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All Journal Jurnal Ilmu Komputer dan Informasi Jurnal Ilmiah Informatika Komputer Techno Nusa Mandiri : Journal of Computing and Information Technology METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Al-Kharaj: Journal of Islamic Economic and Business JURSIMA (Jurnal Sistem Informasi dan Manajemen) Management Studies and Entrepreneurship Journal (MSEJ) Enrichment : Journal of Management Jurnal Sistem Informasi Jurnal Ekonomi Jurnal Kolaboratif Sains Jutech: Jurnal Teknologi Informasi West Science Social and Humanities Studies SAMBARA: Jurnal Pengabdian Kepada Masyarakat Green Engineering: Journal of Engineering and Applied Science Journal of Law, Economics, and Engineering Global Science: Journal of Information Technology and Computer Science Technema: Journal of Intelligent Engineering and Computing
Rian Ardianto
Universitas Harapan Bangsa
Religion Agriculture, Biological Sciences & Forestry 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 Environmental Science Health Professions Immunology & microbiology Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Fenomena Brain Rot di Kalangan Anak Muda: Refleksi Penggunaan Teknologi dan Revitalisasi Peran Kepemudaan Rosyid Al-Hakim; Rian Ardianto; Riska Suryani; Hadi Jayusman
Journal of Law, Economics, and Engineering Vol. 1 No. 1 (2025)
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

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Abstract

Fenomena brain rot semakin sering muncul di kalangan anak muda sebagai bentuk penurunan fokus, motivasi, dan daya pikir akibat konsumsi berlebihan terhadap konten digital yang dangkal dan cepat. Era media sosial yang serba instan menciptakan kebiasaan doom scrolling, short attention span, dan kecenderungan menghindari aktivitas produktif yang membutuhkan konsentrasi mendalam. Tulisan ini bertujuan mengulas penyebab utama brain rot dari perspektif penggunaan teknologi serta menawarkan pendekatan keseimbangan melalui partisipasi dalam kegiatan kepemudaan. Kajian ini menggunakan metode literatur naratif yang mengombinasikan temuan ilmiah mengenai digital fatigue dan cognitive overload dengan observasi fenomenologis pada pola perilaku generasi muda. Hasil telaah menunjukkan bahwa brain rot bukan sekadar akibat teknologi, tetapi juga refleksi kurangnya kontrol diri dan orientasi terhadap makna kegiatan digital. Revitalisasi peran kepemudaan melalui aktivitas sosial, edukatif, dan kreatif dapat menjadi bentuk terapi sosial yang efektif untuk memulihkan fokus dan kualitas diri anak muda di era digital.
Adaptive Graph Based Intelligence Models for Cross Domain Knowledge Discovery in Large Scale Heterogeneous Information Systems Winny Purbaratri; Krisna Widi Nugraha; Rian Ardianto; Rosyid Ridlo Al-Hakim; Yogiek Indra Kurniawan; Ribut Julianto
Global Science: Journal of Information Technology and Computer Science Vol. 1 No. 4 (2025): December: Global Science: Journal of Information Technology and Computer Scienc
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/globalscience.v1i4.193

Abstract

The rapid growth of heterogeneous information systems across multiple domains has introduced complex challenges in data analysis, particularly when dealing with diverse data types such as text, images, and sensor data. Traditional machine learning (ML) methods often struggle to capture the intricate relationships inherent in these large scale datasets, as they typically rely on linear models and feature vectors that fail to represent the full complexity of the data. This study aims to develop an adaptive graph based intelligence model that addresses these challenges by leveraging the power of graph structures to represent heterogeneous data and capture both structural dependencies and semantic connections. The proposed model integrates Graph Neural Networks (GNNs) with adaptive learning mechanisms, allowing for continuous knowledge extraction, pattern discovery, and cross domain inference. By representing diverse data sources as interconnected graphs, the model enables the transfer of knowledge across different domains, improving its ability to make accurate predictions and generate insights in dynamic environments. The results demonstrate that the graph based model outperforms traditional machine learning techniques in terms of accuracy, efficiency, and scalability, especially when applied to real world applications involving large and complex datasets. This paper also discusses the advantages of the adaptive learning mechanisms, which personalize the model’s training process and improve its robustness over time. Furthermore, the findings highlight the model’s potential for cross domain knowledge discovery, with applications in fields such as healthcare, marketing, and industrial automation. Finally, the paper offers recommendations for future research, including refining adaptive learning mechanisms and exploring new graph based techniques to enhance the representational power of the model. The study contributes to the ongoing development of intelligent systems capable of handling heterogeneous data across multiple domains and offers a foundation for future advancements in cross domain knowledge discovery.
Digital Twin Technology for Sustainable Industrial Operations Erlita Sulistiati; Bustomi Bustomi; Guslila Sari Nasution; Atina Salamah; Rian Ardianto
Technema: Journal of Intelligent Engineering and Computing Vol. 1 No. 2 (2026): : June: Technema: Journal of Intelligent Engineering and Computing
Publisher : CV SCRIPTA INTELEKTUAL MANDIRI

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Abstract

Digital Twin technology has emerged as a strategic enabler for sustainable industrial transformation by integrating physical operations, virtual representations, predictive analytics, and sustainability-oriented decision support into a unified cyber–physical environment. This study aims to develop and analytically evaluate a comprehensive Digital Twin framework capable of supporting sustainable industrial operations through the integration of operational efficiency, energy performance, resource optimization, and system resilience dimensions. A non-empirical system design approach was employed to construct a multilayer architecture consisting of physical operation, data acquisition, communication and synchronization, digital twin modeling, analytics and optimization, and sustainability decision-support layers. Technical evaluation was conducted through model-based simulation and analytical assessment using standardized sustainability and operational indicators. The findings demonstrate that the proposed framework strengthens operational visibility, predictive maintenance capability, energy efficiency, resource utilization, responsiveness, and resilience through continuous interaction between physical and virtual environments. The analysis further indicates that Digital Twin integration facilitates circularity, sustainability governance, and Industry 5.0 readiness by enabling adaptive and data-driven industrial decision making. The study contributes a holistic conceptual framework that advances the understanding of Digital Twin technology as a sustainability-enabling infrastructure for future industrial systems.  
AI driven Circular Waste to Energy Conversion System Using Smart Thermal Monitoring and Emission Optimization for Sustainable Urban Infrastructure Kiki Ahmad Baihaqi; Krisna Widi Nugraha; Rian Ardianto; Rosyid Ridlo Al-Hakim; Riza Phahlevi Marwanto; Erick Fernando
Green Engineering: International Journal of Engineering and Applied Science Vol. 2 No. 2 (2025): April : Green Engineering: International Journal of Engineering and Applied Sci
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v2i2.289

Abstract

This study explores the integration of Artificial Intelligence (AI) with thermal optimization in Waste-to-Energy (WtE) systems to enhance both energy recovery and emission control. Introduction: The growing need for sustainable urban waste management has highlighted the importance of optimizing WtE systems. AI technologies, including machine learning and deep learning, have shown potential in improving the efficiency of WtE processes, especially in reducing emissions and enhancing energy recovery. Literature Review: Previous research indicates that AI has been successfully applied to various WtE technologies such as pyrolysis, gasification, and incineration, yet the integration of AI specifically for thermal optimization remains underexplored. Most studies focus on predictive models for emission reduction rather than real time thermal optimization. Materials and Method: The study proposes the development of an AI-driven framework that integrates real time data collection from IoT sensors, predictive modeling, and real time control algorithms. The system optimizes key parameters such as combustion temperature and fuel flow to enhance energy recovery and minimize emissions. The method includes data collection from operational WtE plants, followed by model development using machine learning algorithms. Results and Discussion: Initial simulations and pilot testing showed significant improvements in energy efficiency and emission reduction. AI-driven systems outperformed conventional WtE systems by optimizing operational parameters in real time. The study identifies gaps in AI integration for thermal optimization and suggests future research directions, including the integration of AI with smart grids and carbon credit systems for more sustainable WtE operations.
Integrasi Teknologi IoT dan Aplikasi Telegram Untuk Pemantauan Kadar Gula Darah Penderita Diabetes: Membuat sebuah alat pengecekaan kadar gula darah secara non-invasive Jessa Syah Putra; Deny Nugroho Triwibowo; Rian Ardianto
Jurnal Teknologi Informasi (JUTECH) Vol. 6 No. 2 (2025): JUTECH: Jurnal Teknologi Informasi
Publisher : ITB Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/jutech.v6i2.3191

Abstract

Blood sugar (glucose) is the body's main source of energy and is classified as a monosaccharide. Blood sugar levels are divided into low, normal, and high, with high levels potentially triggering diabetes, one of the main health issues in Indonesia. This research proposes an Internet of Things (IoT)-based health monitoring system to measure blood sugar levels using a photodiode sensor and a red LED as the light source. The system is equipped with real-time notifications via Telegram and data display on an OLED screen. The method used is a prototype with accuracy testing against a glucometer as a comparison tool. The test results showed an average error of 5.28% out of a total error of 105.77%. However, the device often displays the same measurement results repeatedly and shows a “finger not detected” notification due to the sensor's sensitivity to surrounding light.
Klasifikasi Berisiko Stunting pada Balita: Perbandingan K-Nearest Neighbor, Naïve Bayes, Support Vector Machine Ramadya Wahyu Dwinanto; Arif Setia Sandi A; Rian Ardianto
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No2.pp264-273

Abstract

Stunting in children under five is a significant health problem that impacts child development. This study aims to develop a classification model to predict stunting risk using SVM, KNN, and Naïve Bayes algorithms. Data from the Jatilawang Health Center included 523 under-fives with variables such as age, weight, length, arm circumference, z-score, parental education, and maternal health history. Following the CRISP-DM steps, the data was processed through handling missing data, feature selection, and dividing the data into training and testing sets with a ratio of 80:20. Results showed SVM had the highest accuracy of 90%, followed by KNN 89%, and Naïve Bayes 85%. This research produces a stunting risk prediction model that is implemented in a simple website, supporting early intervention and decision-making in stunting prevention efforts.
Implementasi Teknologi Cerdas Berbasis IoT dan Telegram untuk Monitoring Kesehatan Jantung Lintang Desy Pangesti; Arif Setia Sandi A; Rian Ardianto
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 2 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No2.pp332-339

Abstract

The human heart acts as a vital organ that pumps blood throughout the body, and heart disease is the leading cause of death globally, including in Indonesia. To address this issue, this research proposes an Internet of Things (IoT)-based health monitoring system that can measure heart rate, oxygen saturation, and body temperature using MAX30100 and LM35 sensors. The system is equipped with real-time notification via Telegram and data display on an OLED screen. The method used is prototyping, with testing of sensor accuracy compared to conventional measuring instruments. The test results show good accuracy in BPM and SpO₂ measurements with an error of 5.78% and 3.6%, respectively, compared to the oximeter. However, body temperature measurement using the LM35 sensor showed an average error of 7.78%, due to the sensitivity of the sensor to ambient temperature.
Desain Sistem Informasi Geografis (GIS) untuk Pengelolan Infrastruktur Telekomunikasi di Daerah Terpencil: Geographic Information System (GIS) Design for Telecommunication Infrastructure Management in Remote Areas Moh. Khoridatul Huda; Rian Ardianto; Hadi Jayusman; Rosyid Ridlo Al-Hakim
Jurnal Kolaboratif Sains Vol. 7 No. 7: July 2024 - Jurnal Kolaboratif Sains (JKS)
Publisher : Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/jks.v7i7.5903

Abstract

Penelitian ini bertujuan untuk merancang Sistem Informasi Geografis (GIS) guna mendukung pengelolaan infrastruktur telekomunikasi di Desa Kutorojo, Kecamatan Kajen, Kabupaten Pekalongan. Menggunakan pendekatan kualitatif dengan metode survei, penelitian ini melibatkan wawancara mendalam dan observasi lapangan untuk mengumpulkan data terkait kondisi infrastruktur dan kebutuhan masyarakat. Hasil penelitian menunjukkan bahwa penerapan GIS meningkatkan akses dan kualitas layanan telekomunikasi, dengan 75% rumah tangga kini memiliki akses telekomunikasi yang lebih baik. Mayoritas pengguna melaporkan kepuasan tinggi terhadap kualitas layanan, berkat peningkatan kecepatan dan stabilitas jaringan. Partisipasi masyarakat dalam pengelolaan infrastruktur juga meningkat, mencapai 60%, yang berdampak positif pada pemeliharaan jangka panjang. Efisiensi pengelolaan infrastruktur ditingkatkan dengan pengurangan waktu perawatan sebesar 30% dan biaya sebesar 25%. Penelitian ini menyimpulkan bahwa GIS adalah solusi efektif dalam pengelolaan infrastruktur telekomunikasi di daerah terpencil, memberikan dampak ekonomi dan sosial yang positif. Penerapan GIS tidak hanya meningkatkan kualitas hidup masyarakat, tetapi juga menawarkan model pengelolaan infrastruktur yang dapat diterapkan di wilayah lain dengan tantangan serupa.
Socialization Of The Risks Of Polypharmacy And Education On Safe Medication Management For Elderly Patients With Degenerative Diseases Siti Setianingsih; Galih Samodra; Mega Kartika Sari; Lukman Hakim; Rian Ardianto; Atina Salamah
SAMBARA: Jurnal Pengabdian Kepada Masyarakat Vol 4 No 3 (2026): September
Publisher : CV Putra Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58540/sambarapkm.v4i3.2073

Abstract

Peningkatan populasi lansia berdampak pada tingginya penggunaan obat yang berisiko menimbulkan masalah polifarmasi, yang dapat menyebabkan interaksi obat berbahaya dan menurunkan kualitas hidup pasien. Kegiatan pengabdian masyarakat ini bertujuan meningkatkan pemahaman Kader Pemberdayaan Masyarakat (KPM) terkait pengelolaan obat berdasarkan prinsip DAGUSIBU (Dapatkan, Gunakan, Simpan, Buang) untuk mencegah risiko polifarmasi pada lansia penderita penyakit degeneratif. Metode yang digunakan adalah Edu-Tech Empowerment Cycle yang meliputi tahapan explore, design, build, implement, dan measure. Kegiatan dilaksanakan di Desa Karangrau dengan melibatkan 20 KPM melalui penyuluhan, diskusi, dan simulasi menggunakan media buku saku dan video tutorial. Evaluasi dilakukan menggunakan kuesioner pre-test dan post-test yang dianalisis secara deskriptif. Hasil kegiatan menunjukkan peningkatan pemahaman peserta pada seluruh indikator, dengan nilai rata-rata meningkat dari 74% pada pre-test menjadi 89% pada post-test. Kesimpulan kegiatan ini menunjukkan bahwa pendekatan edukasi partisipatif berbasis teknologi efektif meningkatkan kapasitas KPM sebagai agen edukasi kesehatan, yang berpotensi mendukung perbaikan kualitas kesehatan masyarakat secara berkelanjutan, khususnya pada lansia penderita penyakit degeneratif.
Strengthening Early Detection Of Pregnancy Risks Via An Intelligent System In Rural Communities Rian Ardianto; Deny Nugroho Triwibowo; Riska Suryani; Atina Salamah
SAMBARA: Jurnal Pengabdian Kepada Masyarakat Vol 4 No 3 (2026): September
Publisher : CV Putra Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58540/sambarapkm.v4i3.2098

Abstract

Maternal health is a crucial indicator of public health quality, yet monitoring in rural areas is often conducted manually with low technological literacy. This study aims to evaluate the effectiveness of technology-based education using a web-based application in improving health cadres' knowledge and skills regarding pregnancy danger signs, maternal and child nutrition, and early pregnancy risk detection. The method used is a participatory approach based on community engagement adapted with a design sprint framework, encompassing understand, define, develop, deliver, and evaluate stages. The activity involved 30 health cadres in Karangrau Village through counseling, discussions, and web-based application simulations. Evaluation used a descriptive Likert-scale pre-test and post-test questionnaire. Results showed a significant improvement in participants' understanding, with average scores increasing from 89% in the pre-test to 99% in the post-test. The use of a web-based application proved effective in concretely visualizing health data. In conclusion, the integration of participatory education and interactive technology effectively enhances cadre capacity and has the potential to become a sustainable educational model. This program is expected to encourage the utilization of simple technology as a medium for delivering health information at the community level.
Co-Authors Ainun Zumarniansyah Anis Okta Cahyaningrum Annisa Elfina Augustia Annisa Risqi Sulistya Kusuma Wardhani Arif Setia Sandi A. Asti Herliana, Asti Atina Salamah Atina Salamah Atina Salamah Baihaqi, Kiki Ahmad Bunga Aditi Bustomi Bustomi Dasril Aldo Deny Nugroho Triwibowo Emy Yunita Rahma Pratiwi, Emy Yunita Rahma Erick Fernando Erlita Sulistiati Euis Kusumarini Fachrurazi Ferdinandus Sampe Fitra Septia Nugraha Galih Samodra Gata, Windu Guslila Sari Nasution Hadi Jayusman Herdiyanti I Ketut Suada Iis Setiawan Mangkunegara Ita Soegiarto Jessa Syah Putra Julianto, Ribut Krisna Widi Nugraha Kurniawan, Yogiek Indra Lintang Desy Pangesti Loso Judijanto Lukman Hakim Mega Kartika Sari Moh. Khoridatul Huda Muhammad Asir Muhammad Ilham Prasetya Muhammad Yusuf Nila Hardi Qudsiah Nur Azizah Ramadya Wahyu Dwinanto Riska Suryani Riza Phahlevi Marwanto Rosyid Al-Hakim Rosyid Ridlo Al-Hakim Rosyid Ridlo Alhakim Siti Setianingsih Tb. Dedy Fuady Tri Rivanie Warkianto Widjaja Widya Lelisa Army Winny Purbaratri Yuris Alkhalifi Zarkasi Zarkasi