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All Journal Jurnal Teknologi Telematika : Jurnal Informatika dan Teknologi Informasi Seminar Nasional Informatika (SEMNASIF) Journal of Information Systems Engineering and Business Intelligence Register: Jurnal Ilmiah Teknologi Sistem Informasi EMITTER International Journal of Engineering Technology Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Conference SENATIK STT Adisutjipto Yogyakarta Indonesian Journal of Innovation Studies Dharma: Jurnal Pengabdian Masyarakat
Rifki Indra Perwira
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Aerospace Engineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Social Sciences

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Combining TAM-IS Success Model to Identify Key Factors Affecting Wimaya E-Learning: Menggabungkan Model Kesuksesan TAM-IS untuk Mengidentifikasi Faktor-Faktor Kunci yang Mempengaruhi E-Learning Wimaya Perwira, Rifki Indra; Purnama, Ida Ayu; Agusdin, Riza Prapascatama
Indonesian Journal of Innovation Studies Vol. 26 No. 2 (2025): April
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v26i2.1388

Abstract

General Background: E-learning has rapidly expanded worldwide due to the widespread accessibility of the Internet and the increasing availability of digital devices. As a web-based learning ecosystem, e-learning integrates multiple stakeholders, technologies, and processes to facilitate knowledge acquisition. Specific Background: Universities have increasingly adopted e-learning platforms to enhance learning experiences. However, the success of these implementations varies, necessitating a deeper understanding of the factors influencing their effectiveness. Knowledge Gap: While previous studies have explored the technical and pedagogical aspects of e-learning, limited research has examined the indirect effects of information and system quality on user behavior within university settings. Aims: This study aims to evaluate the success factors of the Spada Wimaya e-learning system in a university setting by assessing the relationships between system quality, information quality, perceived usefulness, perceived ease of use, behavioral intention, and actual system use. Results: The findings reveal that information and system quality indirectly influence behavioral intention and actual use through perceived usefulness and perceived ease of use. These results highlight the importance of user perceptions in determining the adoption and sustained utilization of e-learning platforms. Novelty: By adapting the research model from Presetyo et al. (2021), this study provides empirical evidence on the indirect mechanisms through which system and information quality affect user engagement in e-learning. Implications: The insights gained from this research can guide improvements in the Spada Wimaya e-learning system and serve as a reference for other universities aiming to enhance their digital learning environments. Highlights: User Perception Matters – System and information quality impact usage through perceived usefulness and ease of use. Indirect Influence – Quality factors do not directly affect behavior but work through user perceptions. Scalability – The model can be applied to improve e-learning systems in other universities. Keywords: E-Learning, Information System Model, Success Factors
Comparison of Adaptive Ant Colony Optimization for Image Edge Detection of Leaves Bone Structure Liantoni, Febri; Perwira, Rifki Indra; Bataona, Daniel Silli
EMITTER International Journal of Engineering Technology Vol 6 No 2 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (455.566 KB) | DOI: 10.24003/emitter.v6i2.306

Abstract

Leaf bone structure has a characteristic that can be used as a reference in digital image processing. One form of digital image processing is image edge detection. Edge detection is the process of extracting edge information from an image. In this research, Adaptive Ant Colony Optimization algorithm is proposed for edge image detection of leaf bone structure. The Adaptive Ant Colony Optimization method is a modification of Ant Colony Optimization, in which the initial an ant dissemination process is no longer random, but it is done by a pixel placement process that allows for an edge based on the value of the image gradient. As a comparison also performed edge detection using Robert and Sobel method. Based on the experiments performed, Adaptive Ant Colony Optimization algorithm is capable of producing more detailed image edge detection and has thicker borders than others. Keywords: edge detection, ant colony optimization, robert, sobel
Co-Authors Adhita Putra, Bertha Pratama Agusdin , Riza Prapascatama Agusdin, Riza Prapascatama Ahmad Juni Haryanto, Fandi Bambang Yuwono Bataona, Daniel Silli Bataona, Daniel Silli Budi Santosa Budi Santosa Danang Yudhiantoro, Danang Dessyanto Boedi Prasetyo Edy Nursanto Eny Endah Pujiastuti Febri Liantoni, Febri Hanifah, Qurrotu'ain Hari Prapcoyo Herdiansyah, Fachrizal Heru Cahya Rustamaji Hidayatulah Himawan Ida Ayu Purnama, Ida Ayu Mangaras Yanu F Novrido Charibaldi Nur Heri Cahyana Nur Utomo, Hastho Joko Purnamasari , Dian Indri Qurrotu'ain Hanifah Rifki Firmansyah, Rifki Rustamadji, Heru C. Santosa, Budi Siswoyo, Risya Ines Putri Syaputra, Hendra Arya Vynska Amalia Permadi Yuli Fauziah