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All Journal Bulletin of Electrical Engineering and Informatics Techno (Jurnal Fakultas Teknik, Universitas Muhammadiyah Purwokerto) Semesta Teknika Jurnal Ilmiah Dinamika Rekayasa (DINAREK) Techne : Jurnal Ilmiah Elektroteknika Indonesian Journal of Community Services Makara Journal of Technology Techno Jurnal Rekayasa elektrika RENATA Jurnal Pengabdian Masyarakat Kita Semua Jurnal INFOTEL
Hesti Susilawati
Program Studi Teknik Elektro, Fakultas Sains Dan Teknik, Universitas Jenderal Soedirman, Purwokerto 53122
Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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Journal : Semesta Teknika

 1 
Sistem Pendeteksian Kerusakan Mesin Sepeda Motor 4-Langkah Berbasis Suara Menggunakan Support Vector Machine (SVM) et.al, Hesti Susilawati ,
Jurnal Semesta Teknika Vol 14, No 1 (2011): MEI 2011
Publisher : Jurnal Semesta Teknika

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Abstract

Detection process early towards motorcycle engine condition will be important matter especially for common user motorcycle. This detection can be used to estimate motorcycle engine condition (normal or damage), damage kind, how big damage influence towards motorcycle continuance, motorcycle duration can survive with damage and cost estimate that taked suppose will repair damage. In this research is built 4-stroke motorcycle engine damage detection system based on voice uses Support Vector Machine (SVM) multi class. In system that proposed, motorcycle engine voice is recorded and then cultivated so that produce feature shaped coefficient Linear Predictive Coding (LPC). Coefficient LPC that extracted from this motorcycle engine voice then become an input for SVM. Furthermore SVM will determine motorcycle engine condition. Engine condition detection system based on SVM this meant to detect three engine conditions that is normal condition, damage cham chain and damage ignition system. System applications that proposed show that motorcycle engine condition detection system based on voice uses SVM has good accuracy that is 100%.
Simulasi Cell Breathing CDMA 2000 1x Menggunakan DELPHI Perdana, Ilham; Hikmaturokhman, Alfin; Susilawati, Hesti
Jurnal Semesta Teknika Vol 10, No 1 (2007): MEI 2007
Publisher : Jurnal Semesta Teknika

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Abstract

Cell breathing is variation of CDMA cell size depends upon the amount of traffic occurs within the cell. This work assume that the cell is in the ideal condition based on  the following assumptions,  each cell is completely isolated from the other cells, with the result that no intercell interference and signals from MS cause no interference within the cell. It makes no intracell interference occurs within the cell. In an ideal condition where is none of interference occurs, cell size and amount of users in a cell depend on several factors such as bitrate, required signal strength that MS must deliver to BS, voice activity factor, power control accuracy factor and Eb/It of the system. The result obtained by change the values of the parameters and based on the result obtained, the impact of the parameter to the cell size and amount of user in a cell could be recognized.
Sistem Pendeteksian Kerusakan Mesin Sepeda Motor 4-Langkah Berbasis Suara Menggunakan Support Vector Machine (SVM) et.al, Hesti Susilawati ,
Semesta Teknika Vol 14, No 1 (2011): MEI 2011
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/st.v14i1.584

Abstract

Detection process early towards motorcycle engine condition will be important matter especially for common user motorcycle. This detection can be used to estimate motorcycle engine condition (normal or damage), damage kind, how big damage influence towards motorcycle continuance, motorcycle duration can survive with damage and cost estimate that taked suppose will repair damage. In this research is built 4-stroke motorcycle engine damage detection system based on voice uses Support Vector Machine (SVM) multi class. In system that proposed, motorcycle engine voice is recorded and then cultivated so that produce feature shaped coefficient Linear Predictive Coding (LPC). Coefficient LPC that extracted from this motorcycle engine voice then become an input for SVM. Furthermore SVM will determine motorcycle engine condition. Engine condition detection system based on SVM this meant to detect three engine conditions that is normal condition, damage cham chain and damage ignition system. System applications that proposed show that motorcycle engine condition detection system based on voice uses SVM has good accuracy that is 100%.
Co-Authors Agung Mubyarto Akhmad Khahlil Gibran Alfin Hikmaturokhman Azis Wisnu Widhi Nugraha Azis Wisnu Widhi Nugraha Baharudin Yudha Permana Dimass Noly Mardhiko Dimass Noly Mardhiko Dwi Ary Asmoro Dwi Ary Asmoro, Dwi Ary Farida Asriani FX Anjar Tri Laksono Gibran, Akhmad Khahlil Gito Sugiyanto Gito Sugiyanto Hari Prasetijo Huzaely Latief Sunan Ilham Perdana Melani Widyaningsih Muhamad Ridwan Murdyantoro Am, Eko Nur Chasanah Priswanto Purnomo, Widhiatmoko Herry Rahmat K. Noviandono Rahmat K. Noviandono, Rahmat K. Rani Aulia Imran Shinta Yunita Sari Suroso Suroso Suroso Suroso Tantiningrum Niken Taufik Faturohman Teguh Cahyono Tigar Putri Adhiana Widhiatmoko H.P. Widhiatmoko Herry Purnomo Widhiatmoko Widhiatmoko Widhiatmoko Widhiatmoko, Widhiatmoko