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All Journal Buletin Udayana Mengabdi Majalah Ilmiah Teknologi Elektro Majalah Ilmiah Teknologi Elektro
N Paramaita
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Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering

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PERENCANAAN INSTALASI KELISTRIKAN GEDUNG PASANGAN TETAP DI BALE BANJAR PEKEN DESA PAKRAMAN SANGSIT KECAMATAN SAWAN KABUPATEN BULELENG A Dharma; N Gunantara; M Amir; N Paramaita
Buletin Udayana Mengabdi Vol 15 No 2 (2016): Jurnal Udayana Mengabdi
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (798.242 KB)

Abstract

dipakai untuk kegiatan-kegiatan desa yang bersifat sosial kemasyarakatan. Ciri khas bangunan adalah adanyarelief Burung Garuda Pancasila yang terpahat di dinding (leufel) depan bale Banjar dengan ukuran besarsehingga sangat menjolok dan terlihat dari jalan raya utama Desa Sangsit, inilah satu-satunya bale banjarberukir Burung Garuda yang menunjukan rasa nasionalisme krama banjar yang tidak disangsikan lagi untukrela berkorban “nindihin gumi pertiwi”. Kondisi bangunan sangat mengkhawatirkan karena usia, terbuktipada kolom utama penyangga lantai dua yang ada dibagian belakang terdapat retak-retak besar menandakanterjadinya kegagalan struktur. Sehingga secara langsung tidak dapat dipergunakan oleh warga untukkegiatan-kegiatan banjar/ atau Dusun. Melalui rapat banjar, akhirnya diputuskan untuk melakukanpembangunan gedung baru dengan membentuk panitia pembangunan. Pembangunan tahap awal telah sampaipada struktur gedung dan utilitas penting seperti sistem penerangan dan dayanya. Tim Pengabdi telahmerencanakan instalasi listrik beserta perlengkapannya yang aman berdasarkan PUIL dan telah berfungsidengan baik. Diharapkan apabila gedung telah rampung seluruhnya nanti, bisa lebih memotivasi warga agarberperan aktif memakai gedung bale banjar disaat ada kegiatan-kegiatan yang dilakukan malam hari.
Penentuan Notasi Gamelan Rindik Menggunakan Metode Transformasi Wavelet I Gusti Made Meri Utama Yasa; Linawati Linawati; N Paramaita
Jurnal Teknologi Elektro Vol 17 No 3 (2018): (September - Desember) Majalah Ilmiah Teknologi Elektro
Publisher : Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (449.188 KB) | DOI: 10.24843/MITE.2018.v17i03.P03

Abstract

Abstract—This paper present about recognition of gamelan rindik pattern using wavelet transform. Wavelet transform is used to find the special characteristic of gamelan rindik, which had previously been recorded and stored in computer with format *.wav. The data was subsequently used as training and tested data, Probabilistic Neural Network (PNN) was used to recognize gamelan rindik pattern using. The training and tasted data process used four different rindics, consisting 0f 240 gamelan rindik data. Discrete Wavelet Transform (DWT) was used as the method of feature extraction, with Symlet, Haar, and Daubechies Wavelet function. Those three functions of the wavelet shows the average accuracy level for Symlet 94.58%, Haar 93.33%, and wavelet Daubechies 94.58%.
Penentuan Notasi Gamelan Rindik Menggunakan Metode Transformasi Wavelet I Gusti Made Meri Utama Yasa; Linawati Linawati; N Paramaita
Jurnal Teknologi Elektro Vol 17 No 3 (2018): (September - Desember) Majalah Ilmiah Teknologi Elektro
Publisher : Program Studi Magister Teknik Elektro Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MITE.2018.v17i03.P03

Abstract

Abstract—This paper present about recognition of gamelan rindik pattern using wavelet transform. Wavelet transform is used to find the special characteristic of gamelan rindik, which had previously been recorded and stored in computer with format *.wav. The data was subsequently used as training and tested data, Probabilistic Neural Network (PNN) was used to recognize gamelan rindik pattern using. The training and tasted data process used four different rindics, consisting 0f 240 gamelan rindik data. Discrete Wavelet Transform (DWT) was used as the method of feature extraction, with Symlet, Haar, and Daubechies Wavelet function. Those three functions of the wavelet shows the average accuracy level for Symlet 94.58%, Haar 93.33%, and wavelet Daubechies 94.58%.
Co-Authors A Dharma I Gusti Made Meri Utama Yasa I Nyoman Gunantara Linawati Linawati M Amir