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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Edutech: Jurnal Teknologi Pendidikan Jurnal Pemikiran dan Pengembangan Sekolah Dasar (JP2SD) Jurnal Edukasi dan Penelitian Informatika (JEPIN) Journal of Educational Science and Technology Scientific Journal of Informatics CESS (Journal of Computer Engineering, System and Science) JOIN (Jurnal Online Informatika) International Journal of Artificial Intelligence Research SISFOTENIKA Technomedia Journal Aptisi Transactions on Management Journal of Innovation and Future Technology (IFTECH) Indonesian Journal of Electrical Engineering and Computer Science Journal of Innovation in Educational and Cultural Research ADI Bisnis Digital Interdisiplin (ABDI Jurnal) ADI Pengabdian kepada Masyarakat Jurnal (ADIMAS Jurnal) ProBisnis : Jurnal Manajemen International Journal of Cyber and IT Service Management (IJCITSM) NUSANTARA: Jurnal Pengabdian Kepada Masyarakat CEMERLANG :Jurnal Manajemen dan Ekonomi Bisnis Startupreneur Business Digital (SABDA Journal) Media Riset Akuntansi Auditing & Informasi Profit: Jurnal Manajemen, Bisnis dan Akuntansi Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi International Transactions on Education Technology (ITEE) Nusantara Journal of Computers and its Applications Blockchain Frontier Technology (BFRONT) International Transactions on Artificial Intelligence (ITALIC) Journal of Computer Science and Technology Application JOT
Nuke Puji Lestari Santoso
Universitas Raharja
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Utilization of Digital Technology in English Language Learning to Support Community Literacy and Smart Cities Herman Herman; Yunita Wulansari; Nuke Puji Lestari Santoso; Sheila Aulia Anjani; Fhia Amelia; Zanele Xolani
Technomedia Journal Vol 11 No 2 (2026): October
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/s2evfp35

Abstract

The rapid evolution of smart cities demands urban citizens to possess high digital literacy and adaptive international communication skills; however, current community based English language learning practices still face significant challenges due to the lack of structured digital integration and accessible learning tools. To address this critical gap, this study aims to evaluate the objective and effectiveness of utilizing digital technology in English language learning to enhance community literacy and accelerate smart city development initiatives. This research employs a comprehensive mixed methods approach combining a quasi experimental design using an artificial intelligence powered mobile learning application distributed to 350 participants across three pilot smart city zones, rigorous pre and post intervention skill testing, quantitative surveys, and qualitative semi structured interviews. Empirical results demonstrate that the integration of digital technology significantly increased participants’ English proficiency and digital literacy scores by 38.5%, while simultaneously driving higher civic participation with municipal digital service platforms. Furthermore, interactive engagement through digital tools accelerated vocabulary acquisition, structural grammar mastery, and communicative confidence among diverse urban demographics. In conclusion, embedding digital technology into community English education not only effectively bridges global communication barriers, but also serves as a vital strategic framework to empower citizens and foster an inclusive, innovative, and sustainable smart city ecosystem.
Enhancing Adaptive Learning Environments in Learning Factories through Artificial Intelligence Ersa Aura Natasya; Nuke Puji Lestari Santoso; Lukita Pasha; Chua Toh Hua; Carlos Perez
International Transactions on Education Technology (ITEE) Vol. 4 No. 1 (2025): International Transactions on Education Technology (ITEE)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/itee.v4i1.957

Abstract

The rapid advancement of Artificial Intelligence (AI) has significantly trans- formed educational paradigms, particularly in adaptive learning environments where real-time personalization and intelligent feedback are essential. This study aims to explore how AI-driven mechanisms can enhance adaptive learning within learning factory environments by utilizing data analytics to personalize learning processes and optimize instructional delivery. Employing a quantita- tive research design, the data collection process involved distributing question- naires to 200 university students enrolled in AI-supported learning factory pro- grams. From this distribution, 120 valid responses were successfully obtained and analyzed, consisting of 80 students and 40 instructors across three universi- ties, representing the final usable dataset for this study. Statistical analysis was performed using regression and correlation models to assess the impact of AI- based adaptivity on learning performance, engagement, and cognitive retention. The findings reveal that AI integration within learning factories leads to sig- nificant improvements in learner adaptability, interaction efficiency, and overall academic achievement. The adaptive AI models dynamically adjusted learning content based on individual performance metrics, resulting in higher engage- ment rates and enhanced skill mastery compared to traditional non-AI-based environments. The outcomes confirm that AI can function as a critical enabler of responsive and data-driven education by bridging theoretical and practical as- pects of industrial learning. This research underscores the transformative poten- tial of Artificial Intelligence in reshaping adaptive learning environments within learning factories, emphasizing the need for further development of AI systems that prioritize personalization, continuous assessment, and the seamless integra- tion of human and machine intelligence
Leveraging Blockchain Governance and Smart Contracts for Entrepreneurs in Social Media Kanon Mommsen Wongkar; Triananda Fajar Satriawan; Nuke Puji Lestari Santoso; Noah Rangi
Blockchain Frontier Technology Vol. 6 No. 1 (2026): Blockchain Frontier Technology
Publisher : Indonesian Association of Higher Education in Informatics and Computing (APTIKOM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/b-front.v6i1.1090

Abstract

Social media entrepreneurship is shaped by centralized platforms controlling algorithms, monetization, and data, often limiting autonomy and bargaining power. Blockchain governance and smart contracts offer alternative arrangements to enhance transparency, trust, and value distribution. This study aims to examine the role of blockchain governance and smart contracts as alternative institutional mechanisms for entrepreneurs in social media ecosystems, with a focus on implementation conditions, strategic opportunities, and associated limitations. This research adopts a qualitative conceptual approach based on a systematic review of indexed academic literature published between 2022 and 2025, complemented by an analysis of documentation from blockchain based social media platforms, white papers, and relevant industry reports. The analysis maps key challenges faced by social media entrepreneurs onto blockchain governance mechanisms and smart contract functionalities. The findings indicate that blockchain governance and smart contracts can enhance entrepreneurial participation, improve transparency in revenue distribution, and strengthen the protection of digital assets. However, these benefits are context dependent and con- strained by several factors, including technical complexity, unequal token distribution, and regulatory uncertainty. Therefore, blockchain governance and smart contracts should not be viewed as universal solutions, but as strategic instruments whose effectiveness depends on inclusive governance design, sufficient technical readiness, and adaptive policy frameworks to support sustainable social media entrepreneurship. This article contributes by proposing an evaluative framework to assess the implementation of blockchain governance and smart contracts in social media entrepreneurship, emphasizing alignment be- tween technological design, governance inclusivity, and ecosystem readiness.
Pelatihan Learning Factory Berbasis LaserPecker untuk Peningkatan Kompetensi Siswa SMK Yuppentek 2 Curug Qurotul Aini; Nuke Puji Lestari Santoso; Richard Andre Sunarjo; Ageng Setiani Rafika; Irene Apriani Widjaya; Syahrul Mu’Arif Wahid
Nusantara: Jurnal Pengabdian kepada Masyarakat Vol. 6 No. 4 (2026): November: NUSANTARA Jurnal Pengabdian Kepada Masyarakat
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/nusantara.v6i4.10186

Abstract

The rapid development of modern manufacturing, driven by digitalization and precision technology, requires vocational education graduates to possess competencies relevant to industry needs. However, limited hands-on experience with digital manufacturing technologies remains a challenge in vocational high school education. This Community Service Program (PKM) aims to improve the manufacturing competencies of students at SMK Yuppentek 2 Curug through a Learning Factory approach based on LaserPecker technology. The program was implemented in five stages: socialization, training, technology implementation, mentoring, and program sustainability. Evaluation was conducted using pre-tests and post-tests, practical observations, and participant satisfaction questionnaires. The evaluation results indicated improvements across all five competency indicators measured. The average achievement percentage increased from 51.2% before the training to 90.6% after the training, representing an increase of 39.4 percentage points. The greatest improvement was observed in the use of LaserPecker Design Space software, with scores increasing from 46% to 91%. These findings indicate that Learning Factory-based training has the potential to enhance students' understanding and skills in digital manufacturing.
Analisis Sentimen Electronic Word-of-mouth TikTok pada Bisnis Jasa Photobox untuk Mendukung Strategi Pemasaran Digital Kelvin Siahaan; Muhamad Yusup; Tuti Nurhaeni; Nuke Puji Lestari Santoso
CEMERLANG : Jurnal Manajemen dan Ekonomi Bisnis Vol. 6 No. 3 (2026): Agustus: CEMERLANG : Jurnal Manajemen dan Ekonomi Bisnis
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/cemerlang.v6i3.9863

Abstract

The self-photo (photobox) business in Indonesia has grown rapidly as a digital-era experience service, propelled largely by user-generated content (UGC) that acts as electronic word-of-mouth (eWOM) on TikTok. For small businesses, the public opinion embedded in these comments is a valuable yet underused marketing asset. This study analyses consumer sentiment toward photobox services and positions the analysis as a social-media-analytics tool to support digital marketing decisions. A machine-learning approach was applied to 1.086 labelled Indonesian TikTok comments grouped into positive, neutral, and negative classes. Comments were represented with TF-IDF features and classified using Naive Bayes, Logistic Regression, Random Forest, and Support Vector Machine, evaluated through five-fold stratified cross-validation, with SMOTE and SMOTE with Tomek Links applied to handle class imbalance. The results show that the eWOM is overwhelmingly positive (64,0%) and that most comments are extremely short. The best accuracy reached about 63,2%, but every model struggled with the neutral and negative classes; Logistic Regression with SMOTE detected negative opinion best. Read through the Elaboration Likelihood Model, the brevity of the comments reflects low-effort, peripheral-route reactions common on short-video platforms. Managerially, the strong positive buzz signals healthy brand momentum, yet the scarcity of substantive feedback means business owners must combine sentiment analytics with other listening channels to obtain actionable insight.
Peran Teknologi Blockchain dalam Memperkuat Kapabilitas Pengelolaan Data Digital untuk Operasional Layanan Asuransi Tuti Nurhaeni; Sudaryono Sudaryono; Nuke Puji Lestari Santoso; Rizal Hafidz Lazuardi
Profit: Jurnal Manajemen, Bisnis dan Akuntansi Vol. 5 No. 4 (2026): November: Profit : Jurnal Manajemen, Bisnis dan Akuntansi
Publisher : UNIVERSITAS MARITIM AMNI SEMARANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58192/profit.v5i4.5330

Abstract

Digital transformation in the insurance industry has increased the strategic importance of organizational data, making Digital Data Management Capability (DDMC) essential for improving operational efficiency. However, many insurance service organizations continue to face challenges related to fragmented data systems, inconsistent data quality, limited accessibility, and inadequate data integration. This study examines the effect of DDMC on operational efficiency by focusing on five dimensions: data quality, data accessibility, data integration, data governance, and data security. A quantitative cross-sectional survey was conducted among employees of insurance service organizations, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that DDMC has a positive and significant effect on operational efficiency. Among its dimensions, data quality, data integration, and data governance are the strongest contributors to improving operational performance, accelerating service processes, enhancing decision-making accuracy, and optimizing service delivery. In addition, blockchain technology supports data security, transparency, and integrity within insurance ecosystems. This study extends the application of Dynamic Capability Theory in the insurance sector and provides practical insights for organizations seeking to improve operational efficiency through effective digital data management.
Machine Learning-Based Prediction of Electric Vehicle Charging Demand for Sustainable Transportation Nyree Ani; Nuke Puji Lestari Santoso; Rajendra Kumar
International Transactions on Artificial Intelligence Vol. 5 No. 1 (2026): November
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v5i1.1245

Abstract

The increasing adoption of Electric Vehicles (EV) presents challenges in managing uncertain charging demand, optimizing infrastructure utilization, and maintaining energy system stability. This study aims to develop and evaluate a machine learning-based prediction framework for estimating EV charging energy demand and identifying the most effective predictive algorithm to support sustainable transportation planning. The proposed framework employs historical EV charging observations and contextual variables, including charging duration, charging time, day of the week, ambient temperature, charging frequency, and historical energy consumption. Three supervised machine learning algorithms, namely Random Forest (RF), Support Vector Regression (SVR), and Extreme Gradient Boosting (XGBoost), are comparatively evaluated. Predictive performance is assessed using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and the coefficient of determination (R²). The reported experimental findings indicate that XGBoost achieves the highest predictive accuracy, with an RMSE of 2.84 kWh, MAE of 1.97 kWh, MAPE of 6.21%, and R² of 0.941. However, the comparative performance metrics for RF and SVR must be reported in the main Results section to substantiate the claimed superiority of XGBoost. The proposed framework demonstrates the potential of machine learning to identify charging demand patterns using historical charging, temporal, and environmental information. Subject to further experimental verification, the findings may support data-driven charging infrastructure management, electricity resource allocation, and sustainable transportation planning.
Integrating Design Thinking and Advertising Analytics for Startup Marketing Optimization Nuke Puji Lestari Santoso; Anggi Maharani; Adam Faturahman; Stuart Jackson
Startupreneur Business Digital (SABDA Journal) Vol. 6 No. 1 (2027)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sabda.v6i1.1102

Abstract

In an increasingly competitive digital environment, startups in the creative industry face challenges in maintaining audience engagement and improving advertising effectiveness due to social media saturation and rapidly changing platform algorithms. Conventional promotional approaches are becoming less effective as consumers increasingly prefer authentic, educational, and interactive content. This study aims to develop and evaluate a consumer-centered Instagram advertising strategy using the design thinking approach. The novelty of this research lies in integrating design thinking stages with digital advertising performance metrics to design and assess empathy-based advertising content for a beaded jewelry startup. This study employed a mixed-methods exploratory sequential design. The qualitative phase involved participatory observation, social listening, and analysis of audience interactions on the Instagram account @pritistuff.id to identify consumer pain points and develop advertising content prototypes. The quantitative phase utilized A/B testing through Meta Ads Manager to evaluate campaign performance using Click-Through Rate (CTR), Cost Per Click (CPC), Cost Per Mille (CPM), and Conversion Rate. The findings identified three major consumer concerns uncertainty regarding product quality, difficulty visualizing product size when worn, and resistance to hard-selling advertisements. These insights were translated into educational Carousel content and User-Generated Content (UGC)-based Reels prototypes. The campaign achieved a CTR of 22.49%, CPC of IDR 70 per interaction, CPM of IDR 15,646, and a Conversion Rate of 1.99%, indicating improved engagement and advertising efficiency. The study concludes that design thinking provides an effective framework for developing consumer-centered digital advertising strategies that enhance audience engagement and support sustainable business growth.
Co-Authors Abdul Hamid Arribathi Abdul Hayat Abdullah Arif Kamal Achani Rahmania Az Zahra Adam Faturahman Aditya Mardiansyah Agustinus Purna Irawan Amelia, Sindy Amitkumar Dudhat Anandha Fitriani Andzelika Birgithri Anggi Maharani Anggun Oktariyani Ariana Delhi Aswadi Jaya Ayi Rakhmat Ramdani Carlos Perez Chandra Eka Chua Toh Hua Diana Putri Lazirkha Disman Disman Dwi Apriliasari Edward Guustaaf Efa Ayu Nabila Eka Dian Astuti Elisa Royani Dewi Ersa Aura Natasya Euis Siti Nur Aisyah Felix Sutisna Fhia Amelia Fitra Putri Oganda Galih Putra Cesna Harahap, Eka Purnama Hardjanto Nusantoro Harry Agustian Herman Herman Husni Teja Sukmana Irene Apriani Widjaya Isyak Meirobie Jett Lee Wilson Kanon Mommsen Wongkar Kelvin Siahaan Ketut Gunawan Khoirunisa, Alfiah Kristina Vaher Lukita Pasha Mardiana Mardiana Mardiana Mardiana Marliani Herlina Marviola Hardini Maulana Faqih Farail Melani Rapina Tangkaw Migunani Migunani Muchlishina Madani Muh. Tahir Muhamad Fabio Muhamad Stabil Tanwin Saputra Muhamad Yusup Muhammad Rehan Anwar Muhammad Rifat Syauqy Mukti Budiarto Nesti Anggraini Santoso Nevizond, Reza Filander Ninda Lutfiani Noah Rangi Noah Rangi Nugroho Prihantoni Wibowo Nur Azizah Nyree Ani Oliver Sauntos Panca Oktavia Hadi Putra Po Abas Sunarya Prihastiwi, Wahyu Yustika Qurotul Aini Qurotul Aini Qurotul Aini Qurotul Aini Rafika, Ageng Setiani Rahmat Salam Rajendra Kumar Rakhmansyah, Mohamad Ramzi Zainum Ikhsan Refa Azka Reyhan Algiffary Gunawan Richard Andre Sunarjo Ridhuan Ahsanitaqwim Risma Nurmala Rizal Hafidz Lazuardi Ruli Supriati, Ruli Sabda Maulana Sabda Maulana Sheila Aulia Anjani Sherli Triandari Shofiyul Millah Shofiyul millah Sindy Amelia Sri Watini Steven Harazaki Lase Stuart Jackson Sudaryono Sudaryono Sulis Setiawati Sulthan Taqi Sampoerna Suryari Purnama Syahrul Mu'Arif Wahid Syahrul Mu’Arif Wahid Syifa Muthiatunnisa Triananda Fajar Satriawan Tuti Nurhaeni Udin Saefudin Sa’ud Untung Rahardja Viola Tashya Devana Wahyu Sopandi Wahyu Yustika Prihastiwi Widhy Setyowati Yunita Wulansari Zanele Xolani