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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Teknologi Proceeding of the Electrical Engineering Computer Science and Informatics Conference SENATIK STT Adisutjipto Yogyakarta International Journal of Applied Sciences and Smart Technologies Abdimas Altruis: Jurnal Pengabdian Kepada Masyarakat Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Linggo Sumarno
Universitas Sanata Dharma
Aerospace Engineering Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Other

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Pengenalan Kerusakan Mekanis Pompa Air Berbasis Sinyal Getaran pada Ranah Frekuensi Linggo Sumarno; R.B. Dwiseno Wihadi; Tjendro; Wiwien Widyastuti
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 4 No 2: Mei 2015
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (984.762 KB)

Abstract

One way in recognizing mechanical faults of electrical machines is using the vibration signals. This paper studies the recognition of mechanical faults of electrical machines which have faulty bearing, faulty impeller, and faulty foot valve. Electrical machines studied in this paper are household water pumps. The recognition of mechanical faults is conducted using the vibration signals at the frequency domain at various frequency resolution. The recognition method used is template matching for pattern classes. Euclidean distance function is used in this template matching. Based on the results, the highest recognition rate of 100% is optimally obtained using the vibration signal at frequency resolution of 5,9 Hz, and the number of 5 samples/classes in the water pump database. The 5,9 Hz frequency resolution was obtained using a 256 point FFT, where the number of 128 FFT coefficients are used as the feature extraction.
Musical Instrument Tone Recognition Using DCT Based Feature Extraction And Gaussian Windowing Sumarno, Linggo
SENATIK STT Adisutjipto Vol 5 (2019): Peran Teknologi untuk Revitalisasi Bandara dan Transportasi Udara [ISBN 978-602-52742-
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/senatik.v5i0.295

Abstract

The conducted research studied a feature extraction method in a musical instrument tone recognition system. The purpose of this study was to obtain a number of feature extraction coefficients that are smaller than those obtained in previous studies. The studied feature extraction was a DCT (Discrete Cosine Transform)-based segment averaging and Gaussian windowing. The testing of the musical instrument's tone recognition system was carried out using pianica, tenor recorder, and bellyra musical instruments, each of which represented many, several, and one significant local peaks in the transform domain. The test results showed that the optimal number of feature extraction coefficient was 8 coefficients, which could give a recognition rate of up to 100%. The test results were achieved using a Gaussian window with a sigma value of 2-6, and a 128 points DCT.
Evaluating The Performance of DWT-DCT Feature Extraction in Guitar Chord Recognition Sumarno, Linggo
International Journal of Applied Sciences and Smart Technologies Volume 06, Issue 2, December 2024
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/ijasst.v6i2.9972

Abstract

This study presents advancements in audio signal processing techniques, specifically in enhancing the efficiency of guitar chord recognition. It is a continuation of the previous studies, which also aim at minimizing the feature extraction length with the intended performance. This study adopted two signal processing techniques that are common: Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT) for use in the feature extraction method. By conducting a systematic evaluation of two key parameters: frame blocking length and wavelet filter selection, a significant achievement could be achieved. The recognition system managed to obtain chord recognition with an accuracy of up to 91.43%, by using a feature extraction length of only three, which brought about smaller representation than the previous studies. The outcome of this study will help improve the data processing, which can be applied in real time, in this case in Field Programmable Gate Array (FPGA)-based chord recognition systems. Keywords: chord recognition, Discrete Wavelet Transform, Discrete Cosine Transform, feature extraction
RELOKASI SISTEM PANEL SURYA UNTUK KEPERLUAN POMPA AIR DI PANTAI GRIGAK GUNUNG KIDUL Sumarno, Linggo; Suwarno, Djoko Untoro; Iswanjono, Iswanjono; Martanto, Martanto
ABDIMAS ALTRUIS: Jurnal Pengabdian Kepada Masyarakat Vol 7, No 2 (2024): Oktober 2024
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/aa.v7i2.10198

Abstract

The Grigak Beach community experiences difficulty obtaining clean water, especially during the dry season. The lack of duration of the solar panel system that powers the water pump in the drilled well is the cause. Therefore, an effort was made to relocate the solar panel system from the previous location to a new location, which allows the solar panel system to have a longer lifespan. The community service that was carried out successfully relocated the solar panel system from the old location to the new one. The solar panel system can have a lifespan of about two hours longer.
Co-Authors Anak Agung Istri Sri Wiadnyani Damar Widjaja Damar Widjaja Djoko Untoro Suwarno Gunawan, Vincentius Abdi Iswanjono Iswanjono Iswanjono Iswanjono Kuntoro Adi Martanto . Martanto Martanto Petrus Setyo Prabowo Primawan, A.Bayu Putra, Leonardus Sandy Ade R.B. Dwiseno Wihadi Rifai Chai Setiyani, Th. Prima Ari Theresia Prima Ari Setiyani Tjendro Tjendro Tjendro Wihadi, R.B. Dwiseno Wiwien Widyastuti