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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan
Dinita Rahmalia
Department of Mathematics, University of Islam Darul Ulum Lamongan, Indonesia
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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ESTIMATION OF THIRD FINGER MOTION USING ENSEMBLE KALMAN FILTER Teguh Herlambang; Hendro Nurhadi; Abdul Muhith; Dinita Rahmalia; Berny Pebo Tomasouw
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 3 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (460.243 KB) | DOI: 10.30598/barekengvol16iss3pp1079-1086

Abstract

Post-stroke is a stage a patient undergoes if the patient has had a previous stroke. Stroke is a big and serious problem. As the second most common cause of disability of people at age of over 60 years. For patients having experienced a stroke, rehabilitation is a way to make them able to do activities of daily living as before. Stroke Rehabilitation is a comprehensive medical management and rehabilitation (in medical, emotional, social, and vocational aspects) concerning disabilities caused by stroke through a neuro-rehabilitation approach with the aim of optimizing recovery. The finger prosthetic arm robot is one of the results of the health technology development to help accelerate the rehabilitation process specifically for finger movements. One of the efforts to develop a finger robot is to estimate the movement of the fingers, in this case the finger size used is taken from those of Javanese people in Indonesia as the data to be simulated. In this paper is an estimation of the finger motion,particularly that of the third finger of the right hand, conducted using the Ensemble Kalman Filter (EnKF) method. The simulation results produced the third finger motion estimates with an accuracy of around 92% - 99%.
DIVING MOTION ESTIMATION OF REMOTELY OPERATED VEHICLE USING ENSEMBLE KALMAN FILTER AND H-INFINITY Teguh Herlambang; Andy Suryowinoto; Dian Adrianto; Dinita Rahmalia; Hendro Nurhadi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (423.202 KB) | DOI: 10.30598/barekengvol17iss1pp0095-0100

Abstract

ROV (Remotely Operated Vehicle) is a product of technological development, functioning to perform tasks in the water. Big tasks such as coral reef exploration, oil refineries, underwater monitoring, and sea accident rescue are carried out by such technology. ROV or unmanned submarines have 6 degrees of freedom, but for diving it requires only 3 movements, that is, surge, heave, and pitch motions. In its operation, the ROV requires a navigation system in the form of estimation of the ROV position under diving conditions. In this study, two methods were used to estimate the ROV position under diving conditions, that is, the H-infinity method and the Ensemble Kalman Filter (EnKF). Both methods proved reliable on other platforms. The simulation results in this study showed that the EnKF method was more accurate than the H-Infinity method. The H-Infinity method had an accuracy of around 87%, while the EnKF method reached an accurate of 99 %.
Co-Authors Abdul Muhith Andy Suryowinoto Dian Adrianto Hendro Nurhadi Teguh Herlambang Tomasouw, Berny Pebo