

Abstract

In the last decades, various Software Development Lifecycle (SDLC) models have been developed to meet the different needs and challenges in the software industry. The purpose of this research is to analyze and compare some of the most common SDLC methods. After the selection and evaluation process is complete, a literature review is carried out by collecting articles, books, and other sources related to the SDLC method. Several main SDLC methods were selected for thorough analysis. Waterfall, Agile and Scrum are some of the methods. Important factors such as flexibility, speed of development, ability to adapt to changing requirements, and project risk are evaluated. The results of the analysis show that each SDLC method has strengths and weaknesses, and that they are appropriate for a variety of situations. While Agile and Scrum methods emphasize flexibility and teamwork, the Waterfall method provides greater structure and clarity to plans. This study aims to determine the best process method for software development. This literature review provides an in-depth understanding of the features, strengths, and weaknesses of various existing SDLC methods. With a better understanding of these methods, organizations can choose the SDLC method that best suits their project needs, thereby increasing the efficiency and effectiveness of software development. This research resulted in a process method that is widely used in software development, namely the Agile method.
Hybrid Model Transfer Learning ResNet50 and Support Vector Machine for Face Mask Detection Eko Agus Moh. Iqbal; Ririen Kusumawati; Irwan Budi Santoso
International Journal of Advances in Data and Information Systems Vol. 4 No. 2 (2023): October 2023 - International Journal of Advances in Data and Information System
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i2.1297

Abstract

The Covid-19 virus caused a health crisis in Indonesia. This virus is so deadly that it has caused many fatalities which have caused the whole world including the government to pay major attention to the Covid-19 pandemic. The Indonesian government has issued several policies to prevent the spread of this epidemic, one of which is wearing a mask in public places. One approach that is widely used in the field of computer vision is the Convolutional Neural Network (CNN) transfer learning. In this study, Hybrid Model Transfer Learning ResNet50 and SVM with RGB to HSV preprocessing is presented to detect masks in facial images. This model consists of three process components. The first is preprocessing RGB images to HSV, the second component is for Feature Extraction with ResNet50 and the third is mask classification on face images with Support Vector Machine (SVM). From dataset of 7328 training and testing data were carried out. The first model, without preprocessing the image data with ResNet50, produces an accuracy of 86.52%. The second model, the model with preprocessing converts image data from RGB to HSV with ResNet50 resulting in an accuracy of 99.18%. In the third model, without preprocessing with ResNet50 and SVM which has an accuracy of 90.55%. The fourth model, the model with preprocessing converts image data from RGB to HSV with ResNet50 and SVM resulting in an accuracy of 98.36%.

Page 5 of 17 | Total Record : 168

 3   4   5   6   7 

Filter by Year

2020 2026


Reset
Filter By Issues
All Issue Vol. 7 No. 1 (2026): April 2026 - International Journal of Advances in Data and Information Systems Vol. 6 No. 3 (2025): December 2025 - International Journal of Advances in Data and Information Syste Vol. 6 No. 2 (2025): August 2025 - International Journal of Advances in Data and Information Systems Vol. 6 No. 1 (2025): April 2025 - International Journal of Advances in Data and Information Systems Vol. 5 No. 2 (2024): October 2024 - International Journal of Advances in Data and Information System Vol. 5 No. 1 (2024): April 2024 - International Journal of Advances in Data and Information Systems Vol. 4 No. 2 (2023): October 2023 - International Journal of Advances in Data and Information System Vol. 4 No. 1 (2023): April 2023 - International Journal of Advances in Data and Information Systems Vol. 3 No. 2 (2022): October 2022 - International Journal of Advances in Data and Information System Vol. 3 No. 1 (2022): April 2022 - International Journal of Advances in Data and Information Systems Vol. 2 No. 2 (2021): October 2021 - International Journal of Advances in Data and Information System Vol. 2 No. 1 (2021): April 2021 - International Journal of Advances in Data and Information Systems Vol. 1 No. 2 (2020): October 2020 - International Journal of Advances in Data and Information System Vol. 1 No. 1 (2020): April 2020 - International Journal of Advances in Data and Information Systems More Issue