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All Journal ELINVO (Electronics, Informatics, and Vocational Education) Voice Of Informatics YUME : Journal of Management JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Syntax Idea International Journal of Advances in Data and Information Systems Jurnal Abdidas Dinasti International Journal of Economics, Finance & Accounting (DIJEFA) Economics and Digital Business Review Informatics and Digital Expert (INDEX) Jurnal Abmas Negeri (JAGRI) Jurnal Minfo Polgan (JMP) Jurnal Algoritma Data Sciences Indonesia (DSI) Journal of Artificial Intelligence and Digital Business Jurnal Masyarakat Madani Indonesia IIJSE Jurnal Pengabdian Nasional (JPN) Indonesia Jurnal Ilmu Komputer dan Informatika Journal of Business and Information System
Nugraha, Muhammad Rizki
Program Studi Bisnis Digital, Universitas Pendidikan Indonesia, Indonesia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Physics Public Health Social Sciences Other

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Deteksi Komentar Spam Judi Online Berbahasa Indonesia Menggunakan XGBoost dan TF-IDF Arrayyan, Dzakwan Rafi; Guntara, Rangga Gelar; Nugraha, Muhammad Rizki
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.3012

Abstract

The phenomenon of online gambling continues to show growth with increasingly worrying trends. One of the challenges faced is the proliferation of gambling promotional comments on the YouTube platform due to the suboptimal performance of spam detection systems in recognizing manipulative language patterns. To address this issue, this study proposes a model for detecting spam comments in Indonesian using a combination of Term Frequency–Inverse Document Frequency (TF-IDF) and Extreme Gradient Boosting (XGBoost). The dataset contains 10,220 YouTube comments that have been manually labeled and processed through preprocessing stages, including unicode normalization and cleaning of irrelevant characters. The model was evaluated using 20% of the test data and produced an accuracy of 91%, precision of 92%, recall of 91%, and an F1-score of 91%. These results show that the combination of TF-IDF and XGBoost is effective for classifying short texts in YouTube comments. Thus, this study contributes to the development of Indonesian-language spam comment detection models, which are still rarely researched, and can also be used as a reference for media platforms in improving the effectiveness of stopping the spread of illegal content through social media comment sections.
Peningkatan Akurasi Rekomendasi Film Menggunakan Neural Collaborative Filtering dengan Arsitektur RecommenderNet Sukmana, Dimas; Guntara, Rangga Gelar; Nugraha, Muhammad Rizki
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.3013

Abstract

The rapid growth of the film industry and streaming platform users has given rise to the challenge of information overload, where users find it difficult to find films that suit their preferences amid the abundance of content choices. This study aims to develop a Neural Collaborative Filtering (NCF)-based movie recommendation system model with a RecommenderNet architecture to improve prediction accuracy and personal recommendation relevance. The model was evaluated using the Root Mean Square Error (RMSE) metric to assess rating prediction accuracy and Normalized Discounted Cumulative Gain (NDCG@100) to measure recommendation quality and order. The results show that the model achieves an RMSE of 0.1946 and an NDCG@100 of 0.8136, indicating the model's ability to learn user preferences and generate relevant and well-ordered recommendations. This research contributes to the development of more effective and personalized recommendation systems in the digital streaming domain and offers an efficient approach to reducing the impact of information overload and improving the user experience.
Impact of AI-powered chatbot choki on Shopee users' continuance intention Ivana Ester Claudia; Syti Sarah Maesaroh; Muhammad Rizki Nugraha
Journal of Business and Information Systems (e-ISSN: 2685-2543) Vol. 7 No. 2 (2025): Journal of Business and Information Systems
Publisher : Department of Accounting, Faculty of Business, Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/jbis.v7i2.327

Abstract

Indonesia’s fast-growing digital economy is driving e-commerce firms to adopt artificial intelligence (AI) to enhance their services. One common tool is the AI-powered chatbot, which helps users quickly and efficiently. Shopee introduced its AI-powered chatbot, Choki, to facilitate seamless, automated customer interactions. This study examines the impact of system quality, information quality, and service quality on user satisfaction and, in turn, on continuance intention. Data were collected from 242 Shopee users in the Jabodetabek region and analyzed using SEM-PLS. The findings reveal that system quality has a significant effect on continuance intention, while information and service quality indirectly affect it through user satisfaction. These results highlight the crucial role of AI-driven system reliability in sustaining users’ long-term engagement with e-commerce platforms. Theoretically, this research strengthens the application of the DeLone and McLean Information Systems Success Model in the e-commerce context, while practically offering practitioners insights to enhance user experience by improving chatbot information accuracy and service responsiveness
Analysis of Success Factors for One Single ERP (Enterprise Resource Planning) Implementation (Case Study of Soe Holding) Ariq Qorihatunnasik; Syti Sarah Maesaroh; Muhammad Rizki Nugraha
Indonesian Interdisciplinary Journal of Sharia Economics (IIJSE) Vol 8 No 1 (2025): Sharia Economics
Publisher : Universitas KH. Abdul Chalim Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31538/iijse.v8i1.6349

Abstract

This research examines the implementation of One Single ERP system in SOE Holding, which previously faced challenges in consolidating data from three State-Owned Enterprises (SOEs) with different ERP systems. This research uses the ADKAR framework (Awareness, Desire, Knowledge, Ability, Reinforcement) to manage organizational change, overcome cultural and business process differences, and minimize resistance. The result of this research is that Employee Readiness requires a large allocation of effort to improve employee readiness through training, mentoring, and reinforcement. Top Management Support is also important to ensure strategic support and policies are aligned with transformation goals. Not all factors have an equal influence on successful implementation. With limited resources, Holding needs to prioritize the most influential factors, such as Employee Readiness and Top Management Support, so that efforts can be focused effectively and increase the chances of success. This approach accelerates the ERP implementation process while minimizing risks so that digital transformation goals can be achieved more quickly and efficiently.
Hilirisasi Aplikasi Minnova melalui Workshop Pemanfaatan Minyak Jelantah di Kota Tasikmalaya Kaffita Silaturahma; Najwa Alya Zulkifli; Alifya Arina Zahra; Syti Sarah Maesaroh; Muhammad Rizki Nugraha
Jurnal Masyarakat Madani Indonesia Vol. 4 No. 4 (2025): November
Publisher : Alesha Media Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59025/tcekpb33

Abstract

Pengelolaan minyak jelantah di Indonesia masih menghadapi kendala, terutama pada tingkat rumah tangga. Program pengabdian masyarakat ini bertujuan meningkatkan literasi lingkungan dan partisipasi dalam pengelolaan minyak jelantah melalui edukasi praktis dan pemanfaatan teknologi digital. Kegiatan meliputi sosialisasi, demonstrasi, praktik pembuatan lilin aromaterapi dari minyak jelantah, serta uji coba platform Minnova sebagai media pengumpulan minyak jelantah berbasis digital. Program diikuti oleh 57 peserta yang terdiri dari mahasiswa dan ibu rumah tangga. Hasil evaluasi menunjukkan peningkatan signifikan pada aspek pengetahuan, dari rata-rata skor 45,81 menjadi 92,58 (p < 0,001) serta mengindikasikan bahwa seluruh peserta berhasil menghasilkan produk lilin aromaterapi sesuai standar. Program ini membuktikan bahwa kombinasi edukasi praktis dan teknologi digital efektif dalam meningkatkan kesadaran serta mendorong praktik ekonomi sirkular di masyarakat.
Strategi Pertahanan Keamanan Siber Berbiaya Rendah untuk UMKM: Tinjauan Literatur Pratama, Nugraha Adhi; Nugraha, Muhammad Rizki
Jurnal Ilmu Komputer dan Informatika | E-ISSN : 3063-9026 Vol. 2 No. 3 (2026): Januari - Maret
Publisher : GLOBAL SCIENTS PUBLISHER

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

Abstract

Digital transformation is driving Micro, Small, and Medium Enterprises (MSMEs) to adopt information technology in their business activities. However, reliance on digital systems increases cybersecurity risks, while limited resources are a major obstacle for MSMEs in implementing comprehensive security systems. This study reviewed 18 scientific articles related to low-cost cybersecurity defense strategies applicable to MSMEs. The review results indicate that MSMEs are vulnerable to cyber threats due to budget constraints, low security literacy, and weak information governance. A realistic strategy emphasizes three key aspects: people, processes, and simple technology, through education and training, basic security policies, consistent operational procedures, and the use of affordable technology. This study is expected to serve as a reference for MSMEs and researchers in designing effective, efficient, and sustainable cybersecurity strategies.
IMPLEMENTASI MODEL UTAUT UNTUK MENGIDENTIFIKASI FAKTOR-FAKTOR YANG MEMENGARUHI PENERIMAAN CHATBOT META AI WHATSAPP Anargya, Layra Narda; Purwaamijaya, Btari Mariska; Nugraha, Muhammad Rizki
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 4 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i4.9337

Abstract

Perkembangan Generative Artificial Intelligence (GenAI) mendorong integrasi chatbot ke berbagai platform, termasuk WhatsApp melalui fitur chatbot Meta AI. Namun, tingkat penerimaan pengguna terhadap fitur ini masih lebih rendah dibandingkan chatbot lain seperti ChatGPT dan Gemini. Penelitian ini bertujuan menganalisis faktor-faktor yang memengaruhi penerimaan pengguna terhadap chatbot Meta AI WhatsApp dengan menggunakan model Unified Theory of Acceptance and Use of Technology (UTAUT). Penelitian ini menggunakan metode kuantitatif melalui survei terhadap 270 pengguna aktif WhatsApp yang telah mencoba chatbot Meta AI, dengan analisis data menggunakan SEM-PLS. Hasil penelitian menunjukkan bahwa performance expectancy (p = 0,000), effort expectancy (p = 0,000), dan social influence (p = 0,000) berpengaruh positif signifikan terhadap behavioral intention, sedangkan facilitating conditions tidak berpengaruh signifikan (p = 0,949). Selain itu, behavioral intention berpengaruh positif signifikan terhadap use behavior (p = 0,000). Temuan ini menegaskan bahwa persepsi manfaat, kemudahan penggunaan, dan pengaruh sosial merupakan faktor utama dalam membentuk niat penggunaan, sementara dukungan teknis bukan lagi faktor penentu. Dengan demikian, peningkatan relevansi fitur dan pengalaman pengguna diperlukan agar persepsi positif terhadap chatbot Meta AI WhatsApp dapat berkembang menjadi perilaku penggunaan yang berkelanjutan.
Co-Authors Adam Hermawan Adi Prehanto Ahmad Hamidi Al-Qorin, Fadillah Alifya Arina Zahra Alkatili, Ali Akbar Anargya, Layra Narda Annamayra, Ajeng Ar-Ridlo, Muhammad Dzikri Arhesa, Sandra Ariq Qorihatunnasik Arrayyan, Dzakwan Rafi Asep Nuryadin Awit Marwati Sakinah Bakhri, Rafdlal Saeful Btari Mariska Purwaamijaya Cepi Rahmat Hidayat Chaeroni, Ahmad Dede Syahrul Anwar Egi Badar Sambani, Egi Badar Evi Dewi Sri Mulyani Gelar Guntara, Rangga Gita Febria Friskawati Guntara, Rangga Gelar Hidayatuloh, Ade Taopik Hilwana, Atthaya Layla Zhafira Ivana Ester Claudia Kaffita Silaturahma Khairunisa, Alamanda Khoerunnisa, Garda Kusdinar, Yopi Lina Listiani Maesaroh, Syti Sarah Malik, Arief Abdul Mashudan, Muhammad Vajri Muchamad Arif Al Ardha Muhammad Dzikri Ar Ridlo Najwa Alya Zulkifli Nazwa Aprilia, Nyra Nilan, Fariha Nur, Lutfi Pratama, Nugraha Adhi Purwaamijaya, Btari Mariska Purwati Purwati Rangga Gelar Guntara Riska Aprilia Sukmana, Dimas Teten Hidayat, Teten Teuku Mufizar yogi prasetyo Yuda Purnama Putra Yusep Rosmansyah