Article Per Year (5 Year)
p-Index From 2021 - 2026
2.189
P-Index
This Author published in this journals
All Journal Telematika : Jurnal Informatika dan Teknologi Informasi Seminar Nasional Informatika (SEMNASIF) Studies in Learning and Teaching Nusantara Science and Technology Proceedings TIERS Information Technology Journal International Journal of Data Science, Engineering, and Analytics (IJDASEA)
Prismahardi Aji Riyantoko
Department Of Data Science, Universitas Pembangunan Nasional “Veteran” Jawa Timur, Surabaya 60294, Indonesia
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Medicine & Pharmacology Other

Published : 15 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 15 Documents
Search

 1   2 
The Effect of Information Quality and Service Quality on User Satisfaction of the Government of Kabupaten Malang Dwi Arman Prasetya; Anggraini Puspita Sari; Prismahardi Aji Riyantoko; Tresna Maulana Fahrudin
TIERS Information Technology Journal Vol. 4 No. 1 (2023)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/tiers.v4i1.4328

Abstract

Currently, the government has implemented performance digitization through information systems that are published through official channels owned by the government, one of which is the government of Kabupaten Malang. The objective of this research was to assess or gauge the measurement and test variables and indicators that affect the quality of the Kabupaten Malang government website with the link www.malangkab.go.id/mlg The problem is, not many governments have launched applications paying attention to the factors that influence user satisfaction so that the government has not been able to prioritize repairs and optimize website performance to meet constituent needs that continue to grow in the digital era. This research employs a survey to identify the causal elements that impact the factors contributing to user satisfaction on the website. The causal factors include website service quality, information quality, and usability quality in user satisfaction. Respondents used in this study were website operators for regional apparatus in Kabupaten Malang, consisting of 81 respondents who met the requirements. In obtaining valid and reliable data, multiple linear regression and hypothesis testing were carried out. There are 4 multiple linear regressions that are carried out, namely, multicollinearity test, autocorrelation test, heteroscedasticity test, and normality test. The results of the influence of service quality, and information quality on user satisfaction through usability quality are 5 models that have a significant influence, that is Service Quality to Usability Quality, Information Quality to Usability Quality, Service Quality to User Satisfaction, Information Quality to User Satisfaction, and Usability Quality to User Satisfaction.
Pneumonia Classification Utilizing VGG-16 Architecture and Convolutional Neural Network Algorithm for Imbalanced Datasets Mohammad Idhom; Dwi Arman Prasetya; Prismahardi Aji Riyantoko; Tresna Maulana Fahrudin; Anggraini Puspita Sari
TIERS Information Technology Journal Vol. 4 No. 1 (2023)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/tiers.v4i1.4380

Abstract

This research focuses on accurately classifying pneumonia in children under the age of 5 using X-ray images, considering the challenge of an imbalanced dataset. A modified VGG-16 CNN architecture is evaluated for pneumonia classification in Chest X-Ray Images. The study compares testing results with and without data augmentation techniques and explores the potential application of the model in an Android-based machine learning system for pneumonia diagnosis assistance. Using a dataset of 5,856 Chest X-Ray images categorized as normal or pneumonia, obtained from Kaggle, the research conducts two test scenarios: one without data augmentation and another with data augmentation techniques. The modified VGG-16 CNN algorithm's performance is evaluated using the accuracy metric. The results highlight the effectiveness of data augmentation in improving pneumonia classification accuracy. The augmented tests outperform the non-augmented ones, achieving an impressive 92% accuracy, indicating a significant 15% improvement over the non-augmented scenario. This improvement underscores the efficacy of data augmentation techniques in enhancing the CNN's ability to accurately classify pneumonia, particularly when faced with an imbalanced dataset. Furthermore, the research explores the potential integration of the trained model into an Android-based machine learning system for pneumonia diagnosis assistance. This integration would enable doctors to analyze X-ray images and identify potential pneumonia cases in patients. The integration of advanced machine learning systems in healthcare holds promise for improving patient care and the accuracy of pneumonia diagnoses. In summary, this research contributes to the accurate classification of pneumonia in children under 5 years old using X-ray images. It emphasizes the efficacy of data augmentation techniques in enhancing classification accuracy and explores the practical application of an Android-based machine learning system for pneumonia diagnosis assistance. These findings underscore the importance of advanced machine learning systems in healthcare and their potential to improve pneumonia diagnosis accuracy and enhance patient care.
Teacher's Readiness to Teach Literacy and Numeracy: A Literature Review Wahyu Kyestiati Sumarno; Prismahardi Aji Riyantoko; Ali Shodikin; Nur Imro’atus Solikha; Novandi Kevin Pratama
Nusantara Science and Technology Proceedings 8th International Seminar of Research Month 2023
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2024.4129

Abstract

The preparedness of educators to teach foundational skills such as literacy and numeracy is critical for student success, especially in the early years of education. This literature review explores the current body of research on teacher readiness to instruct in these essential areas. Methodologically, the review synthesizes empirical studies, theoretical frameworks, and best practices published in peer-reviewed journals, reports, and educational white papers. Key findings reveal that teacher readiness is influenced by multiple factors including educational background, professional development, access to resources, and pedagogical support. The review also identifies gaps in the existing literature, particularly in the context of digital transitions and inclusive education. The insights gained from this study could guide future research and inform policy interventions aimed at enhancing teacher readiness for effective literacy and numeracy instruction.
A Simple Data Sentiment Analysis using Bjorka phenomenon on Twitter Prismahardi Aji Riyantoko; Amri Muhaimin
Nusantara Science and Technology Proceedings 7st International Seminar of Research Month 2022
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2023.3353

Abstract

Social media is one of the means used by netizens to access, share and discuss the latest and hottest news issues. Twitter as one of the social media is a platform that in real-time is often chosen to communicate that matter. Through sentiment analysis with the text method mining on Twitter, we can understand how people describe and express their perceptions of obesity both positively and negatively nor neutral. This analysis is important to see the extent to which social media such as Twitter is used today. Those are one of the instruments for disseminating information data security in Indonesia. Research objectives for identifying sentiment analysis on related Twitter the Bjorka phenomenon in Indonesia using the text mining method. The type of research is cross-sectional. This research plan was chosen because of the data taken from Twitter in the last four-month time series (June 2022 - October 2022). The result of web scraping on Twitter is 998 Indonesian tweets. Taking data using the Twitter Scraping extension pack and analyzing using Python 3.7.2. Based on the results of sentiment analysis tweets got a neutral sentiment of 744 (75%) tweets, followed by negative sentiment of as much as 175 (18%) tweets and positive sentiment by the number 75 (8%) of a total of 994 tweets. The conclusion was presented the modelling in based on the topic, and we got three topic most relevant terms for topic 0, 1, or 2 with 35,3%, 33%, 31,7% of tokens, respectively.
Internet of Things ESP8266 Module for Vocational High School Student Prismahardi Aji Riyantoko; Ahmad Khairul Faizin; Burhan Syarif Acarya; Fairuz Mumtaz Idhizar Farraz
Nusantara Science and Technology Proceedings 7st International Seminar of Research Month 2022
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2023.3354

Abstract

The development of information and communication technology in the industrial era 4.0 is very rapid, especially in the field of IoT (Internet of Things). To get data and process data very quickly and in real-time, it takes a device that is connected to the internet network that will be able to provide information to anyone who is connected to the IoT device. IoT is the development of a system that can monitor and control from a remote place via the internet. In the current era, almost all people can access the internet easily, so by utilizing and optimizing the use of communication through the internet network by connecting sensor and actuator devices to the internet network. With this development, we need to provide the community with knowledge and skills about IoT through workshops, training and mentoring. The training includes knowledge of sensors, microcontrollers, and actuators that can be programmed and connected to the internet network. The ESP8266 microcontroller is a control device that can be filled with a program for controlling and monitoring devices installed on the internet network
Co-Authors Ahmad Khairul Faizin Ali Shodikin Amri Muhaimin Anggraini Puspita Sari Burhan Syarif Acarya Dwi Arman Prasetya Dwi Arman Prasetya Eristya Maya Safitri Fairuz Mumtaz Idhizar Farraz Hendri Prabowo I Gede Susrama Mas Diyasa I Gusti Putu Asto Buditjahjanto Kartika Maulida Hindrayani Kartika Maulida Hindrayani Made Hanindia Prami Swari Mohammad Idhom Mohammad Idhom Munoto Novandi Kevin Pratama Nur Imro’atus Solikha Tahta Dari Timur Tresna Maulana Fahruddin Tresna Maulana Fahrudin Tresna Maulana Fahrudin Tresna Maulana Fahrudin Tresna Maulana Fahrudin Trimono, Trimono Wahyu Kyestiati Sumarno