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All Journal TIERS Information Technology Journal Jurnal Pengabdian Masyarakat SENSASI
Tresna Maulana Fahrudin
Universitas Pembangunan Nasional Veteran Jawa Timur
Humanities Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences

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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.
OPTIMALISASI HASIL PEMBELAJARAN DALAM STUDI INDEPENDEN BATCH 6 MELALUI CAPSTONE PROJECT MENGGUNAKAN GOOGLE BIG QUERY DAN LOOKER STUDIO Abdul Mukti; Tresna Maulana Fahrudin
Jurnal Pengabdian Masyarakat SENSASI Vol. 4 No. 2 (2024): Jurnal Pengabdian Masyarakat SENSASI
Publisher : Faculty of Economics and Bussiness, UPN "Veteran" Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/sensasi.v4i2.81

Abstract

Pendidikan adalah sistem komunikasi yang melibatkan transformasi pengetahuan dan keterampilan sepanjang hayat. Untuk menanggapi perubahan sosial, budaya, teknologi, dan industri, Kemendikbudristek memperkenalkan Kebijakan Merdeka Belajar dengan inisiatif Kampus Merdeka, yang memberi mahasiswa kebebasan untuk belajar di luar program studi dan kampus. RevoU Tech Academy, sebagai mitra program Studi Independen Bersertifikat, menawarkan program Data Analytics & Software Engineering yang menggunakan berbagai metode pembelajaran dan proyek akhir (capstone project). Dalam capstone project, penulis dan Tim 5 Surabaya menganalisis dataset "Bike Sales in Europe" dari Kaggle, melakukan pembersihan dan analisis data menggunakan Google Spreadsheet dan Google Cloud BigQuery, serta visualisasi menggunakan Looker Studio. Proyek ini juga mencakup pengembangan dashboard web yang intuitif. Dashboard ini dirancang dengan antarmuka pengguna yang mudah digunakan, fitur filter yang dapat disesuaikan, dan aksesibilitas melalui perangkat mobile. Hasil proyek ini tidak hanya meningkatkan keterampilan teknis seperti analisis data dan pengembangan perangkat lunak, tetapi juga mengembangkan soft skills melalui kolaborasi tim, komunikasi efektif, dan manajemen waktu yang baik.
Co-Authors Abdul Mukti Anggraini Puspita Sari Dwi Arman Prasetya Mohammad Idhom Prismahardi Aji Riyantoko