Article Per Year (5 Year)
p-Index From 2021 - 2026
8.72
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Sains dan Teknologi Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUITA : Jurnal Informatika Jurnal Sistem dan Informatika Journal of Information Systems Engineering and Business Intelligence E-Dimas: Jurnal Pengabdian kepada Masyarakat Format : Jurnal Imiah Teknik Informatika JOIV : International Journal on Informatics Visualization Tech-E Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal ULTIMA InfoSys Jurnal ULTIMATICS ComTech: Computer, Mathematics and Engineering Applications Jurnal Teknologi Komputer dan Sistem Informasi JISKa (Jurnal Informatika Sunan Kalijaga) Journal of Information Systems and Informatics bit-Tech eCo-Buss Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) Jurnal Teknik Informatika (JUTIF) International Journal of Digital Entrepreneurship and Business (IDEB) Algor eCo-Fin Abdi-Dharma SATIN - Sains dan Teknologi Informasi Inovasi Gagasan Abdimas & Kuliah Kerja Nyata RUBINSTEIN JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi) Jurnal Manajemen Kreatif dan Inovasi
Aditiya Hermawan
Universitas Buddhi Dharma
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Social Sciences Other

Published : 72 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 72 Documents
Search

 4   5   6   7   8 
A Systematic Review of Machine Learning and Deep Learning Techniques for Deepfake Image Detection: Trends, Challenges, and Future Directions Samuel Rhesa; Aditiya Hermawan
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 8 No. 1 (2026): Maret
Publisher : Universitas Wahid Hasyim

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

Abstract

The rapid development of deep learning based face manipulation techniques has produced synthetic images that are increasingly realistic and visually indistinguishable from authentic ones. The deepfake phenomenon poses serious challenges to digital information authenticity and cybersecurity. This research presents a Systematic Literature Review (SLR) of publications from the 2020–2025 period to map trends, methodological approaches, and key challenges in machine learning and deep learning based image deepfake detection. Through an analysis of 24 empirical studies, this review identifies a shift in research direction from conventional convolutional architectures toward hybrid and attention based approaches that emphasize efficiency, adaptivity, and cross domain generalization. Findings show that although recent models such as Vision Transformer and hybrid CNN–LSTM are capable of achieving high accuracy under controlled conditions, their performance remains limited when tested on new domains. Key challenges identified include limited generalization against new manipulation types, vulnerability to image distortion and compression, and low transparency in model decision-making. This study fills research gaps by providing a comprehensive methodological map of architectural evolution, feature representation strategies, and evaluation metrics. Theoretically, this research expands the understanding of deepfake detection research dynamics, while practically, the results provide direction for developing adaptive, transparent, and efficient detection systems for real-time implementation.
Pelatihan Membuat Presentasi Menarik Menggunakan Canva Untuk Anggota Penyuluh Agama Buddha Provinsi Banten Ardie Halim; Yo Ceng Giap; Raditya Rimbawan O; Wiyono; Andri Wijaya; Aditiya Hermawan; Jessen Laorenza Suwandi; Arvin Lawistra
Jurnal Igakerta Vol. 1 No. 4 (2024): Jurnal Igakerta
Publisher : IGAKERTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70234/h700cz90

Abstract

Pengabdian kepada masyarakat (PkM) yang dilakukan oleh tim dosen dan mahasiswa Fakultas Sains dan Teknologi Universitas Buddhi Dharma, Tangerang bertujuan untuk memberikan pelatihan dalam membuat  materi  pembelajaran  secara  interaktif  dan  inovatif  menggunakan  media  berbasis  digital canva  kepada  anggota  penyuluh  agama  Buddha  (PAH)  agar  dapat  membuat  materi  ceramah  yang sesuai  dengan  cara  yang  interaktif  dan  inovatif.  Metode  yang  digunakan  dalam  PkM  ini  adalah demontrasi  (peragaan),  praktikum  (membuat  materi  ceramah  secara  langsung  menggunakan komputer  di  laboratoriom  komputer  Universitas  Buddhi  Dharma)  dan  studi  kasus  (latihan  mandiri membuat materi presentasi yang dipandu oleh tutor). Hasil PkM ini adalah para anggota PAH dapat memperoleh  pemahaman  dan  pengetahuan  tentang  cara  membuat  slide  presentasi  dalam  beberapa bentuk seperti teks, gambar, audio, video dengan menggunakan canva, sehingga akan mempermudah dalam  penyampaian  materi  ceramah.  Hal  ini  terlihat  dari  hasil  kuesioner  dengan  persentase  74% peserta  sangat  setuju  bahwa  materi  yang  disampaikan  sangat  bermanfaat  dan  dapat  dipraktekkan untuk mendukung pembuatan materi presentasi
Trends and Keyword Networks in Machine Learning-Based Click Fraud Detection Research Kevin Kevin; Aditiya Hermawan
ULTIMATICS Vol 17 No 2 (2025): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v17i2.4131

Abstract

The rapid advancement of the digital economy has significantly increased the use of online advertising while concurrently giving rise to critical challenges, particularly in the form of click fraud”a manipulative act that harms advertisers by generating fraudulent clicks on digital advertisements. As click fraud attack patterns grow increasingly complex, machine learning (ML)-based research has emerged as a principal approach for detecting and mitigating these threats. This study aims to map the research landscape of ML-based click fraud detection through a bibliometric analysis to identify publication trends, patterns of international and institutional collaboration, and key thematic domains within this field. Employing a bibliometric methodology, the study analyzed 61 publications retrieved from Dimensions.ai spanning the years 2015–2024. The data were collected, refined using OpenRefine, and visualized with VOSviewer to examine keyword co-occurrences and research trends. The findings reveal a marked increase in publication volume since 2019, with dominant contributions from India, China, Saudi Arabia, and the United States. Furthermore, four principal research clusters were identified: cybersecurity, the relationship between click fraud and the digital advertising industry, dataset processing and evaluation techniques, and the development of ML-based detection systems. Each cluster offers practical contributions in areas such as system protection strategies, ad budget optimization, improved detection accuracy, and the development of scalable, real-time detection solutions. Recent trends highlight growing scholarly interest in model performance evaluation and the challenges posed by class imbalance (class skewness). This study concludes that more effective data management and the development of adaptive ML models capable of addressing evolving attack patterns are pivotal for future research. By providing a clearer mapping of current trends, this study aims to support the scientific community in developing more accurate and efficient click fraud detection strategies, thereby strengthening the integrity of the global digital advertising ecosystem.
Multimodal Wearable-Based Stress Detection Using Machine Learning: A Systematic Review of Validation Protocols and Generalization Gaps (2021 – 2025) Pannavira; Aditiya Hermawan
ULTIMATICS Vol 17 No 2 (2025): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v17i2.4488

Abstract

Stress is a major determinant of mental health and productivity. Consequently, continuous, unobtrusive stress detection using wearable sensors and machine learning (ML) has become a key priority in digital health. This paper presents a Systematic Literature Review (SLR) of 19 peer-reviewed articles, selected from 36 initial papers via structured inclusion/exclusion criteria focusing on studies from 2021-2025 that report quantitative ML performance. We employed a quantitative and qualitative synthesis to analyze and map five key dimensions: sensing modalities, ML/DL algorithms, datasets, validation protocols, and societal feasibility. Findings reveal a clear state-of-the-art: multimodal physiological fusion (notably PPG, EDA, and ACC) paired with hybrid deep models (CNN-LSTM) consistently achieves the highest accuracy (85–96%) on benchmark datasets. Our research reveals a significant lab-to-field gap. Most studies utilize intra-subject or k-fold cross-validation, whereas the more robust Leave-One-Subject-Out (LOSO) validation is hardly employed, constraining model applicability. Furthermore, fewer than 15% of studies explicitly address vital practical constraints such as privacy, computational efficiency (Edge AI), or power consumption. This review methodically quantifies the gap, emphasizing that current models, despite their accuracy, are not yet suitable for real-world implementation. We conclude with actionable directions toward generalizable, lightweight, and privacy-aware stress-aware systems.
Penguatan Literasi Digital Pendidik Agama Buddha melalui Pelatihan Terintegrasi ChatGPT dan Canva: Evaluasi Pretest–Posttest pada Komunitas PERGABI Aditiya Hermawan; Lianny Wydiastuty; Hartana Wijaya; Santa Margita
Abdi Dharma Vol. 6 No. 1 (2026): Jurnal Abdi Dharma (Jurnal Pengabdian Masyarakat)
Publisher : LP3kM Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/ad.v6i1.4409

Abstract

Perkembangan pesat kecerdasan buatan generatif (Artificial Intelligence/AI) dan platform desain visual telah mengubah praktik pedagogis; namun, bukti empiris mengenai pelatihan terintegrasi berbasis praktik dalam konteks pendidikan keagamaan masih terbatas. Penelitian ini mengevaluasi program pengabdian kepada masyarakat yang bertujuan meningkatkan literasi digital pendidik agama Buddha yang tergabung dalam PERGABI melalui pelatihan terstruktur penggunaan ChatGPT dan Canva. Intervensi dirancang dengan pendekatan praktik langsung, meliputi teknik prompt engineering untuk penyusunan materi ajar berbantuan AI serta perancangan media pembelajaran visual menggunakan Canva. Desain penelitian menggunakan one-group pretest–posttest untuk mengukur perubahan tingkat familiaritas, kepercayaan diri instruksional, dan persepsi kemudahan penggunaan kedua perangkat tersebut. Data dikumpulkan melalui kuesioner daring sebelum dan sesudah pelatihan selama enam jam. Hasil analisis deskriptif dan komparatif menunjukkan peningkatan konsisten pada seluruh indikator. Familiaritas terhadap AI meningkat dari tingkat sedang menjadi tinggi, dengan lonjakan terbesar terjadi pada kepercayaan diri dalam memanfaatkan AI untuk kegiatan pembelajaran. Peningkatan juga terjadi pada penggunaan Canva, meskipun relatif lebih kecil karena tingkat familiaritas awal yang sudah tinggi. Peserta melaporkan tingkat kepuasan yang tinggi dan menilai pelatihan relevan dengan praktik pengajaran. Meskipun demikian, keterbatasan akses perangkat dan kestabilan internet menjadi hambatan implementasi. Temuan ini menegaskan bahwa pelatihan digital terintegrasi mampu menurunkan persepsi kompleksitas AI dan mempercepat adopsi pedagogis. Dukungan institusional berkelanjutan dan evaluasi longitudinal diperlukan untuk memastikan dampak pembelajaran jangka panjang.
Ethical Dimensions of Artificial Intelligence in the Digital Entrepreneurship Ecosystem: A Systematic Literature Review Salman Alfarisi; Adith Aulia Rahman; Zaqi Kurniawan; Aditiya Hermawan; Yan Everhard Riwurohi
RUBINSTEIN Vol. 4 No. 2 (2026): RUBINSTEIN (juRnal mUltidisiplin BIsNis Sains TEknologI & humaNiora)
Publisher : LP3kM Buddhi Dharma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/rubin.v4i2.4580

Abstract

The rapid adoption of artificial intelligence (AI) in digital entrepreneurship has created new opportunities for innovation, efficiency, and data-driven decision-making, while simultaneously raising ethical concerns related to fairness, transparency, privacy, accountability, and explainability. This study presents a systematic literature review to examine the ethical dimensions of AI within the digital entrepreneurship ecosystem. Guided by the PRISMA 2020 protocol and the PICO framework, searches were conducted across Web of Science, Scopus, and IEEE Xplore for studies published between 2020 and 2026. From 512 initially identified articles, 24 studies met the inclusion criteria and quality assessment requirements. The selected studies were analyzed using thematic coding, narrative synthesis, and quality-based evidence mapping to identify recurring ethical dimensions, operational mechanisms, and governance gaps. The findings reveal four dominant ethical problem clusters: algorithmic fairness in entrepreneurial decision-making, transparency deficits in black-box AI systems, data privacy and cybersecurity vulnerabilities, and weak accountability mechanisms in AI governance. The review further shows that responsible AI frameworks, explainability techniques, bias audits, data governance protocols, and risk-based regulatory approaches are central mechanisms for translating ethical principles into practice. The findings contribute to responsible AI scholarship, digital entrepreneurship governance, and policy-oriented debates by offering practical guidance for entrepreneurs, regulators, and researchers concerned with ethical AI adoption in resource-constrained business environments. This study provides an evidence-based roadmap for strengthening ethical, accountable, and socially responsible AI implementation in digital entrepreneurship ecosystems.
Perceived Trust as Mediator of Impulsive Buying in Live Streaming Commerce Aditiya Hermawan; Yanti Pusparini; Eso Hernawan
eCo-Buss Vol. 9 No. 1 (2026): eCo-Buss
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/eb.v9i1.4005

Abstract

This study aims to analyze the influence of streamer characteristics, interactions with other viewers, and product presentation on impulsive buying in live streaming commerce, with perceived trust serving as a mediating variable. The study adopts the Stimulus-Organism-Response (S-O-R) framework to explain how external stimuli in digital shopping environments shape consumers’ psychological states and encourage spontaneous purchasing responses. A quantitative approach was employed through a survey of 338 live streaming commerce users in Indonesia who had prior shopping experience through live streaming features. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 3.0 and a bootstrapping procedure involving 5,000 subsamples. The findings reveal that streamer characteristics, interactions with other viewers, and product presentation significantly influence perceived trust. These three stimuli also have significant effects on the urge to buy impulsively. In addition, perceived trust is shown to positively influence impulsive buying and mediate the relationship between live streaming commerce stimuli and impulsive buying behavior. These findings affirm that trust is not merely a supporting factor, but a central psychological mechanism that links interactivity, credibility, and information transparency with spontaneous purchasing decisions. Practically, this study suggests that e-commerce practitioners should strengthen streamer credibility, encourage positive social interaction, and provide clear product demonstrations to enhance consumer engagement, reduce uncertainty, and improve the sustainable effectiveness of live streaming commerce strategies.
Aplikasi E-voting Berbasis Blockchain dengan Metode Smart Contract Junaedi Junaedi; Albert Fernando; Aditiya Hermawan
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 2 (2024): September
Publisher : Universitas Wahid Hasyim

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

Abstract

Voting is an important process in many contexts, such as in organizational decisions and the selection of leaders. With the development of technology, the concept of electronic voting emerged, where humans can cast their votes electronically. Electronic voting has become an important alternative in organizational decision making and leader selection, but often faces challenges related to security and fraud. In this study, a blockchain-based electronic voting application has been developed using the Smart Contract method. Blockchain technology was chosen because of its decentralized and public nature, which can provide a high level of security and transparency to voting data. Evaluation of the application was carried out through a questionnaire filled out by 39 respondents. The results showed a high level of agreement, with 91.46% of respondents stating that they strongly agreed with the effectiveness of this application. This indicates that the implementation of a blockchain-based electronic voting system has the potential to increase trust and integrity in the election process. In addition, this application also offers easy access and data transparency, which is expected to increase public participation in the democratic process. By continuing to conduct further research and development, this blockchain-based electronic voting application has great potential to become the standard in future elections.
A Hybrid Conversational Tourism Recommender Integrating Collaborative and Content-Based Filtering: Design and Evaluation on a Sparse Google Maps Review Dataset Robert Ananda Aritonang; Aditiya Hermawan; Junaedi Junaedi; Riki Riki; Satria Abadi
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 5 (2026): JUTIF Volume 7, Number 5, October 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.5.5644

Abstract

Tourism recommendation systems frequently encounter extreme data sparsity, cold-start problems, and limited personalization when relying solely on either collaborative or content-based approaches, particularly in real-world review platforms where user–item interactions are unevenly distributed. Such conditions reduce prediction reliability and weaken the practical usefulness of recommendation outputs. This study aims to design and empirically evaluate a hybrid conversational tourism recommender that improves recommendation accuracy and ranking relevance under sparse data conditions. The proposed framework integrates collaborative filtering and content-based filtering within a hybrid architecture, combining interaction-driven preference learning with textual content modeling derived from user reviews. The recommendation engine is operationalized through a conversational chatbot interface to support interactive preference elicitation and real-time recommendation delivery. The system is evaluated using a Google Maps review dataset characterized by high sparsity. Model performance is assessed using rating prediction metrics and top-K ranking metrics to ensure comprehensive evaluation. Experimental results indicate that the hybrid model achieves a Root Mean Squared Error of 0.6985 and a Mean Absolute Error of 0.5448, outperforming standalone collaborative and content-based models. In top-10 recommendation evaluation, the model attains Precision@10 of 0.52, Recall@10 of 0.91, and F1-score@10 of 0.66, demonstrating improved relevance and coverage. These findings highlight the effectiveness of hybrid conversational integration in mitigating sparsity-related limitations and provide practical implications for scalable, data-driven personalization in digital tourism platforms.
Hubungan Motivasi Belajar, Keterampilan Komunikasi, dan Dukungan Orang Tua terhadap Kesiapan Kerja Generasi Muda di SMAK Kasih Anugrah Kelas XII Helen Griselda; Aldi Aditiya Hermawan; Imam Hidayat; Maria Goreti Mona Lako; Nisfu Ramadhan Ayatullah Habibi; Siti Zahrani Irawan; Rifkhan Rifkhan
Jurnal Manajemen Kreatif dan Inovasi Vol. 4 No. 1 (2026): Januari : Jurnal Manajemen Kreatif dan Inovasi
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jmki-widyakarya.v4i1.5864

Abstract

The high unemployment rate in Indonesia highlights the importance of enhancing work readiness among young people from an early educational stage. Work readiness is influenced by several factors, including learning motivation, communication skills, and parental support. This study aims to examine the relationship between learning motivation, communication skills, and parental support with work readiness among twelfth-grade students at SMAK Kasih Anugrah. This research employed a quantitative approach with a cross-sectional design. The population consisted of all 30 twelfth-grade students, and a saturated sampling technique was applied. Data were collected using structured questionnaires and analyzed through univariate and bivariate analysis using the Chi-Square test. The results indicate a significant relationship between learning motivation and work readiness (p-value = 0.021), communication skills and work readiness (p-value = 0.014), and parental support and work readiness (p-value = 0.005). These findings suggest that learning motivation, communication skills, and parental support play a crucial role in improving students’ readiness to enter the workforce. The results of this study are expected to provide practical implications for schools and parents in strengthening students’ preparation for the world of work
Co-Authors A Damiyati Abidin Abidin Adith Aulia Rahman Agus Setiawan Albert Fernando Alvin Rahayu Amin Suyitno Andre Sahulata Andri Wijaya Andrie Suak Tiwa Anton Halim Anwan Chailes Aprilyanti, Rina Ardiane Rossi Kurniawan Maranto Ardiane Rossi Kurniawan Maranto Ardie Halim Arvin Lawistra Benny Daniawan Benny Daniawan Berlian, Pio Putra Budi Susilo Ceng Giap, Yo Culadi, Rafael Daniel Daniawan, Benny Dera Susilawati Desman Hidayat Deviastati Putri Sugiarta Karlim Edy edy Edy Edy Edy Edy Edy Edy Edy Edy Elfindah Princes Ellysha Dwiyanthi Kusuma Eso Hernawan Eva Eva Evan - Evien Fadeli Muhammad Habibie Fernando, Albert Gustayo, Teven Halim Wijaya, Ardie Hargiani, Fransisca Xaveria Hartana Wijaya Helen Griselda Henry Henry Indira Tyas Widyastuti Indrawan Intan Anjali Putri Jelvin Putra Halawa Jessen Laorenza Suwandi Joese Nathaniel Johan Santoso Jowensen, Indrico JUNAEDI Junaedi Junaedi Junaedi Junaedi Junaedi Junaedi Junaedi Junaedi Junaedi Kevin Ivone Sim Kevin Kevin Kevin Kevin Khanti Kusuma Dewi Kristen Kumala, Sonya Ayu Kurnia , Yusuf Kurniawan Maranto, Ardiane Rossi Leonardo Lianata Lianny Wydiastuty Lianny Wydiastuty Kusuma Lidya Lunardi Luis Alpianto Lunardi, Lidya Mampow, Vanessa Keysa Immanuela Maranto, Ardiane Rossi Kurniawan Margaretha Natalya Maria Goreti Mona Lako Mariana Purnamasari Mesakh Septiadi Simijaya Michael Sidharta Dharma michael vernannes marpaung Nandivadhano, Revatta Manggala Nathaniel Felix Fraderic Nathaniel, Joese Nazzua Azzahra Niki Destiandi Nisfu Ramadhan Ayatullah Habibi Oscar Hasan Putra Pannavira Philip Kristy Wijaya Qurrohman, Taufik Raditya Rimbawan O Raditya Rimbawan Oprasto Ramadhani, Tyas Ayu Rheza Vincentius Rico Yusuf RIFKHAN RIFKHAN Riki Riki Riki Riki Riki Riki RIKI RIKI, RIKI Rino Rino Rino Rino Robert Ananda Aritonang Rossi , Ardiane Rossi Kurniawan Maranto, Ardiane Rossi Salman Alfarisi Samuel Rhesa Santa Margita Satria Abadi Satria Abadi Sevtian Ferdian Shofa, Ghina Zahira Siska Damayanti Siti Zahrani Irawan Sonya Eliesse Dameria Stanley Ananda Sutopo, Prihantoro Syahdu Suwitno Tia Nurapriyanti Umarkhon Mukhamedov Wicaksono, Baghas Budi Willy Wijaya, Willy Wiyono Wydiastuty Kusuma, Lianny Yan Everhard Riwurohi Yance Gusnadi Yanti Pusparini Yanti, Lia Dama Yo Ceng Giap Yo Ceng Giap Yuliastati Putri Sugiarta Karlim Yunia Oktari Yusuf Kurnia Yusuf Kurnia Yusuf Kurnia, Yusuf