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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Pengabdian Kepada Masyarakat (Indonesian Journal of Community Engagement) Jurnal CoreIT Syntax Literate: Jurnal Ilmiah Indonesia JPP IPTEK (Jurnal Pengabdian dan Penerapan IPTEK) Jurnal Nasional Komputasi dan Teknologi Informasi Jesya (Jurnal Ekonomi dan Ekonomi Syariah) TELEKONTRAN: Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan Majalah Ilmiah UNIKOM Infotronik : Jurnal Teknologi Informasi dan Elektronika Journal of Islamic Civilization JPKMI (Jurnal Pengabdian Kepada Masyarakat Indonesia) REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat Jurnal Digit : Digital of Information Technology Journal of Computer, Electronic, and Telecommunication (COMPLETE) Jurnal Pengabdian Masyarakat Indonesia Asean Journal of Science and Engineering (AJSE) International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) International Journal of Research and Applied Technology (INJURATECH) Jurnal Locus Penelitian dan Pengabdian IJCOSIN : Indonesian Journal of Community Service and Innovation Jurnal Sistem Informasi dan Bisnis Cerdas Economics and Business Journal Jurnal Pengabdian Masyarakat Tekno ASEAN Journal for Science and Engineering in Materials Technologia Journal Big Data Analytics and Data Science Cyber Security and Network Management
Bobi Kurniawan, Bobi
Universitas Komputer Indonesia
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering 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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Public Health Social Sciences Transportation Other

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Analysis of the Effectiveness of Patient Flow Management in Improving Service Speed Hermawan, Randy; Umi Narinawati; Bobi Kurniawan
Jurnal Locus Penelitian dan Pengabdian Vol. 5 No. 3 (2026): JURNAL LOCUS: Penelitian dan Pengabdian
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/locus.v5i3.5557

Abstract

Speed of service is a vital indicator of the quality of health services, but the imbalance between surge in patient visits and facility capacity often leads to bottlenecks and long wait times. This study aims to analyze the effectiveness of the implementation of Patient Flow Management in improving service speed and operational efficiency in health facilities. The study used a quantitative descriptive approach through field observation (time and motion study), operational data measurement, and satisfaction survey at a private hospital during the period from July to September 2025. The results showed a significant impact post-implementation, where the average total waiting time was reduced by 41.5%, the doctor's workload ratio became more balanced from 1:38 to 1:26, and there was an increase in patient satisfaction scores by 30%. This efficiency is achieved through an effective strategy of digitizing the queue system and redistributing triage loads. In conclusion, Patient Flow Management has proven to be effective as an operational solution to unravel service density, but its success relies heavily on the integration of information systems and management support in adapting staff work cultures.
Konseptualisasi Ethno-Prompting: Strategi Humanisasi Layanan Kesehatan Digital Berbasis Kearifan Lokal Sunda Zaenudin, Aditya Rifandi; Narinawati, Umi; Kurniawan, Bobi
Jurnal Locus Penelitian dan Pengabdian Vol. 5 No. 3 (2026): JURNAL LOCUS: Penelitian dan Pengabdian
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/locus.v5i3.5559

Abstract

Latar belakang: Perkembangan layanan kesehatan digital berbasis kecerdasan buatan (Artificial Intelligence/AI) menghadirkan efisiensi dan aksesibilitas yang tinggi, namun di sisi lain menimbulkan tantangan berupa berkurangnya aspek humanisasi dan sensitivitas budaya dalam interaksi antara sistem dan pengguna. Di Indonesia, khususnya pada masyarakat Sunda yang menjunjung tinggi nilai kesantunan, empati, dan harmoni sosial, pendekatan layanan kesehatan digital yang bersifat generik berpotensi menimbulkan jarak psikologis serta menurunkan kepercayaan pengguna. Tujuan: Artikel ini bertujuan untuk mengembangkan konseptualisasi ethno-prompting sebagai strategi humanisasi layanan kesehatan digital berbasis kearifan lokal Sunda. Metode: Metode yang digunakan adalah pendekatan konseptual-deskriptif melalui kajian literatur interdisipliner yang mencakup etnografi Sunda, human-centered AI, komunikasi kesehatan, dan desain interaksi digital. Hasil: Hasil kajian menunjukkan bahwa ethno-prompting dapat dipahami sebagai teknik perancangan prompt AI yang mengintegrasikan nilai-nilai lokal Sunda seperti someah, silih asah, silih asih, dan silih asuh ke dalam struktur bahasa, gaya komunikasi, dan logika respons sistem digital. Pendekatan ini berpotensi meningkatkan rasa kedekatan emosional, kepercayaan, serta penerimaan masyarakat terhadap layanan kesehatan digital. Kesimpulan: Artikel ini berkontribusi pada pengembangan model konseptual layanan kesehatan digital yang lebih inklusif, kontekstual, dan berorientasi pada nilai budaya lokal.
Algorithmic Decision Making in Management: A Philosophical Inquiry from an Islamic Ethical Perspective Koswara, Asep; Umi Narimawati; Bobi Kurniawan
Journal of Islamic Civilization Vol 7 No 2 (2025): Journal of Islamic Civilization
Publisher : Universitas Nahdlatul Ulama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33086/jic.v7i2.8471

Abstract

The rapid diffusion of algorithmic decision making in management has reshaped how organizations evaluate employees, allocate resources, and exercise managerial authority. While such systems promise efficiency and objectivity, growing evidence shows that they also generate serious epistemological, ethical, and governance challenges. This paper aims to critically examine algorithmic decision making in management from an Islamic ethical and philosophical perspective, focusing on its epistemological, ontological, and axiological implications. Using a qualitative and conceptual research design, the study applies interpretive and normative analysis to major theories in management, artificial intelligence ethics, and Islamic moral philosophy. The results indicate that algorithmic decision making is built on epistemic assumptions that overstate objectivity, ontological ambiguities that risk displacing human moral agency, and axiological limitations that undermine justice, accountability, and human dignity. Drawing on Islamic ethical principles, particularly maqāṣid al-sharīʿah, justice (ʿadl), and trust (amanah), the study proposes a normative framework that re-centers human responsibility and ethical governance in the use of algorithmic systems. In conclusion, algorithmic decision making should be treated as a decision-support mechanism rather than an autonomous authority, and its legitimacy in management depends on its alignment with Islamic ethical values and the preservation of human moral agency.
Energy-Harvesting Materials for Autonomous Smart Farming Sensors: A Literature Review Riska Endah Septiani; Bobi Kurniawan; Senny Luckyardi; Eddy Soeryanto Soegoto; Dostnazar Ximmataliyev; Mohd. Kamir Yusof; Tomas Chochole; Hewa Majeed Zangana
ASEAN Journal for Science and Engineering in Materials Vol 6, No 1 (2027): AJSEM: Volume 6, Issue 1, March 2027
Publisher : Bumi Publikasi Nusantara

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

Abstract

The integration of the Internet of Things (IoT) in smart farming is hindered by limited battery life and the environmental impact of electronic waste. This review evaluates the development of energy-harvesting materials as a solution to power autonomous agricultural sensors. Through a systematic review, this paper analyzes three main mechanisms: Organic Photovoltaic (OPV), triboelectric nanogenerator/piezoelectric nanogenerator (TENG/PENG), and thermoelectric generator (TEG). Flexible polymers for TENGs and perovskite-based solar cells have the highest potential in addressing canopy shading and outdoor weather challenges. However, material toxicity and degradation due to UV and humidity remain major obstacles. Future research must prioritize biocompatible materials and hybrid systems to ensure the sustainability of precision agriculture.
IMPLEMENTASI METODE K-NEAREST NEIGHBOR (K-NN) DAN FORWARD CHAINING UNTUK MONITORING TUMBUH KEMBANG BALITA Petrus Sokibi Sukanto; Rifqi Fahrudin; Ridho Taufiq Subagio; Ednawati Rainarli; Adam Mukharil Bachtiar; Hanhan Maulana; Bobi Kurniawan
Jurnal Digit : Digital of Information Technology Vol 16, No 1 (2026)
Publisher : Universitas Catur Insan Cendekia (CIC) Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51920/jd.v16i1.460

Abstract

Pelayanan pelaporan hasil pemeriksaan balita di Posyandu seringkali menghadapi kendala akurasi dan keterlambatan informasi, yang menyulitkan kader serta orang tua dalam memantau tumbuh kembang anak secara efektif. Penelitian ini bertujuan untuk merancang bangun model sistem informasi berbasis website yang mampu menentukan status gizi dan perkembangan motorik balita secara akurat. Sistem ini mengintegrasikan dua metode kecerdasan buatan: K-Nearest Neighbor (K-NN) untuk klasifikasi status gizi berdasarkan antropometri, dan Forward Chaining untuk mendeteksi tahap perkembangan kemampuan motorik balita. Pengembangan model perangkat lunak dilakukan menggunakan framework CodeIgniter dengan pemodelan sistem menggunakan Unified Modelling Language (UML). Hasil penelitian menunjukkan bahwa model website ini memiliki performa yang sangat baik dengan tingkat akurasi sebesar 85,71% untuk penentuan status gizi melalui metode K-NN, dan tingkat akurasi mencapai 100% untuk identifikasi perkembangan motorik menggunakan Forward Chaining. Model ini diharapkan dapat menjadi alat monitoring yang handal bagi tenaga kesehatan dan orang tua. Sebagai pengembangan di masa depan, disarankan penambahan fitur switch akun bagi orang tua yang memiliki lebih dari satu balita untuk mempermudah manajemen data perkembangan anak secara personal.Kata kunci: Posyandu, Status Gizi, Perkembangan Balita, K-Nearest Neighbor, Forward Chaining.
ANALISIS KINERJA FUZZY LOGIC DALAM SISTEM PENETASAN TELUR OTOMATIS DENGAN FITUR MONITORING BERBASIS TELEGRAM BOT Rifqi Fahrudin; Ridho Taufiq Subagio; Petrus Sokibi; Zainal Arifin Hasibuan; Bobi Kurniawan; Sri Supatmi
Jurnal Digit : Digital of Information Technology Vol 16, No 1 (2026)
Publisher : Universitas Catur Insan Cendekia (CIC) Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51920/jd.v16i1.459

Abstract

Temperatur dan kelembaban merupakan dua faktor utama yang menentukan keberhasilan penetasan telur. Berdasarkan referensi, temperatur optimal dalam mesin tetas yaitu 35-39°C dan kelembaban optimal yaitu 40%- 56%RH. Namun kebanyakan mesin penetas telur konvensional yang ada dipasaran hanya memperhitungkan satu faktor saja yaitu temperatur. Untuk itulah digunakan system fuzzy logic control agar kestabilan suhu dapat terjaga. Dengan menggunakan nodemcu sebagai pengontrolan utama, hasil pembacaan sensor akan diproses sesuai dengan Algortitma Fuzzy Logic yang telah ditanamkan dalam minimum sistem. Lalu akan disesuaikan dengan Set Point yang telah ditetapkan. Output dari alat berupa sinyal digital yang akan mengontrol elemen fan cooller berupa kipas 5V DC. Logika fuzzy akan berjalan sesuai suhu ruangan jika suhu didalam ruangan lebih dari 39°C kipas akan berjalan sesuai output dari fuzzy rulebase. Jika suhu melebihi setting point yaitu 37-39°C maka lampu pijar akan mati, dan akan menyala kembali jika suhu kurang dari 38°C. Dalam hal ini semua aktivitas dalam ruangan penetas telur dalam di monitoring melalui telegram.  Hasil pengujian menunjukkan bahwa sistem kendali logika fuzzy berbasis parameter suhu dan kelembapan mampu menghasilkan keluaran yang presisi. Sebagai contoh, pada kondisi suhu 32°C dan kelembapan 60%, sistem secara otomatis mengaktifkan lampu dan mengatur kecepatan kipas sebesar 50% (Level 1) untuk menjaga stabilitas kondisi ruangan.Kata kunci: fuzzy logic control, suhu, kelembaban, NodeMCU, Telegram.
Transforming the Global Aquaculture Supply Chain through the Integration of Artificial Intelligence and Big Data for Overcome Asymmetry Information Hernalom Sitorus; Zaenal Arifin Hasibuan; Bobi Kurniawan; Sri Supatmi
Big Data Analytics and Data Science Vol. 1 No. 2 (2026): June: Big Data Analytics and Data Science
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/bdas.v1i2.443

Abstract

The global aquaculture sector faces structural challenges in the form of information asymmetry that causes a misalignment between production and market demand. The still-dominant production-driven paradigm leads to supply chain inefficiencies, low transparency, and limited traceability. This research aims to develop an information system integration model based on Artificial Intelligence (AI) and Big Data to transform the supply chain into a market-driven one. The research uses the Design Science Research (DSR) method, which includes needs analysis, data integration architecture design, development of Machine Learning and Deep Learning-based predictive models, and evaluation through prototype implementation. Expected outcomes include a data integration architecture, a supply-demand prediction model, and an AI-based traceability framework. This research contributes to improving the efficiency, transparency, and global competitiveness of the aquaculture sector.
Machine Learning Model Development for Adaptive Recruitment Recommendation System Based on Portfolio Analysis and Professional Network Rizki Adha; Zainal Arifin Hasibuan; Bobi Kurniawan; Sri Supatmi
Cyber Security and Network Management Vol. 1 No. 2 (2026): May: Cyber Security and Network Management
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/cybernet.v1i2.410

Abstract

The rapid advancement of digital transformation and artificial intelligence has significantly reshaped recruitment processes within organizations. Conventional recruitment systems predominantly rely on curriculum vitae screening and keyword-based matching, which often fail to capture contextual competencies and relational professional evidence. This study proposes the development of an adaptive machine learning–based recruitment recommendation system that integrates professional portfolio analytics and professional network structures within a unified graphbased framework. The proposed approach adopts a Research and Development (R&D) methodology under a data-driven system development paradigm. Candidate data from an existing recruitment system are integrated with external professional data sources, including GitHub and LinkedIn. A heterogeneous graph representation is constructed to model relationships among candidates, skills, projects, and organizations. Graph Neural Networks (GNN) are employed to learn contextual relational embeddings, while a Gradient Boosting Machine (GBM) is utilized for candidate job suitability classification. The proposed framework is designed to enhance objectivity, contextual awareness, and adaptability in recruitment decision-making. By leveraging multi-source digital professional evidence and incorporating an adaptive learning mechanism, the system aims to reduce skills mismatch and improve alignment between candidate competencies and evolving industry requirements. Future work will focus on empirical validation using real-world recruitment datasets and the integration of fairness-aware and explainable AI mechanisms to ensure transparency and ethical compliance.
Co-Authors Abd. Rasyid Syamsuri Adam Mukharil Bachtiar Agus Kurniawan Agus Riyanto Ahiase, Godwin Albaroky, M F Alviana, Sopian Andrean George Wibisono Ari Prayoga Arif Satria AS, Harun Asep Koswara Astiani, R Atin, Sufa Bachtiar, Adam Mukharil Budi Hartono Budi Herdiana Burhanuddin Burhanuddin Buston Kholik Damayanti, Sri Erina Dostnazar Ximmataliyev Eddy Soeryanto Soegoto Ednawati Rainarli Eko Budi Setiawan Firdaus, Dony Waluya Fitriadi, L H Harjono, Risqi Windu Hartono, Rodi Hermawan, Randy Hernalom Sitorus Heryandi, Andri Hewa Majeed Zangana Imtyramdhan, Afra Haniv Irawan Afrianto Irmayanti, Hani Ishwara, Luki Jana Utama, Jana Leslie Hendric Spits Warnars, Harco Martin Agusta Maryati, Mari Maulana, Hanhan Meyliana, M Meyliana, M. Mohd. Kamir Yusof Muhammad Aria Rajasa Pohan Muhammad Helmi Narinawati, Umi Nawawi, Muhamad Nerinawati, Umi Petrus Sokibi Petrus Sokibi Sukanto Popon Dauni Purnamasari, Novia Puspita, Rita Sari RAHAJOENINGROEM, TRI Rainarli, Ednawati Resviani, Devi Ridho Taufiq Subagio Rifqi Fahrudin Riska Endah Septiani Rizal Rachman, Rizal Rizki Adha Rizki Dwi Nugraha Salim, Andi Agus Santy, Raeny Dwi Senny Luckyardi Sopian Alviana Sopian Alviana Sopian Alviana Sri Supatmi Sri Supatmi Suharjo, Bambang Supatmi , Sri Syaddad, Hasbu Naim Tomas Chochole Tri Rahajoeningroem Umi Narimawati Umi Narinawati Warnars, Harco Leslie Hendric Spits Wildan Zulfikar Djunaedi Zaenal Arifin Hasibuan Zaenudin, Aditya Rifandi Zainal Arifin Hasibuan Zainal Arifin Hasibuan zulkifli, ridwan