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All Journal Jurnal Informatika IPTEK The Journal for Technology and Science JUTI: Jurnal Ilmiah Teknologi Informasi JAVA Journal of Electrical and Electronics Engineering
Mauridhy Hery Purnomo
Bidang Studi Teknik Sistem Komputer,Jurusan Teknik Elektro - Fakultas Teknologi Industri, Institut Teknologi Sepuluh Nopember
Computer Science & IT Control & Systems Engineering Dentistry Education Electrical & Electronics Engineering Library & Information Science

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AUTONOMOUS MOBILE ROBOT BERBASIS PLAYER/STAGE MENGGUNAKAN PARALLEL SELF-ORGANIZING FEATURE MAPS UNTUK PEMETAAN LINGKUNGAN GLOBAL YANG TIDAK DIKETAHUI Hariadi, Mochamad; Muhtadin, Muhtadin; Purnomo, Mauridhy Hery; Rivai, Muhammad
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 6, No 2 Juli 2007
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (416.785 KB) | DOI: 10.12962/j24068535.v6i2.a189

Abstract

Autonomous mobile robot adalah salah satu jenis robot yang dikembangkan dengan kemampuan untuk mengendalikan dirinya sendiri walaupun dalam lingkungan yang tidak diketahui. Untuk dapat melakukan pengendalian secara mandiri, bisa dilakukan dengan melalui proses pembelajaran secara mandiri tanpa supervisi (unsupervised) dengan mempertimbangkan input dari sensor-sensor yang dipakai. Pada saat robot melakukan pengenalan terhadap lingkungannya, diperlukan perosesan komputasi yang berat dengan waktu yang lama. Penelitian ini akan membahas tentang penggunaan Kohonen Self-Organizing Feature Maps (SOFM) atau (SOM)  sebagai metode pembelajaran Autonomous mobile robot dalam mengenali lingkungannya. Proses pembelajaran dilakukan dengan menggunakan parallel processing menggunakan LAM-MPI, Simulasi dilakukan dengan menggunakan software simulasi Player/ Stage. Hasil simulasi menunjukkan bahwa SOM menampilkan performa yang baik dalam memetakan lingkungan yang tidak diketahui tanpa supervisi. Hasil pemrosesan dengan menggunakan parallel processing juga menunjukkan dicapainya kecepatan yang signifikan dalam proses pembelajaran robot untuk mengenali lingkungannya. Planning dengan menggunakan A* mampu untuk memberikan jalur yang efektif bagi robot dalam mencapai titik tujuan. Kata Kunci: autonomous, pemetaan, path-planning, komputasi parallel,  parallel SOM
Design Optimal Feedback Control Using Evolutionary Particle Swarm Optimization in Multi- Machine Power System Priyadi, Ardyono; Purnomo, Mauridhy Hery; Pujiantoro, Margo
JAVA Journal of Electrical and Electronics Engineering Vol 11, No 2 (2013)
Publisher : JAVA Journal of Electrical and Electronics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (108.974 KB)

Abstract

This This paper proposes an application of Evolutionary Particle Swarm Optimization (EPSO) to design weighting matrices Q and R elements in Linear Quadratic Regulator (LQR) optimization process. Solving optimal feedback control has already established by LQR method. However, there still has some problem to find the weighting matrices Q and R.These weighting matrices are the most important components in LQR optimization method. Weighting matrices are calculated using trial and error, Particle Swarm Optimazation (PSO), and EPSO techniques and simulation results are compared. Static and Dynamic loads are considered and comparison is illustrated.
SIMULASI AUTONOMOUS M OBILE ROBOT BERBASIS PLAYER/STAGE MENGGUNAKAN SELF-ORGANIZING FEATURE MAPS UNTUK PEMETAAN LINGKUNGAN GLOBAL YANG TIDAK DIKETAHUI Hariadi, Mochamad; Purnomo, Mauridhy Hery
Jurnal Informatika Vol 8, No 2 (2007): NOVEMBER 2007
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (384.902 KB) | DOI: 10.9744/informatika.8.2.pp. 139-146

Abstract

Nowadays, the development of robotics require more sophisticated technologies that would be able to adapt with global environment. Autonomous mobile robot is one of the robots which have been developed with environment control even in uncharted environment. Regarding this, an autonomous mobile robot should be capable of learning its environment in unsupervised fashion. This is done by monitoring and capturing the information from employed sensors. This paper describes the implementation of Kohonen Self-Organizing Feature Maps (SOM) as the learning methode for an Autonomous mobile robot for learning and recognizing its uncharted environment. Simulations using open source software called Player/Stage demonstrates good performance, since SOM is capable for mapping the uncharted environment very well in unsupervised fashion. Abstract in Bahasa Indonesia : Perkembangan dunia robotika saat ini tidak luput dari teknologi yang mampu beradaptasi dengan lingkungan sekitar robot. Autonomous mobile robot is the one of robot types which has adalah salah satu jenis robot yang dikembangkan dengan kemampuan untuk mengendalikan dirinya sendiri walaupun dalam lingkungan yang tidak diketahui. Untuk dapat melakukan pengendalian secara mandiri, bisa dilakukan dengan melalui proses pembelajaran secara mandiri tanpa supervisi (unsupervised) dengan mempertimbangkan input dari sensor-sensor yang dipakai. Paper ini akan membahas tentang penggunaan Kohonen Self-Organizing Feature Maps (SOM) sebagai metode pembelajaran Autonomous mobile robot dalam mengenali lingkungannya. Simulasi dilakukan dengan menggunakan open source software Player/ Stage. Hasil simulasi menunjukkan bahwa SOM menampilkan performa yang baik dalam memetakan lingkungan yang tidak diketahui tanpa supervisi. Kata kunci: autonomous mobile robot, self-organizing feature maps (som).
Electrolarynx Voice Recognition Utilizing Pulse Coupled Neural Network Arifin, Fatchul; Sardjono, Tri Arief; Purnomo, Mauridhy Hery
IPTEK The Journal for Technology and Science Vol 21, No 3 (2010)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v21i3.45

Abstract

The laryngectomies patient has no ability to speak normally because their vocal chords have been removed. The easiest option for the patient to speak again is by using electrolarynx speech. This tool is placed on the lower chin. Vibration of the neck while speaking is used to produce sound. Meanwhile, the technology of "voice recognition" has been growing very rapidly. It is expected that the technology of "voice recognition" can also be used by laryngectomies patients who use electrolarynx.This paper describes a system for electrolarynx speech recognition. Two main parts of the system are feature extraction and pattern recognition. The Pulse Coupled Neural Network – PCNN is used to extract the feature and characteristic of electrolarynx speech. Varying of β (one of PCNN parameter) also was conducted. Multi layer perceptron is used to recognize the sound patterns. There are two kinds of recognition conducted in this paper: speech recognition and speaker recognition. The speech recognition recognizes specific speech from every people. Meanwhile, speaker recognition recognizes specific speech from specific person. The system ran well. The "electrolarynx speech recognition" has been tested by recognizing of “A” and "not A" voice. The results showed that the system had 94.4% validation. Meanwhile, the electrolarynx speaker recognition has been tested by recognizing of “saya” voice from some different speakers. The results showed that the system had 92.2% validation. Meanwhile, the best β parameter of PCNN for electrolarynx recognition is 3.
Co-Authors Ardyono Priyadi Fatchul Arifin Mochamad Hariadi Muhammad Rivai Muhtadin Muhtadin Pujiantoro, Margo Tri Arief Sardjono