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All Journal Jupiter PROtek : Jurnal Ilmiah Teknik Elektro Jurnal Obsesi: Jurnal Pendidikan Anak Usia Dini Jurnal Ilmiah FIFO Jurnal TAM (Technology Acceptance Model) JURNAL PENGABDI Prosiding Seminar Nasional Darmajaya KACANEGARA Jurnal Pengabdian pada Masyarakat Jurnal Informasi dan Komputer Jurnal Teknologi Terpadu Jurnal ICT : Information Communication & Technology Aisyah Journal of Informatics and Electrical Engineering Abdimas Universal BERNAS: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika (JUTIF) Jurnal Pengabdian Kepada Masyarakat Ungu ( Abdi Ke Ungu) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Metta : Jurnal Ilmu Multidisiplin Connection : Jurnal Pengabdian Kepada Masyarakat Journal of Information Systems and Technology Research Jurnal Algoritma Dharma: Jurnal Pengabdian Masyarakat Jurnal Masyarakat Madani Indonesia Dikdimas : Jurnal Pengabdian Kepada Masyarakat IJOEM: Indonesian Journal of Elearning and Multimedia Finger : Jurnal Ilmiah Teknologi Pendidikan Jurnal Informatika Polinema (JIP) Jurnal Pendidikan Teknologi Informasi dan Komunikasi BACA: Jurnal Dokumentasi dan Informasi Jurnal Rekayasa Perangkat Lunak Jurnal TAM (Technology Acceptance Model)
Nur Aminudin
Universitas Aisyah Pringsewu
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Pengembangan Chatbot AI untuk Informasi Pendaftaran Mahasiswa Baru di FTI UAP Habib, Cahya; Zulkifli, Zulkifli; Aminudin, Nur; Ayu Andini, Dwi Yana
Jurnal Rekayasa Perangkat Lunak Vol. 4 No. 2 (2025): Jurnal Rekayasa Perangkat Lunak (J-Rapa)
Publisher : Universitas Aisyah Pringsewu

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Abstract

Penelitian ini mengembangkan chatbot berbasis kecerdasan buatan (AI) bernama Asvira untuk menyediakan informasi pendaftaran mahasiswa baru di Fakultas Teknologi dan Informatika Universitas Aisyah Pringsewu (FTI UAP). Sistem ini dirancang untuk menjawab pertanyaan umum seperti jadwal pendaftaran, persyaratan, biaya kuliah, dan fasilitas kampus secara otomatis dan real-time, menggantikan sistem konvensional yang mengandalkan staf administrasi. Asvira dibangun menggunakan framework Laravel untuk backend, Blade dan Tailwind CSS untuk antarmuka, serta OpenAI GPT-4.1 API sebagai mesin pemroses bahasa alami. Basis pengetahuan disusun dalam format JSON dari sumber resmi universitas. Metode penelitian yang digunakan adalah Research and Development (R&D) dengan pendekatan prototipe dan evaluasi kualitatif melalui umpan balik pengguna. Hasil pengujian menunjukkan Asvira mampu memberikan respons yang akurat dan cepat dengan antarmuka yang responsif. Evaluasi pengguna juga menunjukkan sistem ini mudah digunakan dan meningkatkan efisiensi layanan informasi pendaftaran. Sistem ini diharapkan mengurangi beban kerja staf dan menjadi model untuk chatbot serupa di layanan akademik lainnya.
Analisis Sentimen Kesehatan Mental di TikTok pada Generasi Milenial, Gen Z, dan Alpha Menggunakan SVM dan Random Forest Rohmah, Nurbaiti; Aminudin, Nur; Wantoro, Agus; Ayu Andini, Dwi Yana
Jurnal Rekayasa Perangkat Lunak Vol. 4 No. 2 (2025): Jurnal Rekayasa Perangkat Lunak (J-Rapa)
Publisher : Universitas Aisyah Pringsewu

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Abstract

Penelitian ini menganalisis dinamika kesehatan mental lintas generasi dalam komunitas K-Pop di TikTok Indonesia, dengan fokus pada FOMO, kecemasan, dan strategi coping digital. Pendekatan mixed-methods digunakan untuk mengintegrasikan survei terhadap 501 responden dan analisis 1.481 komentar publik. Survei mengukur empat konstruk psikologis utama, sementara komentar diklasifikasikan menggunakan algoritma Support Vector Machine (SVM) dan Random Forest, serta divalidasi secara manual melalui analisis tematik. Hasil menunjukkan bahwa Generasi Z memiliki tingkat FOMO dan kecemasan tertinggi, Milenial mengalami stres dan burnout, sedangkan Alpha menunjukkan keterlibatan digital yang pasif namun berisiko terhadap perkembangan sosial-emosional. Random Forest menunjukkan performa klasifikasi terbaik (F1-score 93%), unggul dalam menangkap ekspresi minoritas seperti trauma dan refleksi eksistensial.Temuan ini memperkuat bahwa TikTok bukan sekadar ruang hiburan, melainkan arena ekspresi psikologis yang kompleks. Penelitian ini berkontribusi pada pengembangan kerangka kerja kesejahteraan digital yang adaptif, dengan menekankan pentingnya validasi ganda dan intervensi berbasis data yang empatik.
Sistem Kendali Lampu Pada Smart Home Berbasis IoT Afrianto, Rifki; Aminudin, Nur; Eko Setiawan, Agustinus; Herdian Andika, Tahta
Jurnal Rekayasa Perangkat Lunak Vol. 3 No. 1 (2024): Jurnal Rekayasa Perangkat Lunak (J-Rapa)
Publisher : Universitas Aisyah Pringsewu

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Abstract

Penelitian ini bertujuan untuk mengaplikasikan modul Wemos D1 dalam mengendalikan lampu berbasis IoT melalui aplikasi Blynk pada Smart Home. Dengan menggunakan Wemos D1 dan Blynk, pengguna dapat mengontrol lampu secara efisien dari jarak jauh, meningkatkan efisiensi penggunaan energi. Perbandingan dengan metode tradisional menunjukkan keunggulan dalam kemudahan penggunaan dan efisiensi energi.
A Conceptual Framework for Technology-Enhanced Learning Design: Bridging Pedagogy and Digital Innovation Dita Septasari; Ikna Awaliyani; Nur Aminudin; Septika Ariyanti; Shima Asadi
FINGER : Jurnal Ilmiah Teknologi Pendidikan Vol. 5 No. 1 (2026): Finger : Jurnal Ilmiah Teknologi Pendidikan
Publisher : CV. Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/finger.v5i1.518

Abstract

Background: Learning designs must be grounded in pedagogical principles and make appropriate use of technical advancements in light of the digital transformation of education. Nonetheless, there is still a disconnect in many educational environments between the use of technology and pedagogical requirements.Aims: The research objective is to develop a conceptual framework for Technology-Enhanced Learning Design that bridges pedagogical principles with digital innovation. The research scope included a literature analysis, a review of best practices, and initial validation through education and technology experts.Methods: This research employed a qualitative approach with conceptual analysis and expert validation methods. Data were collected through a systematic literature review (2020–2025) and interviews with education and technology experts. Analysis was conducted using a thematic approach to identify the key dimensions of the technology-based learning design framework.Results: Pedagogical (learner-centered design, active engagement, personalization), technological (interoperability, scalability, AI integration), and implementation (continuous evaluation, institutional context, user readiness) are the three primary dimensions of the conceptual framework that emerged from the research. Compared to earlier studies, this framework has demonstrated the ability to more thoroughly integrate digital innovation with pedagogical concepts.Conclusion: The significance of combining technology and pedagogy in learning design is emphasized by this study. Researchers, educators, and legislators can use the conceptual framework that is produced as a guide for creating digital learning that is more sustainable and successful.
Design and Evaluation of AI-Enhanced Multimedia Learning Systems: Usability, Accessibility, and Engagement in Broadband-Based Online Education Ikna Awaliyani; Dita Septasari; Nur Aminudin; Septika Ariyanti
IJOEM: Indonesian Journal of E-learning and Multimedia Vol. 5 No. 2 (2026): Indonesian Journal of E-learning and Multimedia
Publisher : CV. Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijoem.v5i2.573

Abstract

Background: Artificial intelligence (AI) has increasingly been integrated into multimedia learning environments to support personalization, accessibility, and learner engagement in broadband-based online education. However, many existing systems still evaluate these dimensions separately, which limits their overall effectiveness and scalability.Aims: This study aims to design and empirically evaluate an AI-enhanced multimedia learning system using a unified evaluation framework that integrates system performance, usability, accessibility, and learner engagement within broadband-based higher education contexts.Methods: An explanatory sequential mixed-methods design was employed, involving quantitative analysis with 150 students and qualitative exploration with 12 participants. Data were collected through system performance logs, System Usability Scale (SUS) assessments, WCAG 2.1–based accessibility evaluations, and learner engagement metrics.Results: The findings indicate that AI-driven adaptivity improves system responsiveness, achieves high usability, supports digital accessibility, and enhances learner engagement in broadband-based learning environments. The results demonstrate the effectiveness of the system across technical, experiential, and behavioral dimensions.Conclusion: The key contribution of this study lies in proposing and validating an integrated evaluation framework that holistically captures the performance and user experience of AI-enhanced multimedia learning systems, an area that has been underexplored in prior research. These findings provide important theoretical and practical implications for the design of inclusive, adaptive, and user-centered online learning platforms.
Predicting Consumer Purchasing Behavior Using Random Forest on Retail Transaction Data Ningsiah Ningsiah; Nur Aminudin
Jurnal Ilmiah FIFO Vol. 18 No. 1 (2026)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/fifo.2026.v18i1.002

Abstract

The rapid digital transformation in the retail sector has generated massive volumes of consumer transaction data stored within retail information systems. Although these data hold strategic value for decision-making, their utilization often remains limited to descriptive reporting. This study aims to analyze and predict consumer purchasing behavior by integrating machine learning–based predictive analytics into retail information systems using the Kaggle retail transaction dataset. The research methodology includes data preprocessing, exploratory data analysis, feature selection, and predictive model development using logistic regression, decision tree, and random forest algorithms. Model performance was evaluated using accuracy, precision, recall, and ROC–AUC metrics. The results indicate that the random forest model outperformed the other algorithms, achieving an accuracy of 88.76%, precision of 87.92%, and recall of 86.48%, demonstrating superior discriminative capability. These findings confirm that ensemble-based learning methods effectively capture complex and non-linear consumer purchasing patterns. The study contributes theoretically by extending the role of retail information systems from descriptive reporting tools to predictive decision-support systems, while practically providing a robust analytical framework to support inventory optimization, targeted promotion strategies, and personalized service delivery in data-driven retail environments.
An Intelligence-Oriented System Architecture for Integrated Pharmaceutical Data Analytics and Decision Support Ningsiah; Nur Aminudin; Septika Ariyanti; Ramil Abbasov
Journal of Information Systems and Technology Research Vol. 5 No. 1 (2026): January 2026
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v5i1.1461

Abstract

This study proposes and evaluates an intelligence-oriented hybrid information system architecture for pharmaceutical data analytics and decision support. Unlike conventional approaches that treat analytics as an external component, the proposed framework embeds analytical intelligence directly into the core system architecture through an integrated, multi-layer design. The study adopts an experimental and system development methodology using a large-scale public pharmaceutical dataset consisting of 240,591 records and 10 attributes. Supervised machine learning models are implemented to support data classification and intelligence generation, and system performance is evaluated using accuracy, precision, recall, and F1-score. The results demonstrate that the proposed hybrid system consistently outperforms baseline and non-integrated approaches, achieving higher predictive stability and analytical consistency. The main contribution of this study lies in its system-level integration model, which enables the transformation of raw pharmaceutical data into actionable decision-support intelligence. The findings confirm that embedding analytics within information system architecture significantly enhances both analytical performance and decision-making capability in pharmaceutical information systems.
Pemberdayaan Masyarakat Desa melalui KKN Multidisiplin Berbasis UMKM dan Kesehatan Lingkungan Nur Aminudin; Lukman Alfariz; Vina Akmalia; Iin Triana; Seli Oktaviana; Abelian Saputri; Dimas; Niken Yulia Fantika; Sevira Filensa
Connection : Jurnal Pengabdian Kepada Masyarakat Vol 6 No 1 (2026): Januari Juni
Publisher : Prodi Bimbingan dan Konseling Islam IAIN Langsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32505/connection.v6i1.14266

Abstract

Permasalahan yang dihadapi masyarakat desa umumnya berkaitan dengan keterbatasan kapasitas pengelolaan usaha mikro, rendahnya literasi digital, serta masih kurangnya kesadaran terhadap Perilaku Hidup Bersih dan Sehat (PHBS) dan partisipasi sosial. Kondisi tersebut mendorong perlunya program pengabdian masyarakat yang bersifat integratif dan partisipatif. Kegiatan pengabdian ini bertujuan untuk memberdayakan masyarakat desa melalui program Kuliah Kerja Nyata (KKN) multidisiplin yang berfokus pada penguatan Usaha Mikro, Kecil, dan Menengah (UMKM) serta peningkatan kesadaran kesehatan lingkungan. Metode yang digunakan adalah pendekatan partisipatif melalui tahapan observasi dan identifikasi kebutuhan, sosialisasi program, pelatihan dan pendampingan UMKM, edukasi PHBS, serta penguatan partisipasi sosial masyarakat. Hasil pengabdian menunjukkan adanya peningkatan pemahaman pelaku UMKM terkait pengelolaan usaha sederhana, perbaikan kemasan produk, serta pemanfaatan media digital sebagai sarana promosi. Selain itu, kegiatan edukasi PHBS berkontribusi terhadap meningkatnya kesadaran masyarakat dalam menjaga kebersihan lingkungan dan keterlibatan dalam kegiatan kesehatan serta gotong royong. Secara keseluruhan, program KKN multidisiplin ini mampu mendorong perubahan awal pada aspek ekonomi, kesehatan, dan sosial masyarakat. Kegiatan pengabdian ini diharapkan menjadi model pemberdayaan masyarakat desa yang berkelanjutan melalui kolaborasi multidisiplin dan keterlibatan aktif masyarakat.
Peningkatan Kapasitas Aparatur BAPPEDA Kabupaten Pringsewu dalam Penulisan Jurnal Ilmiah Litbang melalui Pendampingan dan Asistensi Aminudin, Nur; Wantoro, Agus
Jurnal Pengabdi Vol. 9 No. 1 (2026): April 2026
Publisher : Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jplp2km.v9i1.103829

Abstract

The capacity of local government officers in writing scientific journal articles based on Research and Development (R&D) outputs remains relatively low, resulting in limited publication of regional research findings. This issue is also experienced by the Regional Development Planning Agency (BAPPEDA) of Pringsewu Regency, where most R&D outputs are still presented as internal reports rather than publishable journal articles. This Community Service Program (PKM) aims to enhance the knowledge and skills of BAPPEDA officers in scientific journal writing and to produce draft journal articles based on regional R&D studies. The methodology employed includes a scientific writing workshop, direct mentoring in manuscript preparation, and intensive assistance in reviewing participants’ draft articles. The results indicate a significant improvement in participants’ understanding of journal article structure, abstract writing, research methodology application, and the use of proper citation and references. In addition, participants were able to produce initial draft journal articles derived from their existing R&D reports. This PKM activity has a positive impact on strengthening officers’ capacity and fostering a scientific writing culture within BAPPEDA. In conclusion, the mentoring and direct assistance approach is effective in addressing partners’ problems and supporting the improvement of regional R&D scientific publication quality.
Sentiment Analysis of WhatsApp User Reviews as Information Evaluation for Digital Services Nur Aminudin; Agus Wantoro; Dita Septasari
BACA: Jurnal Dokumentasi dan Informasi Vol. 47 No. 1 (2026): BACA: Jurnal Dokumentasi dan Informasi (June)
Publisher : Direktorat Repositori, Multimedia, dan Penerbitan Ilmiah - Badan Riset dan Inovasi Nasional (BRIN Publishing)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/baca.2026.14917

Abstract

This study examines user reviews of the WhatsApp application as digital information objects that reflect user perceptions of digital information service quality. The rapid growth of communication platforms has generated large volumes of user-generated content, which requires systematic analysis and functions as a form of digital documentation. This research aims to evaluate how machine learning and deep learning approaches can support information evaluation through sentiment analysis of user reviews. A publicly available dataset of WhatsApp user reviews obtained from Kaggle was used as the data source. The research methodology consisted of text preprocessing, feature representation, sentiment classification, and performance evaluation. Support Vector Machine (SVM) was employed as a baseline machine learning method, while Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) models represented deep learning approaches. The experimental results show that deep learning models outperform the traditional approach, with CNN achieving the best performance across accuracy, precision, recall, and F1-score metrics. These findings indicate that deep learning-based sentiment analysis is effective in transforming large-scale user reviews into actionable information for evaluating digital information services. This study contributes to documentation and information science by demonstrating the role of artificial intelligence in analyzing user-generated digital documentation to support evidence-based decision-making in digital service development.
Co-Authors Abdullah Umar Faqih Al Ikhsani Abelian Saputri Adamu Abubakar Muhammad Adamu Abubakar Muhammad Adi Prasetia Nanda Afandi, Asep Afanto, Hendri Afnan Zalfa Salsabila A Afrianto, Rifki Agus Wantoro Ahmad Ahlun Nazar Alfazri Putra Pradana Alfina Alfina Andika, Tahta Herdian Andino Maseleno Aprilia, Fenny Arif Alexander Bastian Ariyanti, Septika Aviv Fitria Yulia Ayu Andini, Dwi Yana Bagus Wicaksono, Setepanus Bintoro, Panji Boris Brahmono Budi Usmanto Cahyadi, Septian Damayanti Abdul Karim, Dewi Desni Sagita, Yona Dikpride Despa Dimas Dita Septasari Dwi AD Putra Dwi Feriyanto Dwi Feriyanto Efendi, Dwi Marisa Eko Setiawan, Agustinus El Hanif, Azka Elita Yuni Setiyarini Etanaulia Marsim Fadzlan Thoriq Fahlul Rizki Fandi Ahmad Ferly Ardhi Ferly Ardhy Fiqih Satria Fitra Endi Fernanda, Fitra Endi Habib, Cahya Hasanah, Khuswatun Ida Ayu Putu Anggie Sinthiya Iin Triana Ikna Awaliyani Ilham Ubaidillah Inti Barokah Amaliah Irwan Susilo Khuswatun Hasanah Lukman Alfariz M. Islamahdi MARTHALENA, YENNY Mayang Indah Sari Mitha Franciska Muhammad Farhan Al Farisi Muhammad Kristiawan Muhammad Lathief Syaifussalam Muharni, Sita Mukaromah, Hafsah Mulyono, Andi Mutmainah Mutmainah Naufal Sinatria Naufal Sinatria Niken Yulia Fantika Ningsiah Nuafal Sinatria Nungsiyati . Nurul Hidayat Nurul Isti Fada Ockhy Jey Fhiter Wassalam Panji Bintoro Putra, Dwi AD Ramadhanti, Dinda Ramil Abbasov Ratnasari Ratnasari Ratnasari Ratnasari Rendy Yudha Pratama Rian Candra Pratama Rimanto, Rimanto Rini Wahyuni Rizka Dwi Yovita Rohmah, Nurbaiti Rustam Rustam Salman Alfarisi Salimu Salman Alfarisi Salimu Salsabila A, Afnan Zalfa Satria, Fiqih Seli Oktaviana Septika Yani Veronica Sevira Filensa Shima Asadi Sigit Andriyanto Sukamto, Anton Sumerti, Ela Susilo Setiawan Tahta Herdian Andika Tahta Herdian Andika Tahta Herdian Andika Taufiq Taufiq Tri Adi Nugroho Ulfa Isni Kurnia Vina Akmalia Wicaksono, Garda Arif Wina Safutri Yana Ayu Andini, Dwi Yani Veronica, Septika Yessiana Luthfia B Zalfa Salsabila A, Afnan Zulkifli Zulkifli Zulkifli