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Fajriyanto Fajriyanto
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Other

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KARAKTERISTIK MEKANIK PRODUK FIBERBOARD DARI KOMPOSIT SAMPAH PLASTIK (THERMOPLASTIC)-LIMBAH TANDAN KOSONG KELAPA SAWIT (TKKS) Feris Firdaus; Fajriyanto Fajriyanto
Teknoin Vol. 11 No. 3 (2006)
Publisher : Faculty of Industrial Technology Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/.v11i3.87

Abstract

The research about thermoplastic wastes-oil palm fiber wastes composites have been conducted. Thermoplastic wastes has become a serious problem in Indonesia, and oil palm fiber wastes also become a serious problems in palm oil industries. The quantity and abundance of the wastes are very much but their utilization is not optimal yet even has no significant added ,economic values. The research was to utilize thermoplastic wastes and oil palm fiber wastes as the main materials to produce fiberboards. The research yields showed that thermoplastic wastes and oil palm fiber wastes composites could be used to produce fiberboards with very satisfied mechanical properties. The mechanical properties of the product were very satisfied even competitive to similar products in markets. The mechanical properties of fiberboards recommended for many kind of materials application, like in building materials and exterior-interior accessories in many appropriate places.Keywords: thermoplastic waste, oil palm fiber waste, composite, fiberboard
STUDI KOMPARASI PEMAKAIAN GPS METODE REAL TIME KINEMATIC (RTK) DENGAN TOTAL STATION (TS) UNTUK PENENTUAN POSISI HORISONTAL Fajriyanto Fajriyanto
Rekayasa : Jurnal Ilmiah Fakultas Teknik Universitas Lampung Vol 13, No 2 (2009): Edisi Agustus Tahun 2009
Publisher : UNIVERSITAS LAMPUNG

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Abstract

Measurement of control point by conventional method often given on to some obstacle especiallyrelated to low measurement efficiency and speed, strength of figure and spreading point controlvery suspended condition of field. According to growth and progress of technology with existenceof satellite of GPS have watered down work of geodesy with result of able to be pledged. As systemdetermination of position have satellite bases of GPS very useful in determination of geodeticalposition for the work of mapping and survey. Research conducted by using Total Station TopconGTS-2R and receiver GPS Leica System 300 at polygon network closed which consist of six pointswith one of point as reference station, data processing use SKI software and Microsoft office forthe calculation of polygon by using method bowdith flattening and flattening program TurboPascal. Result of from this research be based to value of confidence region that smaller ellipsvalue mistake from point hence progressively check made polygon network. By using conventionalmethod in the reality more is coming near of order II than GPS method of Real Time Kinematic (RTK). Yielded by Precise Mean GPS method of RTK equal to 0.009 metre, obtained accuration0.0965 correctness and metre relative to conventional method is 0.106 metre. In general alllocated measured points outside ellips standard error at trust 95 %.
OPTIMASI PREDIKSI TINGKAT PRODUKSI BAWANG MERAH NASIONAL MENGGUNAKAN METODE BACKPROPAGATION NEURAL NETWORK BERBASIS ALGORITMA GENETIKA Fajriyanto Fajriyanto; Abdul Syukur; Catur Supriyanto
Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 13 No 2 (2017): Jurnal Teknologi Informasi CyberKU Vol. 13, no 2
Publisher : Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro

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Abstract

Bawang merah merupakan kebutuhan masyarakat yang terus meningkat seiring dengan pertambahan jumlah penduduk dan harga belinya. Oleh sebab itu, untuk mengimbangi kebutuhan agar selalu terpenuhi maka jumlah produksinya harus seimbang. Menurut Direktorat Bina Hortikultura(1980), bahwa bawang merah adalah salah satu yang memberikan preoritas utama untuk pengembangan produksi Hortikultura secara nasional. Data produksi bawang merah dari tahun 1969-2014 produksi pertahun bersifat fluktuatif disebabkan oleh meningkatnya populasi Sementara lahan yang tersedia semakin sempit. Oleh sebab itu, prediksi produksi bawang merah Nasional dibutuhkan. Metode Backpropagation merupakan metode popular untuk Teknik prediksi yang mempunyai nilai RMSE terbaik. Akan tetapi, metode Backpropagation Neural Network mempunyai beberapa kelemahan, oleh sebab itu dibutuhkan sebuah metode optimasi, salah satunya dengan metode optimasi Algoritma genetika. Penelitian ini menggunakan data produksi bawang merah Nasional yang diperoleh dari Direktorat Jendral Holtikultura untuk proses training dan testing dengan menggunakan metode Backpropagation Neural Network dan Algoritma genetika untuk optimasi input weight.Pada panelitian ini metode Backpropagation Neural Network dengan algoritma genetika sebagai optimasi inputan menghasilkan nilai RMSE 0.062 terbaik, sedangkan metode Backpropagation Neural Network tanpa optimasi algoritma genetika menghasilkan nilai RMSE 0.089.
Co-Authors Abdul Syukur Catur Supriyanto Feris Firdaus