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All Journal International Journal of Electrical and Computer Engineering Sinergi Jurnal Teknologi Elektro Journal of Robotics and Control (JRC) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Informatika: Jurnal Pengembangan IT Scientific Contributions Oil and Gas
Galang Persada Nurani Hakim
Universitas Mercu Buana
Aerospace Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Journal : Sinergi

 1 
SENSOR SELECTION COMPARISON BETWEEN FUZZY TOPSIS ALGORITHM AND SIMPLE ADDITIVE WEIGHTING ALGORITHM IN AUTOMATIC INFUSE MONITORING SYSTEM APPLICATION Budiyanto, Setiyo; Hakim, Galang Persada Nurani; Firdausi, Ahmad; I. M, Fajar Rahayu
SINERGI Vol 24, No 3 (2020)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2020.3.005

Abstract

One of the critical equipment to support a patient in the hospital would be an infuse system. One of the main problems with the infuse system was manual monitoring. Few researchers try to build a low cost infuse system using a low-cost sensor and microcontroller. This paper proposes a fuzzy Topsis algorithm and Simple Additive Weighting (SAW) algorithm to choose the best sensor for a low cost to the infuse system, which is one of the Multiple Criteria Decision Making (MCDM) problems. Several simulations using three sensors, such as LDR (photoresistor), phototransistor, and photodiode, are performed. By using these two algorithms, it can be shown that the phototransistor emerges as the best sensor with value 1, even though it has the price six times higher from the LDR sensor and three times higher from the photodiode.
SENSOR SELECTION COMPARISON BETWEEN FUZZY TOPSIS ALGORITHM AND SIMPLE ADDITIVE WEIGHTING ALGORITHM IN AUTOMATIC INFUSE MONITORING SYSTEM APPLICATION Setiyo Budiyanto; Galang Persada Nurani Hakim; Ahmad Firdausi; Fajar Rahayu I. M
SINERGI Vol 24, No 3 (2020)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2020.3.005

Abstract

One of the critical equipment to support a patient in the hospital would be an infuse system. One of the main problems with the infuse system was manual monitoring. Few researchers try to build a low cost infuse system using a low-cost sensor and microcontroller. This paper proposes a fuzzy Topsis algorithm and Simple Additive Weighting (SAW) algorithm to choose the best sensor for a low cost to the infuse system, which is one of the Multiple Criteria Decision Making (MCDM) problems. Several simulations using three sensors, such as LDR (photoresistor), phototransistor, and photodiode, are performed. By using these two algorithms, it can be shown that the phototransistor emerges as the best sensor with value 1, even though it has the price six times higher from the LDR sensor and three times higher from the photodiode.
ANFIS method to enhance FMEA water operation model of Indonesia drinking water distribution system Septiyana, Diah; Abd. Rahman, Mohamed; Mohamed Ariff, Tasnim Firdaus; Rosarina, Desy; Adesta, Erry Yulian T.; Hakim, Galang Persada Nurani; Sukindar, Nor Aiman
SINERGI Vol 29, No 1 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2025.1.016

Abstract

Many problems are found in water treatment and distribution in water operations. Those problems range from low to critical risk. All critical risks must be addressed immediately. The Failure Mode and Effects Analysis (FMEA) prioritizes problems based on Occurrence, Severity, and Detection values to identify critical risks. However, this method is also having problems. With the same risk priority number (RPN) calculation, FMEA would be a ranking problem with the same RPN value; hence, we have a priority problem that is not critical but based on the highest value. To solve this problem, we propose additional methods, such as the ANFIS, to give weight based on risk level classification. From the results of data processing carried out by the ANFIS method, it is proven that it can perform re-ranking, for example, in the L2, R5, S8, and U3 code, which has an FMEA RPN value of 12. However, in FMEA-ANFIS, the RPN value becomes L2 2.05, R5 1.52, S8 1.32, and U3 2.52. Furthermore, with these results, it can be concluded that the ANFIS method can enhance the FMEA model in water operations.
Co-Authors Abd. Rahman, Mohamed Adesta, Erry Yulian T. Ahmad Firdausi Akhmad Wahyu Dani, Akhmad Wahyu Dian Widi Astuti, Budi Irawan Prima Putra, Dian Widi Astuti, Eko Ramadhan Eko Ramadhan Fadli Sirait Firdaus, Dhiya Akmal Habibi, Hamzah Iswanto Suwarno Majid, Huda A. Mirna Yunita Mohamed Ariff, Tasnim Firdaus Mohd. Radzi Abu Mansor Muhammad Hafizd Ibnu Hajar Nurrozan, Iqbal Rachmat Muwardi RAHAYU, FAJAR Ramadhan, Eko Rosarina, Desy Septiyana, Diah Septiyana, Diah Setiyo Budiyanto Sukindar, Nor Aiman