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BEES: Bulletin of Electrical and Electronics Engineering
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 27226522     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering
BEES: Bulletin of Electrical and Electronics Engineering focused on the energy system and power engineering, which is related to advance and develop technology on a wide-scope of all partial themes, but not limited, such as Control System, Artificial Intelligence, Informatics Engineering, Electronics, Advanced energy material, Automatic power control, Battery technology, Distributed generation, Distribution system, Electric power generation, Electric vehicle, Electrical machine, Energy optimization, Energy conversion, Energy efficiency, Energy exploitation, Energy exploration, Energy management, Energy mitigation, Energy storage, Energy system, Fault diagnostics, Green energy, Green technology, High voltage, Insulation technology, Intelligent power optimization, Monitoring operation, Motor drives, Natural energy source, Power control, Power data transaction, Power economic, Power electronics, Power engineering, Power generation, Power optimization, Power quality, Power system analysis, Power system information, Power system optimization, Protection system, Renewable energy, SCADA, Security operation, Smart grid, Stability system, Storage system, Transmission system, and etc.
Arjuna Subject : Ilmu Komputer (semua kategori) - Perangkat Keras dan Arsitektur
Articles 82 Documents
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Integrasi Sensor Elektroanalitik dan Kecerdasan Buatan dalam Pengawasan Pencemaran Industri: Analisis Bibliometrik 1998–2024 Nofriandi, Alwi; Yulkifli, Yulkifli; Dewata, Indang; Yohandri, Yohandri
BEES: Bulletin of Electrical and Electronics Engineering Vol 6 No 1 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bees.v6i1.7588

Abstract

The integration of electroanalytical sensors with artificial intelligence (AI) technology is increasingly becoming a major focus in the development of real-time and accurate industrial pollution monitoring systems. This study uses a bibliometric approach to analyze publication trends, journal sources, authors, and research topics related to voltammetry, impedimetry, and AI sensors in the context of industrial environmental quality monitoring during the period 1998–2024. The analysis results reveal a significant increase in the number of publications and citations since 2019, with the journals Sensors and Biosensors as the main publication channels. Prominent authors and emerging topics such as the use of artificial neural networks mark rapid progress in this field. However, there is still a need for the development of multifunctional sensors, IoT system integration, and more adaptive AI algorithms. This study emphasizes the urgency of further research with a multidisciplinary approach to support sustainable, efficient, and environmentally friendly industrial pollution monitoring.
Analisis Sistem Pendukung Keputusan Pemilihan Merek Pasta Gigi Terbaik Menggunakan Metode SERVQUAL dan ORESTE Safitri, Rahma Dhea; Wanto, Anjar
BEES: Bulletin of Electrical and Electronics Engineering Vol 6 No 1 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bees.v6i1.7713

Abstract

This study aims to address the problem of selecting the best toothpaste brand by developing a decision support system using a combination of the SERVQUAL and ORESTE methods. The problem raised is the difficulty consumers face in determining the most suitable product based on service quality. The SERVQUAL method is used to measure performance based on five dimensions of service quality, while ORESTE is used to rank alternatives without explicit weights. The system is implemented in the form of a data-driven evaluation model designed to mimic real-world conditions. The data reflects the perceived and expected values of several toothpaste brands, with the difference (GAP) calculated and processed using the ORESTE method to generate rankings. The results show that the Ciptadent brand received the highest preference with the lowest total ranking (6), followed by Oral-B and Colgate. The integration of these two methods enables a systematic and objective evaluation of overall service quality and can be used to support accurate consumer decision-making.

Page 9 of 9 | Total Record : 82

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