SISTEM ABSENSI MAHASISWA UNTUK PENENTUAN POSISI BERBASIS RFID MENGGUNAKAN ALGORITMA SUPPORT VECTOR REGRESSION

RABBANI, MUHAMMAD FIKRI and Oklilas, Ahmad Fali (2020) SISTEM ABSENSI MAHASISWA UNTUK PENENTUAN POSISI BERBASIS RFID MENGGUNAKAN ALGORITMA SUPPORT VECTOR REGRESSION. Undergraduate thesis, Sriwijaya University.

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Abstract

There are many kinds of positioning system that have been used in daily life. From global implementation like the gps to indoor uses such as item tracking and factory management. RFID is usually used in indoor positioning system because of cost efficiency and relatively easy implementation. Student attendence management is a field that can be improved with RFID system. Compared to traditional and biometric attendence, RFID can provide positioning feature of students in the class. Position tracking is particularly useful for remote supervision, such as exam where the arrangement of student’s seating is very critical. This research proposed a support vector regression method for predicting student position and kalman filter as preprocessing to reduce fluctuation in signal data. Kalman filter is able to reduce standard deviation of signal data from 147,07 to 21,086. Position prediction has an average error of 70,6 cm for 4 antenna configuration and 57,78 cm for 2 antenna configuration.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Absensi, Penentuan Posisi, RFID, Support Vector Regression, Kalman Filter
Subjects: T Technology > T Technology (General) > T1-995 Technology (General)
T Technology > T Technology (General) > T10.5-11.9 Communication of technical information
T Technology > T Technology (General) > T58.5-58.64 Information technology > T58.5 General works Management information systems Cf. HD30.213 Industrial management Cf. HF5549.5.C6+ Communication in personnel management Cf. TS158.6 Automatic data collection systems (Production control)
Divisions: 09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User: Muhammad Fikri Rabbani
Date Deposited: 25 Jan 2021 04:39
Last Modified: 25 Jan 2021 04:39
URI: http://repository.unsri.ac.id/id/eprint/40768

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