Agfianto Eko Putra
Departemen Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta

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Rancang Bangun Spectrum Analyzer Menggunakan Fast Fouier Transform Pada Single Board Computer Afandi Nur Aziz Thohari; Agfianto Eko Putra
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 7, No 1 (2017): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (690.294 KB) | DOI: 10.22146/ijeis.16417

Abstract

Spectrum analyzer is an instrument device to measure the magnitude of the frequency and the power of signal. It has many benefits, such as used for testing telecommunication devices, determining the allocation of unused frequencies and also for practicum in schools or universities. However, because of these many benefits, the price of this signal measuring equipment soared in the market.As an alternative, a device that can serve as spectrum analyzer yet has an affordable price is invented in the form of the prototype of spectrum analyzer built using a single board computer by applying a fast Fourier transform algorithm. Feedback from the prototype is in the form of radio signal captured using RTL-SDR.The test results showed that the range of frequencies that can be displayed by the prototype is 24 MHz to 1.769 MHz. Then the test results of fast Fourier transform computing on N points showed that the prototype can work smoothly using the N from 512 to 32.768 points. The use of N more than 32.768 points will cause CPU and disk memory overloaded and lead to a slow performance. Finally, comparison of the levels of spectrum was performed using spectrum analyzer Anritsu MS2720T. As a result, it is known that prototype can be used to show the location of the frequency spectrum of the radio signal appropriately.
Deteksi Kesalahan Pengucapan Huruf Jawa Carakan dengan Jaringan Syaraf Tiruan Perambatan Balik JK Aditya Christya Buditama; Catur Atmaji; Agfianto Eko Putra
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 11, No 2 (2021): Oktober
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.53437

Abstract

Javanese is an Indonesian culture which needs to be preserved, but many Javanese students make mistakes in the pronunciation of Javanese letters and find it difficult to analyze errors by human teachers because of the limited time and subjective assessment, so a system is needed to detect incorrect pronunciation of Javanese letters. Mispronunciation detection system has been widely applied in foreign languages, but the system has not been implemented for Javanese carakan letters. This research develops the Javanese letters mispronunciation detection system using Back-Propagation Artificial Neural Networks (BP-ANN). The dataset is obtained from the recorded pronunciation of hanacaraka texts by 24 speakers  with 5 repetitions. ALNS method then used to automatically segment the signal into syllables. ANN-PB use statistical value of Mel-Frequency Cepstral Coefficient (MFCC) method with 7 and 14 coefficients. 10-Fold Cross Validation is used to validate and test the system. The Javanese mispronunciation detection using 7MFCC coefficients produces the highest accuracy of 80,07%. While the Javanese mispronunciation detection using 14 MFCC coefficients produces an accuracy of 82.36% at the highest.