Article Per Year (5 Year)
p-Index From 2021 - 2026
1.827
P-Index
This Author published in this journals
All Journal International Conference on Engineering and Technology Development (ICETD) Jurnal Teknologi Informasi dan Ilmu Komputer IKRA-ITH ABDIMAS JSAI (Journal Scientific and Applied Informatics) Dinasti International Journal of Digital Business Management International Journal of Engineering, Science and Information Technology International Journal of Education, Social Studies, And Management (IJESSM) Unram Journal of Community Service (UJCS) Journal of Information Systems Management and Digital Business Jurnal Pengabdian Masyarakat Nasional
Wachyu Hari Haji
Mercu Buana University Jl. Meruya Selatan No. 1 Jakarta Barat, Indonesia
Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

Published : 14 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : JSAI (Journal Scientific and Applied Informatics)

 1 
Analisis Faktor Kepercayaan dan Kepuasan Pengguna Website Marketplace: Studi Empiris pada E-Commerce Lazada Hari Haji, Wachyu; Ratnasari, Anita; Ayumi, Vina; Noprisson, Handrie; Ani, Nur
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 3 (2024): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i3.7476

Abstract

This study aims to identify the factors influencing trust and user satisfaction in online marketplaces by applying the DeLone & McLean information system success model. Data were collected through an online questionnaire distributed to Lazada marketplace buyers in Indonesia. The empirical results indicate that trust is a key predictor in determining the quality of sellers and their ability to provide the best services. Statistically, the first hypothesis (H1) shows a significant influence of website reputation on user trust (**T-Stat = 8.50; Sig = *). The second hypothesis (H2), regarding the influence of perceived website size on trust, is not significant (T-Stat = 1.42; Sig = NS). The third hypothesis (H3) demonstrates a significant positive relationship between trust and user satisfaction with the website (**T-Stat = 5.62; Sig = *). The fourth hypothesis (H4) confirms a highly significant positive relationship between trust and perceived website quality (**T-Stat = 14.59; Sig = *). This study recommends that online marketplaces enhance the prestige of sellers and maintain customer trust, as these factors play a critical role in improving user satisfaction when shopping on online marketplaces.
Implementasi Dataset Augmentation pada Citra Etnofimedisin Menggunakan Teknik Rotation dan Channel Shift Purba, Mariana; Ayumi, Vina; Haji, Wachyu Hari
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 2 (2025): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i2.8776

Abstract

This study aimed to increase the quantity and variety of ethnopharmacological image datasets using image augmentation techniques, specifically rotation range augmentation (RRA) and channel shift range augmentation (CSA). The dataset augmentation was conducted to enrich the training data for the development of machine learning models used to recognize medicinal plant images. The RRA technique rotated images by random angles, providing variations in object orientation, while CSA altered the color channel values to simulate changes in lighting and the natural colors of plants. The research process included dataset collection, data preprocessing, application of both augmentation techniques, and division of the dataset into training, validation, and testing data. The results showed that the CSA technique produced 2,400 training data, 300 validation data, and 300 testing data, while the RRA technique produced the same amount of data. Therefore, the total data generated from both augmentation techniques amounted to 6,000 images, which could improve the accuracy and performance of deep learning models in recognizing ethnopharmacological images.
Co-Authors Abdul Kholiq Agung Priambodo Agung, Budi Agus Siswanto Alatas, Abd. Rahman Anita Ratnasari Aqbar, Harry Ari Purnadi, Mochamad Ayumi, Vina Christina Catur Widayati Defriansyah Donny Dharmawan Ekasari, Silvia Grace Gata, Grace Hady, Sultan Harries Madiistriyatno, Harries Istiqomah Sumadikarta Jumaryadi, Yuwan Muhammad Usman, Muhammad Murwani Wulansari Noprisson, Handrie Nur Ani Nurdiani, Tanti Widia Olfin Ishak Panjaitan, Bosar Purba, Mariana Riama Sibarani Setiawan, Zunan Sianturi, Heriston Subhan, Akhmad Sukarno Bahat Nauli Suryadi, Dikky Vidianto, Agung Sirajuddin Wilanda, Alifah Yuliadi, Boy Yunus, Andri