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Contact Name
Risky Ayu Kristanti
Contact Email
ayukristanti@gmail.com
Phone
+6282153870439
Journal Mail Official
gisa@tecnoscientifica.com
Editorial Address
Editorial Office - Green Intelligent Systems and Applications Jalan Asem Baris Raya No 116 Kebon Baru, Tebet, Jakarta Selatan Jakarta 12830, Indonesia
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Kota adm. jakarta selatan,
Dki jakarta
INDONESIA
Green Intelligent Systems and Applications
Published by Tecno Scientifica
ISSN : -     EISSN : 28091116     DOI : https://doi.org/10.53623/gisa.v2i1
The journal is intended to provide a platform for research communities from different disciplines to disseminate, exchange and communicate all aspects of green technologies and intelligent systems. The topics of this journal include, but are not limited to: Green communication systems: 5G and 6G communication systems, power harvesting, cognitive radio, cognitive networks, signal processing for communication, delay tolerant networks, smart grid communications, power-line communications, antenna and wave propagation, THz technology. Green computing: high performance cloud computing, computing for sustainability, CPSS, computer vision, distributed computing, software engineering, bioinformatics, semantics web. Cyber security: cryptography, digital forensics, mobile security, cloud security. Internet of Things (IoT): sensors, nanotechnology applications, Agriculture 5.0, Society 5.0. Intelligent systems: artificial intelligence, machine learning, deep learning, big data analytics, neural networks. Smart grid: distributed grid, renewable energy in smart grid, optimized power delivery, artificial intelligence in smart grid, smart grid control and operation.
Articles 61 Documents
Integration of Naïve Bayes-Based Stunting Status Classification and GIS Hotspot Mapping for the Identification of Priority Areas in Tomohon City, Indonesia Eunice Emely Eurika Pitoy; Chatreen Rindu Ceyzia Pontoh; Marike Kondoj; Herry Langi; Maksy Sendiang
Green Intelligent Systems and Applications Volume 6 - Issue 1 - 2026
Publisher : Tecno Scientifica Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53623/gisa.v6i1.1190

Abstract

Stunting remained a public health problem that required data- and area-based monitoring so that interventions could be implemented in a targeted manner. This study aimed to develop an integrated system for classifying stunting status and identifying priority areas in Tomohon City through the combination of WHO Z-Score standards, the Naïve Bayes algorithm, prevalence calculation, and hotspot mapping based on a Geographic Information System (GIS). This study employed a Research and Development (R&D) approach consisting of needs analysis, design, implementation, testing, and evaluation stages. Toddler data were obtained from the Tomohon City Health Office, including age, sex, height or body length, weight, residential area, urban village, district, and community health center. The system was developed using MySQL, Python, PHP Framework CodeIgniter 3, and GIS. The results showed that the system was able to classify toddlers’ nutritional status into normal, stunted, and severely stunted categories, calculate prevalence by urban village, and display the distribution of cases in the form of a digital map. Gaussian Naïve Bayes modeling using 970 training data points and 243 testing data points produced an accuracy of 94.7%, precision of 31.6%, recall of 33.3%, and F1-score of 32.4%. GIS hotspot visualization helped identify priority areas, although data coverage still needed to be expanded to make the results more representative.