Garuda - Garba Rujukan Digital

Classification of Student Understanding on Covid-19 Booster Vaccine Using Machine Learning Cahya Damarjati; Slamet Riyadi; Ricki Irawan
Emerging Information Science and Technology Vol 3, No 2 (2022): November
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v3i2.18680

The outbreak of COVID-19 has been declared a global pandemic by the World Health Organization (WHO). Developing a vaccine is one of the best ways to reduce the virus's impact. Nevertheless, the development of virus mutations produces new variants that diminish the efficacy of the previous vaccine. Booster doses of the Covid-19 vaccine is still a matter of debate among the public, particularly among students, as evidenced by the low rate of booster vaccinations in the community, which is a result of a lack of knowledge about booster vaccines. The purpose of this study is to assess the level of understanding among Universitas Muhammadiyah Yogyakarta (UMY) students regarding booster vaccinations, with the results subsequently serving as a factor or strategy for future government booster vaccination policy decisions. ANN and SVM algorithms could be used to predict the level of understanding of booster vaccinations among UMY students. However, the maximum level of precision in classifying the level of comprehension is not yet known. To determine which of the two methods, kernel and k-fold, provided the maximum level of accuracy, a comparative study was conducted between them. The research was conducted by disseminating questionnaires containing assessments of booster vaccinations to a total of 2095 respondents. Using randomized sampling type, this study yielded an accuracy of 88.45% for the ANN method and 89.93% for the SVM method in each scenario. In addition, the authors conduct feature efficiency, which aims to reduce the time and cost associated with data computation.

Evaluating the Hybrid Multi-Protocol Label Switching (MPLS) on the Enhanced Interior Gateway Routing Protocol (EIGRP) Ridho Novradinata; Slamet Riyadi; Ronald Adrian
Emerging Information Science and Technology Vol 3, No 2 (2022): November
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v3i2.16865

The development of technology and communication is expanding rapidly. In this case, the internet has become a vital necessity in globalization. Technological innovations are required to create a seamless, fast, and secure communication system. This research aims to evaluate the Enhanced Interior Gateway Routing Protocol (EIGRP) implementation by applying the Multiprotocol Label Switching (MPLS) technology. This study adhered to several stages in the Network Development Life Cycle (NDLC) method. The results of the two technology combinations, EIGRP and MPLS, demonstrated MPLS network simulation testing in several dynamic routing systems: EIGRP and OSPF, identified through the Quality of Service (QoS) value. It revealed that the best performance was EIGRP with a throughput of 2152.5 bps, delay of 335.6 ms, and jitter of 411 ms. Furthermore, MPLS and EIGRP network redundancy was better applied in the mesh topology with a multi or backup link than in the linear topology with a single link.

Development and Testing of a Mathematics Learning Application Arif Ahmad Fadlil; Dwijoko Purbohadi; Slamet Riyadi
Emerging Information Science and Technology Vol 4, No 1 (2023): May
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v4i1.18886

Distance learning, or online learning, is essential for both teachers and students as they work to create a system of education to function during a pandemic. Therefore, this research aims to develop a CAI media-based learning application for teaching fractions in mathematics. The survey results conducted at SDN 1 Sukerejo Boyolali revealed that students encountered the most trouble with fractions. Hence, their comprehension of the mathematics learning application was evaluated. The pre-test and post-test results of 30 students in both the control and experiment classes demonstrated that the application was easier to use than direct or traditional learning methods.

Peningkatan Ketrampilan Guru SD dalam Pembuatan Video Pembelajaran dengan Menggunakan Telepon Cerdas Slamet Riyadi; Erwan Sudiwijaya; Apriliya Kurnianti; Arif Bintoro Johan
Jurnal Surya Masyarakat Vol 6, No 1 (2023): November 2023
Publisher : Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsm.6.1.2023.104-110

Learning in digital era demands innovation of learning materials where video is one of the attractive materials. Unfortunately, many teachers don't have skills to make learning videos, including some teachers at the Muhammadiyah Elementary School in Godean. Therefore, this program aims to improve the skills of partners in making learning videos. The main equipment used is a cell phone which is owned by all teachers so there is no need to procure additional equipment. The steps carried out are preparation, implementation and evaluation. Preparations have been made by discussing with partners about the training to be held. The training was completed on April 9, 2022 at the UMY Information Technology Laboratory, attended by 37 teachers from three Muhammadiyah elementary schools in Godean District. Participants received theory and immediately practiced making videos using their respective cell phones. Training evaluation was carried out using pre and post tests as well as observation. This program has succeeded in increasing teachers' knowledge and skills in making learning videos with a significant increase in pre-test and post-test results of 54.7%.

Improving Sentiment Analysis Accuracy Using CRNN on Imbalanced Data: a Case Study of Indonesian National Football Coach Slamet Riyadi; Muhammad Dzaki Mubarok; Cahya Damarjati; Asnor Juraiza Ishak
JUITA: Jurnal Informatika JUITA Vol. 12 No. 2, November 2024
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v12i2.21847

Conducting sentiment research on the perception of the Indonesian people towards Shin Tae Yong's (STY) role as coach of the Indonesian National Football Team (PSSI) is crucial as it can assist PSSI in determining whether to extend STY's contract. Prior studies have demonstrated that Deep Learning achieves a high level of accuracy when applied to sentiment analysis in many domains. Nevertheless, no investigation has been conducted thus far utilizing deep learning techniques to examine emotion towards STY. This study employs modified Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Convolutional Recurrent Neural Networks (CRNN), and CRNN models with and without data oversampling. The research findings indicate that the CRNN model, when combined with data oversampling and a redesigned architecture, achieves the highest level of accuracy (1.00) and consistently performs well. This research provides significant contributions in three areas: firstly, it utilizes Deep Learning techniques for sentiment analysis on STY; secondly, it modifies the CRNN architecture; and thirdly, it applies data oversampling to address the issue of imbalanced data.

Sentiment Analysis of Pro-Israel Product Boycott Action Using IndoBERT Method on Unbalanced Data Auliana Rizky Puspita Dewi; Slamet Riyadi; Cahya Darmajati; Nor Ashidi Mat Isa; Annisa Divayu Andriyani
JUITA: Jurnal Informatika JUITA Vol. 13 Issue 2, July 2025
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v13i2.25976

A boycott was an act taken to stop the purchase or use of a particular product or service as a form of public protest against a particular company or group committing a deviation. The Israeli-Palestinian conflict, which had been ongoing since 1948, peaked in October 2023 and had claimed more than 35,000 Palestinian lives. This conflict generated a wide range of public opinions in Indonesia, which were expressed through social media, especially Twitter. Thus, the sentiment analysis of public reactions on Twitter became important to understand the reactions and perspectives of society towards the boycott of Pro-Israel products. This study used the IndoBERT method, which was a variant of the BERT method specifically designed to understand Indonesian. Although many studies had applied the IndoBERT method for sentiment analysis and text classification in Indonesian, none had used the IndoBERT method along with data balancing techniques to analyze Indonesian sentiments regarding the boycott of Pro-Israel products on Twitter. Therefore, this study aimed to develop a sentiment analysis model using the IndoBERT method with more data to examine sentiments related to the boycott of Pro-Israel products on Twitter using imbalanced data, as well as to evaluate the effect of balancing methods using under sampling and oversampling on the model’s accuracy and performance. The methods used included data crawling, data preprocessing, labeling with a Lexicon-Based approach, data balancing, and data splitting. The IndoBERT model was trained with 20 epochs, a batch size of 16, and a learning rate of 2e-5. The results of the study showed that the model with balanced data using the oversampling method achieved an accuracy of 97% and an F1-Score of 97%, which was better compared to the model with imbalanced data and the undersampling method. Thus, data balancing using the oversampling method proved to be effective in improving accuracy in sentiment analysis. This research made a significant contribution to understanding the behavior of Indonesian society towards a product boycott supporting Israel and suggested further exploration in parameter optimization and evaluation with larger and more diverse data, as well as further development of data balancing methods to improve the generalization and capabilities of the model

Peningkatan Ketrampilan Guru SD dalam Pembuatan Video Pembelajaran dengan Menggunakan Telepon Cerdas Slamet Riyadi; Erwan Sudiwijaya; Apriliya Kurnianti; Arif Bintoro Johan
Jurnal Surya Masyarakat Vol 6, No 1 (2023): November 2023
Publisher : Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsm.6.1.2023.104-110

Learning in digital era demands innovation of learning materials where video is one of the attractive materials. Unfortunately, many teachers don't have skills to make learning videos, including some teachers at the Muhammadiyah Elementary School in Godean. Therefore, this program aims to improve the skills of partners in making learning videos. The main equipment used is a cell phone which is owned by all teachers so there is no need to procure additional equipment. The steps carried out are preparation, implementation and evaluation. Preparations have been made by discussing with partners about the training to be held. The training was completed on April 9, 2022 at the UMY Information Technology Laboratory, attended by 37 teachers from three Muhammadiyah elementary schools in Godean District. Participants received theory and immediately practiced making videos using their respective cell phones. Training evaluation was carried out using pre and post tests as well as observation. This program has succeeded in increasing teachers' knowledge and skills in making learning videos with a significant increase in pre-test and post-test results of 54.7%.

Title

Found 27 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 27 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 27 Documents
Search