cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Brian Rakhmat Aji
Contact Email
brianetlab@gmail.com
Phone
-
Journal Mail Official
ijid@uin-suka.ac.id
Editorial Address
-
Location
Kab. sleman,
Daerah istimewa yogyakarta
INDONESIA
IJID (International Journal on Informatics for Development)
Published by Universitas Islam Negeri Sunan Kalijaga Yogyakarta
ISSN : 22527834     EISSN : 25497448     DOI : -
Core Subject : Science,
Computer Science & IT
One important point in the accreditation of higher education study programs is the availability of a journal that holds the results of research of many investigators. Since the year 2012, Informatics Department has English language. Journal called IJID International Journal on Informatics for Development. IJID Issues accommodate a variety of issues, the latest from the world of science and technology. One of the requirements of a quality journal if the journal is said to focus on one area of science and sustainability of IJID. We accept the scientific literature from the readers. And hopefully these journals can be useful for the development of IT in the world. Informatics Department Faculty of Science and Technology State Islamic University Sunan Kalijaga.
Arjuna Subject : -
Articles 265 Documents
 22   23   24   25   26 
A Hybrid Approach of Pearson Correlation and PCA in Feature Selection for Opinion Mining Tri Romadloni, Nova; Kurniawan, Wakhid; Ariyadi, Muhammad Yusuf; Efendi, Burhan
IJID (International Journal on Informatics for Development) Vol. 14 No. 2 (2025): IJID December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2025.5195

Abstract

This study proposes a hybrid feature selection approach that combines Pearson Correlation and Principal Component Analysis (PCA) to improve classification performance in opinion mining tasks. The rapid growth of e-commerce on social media platforms, such as TikTok, has generated a significant volume of user-generated reviews, which are valuable sources of consumer sentiment. However, the high dimensionality of textual data poses challenges in achieving accurate sentiment classification. To address this issue, the proposed method first applies Pearson Correlation to remove irrelevant features with weak correlation to sentiment labels, followed by PCA to reduce dimensionality. The dataset consists of user reviews from the TikTok Seller platform. Experiments using SVM, Naive Bayes, and Random Forest show that the hybrid approach achieves the highest accuracy of 86.2% (SVM and RF), improving over PCA-only by +0.9% and recovering 13.8% accuracy loss for Naive Bayes (from 72.0% to 83.1%). The results demonstrate that integrating correlation- and projection-based methods yields a more compact and effective feature set. This approach is especially suited for opinion mining in noisy, high-dimensional e-commerce data.
Twitter (X) Sentiment Analysis on Monkeypox: A Systematic Literature Review Chamboko, Hazel; Maguraushe, Kudakwashe; Ndlovu, Belinda
IJID (International Journal on Informatics for Development) Vol. 14 No. 2 (2025): IJID December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2025.5196

Abstract

Monkeypox has a risk of growing into a global threat. Understanding public sentiments is crucial for effective emergency responses, as it helps counter misinformation, enhance communication, and improve the retention and application of public health information. This systematic review of literature aims to provide foundations for identifying existing algorithms, commonly used data collection methods, and pre-processing techniques applied to Twitter discussions on Mpox. The review followed the PRISMA guidelines. Relevant literature was retrieved from ScienceDirect, IEEE, PubMed, and Springer databases, resulting in 15 studies that met the inclusion criteria. Most preprocessing methods include stop word removal, lemmatisation, and tokenisation; commonly used data collection methods include Twitter API, Academic API V2, Snscrape, Twint, and Tweepy. Classification of sentiment tended to be hybrid models like CNN-LSTM or transformer-based models such as BERT, which also perform well in dealing with complex linguistic patterns. These recent models, additionally, addressed other very important issues like misinformation detection, irony, and bot-generated content, which earlier models would often fail to tackle. Despite these advancements, much work still needs to be done in improving the accuracy, generalizability, and interpretability of sentiment analysis models in live monitoring of public health.
Early Detection of Diabetic Retinopathy Through Explainable AI Models: A Systematic Review Ngwazi, Tinashe; Ndlovu, Belinda; Maguraushe, Kudakwashe
IJID (International Journal on Informatics for Development) Vol. 14 No. 2 (2025): IJID December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2025.5200

Abstract

Diabetes, if not detected early, can lead to serious complications such as vision loss, known as diabetic retinopathy. Explainable Artificial Intelligence (XAI) can enhance traditional Machine Learning methods, which are not understandable and transparent in diagnostic tasks. This Systematic Literature Review explores data inputs that influence the performance of XAI models in detecting diabetic retinopathy, how XAI techniques can enhance early detection outcomes in diabetic retinopathy, the challenges in implementing these techniques and the ethical implications of using these models in clinical practice. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses approach guided the search in 4 databases, Springer, Science Direct, PubMed and IEEE Xplore. The findings reveal that XAI techniques like Local Interpretable Model-agnostic Explanations (LIME), SHapley Additive exPlanations (SHAP) and Gradient-weighted Class Activation Mapping (GRAD-CAM) offer opportunities like early detection outcomes, integration with existing clinical processes, enhancing trust in AI systems, improving accuracy and personalised treatment. XAI can also facilitate collaboration among clinicians, maintaining fairness in AI systems and supporting adherence to ethical standards. However, research on clinical validation of these models, as well as standardised performance evaluation metrics, is lacking.
LDA Topic Modeling Analysis of Public Discourse on Indonesia’s Free Nutritious Meals Program (MBG) Cici Suhaeni; Mualifah, Laily Nissa Atul; Wijayanto, Hari
IJID (International Journal on Informatics for Development) Vol. 14 No. 1 (2025): IJID June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2025.5211

Abstract

This study investigates public discourse on Indonesia's Free Nutritious Meals (Makan Bergizi Gratis/MBG) program through Latent Dirichlet Allocation (LDA) topic modeling of YouTube comments. Filling a research gap on online public opinion regarding the MBG policy, this study identifies dominant themes and discursive patterns in public perception. A three-topic model, validated through coherence score evaluation and pyLDAvis visualization, reveals key topics: concerns over food prices and distribution, perceived benefits for children and society, and emotionally and politically driven reactions. The findings provide valuable insights into public opinion, while also highlighting challenges in processing Indonesian-language text, such as informal language and noisy data. This study contributes to understanding public perceptions of social policies in digital environments and recommends future research directions, including improved text preprocessing and alternative topic modeling approaches. By shedding light on online public discourse, this research informs policymakers and stakeholders about the effectiveness and potential areas for improvement in the MBG program.
Topology Analysis of iBGP Confederation Case : Indonesia Research and Education Network (IdREN) Lahusen, Irwin Wijaya; Widyawan, Widyawan; Kusumawardani, Sri Suning
IJID (International Journal on Informatics for Development) Vol. 8 No. 1 (2019): IJID June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2019.08104

Abstract

Implementation of the BGP Confederation topology scenario, found a number of new facts that influence the final decision making for BGP network managers. In previous studies it has been mentioned a number of factors that influence QoS from a topology scheme, among others, the number of Sub AS and the number of routers that make up the iBGP topology. In this study, a number of scenarios were developed by giving variants to bandwidth parameters and adding measurement parameters to Lost Datagram in all scenarios. The results obtained are quite significant, affecting QoS and finding a number of new facts related to the effect of using traffic generators. This research was tested on the Indonesia Research and Education Network (IdREN) network using GNS3.
Analyzing the Accuracy of Answer Sheet Data in Paper-based Test Using Decision Tree Suharto, Edy; Widodo, Aris Puji; Suryono, Suryono
IJID (International Journal on Informatics for Development) Vol. 8 No. 1 (2019): IJID June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2019.08101

Abstract

In education quality assurance, the accuracy of test data is crucial. However, there is still a problem regarding to the possibility of incorrect data filled by test taker during paper-based test. On the contrary, this problem does not appear in computer-based test. In this study, a method was proposed in order to analyze the accuracy of answer sheet filling out in paper-based test using data mining technique. A single layer of data comprehension was added within the method instead of raw data. The results of the study were a web-based program for data pre-processing and decision tree models. There were 374 instances which were analyzed. The accuracy of answer sheet filling out attained 95.19% while the accuracy of classification varied from 99.47% to 100% depend on evaluation method chosen. This study could motivate the administrators for test improvement since it preferred computer-based test to paper-based.
Using Principal Component Analysis for Factor Analysis in Indonesian Automotive Industries Hamida, Ulil
IJID (International Journal on Informatics for Development) Vol. 8 No. 2 (2019): IJID December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2019.08203

Abstract

Policies related to the automotive industry have become significant for the Ministry of Industry. The problem in determining these policies is the determination of important factors for the automotive industry so that the policies formulated are right on target. The search for these important factors can be done by using the factor analysis method. So far, no studies have been conducted to examine the factors that influence the growth of the automotive industry. In this study, factor analysis is performed on factors in the automotive industry using the principal component analysis algorithm. The algorithm seeks to describe independently the aspects that become the main factors in determining the automotive industry. Based on an analysis of factors in the automotive industry production, the most influential factors are foreign investment, vehicle ownership ratios, and at last the change in GDP.
Internet Access Equity Policy Is the Internet Access Equity Policy Through USO Funds effective? Nugroho, Rossi Adi; Nafi'ah, Binti Azizatun
IJID (International Journal on Informatics for Development) Vol. 8 No. 1 (2019): IJID June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2019.08102

Abstract

Indonesia has a disparity in internet access caused by differences in regional factors, especially in geographically difficult areas to reach. The disparity in internet access is narrowed by the existence of programs through USO funds. However, the researchers found that the equalization program for internet access using USO funds had not been effective, especially in the education sector. This paper aims to provide an evaluation of USO-funded programs. This paper uses qualitative descriptive methods with review literature data collection techniques accompanied by qualitative critical analysis techniques. The important finding of this study is that the internet access equalization program has not been effective as evidenced by the ineffectiveness of this program in the education sector. Researchers suggest optimizing the internet access equalization program through USO funds to improve the quality of education.
Information Technology as Science: A New Model for Learning Jayadi, Puguh; Wahid, Fathul
IJID (International Journal on Informatics for Development) Vol. 8 No. 1 (2019): IJID June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2019.08103

Abstract

The integration of learning and Information Technology (IT) currently has a good impact on education. Besides making it easy, IT also provides opportunities to achieve learning goals anytime and anywhere. Many studies have discussed how to achieve successful learning through IT. IT here only serves as a support for learning, not as a science. This research develops a model or instrument used to achieve learning success by placing IT as a science. As a result, a learning model was successfully developed by combining several perspectives related to IT; students (Background, desire, and skill), teacher (teaching), and institution (infrastructure).
Nonlinear Controller Design via Inferenced-Augmentation of Equivalent Linearized System EseOghene, Ovie; D., Chizea F.; M., Akachukwu C.
IJID (International Journal on Informatics for Development) Vol. 8 No. 1 (2019): IJID June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2019.08105

Abstract

Output compensation of nonlinear system response is studied in this work with an inference-based design method used to control the nonlinear dynamics in the presence of non-linear effects. This design which is driven by practical considerations is informed by the comparisons made between nonlinear models and their linearized derivatives. While a detailed mathematical route has not been followed here, the results seem to show the workability of the proposed method and at its core, the design is driven by its intuitiveness. The proposed technique utilizes as primary parameter for comparison, the steady state error term which is derived from the behavior of the linear dynamics. Possible application areas for this design is in reduced energy control of nonlinear systems. The method was tested in simulation on a generic nonlinear system and a cart-driven inverted pendulum benchmark system.

Page 24 of 27 | Total Record : 265

 22   23   24   25   26 

Filter by Year

2012 2026


Reset
Filter By Issues
All Issue 2026 Vol. 14 No. 2 (2025): IJID December Vol. 14 No. 1 (2025): IJID June 2025 Vol. 13 No. 2 (2024): IJID December Vol. 13 No. 1 (2024): IJID June Vol. 12 No. 2 (2023): IJID December Vol. 12 No. 1 (2023): IJID June Vol. 11 No. 2 (2022): IJID December Vol. 11 No. 1 (2022): IJID June Vol. 10 No. 2 (2021): IJID December Vol. 10 No. 1 (2021): IJID June Vol. 9 No. 2 (2020): IJID December Vol. 9 No. 1 (2020): IJID June Vol. 8 No. 2 (2019): IJID December Vol. 8 No. 1 (2019): IJID June Vol. 7 No. 2 (2018): IJID December Vol 7, No 2 (2018): IJID December Vol. 7 No. 1 (2018): IJID June Vol 7, No 1 (2018): IJID June Vol 7, No 1 (2018): IJID June Vol. 6 No. 2 (2017): IJID December Vol 6, No 2 (2017): IJID December Vol 6, No 2 (2017): IJID December Vol 6, No 1 (2017): IJID June Vol. 6 No. 1 (2017): IJID June Vol 6, No 1 (2017): IJID June Vol. 5 No. 2 (2016): IJID December Vol 5, No 2 (2016): IJID December Vol. 5 No. 1 (2016): IJID May Vol 5, No 1 (2016): IJID May Vol. 4 No. 2 (2015): IJID December Vol 4, No 2 (2015): IJID December Vol. 4 No. 1 (2015): IJID May Vol 4, No 1 (2015): IJID May Vol 3, No 2 (2014): IJID December Vol. 3 No. 2 (2014): IJID December Vol. 3 No. 1 (2014): IJID May Vol 3, No 1 (2014): IJID May Vol. 2 No. 2 (2013): IJID December Vol 2, No 2 (2013): IJID December Vol 2, No 1 (2013): IJID May Vol. 2 No. 1 (2013): IJID May Vol 1, No 2 (2012): IJID December Vol 1, No 2 (2012): IJID December Vol. 1 No. 2 (2012): IJID December Vol. 1 No. 1 (2012): IJID May Vol 1, No 1 (2012): IJID May Vol 1, No 1 (2012): IJID May More Issue