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Journal : Journal Of Engineering Sciences (Improsci)

Implementation Of Speech Recognition For Voice Command Use Maturidi, Ade Johar; Osman, Didan; Sulaeman, Muhamad
Jurnal Improsci Vol 3 No 1 (2025): Vol 3 No 1 August 2025
Publisher : Ann Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62885/improsci.v3i1.1008

Abstract

Background. Physical limitations of a person sometimes make it impossible to operate a computer with only a keyboard and mouse, Aims. One tool that can be used is a voice command, which is part of speech recognition technology. Methods. The voice signal will be normalized first, and then the coefficient values will be calculated using the Linear Predictive Coding (LPC) and Fast Fourier Transform (FFT) methods. After the coefficient value is obtained, recognition is performed using the backpropagation method of the Artificial Neural Network. Conclusion. The artificial neural network backpropagation method is used because it can adjust its own weights and produce error values that we can determine, thereby improving accuracy. Implementation. This study implements a voice command system using MARF as its speech engine and Java as its programming language.
Implementation Of The Bagging-Based C4.5 Algorithm To Analyze Customer Satisfaction In Electronic Pulse Sulaeman, Muhamad; Setiawan, Mohamad; Irpan, M. Taufiq
Jurnal Improsci Vol 3 No 1 (2025): Vol 3 No 1 August 2025
Publisher : Ann Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62885/improsci.v3i1.1009

Abstract

Background. Many users of Telkom mobile or gadgets in the world, especially in the field of mobile telecommunications technology, provide much convenience for the customer to make purchases of electronic top-up. Aims. Competition among suppliers of telecommunication service providers requires an analysis to determine the level of customer satisfaction with electronic pulses. Methods. In this study, the C4.5 and C4.5 Algorithm Based on Bagging will be used to analyze customer satisfaction, with data collected from 460 customers and 11 variables related to electronic top-up. Conclusion. This research aims to generate customer satisfaction analysis using the C4.5 and C4.5 algorithms, based on the bagging algorithm, to determine an appropriate method for analyzing customer satisfaction with electronic top-up.