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All Journal Journal of Health (JoH) International Conference on Maritime Technology and Its Application
Nurahmad Hadi Cahyadi
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Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Mechanical Engineering Medicine & Pharmacology Nursing Public Health

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Perancangan Sistem Penentuan Kualitas Lingkungan Kerja Berdasarkan Multy Parameter Input Menggunakan Metode Mamdani Fuzzy Inferensi System (FIS): Design of a System for Determining the Quality of the Work Environment Based on Multi Parameters Input Using the Mamdani Fuzzy Inferenence System (FIS) Method Nurahmad Hadi Cahyadi; Vanny Nastiti; Anugerah Ekha Gusti Audryadmaja; Denny Oktavina Radianto
Journal of Health (JoH) Vol 10 No 2 (2023): Journal of Health (JoH) - July
Publisher : LPPM STIKES Guna Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30590/joh.v10n2.646

Abstract

The work environment has the potential for Occupational Diseases which cause health problems for workers due to physical work environment factors. The physical work environment is in the form of infrastructure conditions, temperature, lighting and noise, while the non-physical work environment is related to work relations and communication. Workers have the right to work in a safe and comfortable working environment because it is the main factor in determining worker conditions. A supportive work environment can trigger workers to increase productivity. The purpose of this study was to determine the comfort level of a workplace using three variables, namely temperature, lighting and noise with the Mamdani Fuzzy Inference System (FIS) approach. Using the Mamdani FIS method and Matlab R2010b program, it is expected to measure the condition of the work environment, including temperature, lighting, and noise, so that if the work environment conditions are inadequate, evaluation and improvement can be carried out. This research was carried out by a system engineering to determine the quality of the workplace environment using the Mamdani FIS method algorithm through the matlab software. It has been assumed that there are three indicator variables used to determine a condition in which each variable has its own decomposition of the input function and fuzzy set. Based on the case study used as a sample, the room conditions had a temperature level of 22°C, 55 db of noise and 210 lux of lighting, which resulted in an environmental quality of 91.3 with good workspace criteria.
Perancangan Sistem Diagnosis Kesehatan Manusia Melalui Screening Digital Berbasis Desktop Application Menggunakan Metode Forward Chaining dan Neural Network: Design of a Human Health Diagnosis System Through Desktop Application-Based Digital Screening Using Forward Chaining and Neural Network Methods Agustin, Indis Dwi; Nurahmad Hadi Cahyadi; Mifta Aulia Ramadhani; Mujtaba Fa’akuli Zazila; Am Maisarah Disrinama
Journal of Health (JoH) Vol 11 No 1 (2024): Journal of Health (JoH) - January
Publisher : LPPM STIKES Guna Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30590/joh.v11n1.702

Abstract

The problem of hospital services, one of which is queuing, is important because it affects hospital productivity. Hospital queues can be caused by the large number of patients and the length of patient treatment. According to the Regulation of the Minister of Health of the Republic of Indonesia Number 30 of 2022, the standard of patient satisfaction with health services must reach ≥ 90% where one of the indicators is the long waiting time. Long waiting times or queues can cause medical services to be less than optimal, especially for patients who have emergency complaints (Prabowo, 2019). Therefore, to increase the productivity of hospital services, a human health diagnosis system is designed through a desktop application-based digital screening using the forward chaining and neural network methods to make it easier for doctors to diagnose patient diseases. This innovation is also equipped with severity detection and treatment recommendations for patients. The purpose of this study is to create a knowledge model that can predict patient disease. The results of this study were obtained that the accuracy of testing the diagnosis of patient disease reached 86.6% with the functional ability of the designed diagnostic application to function 100%. With this innovation, the diagnosis of symptoms of human disease can be carried out precisely and precisely so that hospital productivity and health status in every community in Indonesia increase.
Orientation Holding Control for Autonomous Surface Vehicles using Adaptive Neuro-Fuzzy Inference System Method Dimas Prostovani Riananda; Nurahmad Hadi Cahyadi; Zindhu Maulana Ahmad Putra; Joko Endrasmono; Ryan Yudha Adhitya; Agus Khumaidi
International Conference on Maritime Technology and Its Application Vol. 3 No. 1 (2025): ICOMTA : International Conference on Maritime Technology and Its Application
Publisher : Surabaya State Polytechnic of Shipbuilding

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35991/icomta.v1i1.2

Abstract

The completion of autonomous surface vehicle water missions is required to have adaptive capabilities in maintaining the position, attitude or tilt, and stability of the ship against the influence of external disturbances that can interfere with the ASV's navigation system. Therefore, this research focuses on the orientation holding control system against external disturbances. To determine the value of the angular shift or tilt of the ship's facing direction using the CMPS14 sensor. The control method used to determine the ship's propulsion response in determining the speed based on the heading error value and the amount of rotation speed through the bow thruster in maintaining the ship's heading using the ANFIS (Adaptive Neuro-Fuzzy Inference System) Method. The ANFIS model that has been made for predicting the value has an RMSE value of 1.6169% which is then implemented on a microcontroller with conversion and has an accuracy value of 99,6%. In testing the performance of the ship orientation control system by giving 10 variations of disturbance shows an average response time of 5.08 seconds. So that the application of the ANFIS method in this control system has good performance and can be used as a reference for further research.
Co-Authors Agus Khumaidi Agustin, Indis Dwi Am Maisarah Disrinama Anugerah Ekha Gusti Audryadmaja Dimas Prostovani Riananda Joko Endrasmono Mifta Aulia Ramadhani Mujtaba Fa’akuli Zazila Radianto, Denny Oktavina Ryan Yudha Adhitya Vanny Nastiti Zindhu Maulana Ahmad Putra