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All Journal Prosiding SNATIKA Vol 01 (2011) REKAYASA INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Journal of Economic, Bussines and Accounting (COSTING) Indonesian Journal of Information System Journal of Information System,Graphics, Hospitality and Technology Jurnal Teknologi Informasi dan Multimedia Insyst : Journal of Intelligent System and Computation JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) Joutica : Journal of Informatic Unisla
Edwin Pramana
Institut Sains Dan Teknologi Terpadu Surabaya
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Physics Other

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FACTORS INFLUENCING STUDENTS' INTENTION TO ADOPT E-LEARNING WITH EXTENDED UTAUT Purnomohadi Sutedjo, Sing Tjoen; Pramana, Edwin; Gunawan, Gunawan
Journal of Economic, Bussines and Accounting (COSTING) Vol 7 No 6 (2024): COSTING : Journal of Economic, Bussines and Accounting
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/costing.v7i6.13747

Abstract

This study aims to analyze the factors that influence students' intention to adopt e-learning in Surabaya, using a modified theoretical model of the Unified Theory of Acceptance and Use of Technology (UTAUT). Through a quantitative approach, data were collected from 489 respondents who had used e-learning, using a questionnaire distributed online. The results showed that Performance Expectancy, Effort Expectancy, and Learning Convenience had a significant influence on students' Behavioral Intention to use e-learning. Social Influence and Facilitating Conditions were proven to have no influence on Behavioral Intention. In addition, Educational Level acts as a moderating variable that strengthens the relationship between Learning Convenience and Behavioral Intention, with a stronger effect on postgraduate students. This study provides theoretical contributions by enriching the UTAUT study through the addition of new factors, as well as practical contributions for e-learning developers and educators in designing more effective and user-friendly platforms. These findings are expected to provide broader insights into the acceptance of e-learning across educational levels and geographic contexts.
Extending the Expectation Confirmation Model to Examine Continuous Use Mobile Banking: Security, Trust, and Convenience Habib, Ahmad; Pramana, Edwin; Junaedi, Hartarto; Ronando, Elsen
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 9 No 1 (2025): February 2025
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v9i1.23751

Abstract

Background: Mobile banking adoption continues to grow, but user retention remains a challenge. Understanding the factors influencing continuance intention is crucial for improving long-term engagement. Prior research highlights the importance of confirmation, perceived usefulness, security, satisfaction, trust, and convenience, yet their interrelationships require further exploration. Objective: This study examines key determinants of users' intention to continue using mobile banking services, focusing on how confirmation, perceived usefulness, security, satisfaction, trust, and convenience influence this decision. Methods: A quantitative study was conducted using structural equation modeling (SEM) to analyze relationships among these factors. Data were collected from mobile banking users and assessed for statistical significance. Results: Confirmation significantly impacts perceived usefulness (0.576) and satisfaction (0.527). Perceived usefulness influences satisfaction (0.289) and continuance intention (0.396), while satisfaction also affects continuance intention (0.240). Trust plays a role (0.211), and perceived security strongly influences trust (0.651). Perceived convenience also impacts continuance intention (0.304), emphasizing its importance in user experience. Conclusion: Confirmation and security are critical for satisfaction and trust, which drive continued mobile banking use. Strengthening security, improving perceived usefulness, and fostering trust can enhance user retention. Future studies should explore additional variables, test the model across demographics, and assess the impact of emerging technologies like AI and blockchain. Longitudinal and experimental research may offer deeper insights into these evolving relationships.
Faktor Pengaruh Peralihan ke Online Learning pada Pegawai Negeri Sipil Berbasis Teori Push Pull Mooring Retno Susanti; Pramana, Edwin; Junaedi, Hartarto
Journal of Information System,Graphics, Hospitality and Technology Vol. 7 No. 1 (2025): Journal of Information System, Graphics, Hospitality and Technology
Publisher : Institut Sains dan Teknologi Terpadu Surabaya (d/h Sekolah Tinggi Teknik Surabaya)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37823/insight.v7i1.433

Abstract

Pegawai Negeri Sipil (PNS) diwajibkan untuk terus mengembangkan kompetensi minimal 20 jam per tahun, yang umumnya dilakukan melalui pembelajaran tradisional Pandemi COVID-19 tahun 2020 mengubah paradigma ini dan menjadikan Online Learning sebagai solusi utama akibat pembatasan sosial dan lockdown untuk mengendalikan penyebaran virus.  Bahkan, dalam perkembangannya, banyak instansi pemerintah mengadopsi konsep Corporate University untuk mendukung Online Learning, meskipun banyak menghadapi tantangan, seperti wilayah yang luas dan tersebar pada 38 provinsi dan 514 Kabupaten/Kota dan literasi digital yang rendah. Namun, seiring dengan meredanya pandemi, Online Learning menjadi suatu pilihan, bukan lagi keharusan dan pembelajaran dengan Traditional Learning kembali dibuka. Penelitian ini berusaha mengungkap faktor-faktor Pendorong (push) yang memengaruhi PNS untuk meninggalkan Traditional Learning, faktor-faktor yang menjadi Penarik (Pull) yang memengaruhi PNS untuk beralih pada Online Learning, dan faktor Penambat (Mooring) yang memengaruhi PNS untuk tetap menggunakan Traditional Learning atau beralih pada Online Learning. Berdasarkan data dari 463 responden PNS yang pernah menggunakan Traditional Learning maupun Online Learning yang diolah dengan metode analisa Structural Equation Model (SEM) dengan bantuan aplikasi SPSS dan AMOS, dapat diketahui bahwa seluruh variabel dalam Pull Factor secara keseluruhan memengaruhi keinginan berpindah, dan tidak seluruh variabel dalam Push Factor dan Mooring Factor yang memengaruhi keinginan berpindah.
Continuance Intention Pengguna Online Food Delivery di Indonesia dengan Menggunakan Extended Expectation Confirmation Model Kurniawan, David; Chandra, Francisca Haryanti; Pramana, Edwin
Journal of Information System,Graphics, Hospitality and Technology Vol. 7 No. 1 (2025): Journal of Information System, Graphics, Hospitality and Technology
Publisher : Institut Sains dan Teknologi Terpadu Surabaya (d/h Sekolah Tinggi Teknik Surabaya)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37823/insight.v7i1.434

Abstract

Pertumbuhan pesat layanan online food delivery di Indonesia mengubah perilaku konsumen dalam pembelian makanan menggunakan aplikasi digital. Namun penelitian mengenai perilaku pengguna aplikasi layanan online food delivery ini masih terbatas. Dalam penelitian sebelumnya, variabel brand image dan income sebagai moderator terbukti memengaruhi continuance intention di sektor lain, namun belum banyak dieksplorasi dalam konteks online food delivery. Penelitian ini bertujuan menganalisis faktor-faktor yang mempengaruhi continuance intention pengguna online food delivery di Indonesia serta mengisi kesenjangan tersebut dengan mengeksplorasi pengaruh brand image serta peran income sebagai moderator terhadap continuance intention pengguna aplikasi online food delivery di Indonesia. Penelitian ini mengadopsi Expectation-Confirmation Model (ECM) yang diperluas dengan variabel tambahan seperti brand image, price saving orientation, dan perceived convenience. Income (pendapatan) digunakan sebagai variabel moderator untuk melihat pengaruh berdasarkan tingkat pendapatan pengguna. Metode yang digunakan dalam penelitian ini merupakan metode kuantitatif dengan mengembangkan model dan hipotesis, merancang kuesioner, serta melakukan pengumpulan dan analisis data. Sebanyak 409 responden dengan pengalaman sebelumnya menggunakan layanan online food delivery dianalisis menggunakan Structural Equation Modeling (SEM) dan diproses dengan software AMOS. Hasilnya menunjukkan bahwa confirmation, perceived usefulness, satisfaction, dan perceived convenience berpengaruh positif terhadap continuance intention. Sebaliknya, brand image dan price saving orientation tidak berpengaruh signifikan. Income memoderasi hubungan antara perceived usefulness dan continuance intention, dengan pengaruh yang lebih kuat pada pengguna berpendapatan rendah. Temuan ini memberikan wawasan bagi penyedia layanan untuk meningkatkan retensi, khususnya pada pengguna dengan pendapatan rendah
Mobile Payment Adoption in Generation Z Using Extended Unified Technology Acceptance and Use of Technology Alfa'izy, Erick Ahmad Fahmi; Pramana, Edwin; Gunawan
Indonesian Journal of Information Systems Vol. 6 No. 1 (2023): August 2023
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v6i1.7340

Abstract

This study investigates the possible factors determining the success of m-payment adoption in Generation Z using the basic Unified Technology Acceptance and Use of Technology (UTAUT) model based on previous research. A theoretical model derived from previous research that combines factors from the acceptance model of UTAUT with relevant m-payment factors (Trust, Perceived Security, Network Externalities). The sample includes 735 participants from three cities in Indonesia. Structural equation models are used to analyze and develop theoretical models. Only four hypotheses can be accepted based on the analysis of the seven hypotheses proposed. Trust, Perceived Security, Performance Expectancy, and Social Influence positively and significantly impact Behavioral Intention. Meanwhile, Facilitating Conditions, Effort Expectancy, and Network Externalities are insignificant to Behavioral Intention. There are many research models for adopting m-payments, but in developing countries, including Indonesia, the cellular penetration rate is already very high. However, the acceptance of m-payments in various trade transactions is still embryonic, especially in Generation Z. Therefore, this research presents a comprehensive investigation of the factors that influence the adoption of m-payments in Generation Z in Indonesia.
Adopsi Blended Learning untuk Mahasiswa Perguruan Tinggi dengan Menggunakan Pendekatan Extended UTAUT Munsharif, Achmad; Pramana, Edwin; Zaman, Lukman
Rekayasa Vol 17, No 1: April, 2024
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v17i1.25869

Abstract

This research aims to determine the factors that influence the understanding of students' intentions in higher education in using blended learning and determine the relationship between factors in the theoretical model. This research was conducted because there is still a lack of research in the world that discusses the application of blended learning in higher education in developing countries such as Indonesia. Blended learning in higher education during the Covid-19 pandemic is still needed today because educational institutions have limited space to accommodate students and to follow technological development trends and utilize them in the world of education. Questionnaires distributed via Google Form were used to collect data. The sample was 541 blended learning users from various universities in Indonesia. All variables from the theoretical model are measured using existing scales. Structural Equation Model (SEM) is used to analyze the theoretical model. SPSS and Amos are used as analysis support software. This research contributes to the theoretical understanding of Blended Learning adoption as well as practices and guidelines for higher education institutions to successfully implement Blended Learning in their institutions. Of the eight initial hypotheses, there are seven hypotheses that are very significant. The three factors with the largest magnitude are effort expectancy, performance expectancy and system functionality. Effort expectancy is the most influential factor in implementing blended learning in higher education institutions.
Image Recognition Menggunakan Metode Cosine Distance untuk Aplikasi Penanganan Food Waste Chandra, Monica; Pramana, Edwin
Intelligent System and Computation Vol 4 No 2 (2022): INSYST: Journal of Intelligent System and Computation
Publisher : Institut Sains dan Teknologi Terpadu Surabaya (d/h Sekolah Tinggi Teknik Surabaya)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52985/insyst.v4i2.250

Abstract

Badan Pangan PBB (FAO) menyatakan 33% - 50% makanan yang telah diproduksi, tidak dikonsumsi dengan semestinya. Selain itu, 11% produk makanan yang dibeli terbuang bahkan tidak dibuka. Tahun 2016-2017, Indonesia sendiri telah menjadi negara terbesar kedua setelah Arab Saudi yang menghasilkan food waste terbanyak di dunia. Penumpukan limbah ini berdampak pada lingkungan. Oleh karena itu, aplikasi “Jangan Dibuang” dibuat dengan tujuan untuk mengurangi food waste yang dihasilkan. Aplikasi ini dibuat untuk platform Android dengan framework Flutter dan database Amazon Web Service Aurora. Selain itu, aplikasi ini juga dilengkapi dengan fitur image recognition yang memanfaatkan Tensorflow untuk mempermudah pencarian makanan dengan sebuah gambar yang mana gambar tersebut akan diekstrak fiturnya menjadi matriks yang kemudian dibandingkan dengan metode Cosine Distance. Aplikasi “Jangan Dibuang” dapat digunakan oleh 3 jenis aktor, yaitu administrator, penyedia makanan, dan pembeli. Uji coba dilakukan terhadap 7 penyedia makanan dan 20 pembeli. Berdasarkan hasil uji coba yang telah dilakukan, didapatkan 201 transaksi, yang mana telah menyelamatkan 285 limbah makanan. 59 dari 201 transaksi ditujukan untuk donasi. Fungsionalitas aplikasi penyedia makanan mendapatkan nilai 79,98% untuk kriteria sangat baik. Untuk fungsionalitas aplikasi pembeli, nilai yang didapatkan adalah 83% untuk kriteria sangat baik. Dari sisi Image Recognition sendiri menunjukkan akurasi 93,3% setelah menggunakan Keras Application Model EfficientNetV2 yang membantu mengenali kedua gambar walaupun dengan pencahayaan dan posisi pengambilan yang berbeda.
Continuance Intention Pada Aplikasi Mobile Payment Dengan Menggunakan Extended Expectation Confirmation Model M. Yahya Ubaidillah; Edwin Pramana; Francisca Haryanti Chandra
Jurnal Teknologi Informasi dan Multimedia Vol. 5 No. 2 (2023): August
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v5i2.359

Abstract

This study aims to identify the factors that influence the intention to continue using the mobile payment application during the new normal period after the COVID-19 pandemic, using the Extended Expectation Confirmation Model (EECM) approach. EECM combines aspects of the Expectation Confirmation Model (ECM) with other external factors, ECM is used to understand and explain decision-making related to the continued use of mobile payments. This research was conducted by analyzing data from respondents who have used mobile payment applications after the pandemic. The data was collected through an online survey and analyzed using Structural Equation Modeling (SEM) with the help of Analysis of Moment Structures (AMOS) software, 406 individuals were selected to serve as research participants. The results of the analysis show that factors such as satisfaction, and trust have a significant influence on the continuance intention of mobile payments. In addition, in the context of the new normal, factor such as social influence factors are known to have no significant influence on mobile payment continuance intention. As a result, this research contributes to understanding the factors that influence the intention to continue using mobile payment applications. The validity and reliability test results show that the survey instrument used has an adequate level of validity and reliability, supporting the quality and reliability of the analysis conducted.
A Hierarchical Multi-Label Classification Approach for the Automated Interpretation of Spinal MRI Series Cahyadi, David; Pramana, Edwin; Limantara, Rudi; Wiguna, I Gusti Lanang Ngurah Agung Artha; Deslivia, Maria Florencia; Liando, Ivan Alexander
Intelligent System and Computation Vol 7 No 2 (2025): INSYST: Journal of Intelligent System and Computation
Publisher : Institut Sains dan Teknologi Terpadu Surabaya (d/h Sekolah Tinggi Teknik Surabaya)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52985/insyst.v7i2.438

Abstract

Manually selecting MRI slices is a significant bottleneck in clinical workflows. This issue is worsened by inconsistent naming conventions and variable acquisition protocols across institutions and radiologists, often leading to redundant efforts and potential oversights during medical image data preprocessing. This study introduces a fully automated, four-level hierarchical classification system specifically designed to intelligently filter and select clinically relevant spinal MRI slices directly from raw DICOM series. Our primary objective is to streamline the initial stages of radiological assessment, ensuring that only pertinent images are presented for subsequent analysis and review. We thoroughly evaluated the performance of modern, efficient deep learning architectures, including EfficientViT, MobileNetV4, and RepViT, benchmarking them against a robust ResNet-18 baseline. The proposed pipeline systematically refines its analysis through a structured hierarchy: it first broadly identifies the anatomical region, then precisely classifies the spine location and specific view (axial, sagittal, or coronal). Subsequently, it categorizes the imaging contrast, and finally, confirms the presence of the spinal cord. Our comprehensive experimental results reveal that the EfficientViT-based model achieved the highest end-to-end F1-score of 0.8357, demonstrating robust accuracy across all classification levels. Furthermore, its average inference speed of 9.17 ms per image highlights its computational efficiency. This automated pipeline offers an effective and computationally efficient solution for speeding up initial medical image preprocessing, ensuring subsequent analytical tasks are performed on accurately selected, clinically relevant data.
Co-Authors Adithya Marhaendra Kusuma Agung Adi Saptomo Alfa'izy, Erick Ahmad Fahmi Ari Trivianto Audrey Ayu Dianaris Ayyub Cahyadi, David DAVID KURNIAWAN Deslivia, Maria Florencia Elsen Ronando Endang Setyati Francisca Haryanti Chandra Gunawan Gunawan Gunawan Gunawan Habib, Ahmad Hartarto Junaedi Herman Budianto Judi Prajetno Sugiono Liando, Ivan Alexander Limantara, Rudi Lukman Zaman M. Yahya Ubaidillah Misbahul Aziz Mochamad Alfan Rosid Monica Chandra Munsharif, Achmad Purnomohadi Sutedjo, Sing Tjoen Reddy Alexandro Harianto Retno Susanti Ridho Kurniawan RIDHO KURNIAWAN, RIDHO Sasono, Hikmah Agung Titania Dwi Andini Wiguna, I Gusti Lanang Ngurah Agung Artha Yosi Kristian