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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Jurnas Nasional Teknologi dan Sistem Informasi Journal of Information Systems Engineering and Business Intelligence Jurnal Kajian Informasi & Perpustakaan Edcomtech Jurnal Kajian Teknologi Pendidikan Policy & Governance Review Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Journal of Government and Civil Society Masyarakat Telematika Dan Informasi : Jurnal Penelitian Teknologi Informasi dan Komunikasi Jurnal Teknoinfo Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Informatika Ekonomi Bisnis Jurnal Teknik Informatika (JUTIF) Abditeknika - Jurnal Pengabdian Kepada Masyarakat Asian Management and Business Review ETNIK : Jurnal Ekonomi dan Teknik Jurnal Impresi Indonesia Journal of Business, Social and Technology Eduvest - Journal of Universal Studies Jurnal Informatika Ekonomi Bisnis International Journal of Multidisciplinary Research of Higher Education (IJMURHICA) The Indonesian Journal of Computer Science Scientific Journal of Informatics
Lusa, Sofian
Fakultas Teknologi Informasi, Ilmu Komputer, Universitas Budi Luhur
Religion Aerospace Engineering Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Neuroscience Social Sciences Other

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Factors Influencing the Adoption of Multi Factor Authentication in the Public Sector: A Case Study of Indonesia National Single Window Agency Purnomo, Dencaswo; Ghaisani, Amanda; Sensuse, Dana Indra; Lusa, Sofian; Ramlan, Nurcholis; Indrawati, Nur
The Indonesian Journal of Computer Science Vol. 15 No. 2 (2026): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v15i2.5091

Abstract

This study aims to examine the factors that influence the intention and actual use of Multi-Factor Authentication (MFA) in the National Single Window Agency (LNSW). The research model integrates the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) with the addition of the Perceived Security (PS) construct. Data were collected from employees and vendor teams at the LNSW and analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method. The results show that Perceived Ease of Use (PEOU) and Social Influence (SI) have a positive and significant effect on Behavioral Intention (BI). In addition, Perceived Security (PS) does not have a direct effect on Behavioral Intention, but it has a significant positive effect on Perceived Usefulness (PU). Other findings show that Behavioral Intention (BI) is a strong predictor of Actual Usage (AU) of MFA. These results confirm the relevance of the TAM and UTAUT models in explaining the adoption of security technology in the public sector, and emphasize the importance of ease of use and organizational influence in encouraging the adoption of MFA
User Acceptance Research on The Legal Documentation and Information Network Platform in Majalengka Government Hudoarma, Fathurahman Ma'ruf; Sensuse, Dana Indra; Lusa, Sofian; Putro, Prasetyo Adi Wibowo
The Indonesian Journal of Computer Science Vol. 12 No. 4 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i4.3279

Abstract

The evaluation of JDIH platform's user acceptance in accessing legal documentation and information has not been conducted, resulting in an average visitation rate of only 15%. The objective of this study is to identify the factors that influence user acceptance of the JDIH platform and provide recommendations for enhancing visitor traffic to the JDIH platform. This study was conducted using a mixed methods approach, incorporating the Technology Acceptance Model as its foundational theory and integrating the Innovation Diffusion Theory, DeLone & McLean IS Success Model, and Habit variables as its external constructs. The quantitative data processing method was conducted using the PLS-SEM method with the assistance of the SmartPLS application. The findings of this study reveal that the factors of relative advantage, habit, perceived benefits of use, and intention to use significantly influence user acceptance in utilizing the JDIH platform.
Assessing Service Quality in Passport Application Mobile Apps(M-Paspor) and its Influence on User Satisfaction: A Case Study using e-GovQual Yaziji, Warda; Aprilia, Relaci; Sensuse, Dana Indra; Lusa, Sofian; Wibowo, Prasetyo Adi
The Indonesian Journal of Computer Science Vol. 12 No. 6 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i6.3545

Abstract

Technological advances in this era can support public services to serve the public more quickly and responsively. One of the electronic public services used by citizens in Indonesia is the application for a passport. After launching to the public in early 2022, the mobile app M-Paspor is still experiencing some obstacles. This study aims to get recommendations for government consideration based on public experience as users of the M-Paspor application. This study integrates the e-Govqual model initiated by Papadomichelaki & Mentzas and End User Computing Satisfaction by Doll & Tork Zadeh. Six dimensions are used: ease of use, trust, functionality of the interaction environment, reliability, content and appearance of information, and citizen support. With the questionnaire distributed through social media, we analyzed data from 111 respondents. We conducted an analysis using SmartPLS to validate the survey. The result implied that Citizen Support, Functionality of the Interaction Environment, and Reliability significantly influence End User Computing Satisfaction of M-Paspor users
Strengthening Security Awareness in the Era of Artificial Intelligence-Based Cyber Threats Patria, Nusandika; Amir, Sopian; Sensuse, Dana Indra; Lusa, Sofian; Indrawati, Nur; Ramlan, Nurcholis
International Journal of Multidisciplinary Research of Higher Education Vol 9 No 2 (2026): (April) Theme Education, Religion Studies, Social Sciences, STEM and Economic Dev
Publisher : Islamic Studies and Development Center in Collaboration With Students' Research Center Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Artificial intelligence (AI) is developing rapidly and is increasingly being applied in various fields, including cybersecurity. However, this development also introduces new, more sophisticated threats that are difficult to detect. AI-based cyber threats, including adaptive malware, highly personalized phishing, deepfakes for identity manipulation, adaptive distributed denial of service (DDoS) attacks, and automated ransomware, are projected to escalate by 2025. These threats' complexity requires a security approach that relies not only on technology but also on human awareness as the first line of defense. In Indonesia, the 2024 Cybersecurity Landscape Report, published by the National Cyber and Crypto Agency (BSSN), shows that public and institutional awareness of information security is still relatively low. This study presents a systematic literature review of 30 articles to examine how security awareness is being strengthened in the context of AI-based cyber threats. The review identified six main categories of AI enabled threats social engineering and phishing, content manipulation and impersonation, malware and ransomware, attacks against machine learning models, service disruption, and automated AI-orchestrated attacks. In parallel, seven categories of awareness strategies were synthesized: education and training programs, gamification and simulation-based learning, policy and governance support, technical and system-level controls, collaboration and multi-stakeholder engagement, legal and ethical frameworks, and psychological or human-centric approaches. The findings highlight that strengthening security awareness requires an integrated and multidimensional approach that bridges technological, organizational, regulatory, and human-centered efforts.
Analysis of Public Sentiment Indonesia’s Personal Data Protection Law: A Comparison of SVM and IndoBERT on X Platform Kurniawati, Yulia; Hamid, Ricky Bahari; Sensuse, Dana Indra; Lusa, Sofian; Putro, Prasetyo Adi Wibowo; Indriasari, Sofiyanti
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 2 (2026): JUTIF Volume 7, Number 2, April 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.2.5415

Abstract

The high number of data misuses, thefts, and leaks led to the enactment of the PDP Law, which regulates the rights and obligations of data owners and electronic system providers. The purpose of this study is to examine the public’s response to the implementation of the law through the X platform, using tweet harvest as a scraping tool, and to evaluate model performance through a comparative approach between SVM and BERT. The feature extraction used in this study is TF-IDF for SVM and BERT with IndoBERT. The accuracy results indicate that BERT is better with an accuracy of 86% compared to SVM with a training and test data ratio of 85:15. This advantage is because BERT can understand linguistic context that SVM cannot. On the other hand, SVM has advantages in computational efficiency and faster processing, making it a suitable choice in situations with limited computational resources. The sentiment analysis result revealed that data protection,  digital footprint and the institution's role were the most frequently discussed topics. Furthermore, periodic or real-time evaluations can be conducted on the public's response to the PDP Law to ensure it remains aligned and relevant to technological developments and societal needs.
Factors Influencing Generative AI Adoption in Government: A Case Study in BPS-Statistics of Indonesia Sayyidah, Mutia; Lusa, Sofian; Rizki, Muhammad; Ramlan, Nurcholis; Sensuse, Dana Indra
Jurnal Impresi Indonesia Vol. 5 No. 4 (2026): Jurnal Impresi Indonesia
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jii.v5i4.7666

Abstract

Rapid technological developments hold great potential, one of which is generative AI. Technology that is easily accessible and user-friendly tends to spread quickly, and BPS-Statistics of Indonesia is no exception. The challenges currently faced by BPS-Statistics of Indonesia, such as rapid data growth, high data demand, and data analysis and representation, encourage the institution to be adaptive to new technologies that can accelerate work processes. This research aims to determine the factors influencing the acceptance and use of generative AI (GenAI), such as ChatGPT, Gemini, and others, among BPS-Statistics of Indonesia employees, using Behavioral Intention as the central mediating variable that bridges the influence of these predictor factors on Use Behavior. The model also examines the relationships between external factors, such as Social Influence and Trust, and Perceived Usefulness and Perceived Ease of Use, as well as their effects on Attitude. Additionally, it evaluates the influence of Hedonic Motivation, Facilitating Conditions, Perceived Severity, and Perceived Vulnerability on Behavioral Intention. Based on a survey of 166 respondents at BPS-Statistics of Indonesia, the results reveal that Attitude has a significant influence on Behavioral Intention, while Perceived Severity has a significant negative influence on Behavioral Intention. Furthermore, Behavioral Intention is also shown to have a significant positive influence on Use Behavior. These findings contribute theoretically to the development of technology adoption models in the public sector and have practical implications for BPS-Statistics of Indonesia in formulating AI usage policies.
Systematic Literature Review (SLR) Model LRFM dan Pengelompokan K-Means untuk Strategi Retensi Pelanggan B2B Apriyana, Yeni; Trimanadi, Raden; Sensuse, Dana Indra; Lusa, Sofian
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 13 No 2: April 2026
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.132

Abstract

Dalam era persaingan pasar yang semakin ketat, strategi retensi pelanggan berbasis data menjadi krusial, khususnya dalam konteks Business-to-Business (B2B) yang masih relatif terbatas dibahas dalam literatur. Penelitian ini merupakan Systematic Literature Review (SLR) yang bertujuan untuk memetakan dan mensintesis penelitian terkait penerapan model LRFM (Length, Recency, Frequency, Monetary) dan algoritma K-Means dalam strategi retensi pelanggan. Model metodologi SLR mengikuti protokol Kitchenham et al. (2009) melalui tahapan perumusan pertanyaan penelitian, pencarian literatur, seleksi studi, dan sintesis hasil. Hasil kajian menunjukkan bahwa sebagian besar penelitian LRFM dan K-Means masih berfokus pada konteks B2C, sementara penerapannya dalam lingkungan B2B relatif terbatas dan belum terkonseptualisasi secara memadai. Berdasarkan kesenjangan tersebut, artikel ini mengusulkan kerangka konseptual LRFM-B2B sebagai agenda penelitian masa depan dengan mempertimbangkan karakteristik spesifik B2B, tanpa dilakukan pengujian atau analisis empiris. Penelitian ini berkontribusi pada pemetaan literatur, identifikasi kesenjangan riset, serta perumusan arah pengembangan analitik pelanggan dalam konteks B2B.   Abstract In an era of increasingly intense market competition, data-driven customer retention strategies have become crucial, particularly in the Business-to-Business (B2B) context, which remains underexplored in the existing literature. This study presents a Systematic Literature Review (SLR) that aims to map and synthesize prior research on the application of the LRFM (Length, Recency, Frequency, Monetary) model and K-Means clustering for customer retention strategies. The review follows the Kitchenham et al. (2009) protocol, including research question formulation, literature search, study selection, and result synthesis. The findings indicate that most existing studies focus on B2C contexts, while B2B applications remain limited and conceptually underdeveloped. Based on the identified research gaps, this article proposes a conceptual LRFM-B2B framework as a future research agenda by incorporating B2B-specific characteristics such as contractual value and relationship depth. PT. XYZ is included solely as an illustrative case to contextualize general B2B challenges, without conducting any empirical testing or data analysis. This study contributes by providing a structured literature mapping, identifying critical research gaps, and outlining directions for future B2B customer analytics research.
Pemetaan Topik dan Sentimen Pengguna Aplikasi JAKI untuk Mendukung Knowledge Discovery dalam Peningkatan Layanan Publik Asykar, Mahmud Ali; Saddam, Muhammad; Sensuse, Dana Indra; Lusa, Sofian; Safitri, Nadya; Elisabeth, Damayanti
Jurnal Nasional Teknologi dan Sistem Informasi Vol 12 No 1 (2026): April 2026
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v12i1.2026.18-25

Abstract

Dalam era tata kelola digital, aplikasi mobile seperti JAKI (Jakarta Kini) memainkan peran penting dalam menyediakan layanan publik terintegrasi bagi masyarakat. Di sisi lain, Google Playstore menyimpan banyak ulasan pengguna yang mencerminkan pengalaman, preferensi, dan keluhan pengguna. Oleh karena itu, penelitian ini bertujuan untuk menganalisis umpan balik dari Google Playstore yang bertujuan untuk mengungkap tren sentimen dan topik pembahasan utama yang berkaitan dengan aplikasi JAKI. Dataset yang digunakan terdiri dari 3.895 ulasan pengguna yang telah melalui proses pembersihan data, kemudian diolah menggunakan kombinasi analisis sentimen dengan InSet Lexicon dan pemodelan topik menggunakan Latent Dirichlet Allocation (LDA). Hasil klasifikasi sentimen selanjutnya dievaluasi menggunakan algoritma Naive Bayes, dengan tingkat akurasi keseluruhan sebesar 65%. Hasil survei validasi pengguna menunjukkan bahwa sebagian besar topik yang dihasilkan sesuai dengan pengalaman nyata pengguna. Selain itu, rekomendasi perbaikan dirumuskan berdasarkan topik dengan sentimen netral dan negatif. Temuan ini berkontribusi pada pemahaman yang lebih baik mengenai persepsi pengguna, serta memberikan wawasan yang dapat ditindaklanjuti untuk mendukung pengembangan berkelanjutan layanan publik digital yang berorientasi pada warga Jakarta.
Co-Authors Abdullah, Puja Putri Aditya, Silfa Kurnia Alfiani, Husna Altino, Iqbal Caraka Amir, Sopian Anditama, Muhammad Rizky Andriansyah, Chandra Ansis, Ronny Aprilia, Relaci Apriyana, Yeni Ariani, Septi Assaf Arief, Assaf Asykar, Mahmud Ali Azhari Rangkuti, Herry Baskoro, Aji Brillianto, Bramanti Cahyaningsih, Elin Dana Indra Sensuse Dea Valentina Devit Setiono Editha Putri, Sabrina Elisabeth , Damayanti Elisabeth, Damayanti Erisa Rizkyani Eva Hidayati, Isnina Farhan Fitriya, Ghina Ghaisani, Amanda Hadjar, Siti Hamid, Ricky Bahari Handoko, Lutvianto Pebri Hudoarma, Fathurahman Ma'ruf Husain Husain Inayah, Suci - Indra Sensuse , Dana Indra Sensuse, Dana Indra, Muhammad Nadhirsyah Indriasari , Sofiyanti Indriasari, Sofianti Iriyanti, Iindra Irmayani, Irni Jallow , Fatoumatta Binta Jannah, Miskol Jasir, Khalid Khusnu Perdani, Mizana Kunto D.A , Himawan Kurnia Aditya, Silfa Masbudi, Handika Muhammad Rizki Mutia Mayanda , Alia Nadya Safitri Nadya Safitri, Nadya Nur Chasanah Nur Chasanah Nur Indrawati, Nur Nurcholis Ramlan Nuswantara, Prasetya Gilang Patria, Nusandika Pradipta, Dhea Junestya Prasetyo Adi Prasetyo Adi Wibowo, Prasetyo Adi Prastowo, Rahardito Dio Pratiwi, Maharani Eka Prima, Pudy Purnomo, Dencaswo Putri, Sabrina Editha Putro , Prasetyo Adi Wibowo Putro, Prasetyo Adi Wibowo Raafigustina, Try Annisa Ramadhan, Yudistira Richi R. Siregar, Jani Ridwan Afandi Rina Rahmawati, Rina Riri Satria Rizki Kurniawan, Rizki Rizky, Fajar Ruliputra, Ricky Nauvaldy Saddam, Muhammad Samidi Samidi, Samidi Saputro, Singgih Dwi Sayyidah, Mutia Sensuse, Dana I. Sihombing , Boy Sandi Kritian Sinaga, Andri Parulian Sitompul, Sabar Sofiyanti Indriasari Sudarto, Reska Nugroho Tereuri, Shabrina Trimanadi, Raden Vinc, Richard Wibowo Putro, Prasetyo Adi Wibowo, Wahyu Setyawan Yaziji, Warda Yulia Kurniawati