Student Engagement Prediction Using Deep Learning: Comparative Analysis of Unimodal and Multimodal Approaches Mohammad Bhanu Setyawan, Didik Dwi Prasetya, Triyanna Widyaningtyas, Busro Akramul Umam, Sahlan M. Saleh Beyond Technology Summit on Informatics International Conference Bts I2c 2025, 2025 Accurate assessment of student engagement plays a crucial role in optimizing teaching methods and improving learning performance in an online environment. This study proposes and evaluates a multimodal deep learning framework to assess the level of student engagement by conducting a comparative study between unimodal approaches and multimodal fusion. Specifically, we analyzed data from two main modalities: visual (video) data to capture emotional engagement, and log data (quiz scores) to reflect behavioral and cognitive engagement. We implemented four deep learning architectures for the classification of time-series data—Encoder, FCN, Time-CNN, and MCNN—on three scenarios: video-only, quiz-only, and multimodal fusion (video+quiz). The results of the evaluation showed that the multimodal approach consistently delivered the best performance across the model. The MCNN model achieved the highest accuracy of 72.68% in multimodal configurations, showing a significant improvement over the unimodal approach. These findings confirm that the synergy between emotional data and objective performance data results in more comprehensive and reliable predictions of engagement and highlights the great potential of multimodal systems to create more personalized and effective learning interventions.
Thresholding Value for Contour Segmentation Model in the Detection of Infected Plants with Drone Acquisition Fauzan Masykur, Angga Prasetyo, Ismail Abdurrozaq, Adi Fajaryanto Cobantoro, Arief Rahman Yusuf, Mohammad Bhanu Setyawan Ingenierie Des Systemes D Information, 2025 Segmentation is a method of separating colors between the background and foreground of an image with the aim of obtaining the pixel index value of a certain object.Meanwhile, contour segmentation is a technique used in image processing to detect and extract the boundaries of objects in the image.One of the uses of contour segmentation in this study is to detect infected rice plants based on images of rice plants acquired by drone cameras.The dataset image as an input in model training was carried out by flying a drone over a rice plant to capture the rice plant.The results of the evaluation of contour segmentation detection were carried out by comparing with real conditions which produced a value of 97.02% and an error of 2.80%.
Assessing students’ readiness for artificial intelligence-based project learning to strengthen local wisdom values in Indonesia Sutrisno Sutrisno, Abdul Azis, Mohammad Bhanu Setyawan, Dinie Anggraeni Dewi, Yayuk Hidayah, Muhammad Hakiki, Mustofa Abi Hamid, Radinal Fadli Cogent Education, 2025 The integration of artificial intelligence (AI) into higher education is reshaping learning practices globally, including in Indonesia, where technological advancement intersects with the need to preserve local cultural values. This study examines Indonesian university students’ readiness for AI-based project learning that reinforces local wisdom. A quantitative survey was conducted across four universities to assess students’ technological literacy, attitudes toward AI in learning, and awareness of cultural value integration. The findings reveal that although students generally possess high levels of technological literacy, their readiness to apply AI-based project learning within culturally grounded contexts varies considerably. Key influencing factors include access to technological resources, prior exposure to AI applications, and institutional support. A significant positive correlation was identified between technological literacy and readiness, indicating that strengthening digital competence may enhance students’ preparedness for culturally contextualised AI learning. The study highlights the need for context-sensitive curricula and training that simultaneously foster technological fluency and cultural awareness, supporting inclusive and future-oriented educational practices.
Building a Secure Digital Future: Investigating Cyber Hygiene Levels of Accounting, Finance, and Business Students Fivia Eliza, Radinal Fadli, Yayuk Hidayah, M. Aghpin Ramadhan, Abdulnassir Yassin, Mohammad Bhanu Setyawan, Sutrisno Sutrisno Data and Metadata, 2024 structured in:Introduction: This study aims to investigate the level of cyber hygiene among accounting, finance and business students, to identify strengths and weaknesses to inform the development of cybersecurity in education.Methods: A quantitative research design was employed, utilizing an objective online test to assess cyber hygiene knowledge. The instrument was validated through tests of validity, difficulty level, discriminatory power, and reliability. The study sample consisted of students in finance, administration and business. Data analysis involved statistical methods to compare awareness levels across the three student groups.Results: The results indicated that administration students had the highest overall cyber hygiene awareness, particularly in areas such as Rules & Laws, Access & Password, and Security Settings. Business students showed moderate awareness, while accounting students demonstrated significant gaps, especially in Web Access and Social Media Safety. The findings highlighted the need for targeted educational interventions to address specific weaknesses in each group.Conclusions: This study underscores the importance of cyber hygiene education, especially for accounting, finance, and business students, to prevent cyber incidents. The findings provide actionable insights for the development of curricula and training programs, which contribute to a safer digital environment in professional settings. Further research should expand sample sizes, incorporate qualitative methods, and explore the long-term effectiveness of cyber hygiene education
Predicting Smart Regency Readiness on Sub-Urban Area in Indonesia: A perspective of Technology Readiness Index 2.0 Aang Kisnu Darmawan, Muhsi Muhsi, Mohammad Waail Al Wajieh, Mohammad Bhanu Setyawan, Agus Komarudin, Fathorrozi Ariyanto 9th International Conference on ICT for Smart Society Recover Together Recover Stronger and Smarter Smartization Governance and Collaboration Iciss 2022 Proceeding, 2022 Many e-Government studies have devised different ways to measure how ready a smart city is to use ICT. But many research notes show that the conceptual readiness framework is hard for e-Government researchers to understand. These challenges have included a lack of a scientifically valid model framework and readiness models for village and sub-urban areas, which have been common in numerous developing countries like Indonesia. This study aims to use a readiness model from Parasuraman's (2015) Technology Readiness Index 2.0 (TRI 2.0) framework to determine how ready Sub Urban areas in Indonesia are. By looking at how the mobile-based Smart Regency services were used, the TRI 2.0 framework was changed so that it could be used to measure sub-urban areas in Sumenep and Pamekasan Regencies, Madura Island Districts. A random, stratified, and purposeful sampling method was used to get information from 148 service users and smart city stakeholders. Analysis of data using SmartPLS 3.2 software and structural equation modeling indicated that the four TRI 2.0 model aspects, namely Innovativeness (5,669), Optimism (3,813), Discomfort (7,033), and Insecurity(7,096), all of these have significant effects on Smart Regency Readiness. This research provides a scientific contribution by adapting the TRI 2.0 model in Sub Urban in Indonesia, which is still rarely studied. This research makes a practical contribution by recommending that smart regency stakeholders pay close attention to important factors that affect how ready smart regency development is in underdeveloped countries, especially Indonesia.
Analysis of The Critical Factors Influence Smart Regency Development with Interpretive Structural Modelling(ISM) Approach Aang Kisnu Darmawan, Mohammad Waail Al Wajieh, Agus Komarudin, Mohammad Bhanu Setyawan, Busro Akramul Umam, Rofiuddin Rofiuddin 9th International Conference on ICT for Smart Society Recover Together Recover Stronger and Smarter Smartization Governance and Collaboration Iciss 2022 Proceeding, 2022 The high failure rate of e-Government implementation in developing countries was the impetus for researching the factors influencing success. Exploring CSFs is crucial to avoid failures. However, e-Government implementation is not simple. E-Government is more than simply introducing web-based technologies to government, but it is a complex social system that addresses the most pressing social issues. Several researchers have explored Critical Success Factors (CSF) for e-Government implementation successful but have not found satisfactory results. Based on the literature search, there are still very few studies exploring CSF and describing the relationship among critical factors that determine the success of e-Government in developing countries, including Indonesia. This research aims to understand the relationship of inter-sub element linkage from the factors that determine the success of Smart Regency, a concept for implementing e-Government in Sub Urban areas in Indonesia. The method used is the Interpretive Structural Model (ISM) approach, a form of ranking elements introduced by J. Warfield based on the relationship between elements. The research was conducted by expert judgment on the relationship between 11 elements that influence the success of a smart regency. The results show that the top three elements' most significant factor was the Open Government Data element (level 1), followed by the E-Service Adoption, Public-Private Partnership (Level 2) element. This research contributes in two ways. The first is theoretically by providing scientific contributions to the relationship between factors that influence the success of smart districts based on the ISM perspective, and practical contributions by providing recommendations to local governments and stakeholders to pay more attention to the factors that build smart regencies.
Understanding Smart Regency Services Readiness in Indonesia with TRAM Model Aang Kisnu Darmawan, Busro Akramul Umam, Fathorrozi Ariyanto, Mohammad Bhanu Setyawan, Moh. Aminollah Hamzah, Ahmad Asir 2022 International Seminar on Intelligent Technology and Its Applications Advanced Innovations of Electrical Systems for Humanity Isitia 2022 Proceeding, 2022 Numerous studies in e-Government have developed numerous models to assess smart cities’ readiness to utilise ICT. However, numerous research notes indicate that e-Government researchers are currently confronted with difficulties developing a reliable scientific model framework and developing readiness models for rural and sub-urban areas, which are highly common in several developing countries, including Indonesia. This study aims to adapt a readiness model based on Chien-(2007) Hsi’ s Technology Preparedness and Acceptance Model framework to assess the readiness of Indonesia’ s Suburban Areas, that’ s called Technology Readiness and Acceptance Model(TRAM). The TRAM framework was developed to evaluate the mobile-based Smart Regency services utilised in Pamekasan and Sumenep Regencies, Madura Island Districts. Data were collected by executing a random purposive and stratified random sampling sample of 186 service users and smart regency stakeholders. AMOS software was used to analyse the data and use structural equation modelling. The findings suggested that the three TRAM model constructs, namely with a critical ratio of 8.038 for Perceived Ease of Use (PEOU), 5.569 for Perceived Usefulness (PU), and 1.785 for Use Intention (UI), all have a significant effect on Smart Regency Readiness. This research contributes to science by adapting the TRAM model for use in Sub Urban Indonesia, an area that is still mostly unstudied. And help effectively by advising that stakeholders in smart regencies pay special attention to important factors affecting the readiness of developing countries, notably Indonesia, to build smart regencies.
Knowledge Management System Analysis of Smart Regency Mobile-Apps Service with Software Usability Measurement Inventory (SUMI) Approach Aang Kisnu Darmawan, Mohammad Bhanu Setyawan, Adi Fajaryanto Cobantoro, Fauzan Masykur, Anwari Anwari, Tony Yulianto 8th International Conference on ICT for Smart Society Digital Twin for Smart Society Iciss 2021 Proceeding, 2021 In the Indonesian context, the number of districts is four times the number of cities, so regency development needs serious attention. However, there are still very few studies that explore districts' existence from the perspective of ICT utility governance. This study aims to measure the mobile-based smart regency information system through usability evaluation. The method applies the adoption of the life cycle of the Knowledge Management System (KMSLC). Evaluation of Existing Infrastructure Analysis, Capture Knowledge, Implementing the Knowledge Management (KM) Model, and Evaluation are the stages used. The measures taken include system analysis, application mapping knowledge, implementation results, and usability assessment. The questionnaire was conducted on ten respondents using the mobile-based smart regency application. The questionnaire was conducted in 5 categories: Effectiveness, Efficiency, Control, Support, and Simplicity. Each of 10 questions, so there are 60 questions and three linkers, namely 4 if all agree, 2 if they don't know, and 0 don't agree. The Median SUMI Scale results for the mobile-based Smart Regency application are 60, 62.5, 60, 60, and 57.5. The usability evaluation results above the average mean that the mobile-based smart regency information system's usability is in a good category. This research helps in determining knowledge management in mobile smart regency services. The study also provides insight into the factors affecting the success of knowledge management of smart regency services for application developers and policymakers.
Assessing and Enhancing an Existing User Experience (UX) of Smart Regency Mobile-Apps Service with meCUE 2.0 Framework Aang Kisnu Darmawan, Mohammad Bhanu Setyawan, Bakir Bakir, Miftahul Walid, Moh. Aminollah Hamzah, Ahmad Asir 2021 9th International Conference on Cyber and IT Service Management Citsm 2021, 2021 In the context of Indonesia, the number of regencies is four times the number of cities in the 2020 government administration area data record. This record shows that the development of ICT in regency's areas must be a serious concern. However, the survey shows that very few studies are still exploring and examining the various dimensions of Smart Regencies. This study aimed to evaluate the user experience of two Smart Regency applications, namely Pamekasan Smart Mobile Apps (PSMA) and Sumekar Online Mobile Apps (SOMA). The method used is the meCUE 2.0 framework, a relatively new and comprehensive framework for assessing a user experience application service. The MeCUE 2.0 framework contains a questionnaire consisting of 4 modules, namely Modul I & II (Perception of instrumental and non-instrumental product qualities), Modul III (Emotions), Modul IV (Consequences), and Modul V (Overall evaluation), with a total of 34 statements items. The first stage in this research, namely translating the meCUE 2.0 questionnaire and then distributing it to 60 respondents. So, the results measured using the meCUE 2.0 assessment can be given. The results of the calculation of the highest average value for PSMA are usability indicators (3.81), commitment (3.81), and product loyalty (3.83), and the lowest average value is on the status indicator (3.21), at SOMA the highest average value is the indicator commitment (3.21), positive emoticon (3.21) and product loyalty (3.4), and the average value on the negative emoticon indicator (1.86). The mean scores for the overall UX performance were 3.44 for PSMA and 3.07 for SOMA. This research contributes conceptually and practically by providing UX designers and policymakers recommendations to pay attention to important factors in the development of smart regency applications.
The Road Safety Literacy Strengthening Assistance For The Lentera Community (Orderly And Safe Literacy On The Highway) In Ponorogo Regency IY Rahmawati, MB Setyawan, AF Cobantoro, S Darihastining, T Wahyono, ... KENDURI: Jurnal Pengabdian dan Pemberdayaan Masyarakat 6 (1), 140-147 , 2026 2026
Assessing students’ readiness for artificial intelligence-based project learning to strengthen local wisdom values in Indonesia S Sutrisno, A Azis, MB Setyawan, DA Dewi, Y Hidayah, M Hakiki, ... Cogent Education 12 (1), 2582948 , 2025 2025 Citations: 12
Performance Evaluation of Apriori and FP-Growth Algorithms on Association Rule Mining Concept Map Propositions BA Umam, DD Prasetya, WSG Irianto, MB Setyawan, SM Saleh, ... 2025 2nd Beyond Technology Summit on Informatics International Conference … , 2025 2025
Student Engagement Prediction Using Deep Learning: Comparative Analysis of Unimodal and Multimodal Approaches MB Setyawan, DD Prasetya, T Widyaningtyas, BA Umam, SM Saleh 2025 2nd Beyond Technology Summit on Informatics International Conference … , 2025 2025
Implementation of RFID Technology as an Innovative Solution for Payment Systems in Supermarkets A Fajaryanto, MVDL Islami, R Arifin, MB Setyawan International Journal of Information Systems and Technology 1 (05), 242-251 , 2025 2025
Sistem Pendukung Keputusan Siswa terbaik MAN 2 Ponorogo berbasis Website menggunakan Metode Simple Additive Weight (SAW) AD Bimantoro, MB Setyawan, Y Litanianda KOMPUTEK 9 (2), 86-105 , 2025 2025
Implementasi Geofencing Dengan Algoritma Ray Casting Pada Aplikasi E-Presensi Pengajar Rumah Tahfidz Berbasis Android MOHRA HAKIM, AF Cobantoro, MB Setyawan SinarFe7 7 (1), 646-656 , 2025 2025
Implementasi Text Mining Pada Analisis SentimenPemain Naturalisasi Timnas Indonesia Dengan Algoritma Naïve Bayes dan Support Vector Machine (SVM) FT Widodo, MB Setyawan MEKAR: Journal Information System and Computer Application 1 (1), 8-15 , 2025 2025
Thresholding Value for Contour Segmentation Model in the Detection of Infected Plants with Drone Acquisition F Masykur, A Prasetyo, I Abdurrozaq, AF Cobantoro, AR Yusuf, ... Ingenierie des Systemes d'Information 30 (1), 221 , 2025 2025 Citations: 1
PENERAPAN ALGORITMA SEQUENTIAL SEARCH PADA CHATBOT WHATSAPP UNTUK LAYANAN PENGADUAN APLIKASI SMEP D Rahmawati, MB Setyawan, A Prasetyo Jurnal Media Elektro, 69-80 , 2024 2024 Citations: 3
SISTEM SKCK MENGGUNAKAN ALGORITMA SEQUENTIAL SEARCH DI POLSEK BARAT OP Sejati, MB Setyawan, A Prasetyo Universitas Muhammadiyah Ponorogo , 2024 2024
PENERAPAN ALGORITMA FISHER YATES PADA COMPUTER BASED TEST (CBT) DI SMK NEGERI PONCOL M Qohar, MB Setyawan, AF Cobantoro Universitas Muhammadiyah Ponorogo , 2024 2024
Pemanfaatan Trainer Internet of Things untuk meningkatkan Kompetensi Guru Vokasi Di SMK Negeri Poncol AR Yusuf, A Prasetyo, MB Setyawan GANESHA: Jurnal Pengabdian Masyarakat 4 (2), 221-229 , 2024 2024 Citations: 1
Prokes Warning Attendance System Dengan Kecerdasan Buatan Model Face Recognition Menggunakan Algoritma Haarcascade MB Setyawan, CW Aditya, AF Cobantoro, J Karaman Jurnal Sistem dan Teknologi Informasi (JSTI) 6 (2) , 2024 2024 Citations: 5
PENGENALAN APLIKASI OBYEK WISATA TELAGA NGEBEL BERBASIS VIRTUAL REALITY DAN ALGORTIMA GREEDY MB Setyawan, ADP Putra, K Sussolaikah, IA Zulkarnain, AF Cobantoro Jurnal Media Elektro, 45-52 , 2024 2024
Integration Of Open CV LBF Model To Detect Masks In Health Protocol Surveillance Systems Y Litanianda, MB Setyawan, A Fajaryanto, CW Aditya Journal of Computer Networks, Architecture and High Performance Computing 6 … , 2024 2024 Citations: 2
Building a secure digital future: Investigating cyber hygiene levels of accounting, finance, and business students F Eliza, R Fadli, Y Hidayah, MA Ramadhan, A Yassin, MB Setyawan Data and Metadata 3, 1-. 554 , 2024 2024 Citations: 4
Penerapan Algoritma Linear Search Di Aplikasi Secondhand ND Agustin, AF Cobantoro, MB Setyawan, K Nurfitri NERO (Networking Engineering Research Operation) 8 (2), 107-122 , 2023 2023 Citations: 13
Pemanfaatan Crowdfunding Untuk Optimalisasi Penggalangan Dana Digital Di Panti Asuhan Insan Madani Ponorogo MB Setyawan, F Masykur, AF Cobantoro Jurnal Pengabdian Masyarakat Bangsa 1 (6), 471-478 , 2023 2023
Analisis Implementasi Teknologi Pembelajaran di Bebas UMPO EP Nimasari, AF Cobantoro, SD Andika, MB Setyawan Jurnal Ilmiah Edutic: Pendidikan dan Informatika 9 (2), 162-177 , 2023 2023 Citations: 2
MOST CITED SCHOLAR PUBLICATIONS
Analisis Sentimen Pengguna Gopay Menggunakan Metode Lexicon Based Dan Support Vector Machine R Mahendrajaya, GA Buntoro, MB Setyawan Komputek 3 (2), 52-63 , 2019 2019 Citations: 93
Otomasi Greenhouse Berbasis Mikrokomputer RASPBERRY PI AF Cobantoro, MB Setyawan, MAB Wibowo Jurnal Ilmiah Teknologi Informasi Asia 13 (2), 115-126 , 2019 2019 Citations: 24
Application of message queuing telemetry transport (mqtt) protocol in the internet of things to monitor mushroom cultivation F Masykur, A Prasetyo, I Widaningrum, AF Cobantoro, MB Setyawan 2020 7th International Conference on Information Technology, Computer, and … , 2020 2020 Citations: 23
Penerapan model literasi digital berbasis sekolah untuk membangun konten positif pada internet J Karaman, I Widaningrum, MB Setyawan, S Sugianti Aksiologiya: Jurnal Pengabdian Kepada Masyarakat 5 (1), 19-29 , 2021 2021 Citations: 21
Knowledge Management System Analysis of Smart Regency Mobile-Apps Service with Software Usability Measurement Inventory (SUMI) Approach AK Darmawan, MB Setyawan, AF Cobantoro, F Masykur, A Anwari, ... 2021 International Conference on ICT for Smart Society (ICISS), 1-6 , 2021 2021 Citations: 18
Purwarupa Internet of Things Sistem Kewaspadaan Banjir Dengan Kendali Raspberry Pi A Prasetyo, MB Setyawan Network Engineering Research Operation 3 (3), 201-205 , 2018 2018 Citations: 18
Adaptation of the meCUE 2.0 Version for User Experience (UX) Measurement Approach into Indonesian Context AK Darmawan, MB Setyawan, AF Cobantoro, F Masykur, A Komarudin, ... 2021 Sixth International Conference on Informatics and Computing (ICIC), 1-6 , 2021 2021 Citations: 16
Analisis Sentimen Pengguna Gopay Menggunakan Metode Lexicon Based Dan Support Vector Machine. Komputek, 3 (2), 52 R Mahendrajaya, GA Buntoro, MB Setyawan 2019 Citations: 15
Penerapan Model Literasi Digital Berbasis Sekolah Untuk Membangun Konten Positif Pada Internet. Aksiologiya: Jurnal Pengabdian Kepada Masyarakat, 5 (1), 19–29 J Karaman, I Widaningrum, MB Setyawan, S Sugianti 2020 Citations: 14
Penerapan Algoritma Linear Search Di Aplikasi Secondhand ND Agustin, AF Cobantoro, MB Setyawan, K Nurfitri NERO (Networking Engineering Research Operation) 8 (2), 107-122 , 2023 2023 Citations: 13
Hoax news analysis for the Indonesian national capital relocation public policy with the support vector machine and random forest algorithms AK Darmawan, MW Al Wajieh, MB Setyawan, T Yandi, H Hoiriyah Journal of Information Systems and Informatics 5 (1), 150-173 , 2023 2023 Citations: 13
Implementasi Logika Fuzzy untuk Prediksi Hasil Panen Padi dengan Metode Tsukamoto S Nurkasanah, A Prasetyo, MB Setyawan Jurnal Rekayasa Teknologi dan Komputasi 1 (1), 25-36 , 2022 2022 Citations: 13
Assessing students’ readiness for artificial intelligence-based project learning to strengthen local wisdom values in Indonesia S Sutrisno, A Azis, MB Setyawan, DA Dewi, Y Hidayah, M Hakiki, ... Cogent Education 12 (1), 2582948 , 2025 2025 Citations: 12
Konstruksi jiwa kewirausahaan melalui pelatihan startup digital 4.0 bagi siswa sma MB Setyawan, A Alwi, M Munirah Jurnal Masyarakat Mandiri 2 (1), 19-28 , 2018 2018 Citations: 11
Rekayasa Aplikasi Eposal Menggunakan Algoritma Base64 Untuk Menyimpan Data Pengguna AF Cobantoro, MB Setyawan, H Oktavianto Jurnal Komtika (Komputasi dan Informatika) 7 (1), 31-38 , 2023 2023 Citations: 10
Predicting Smart Regency Readiness on Sub-Urban Area in Indonesia: A perspective of Technology Readiness Index 2.0 AK Darmawan, M Muhsi, MW Al Wajieh, MB Setyawan, A Komarudin, ... 2022 International Conference on ICT for Smart Society (ICISS), 01-06 , 2022 2022 Citations: 10
Epoch optimization on rice leaf image classification using Convolutional Neural Network (CNN) mobilenet F Masykur, MB Setyawan, K Winangun CESS (Journal of Computer Engineering, System and Science) 7 (2), 581-591 , 2022 2022 Citations: 10
Rancang Bangun IoT Smart Fish Farm Dengan Kendali Raspberry Pi Dan Webcam KY Nashrullah, MB Setyawan, AF Cobantoro KOMPUTEK 3 (1), 81-91 , 2019 2019 Citations: 9
Assessing and Enhancing an Existing User Experience (UX) of Smart Regency Mobile-Apps Service with meCUE 2.0 Framework AK Darmawan, MB Setyawan, B Bakir, M Walid, MA Hamzah, A Asir 2021 9th International Conference on Cyber and IT Service Management (CITSM … , 2021 2021 Citations: 8
Perancangan Aplikasi Data Alumni Sekolah Berbasis Web Di Sman 3 Ponorogo S Anwar, D Ariyadi, MB Setyawan KOMPUTEK 4 (1), 90-95 , 2020 2020 Citations: 8
