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                <text>Aprianty</text>
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                <text>EFEKTIVITAS PROGRAM LIVELIHOOD TERHADAP NELAYAN BUDIDAYA DI DESA LAMNGA KECAMATAN MESJID RAYA KABUPATEN ACEH BESAR Oleh : Aprianty/ Agribisnis Unsyiah ABSTRAK Peristiwa tsunami pada Desember 2004 telah menyebabkan ribuanhektar budidaya air payau (tambak) produktif hilang dalam hitungan menit. Berbagai aktivitas peningkatan mata pencaharian (Livelihood) dibidang perikananan budidaya telah banyak dilakukan. Penelitian ini dilakukan di  Desa Lamnga Kecamatan Mesjid Raya Kabupaten Aceh Besar. Metode Analisis data menggunakan metode statistik sederhana dan statistik uji-t berpasangan (paired t-test). Hasil penelitian bahwa  efektivitas program  livelihoodadalah sebesar 47,78%, yang artinya program tersebut tidak efektif dilihat dari  segi ketepatan sasaran, ketepatan jumlah dan ketepatan waktu pemberian bantuan. Faktor-faktor yang mempengaruhi efektivitas program  Livelihoodadalah ketidaktepatan sasaran, ketidaktepatan jumlah bantuan, dan ketidaktepatan waktu penyaluran bantuan dan faktor lain seperti bantuan yang diberikan berbasis kebutuhan, proses birokrasi yang terlalu lama, jumlah bantuan tidak sesuai dengan kebutuhan, perilaku nelayan yang menganggap bantuan sebagai proyek dan tidak adanya pertanggung jawaban dari bantuan yang telah diterima. Pendapatan nelayan budidaya sebelum adanya program adalah sebesar Rp. 1.888.333/bulandan setelah adanya program menjadi Rp 1.448.333/bulan. Hasil dari uji-t berpasangan diperoleh hasil bahwa nilai t. hitung (-0,98) &lt; t. tabel (-1,69) yang artinya tidak terdapat perbedaan/tidak adanya peningkatan terhadap pendapatan nelayan budidaya setelah adanya program livelihood.Kata Kunci: Efektivitas, program livelihood, Lamnga, nelayan budidaya</text>
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                <text>Banda Aceh</text>
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                <text>FISHERMEN</text>
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                <text>LIVELIHOOD</text>
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                <text>AGRICULTURAL-ECONOMIC ASPECTS</text>
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                <text>EFEKTIVITAS PROGRAM LIVELIHOOD TERHADAP NELAYAN RNBUDIDAYA DI DESA LAMNGA KECAMATAN MESJID RAYA RNKABUPATEN ACEH BESAR</text>
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                <text>Muhammad Ridho</text>
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                <text>Kata Kunci : Susu Kambing, E. coli, Perhitungan Jumlah Bakteri.Penelitian berjudul Analisis Bakteriologi Susu Kambing telah dilakukan sejak tanggal 1 Juni sampai dengan 30 Juni 2013 di Laboratorium Mikrobiologi Jurusan Biologi FMIPA Universitas Unsyiah Kuala. Tujuan penelitian ini adalah untuk mengetahui adanya kontaminasi E. coli dan menghitung jumlah koloni bakteri pada susu segar, susu pasteurisasi dan susu kemasan. Sampel penelitian  adalah susu segar, susu pasteurisasi dan susu kemasan yang diambil di peternakan kambing perah Lamnyong. Penelitian ini menggunakan pendekatan kuantitatif dan jenis penelitian adalah ekperimen. Penelitian ini bersifat deskriptif dengan menggunakan metode MPN (Most Probable Number) untuk mengetahui kontaminasi E. coli pada sempel dan metode TPC (Total Plate Count) digunakan menghitung jumlah bakteri pada sampel. Hasil penelitian menunjukkan adanya kontaminasi bakteri E. coli pada susu pasteurisasi berkisar antara 2.2-240/100 ml sampel dan pada susu kemasan berkisar antara 5-240/100 ml sampel.  Sedangkan pada susu segar tidak terkontaminasi bakteri E. coli.  Pada media EMB agar bakteri E. coli terlihat berwarna merah mengkilat (metallic sheen). Pada pemeriksaan jumlah koloni bakteri menggunakan metode TPC diketahui susu segar 300x102 CFU/ml, susu kemasan 300x102 CFU/ml dan susu pasteurisasi 193x102 CFU/ml.</text>
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                <text>http://etd.unsyiah.ac.id//index.php?p=show_detail&amp;id=4411</text>
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                <text>ANALISIS BAKTERIOLOGI SUSU KAMBING</text>
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                <text>Sugiarto, Sugiarto; Jurusan Teknik Sipil, Fakultas Teknik, Universitas Syiah Kuala</text>
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            <name>Date</name>
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                <text>2012-01-01</text>
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                <text>Abstract: The generalized linear model-poison distribution was employed incorporating available geometric data, exposure, etc. The explanotary variables used were average annual daily traffic (AADT), length of segment, heavy vehicle percentage, median, availability of shoulder, number of acces, number of intersection, number of curve per km, and amount of rain fall in a year in two Major National Highways in Thailand. Maximum Likelihood Method (MLM) was used for determining of estimation parameters by using Statistical Package for the Social Sciences (SPSS) version 16. Poison regression models were selected for the model SPFs of the accident, fatality and injury with the total explained variation (RD2) on average 0.44%, 0.25%, and 0.36% respectively. The final of developed models can be used for identifying and analyzing of hazardous locations, prioritizing an effective maintenance strategy tool with the identified hazardous locations along the road section.Keywords: Generalized Linear Models (GLM), Safety Performance Function (SPFs), Maximum Likelihood Model (MLM), Poisson Regresion, Total Explained Variation, SPSS, Hazardous Locations.Abstrak: Distribusi Poison yang digeneralkan sebagai model linier digunakan dalam penelitian ini dengan mengakomodir data geometrik, parameter traffic (exposure), dan lainya. Parameter penjelas (explanotary) diambil di dua Jalan Raya (highway) utama di Thailand termasuk data didalamnya average annual daily traffic (AADT), panjang segmen yang ditinjau, persen kendarangan berat, jenis dan keberadaan median, jenis dan keberadaan bahu jalan, jumlah bukaan akses, jumlah persimpangan, jumlah kurva per km, dan nilai curah hujan per tahun. Metode Maximum Likelihood Model (MLM) digunakan untuk mendeterminasi parameter estimasi model dengan bantuan perangkat lunak SPSS (Statistical Package for the Social Sciences) versi 16. Hasil regresi menggunakan distribusi poison digunakan sebagai model keselamatan untuk model jumlah kecelakaan, kematian, dan luka-luka. Katagori pemilihan model terbaik berdasarkan nilai total explained variation (RD2) yang berturut-turut dengan nilai rata-rata 0.44%, 0.25%, and 0.36% utuk model jumlah kecelakaan, kematian, dan luka-luka. Hasil final model dapat digunakan untuk identifikasi dan analisis segment rawan kecelakan, dan juga dapat digunakan untuk menganalisis prioritas penanganan daerah rawan kecelakaan yang telah teridentifikasi.Kata Kunci: Generalized Linear Models (GLM), Model Keselamatan Lalulintas, Maximum Likelihood Model (MLM), Poisson Regresion, Total Explained Variation, SPSS, Rawan kecelakaan.</text>
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                <text>application/pdf</text>
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                <text>http://jurnal.unsyiah.ac.id/JTS/article/view/789</text>
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                <text>eng</text>
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                <text>Jurnal Teknik Sipil</text>
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                <text>http://jurnal.unsyiah.ac.id/JTS/article/view/789/729</text>
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                <text>Jurnal Teknik Sipil; Vol 1, No 2 (2012): Volume 1, Nomor 2, Januari 2012; 143 - 152</text>
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                <text>2088-9321</text>
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                <text>MODELING SAFETY PERFORMANCE FUNCTION (SPFs) USING POISON-GENERALIZED LINEAR MODEL</text>
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                <text>Nurul Husna</text>
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                <text>KEANEKARAGAMAN DAN ETNOBOTANI TANAMAN PADA FLORIST GARDEN DI KOTA BANDA ACEH</text>
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                <text>Novia Faradilla</text>
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            <name>Date</name>
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                <text>2013</text>
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            <name>Description</name>
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                <text>Banda Aceh</text>
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                <text>SKR</text>
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            <name>Identifier</name>
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                <text>http://etd.unsyiah.ac.id//index.php?p=show_detail&amp;id=4414</text>
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                <text>id</text>
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                <text>Fakultas Keguruan dan Ilmu Pendidikan</text>
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            <name>Subject</name>
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                <text>PICTURE AND PICTURE TYPE</text>
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                <text>LEARNING ACHIEVEMENT</text>
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                <text>PENERAPAN MODEL PEMBELAJARAN KOOPERATIF TIPE PICTURE AND PICTURE PADA MATERI AKTIVITAS EKONOMI DAN SUMBER DAYA ALAM TERHADAP PRESTASI BELAJAR DI KELAS IV SD NEGERI 36 BANDA ACEH</text>
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                <text>Dirwan, Dirwan; Jurusan Teknik Sipil, Fakultas Teknik, Universitas Syiah Kuala</text>
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                <text>Bangun, Ngajari; Jurusan Teknik Sipil, Fakultas Teknik, Universitas Syiah Kuala</text>
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                <text>2012-05-01</text>
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                <text>Abstract: This research deals with the application of artificial grass planted on the channel banks influences to the Manning roughness coefficient (n). The information is useful in vegetative channel flow design, because the grass will stabilize the channel cross section, consolidate bed soil mass, control the bed and banks erosion and also the sediment movement along the channel's banks. This research was conducted at the Hydraulics Laboratory Engineering Faculty Unsyiah. A Multi Purpose Teaching Flume was used to model the channel. The flume wall was attached by artificial grass made of 'braided hafiah ropes' which varies in 5 different height and 3 different thickness. The flow depth also varies with 5 different height. The research results show that the higher and the thicker the grass, the greater the n Manning values and also its resistance. The Manning roughness coefficient (n) for the 12 cm grass height with 3 different grass thickness was in the range of 0.0118 to 0.0597. The 10 cm grass height with 3 different thicknesses shows the Manning coefficient in) in the range of 0.0080 to 0.0455. The 8 cm, 6 cm, and 4 cm grass height give the Manning roughness coefficient (n) range between 0.0081 to 0.0306, 0.0109 to 0.0431, and 0.0135 to 0.0425 respectively.Keywords : grass channel, Manning roughness coefficient (n)Abstrak: Penelitian ini bertujuan untuk melihat pengaruh pemberian rumput buatan pada tebing saluran terhadap koefisien kekasaran Manning. Manfaatnya adalah informasi yang diperoleh dapat digunakan dalam perencanaan tampang aliran saluran rumput, karena saluran rumput tersebut akan menstabilkan tubuh saluran, mengkonsolidasikan massa tanah di dasar saluran, dan mengontrol erosi permukaan saluran serta gerakan butiran tanah di sepanjang dinding saluran. Penelitian ini dilakukan di Laboratorium Hidrolika Fakultas Teknik Unsyiah. Model saluran yang digunakan adalah Multi Purpose Teaching Flume. Sisi kiri dan kanan flume diberi rumput buatan yang terbuat dari jalinan tali hafiah dengan 5 variasi ketinggian dan 3 variasi ketebalan. Kedalaman aliran juga bervariasi dengan 5 kedalaman yang berbeda. Hasil penelitian menunjukkan bahwa semakin tinggi dan semakin tebal rumpun rumput yang tumbuh pada tebing saluran, akan semakin besar nilai koefisien kekasaran Manning (n) yang diperoleh, dan begitu pula hambatan alirannya. Koefisien n Manning untuk rumput setinggi 12 cm dengan ketebalan 1, 2, dan 3 pasang anyaman hafiah nilainya antara 0,0118 sampai 0,0597. Rumput setinggi 10 cm dengan tiga macam ketebalan tersebut menghasilkan nilai koefisien n Manning antara 0,0080 sampai 0,0455. Rumput setinggi 8 cm, 6 cm, dan 4 cm dengan tiga macam ketebalan tersebut masing-masing menghasilkan nilai koefisien n Manning 0,0081 sampai 0,0306; 0,0109 sampai 0,0431; dan 0,0135 sampai 0,0425.Kata kunci : saluran rumput buatan, koefisien kekasaran Manning (n).</text>
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            <description>The file format, physical medium, or dimensions of the resource</description>
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                <text>application/pdf</text>
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                <text>http://jurnal.unsyiah.ac.id/JTS/article/view/877</text>
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                <text>eng</text>
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                <text>Jurnal Teknik Sipil</text>
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                <text>http://jurnal.unsyiah.ac.id/JTS/article/view/877/814</text>
              </elementText>
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            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
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              <elementText elementTextId="51271">
                <text>Jurnal Teknik Sipil; Vol 1, No 3 (2012): Volume 1, Nomor 2, Mei 2012; 269 - 278</text>
              </elementText>
              <elementText elementTextId="51273">
                <text>2088-9321</text>
              </elementText>
            </elementTextContainer>
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          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="51275">
                <text>RENATURALISASI SALURAN DENGAN PENANAMAN RUMPUT PADA TEBING</text>
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            </elementTextContainer>
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              <elementText elementTextId="51277">
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                <text>Yoanda Rauza</text>
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                <text>http://etd.unsyiah.ac.id//index.php?p=show_detail&amp;id=4416</text>
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            <description>A name given to the resource</description>
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              <elementText elementTextId="51268">
                <text>HUBUNGAN FAKTOR SANITASI DAN SOSIODEMOGRAFI DENGAN KEJADIAN DIARE PADA BALITA DI GAMPONG BAET KECAMATAN BAITUSSALAM ACEH BESAR</text>
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                <text>YENI YUSRINA</text>
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            <description>An unambiguous reference to the resource within a given context</description>
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            <name>Title</name>
            <description>A name given to the resource</description>
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              <elementText elementTextId="51276">
                <text>SIKAP SISWA TERHADAP SAMPAH DAN PEMELIHARAAN LINGKUNGAN HIDUP DI SMA NEGERI 12 BANDA ACEH</text>
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              <description>A name given to the resource</description>
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          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="51280">
                <text>Nanda Rezeki Yani</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="43">
            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
            <elementTextContainer>
              <elementText elementTextId="51281">
                <text>http://etd.unsyiah.ac.id//index.php?p=show_detail&amp;id=4418</text>
              </elementText>
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          </element>
          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="51282">
                <text>TINGKAT PENGETAHUAN DAN TINDAKAN PENCEGAHAN TENTANG PENYAKIT STROKE PADA MASYARAKAT KOTA SABANG</text>
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            </elementTextContainer>
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              <name>Title</name>
              <description>A name given to the resource</description>
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                <elementText elementTextId="31035">
                  <text>e-Journal USK</text>
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              </elementTextContainer>
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        <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
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          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="51283">
                <text>Afifuddin, Mochammad; Jurusan Teknik Sipil, Fakultas Teknik, Universitas Syiah Kuala</text>
              </elementText>
              <elementText elementTextId="51284">
                <text>Putra, Rudiansyah; Jurusan Teknik Sipil, Fakultas Teknik, Universitas Syiah Kuala</text>
              </elementText>
              <elementText elementTextId="51285">
                <text>Akbar, Andika; Alumni Jurusan Teknik Sipil Fakultas Teknik, Universitas Syiah Kuala</text>
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            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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              <elementText elementTextId="51287">
                <text>2013-01-01</text>
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            <name>Description</name>
            <description>An account of the resource</description>
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                <text>Abstract: Objective of this study to predict the flexural behavior of channel profiles (C) Ferosemen by using Artificial Neural Network (ANN). In modeling the effect of different variables is high-profile, number of layers wiremesh, and the amount of reinforcement appeal. The model derived from laboratory test data for 9 pieces of specimen testing that has been done by previous researchers. Steps being taken on the application of ANN there are three stages, namely training, validation, and forecasting. In training randomly selected 7 data for training, and the remaining 2 data selected for validation. Having ascertained the results of training and validation have been getting lessons well, followed by forecasting (predicting). Taken 9 for forecasting new data that has been modified high-profile, number of layers wiremesh, and the amount of tensile reinforcement. From the results obtained values forecasting greatest moments occurred in a high profile 350 mm, 3 layers wiremesh, and 4 rod tensile reinforcement, while the value of the moment of the smallest and the largest value of the deflection occurs in the high profile 150 mm, 3 layers wiremesh, and 2 tensile reinforcement , while the value of the smallest deflection occurs in the high profile 250 mm, 4 layers, wiremesh, and 3 tensile reinforcement. In secondary data, the value of the moment and deflection between ANN modeling (training and validation) compared with laboratory data had an average percentage of 101.81% and 97.45%, while the value of the moment and deflection between theoretical calculations compared with ANN modeling (training and validation) had an average percentage of 80.73% and 58.44%. In the new data, the value of the moment and deflection between theoretical calculations compared with ANN modeling (forecasting) has an average percentage of 78.12% and 60.95%.Keywords : Canal profile (C), ferrocement, Artificial Neural Network, backpropagation.Abstrak: Penelitian ini bertujuan untuk memprediksi perilaku lentur profil kanal (C) Ferosemen dengan menggunakan Artificial Neural Network (ANN). Dalam permodelan yang menjadi variabel adalah pengaruh perbedaan tinggi profil, jumlah lapis wiremesh, dan jumlah tulangan tariknya. Model diambil dari data hasil uji laboratorium terhadap 9 buah benda uji yang telah dilakukan pengujiannya oleh peneliti sebelumnya. Tahapan yang dilakukan pada aplikasi ANN ada tiga tahap, yaitu training, validasi, dan forecasting. Pada training dipilih 7 data secara acak untuk dilatih, dan 2 data sisanya dipilih untuk validasi. Setelah dipastikan hasil training dan validasi telah mendapatkan pembelajaran dengan baik, dilanjutkan dengan forecasting (memprediksi). Diambil 9 data baru untuk forecasting yang telah diubah tinggi profil, jumlah lapis wiremesh, dan jumlah tulangan tarik. Dari hasil forecasting diperoleh nilai momen terbesar terjadi pada profil dengan tinggi 350 mm, 3 lapis wiremesh, dan 4 batang tulangan tarik, sedangkan nilai momen terkecil dan nilai lendutan terbesar terjadi pada profil dengan tinggi 150 mm, 3 lapis wiremesh, dan 2 buah tulangan tarik, sedangkan nilai lendutan terkecil terjadi pada profil dengan tinggi 250 mm, 4 lapis wiremesh, dan 3 buah tulangan tarik. Pada data sekunder, nilai momen dan lendutan antara permodelan ANN (training dan validasi) dibandingkan dengan data laboratorium memiliki persentase rata–rata sebesar 101,81% dan 97,45%, sedangkan nilai momen dan lendutan antara perhitungan teoritis dibandingkan dengan permodelan ANN (training dan validasi) memiliki persentase rata–rata sebesar 80,73% dan 58,44%. Pada data baru, nilai momen dan lendutan antara perhitungan teoritis dibandingkan dengan permodelan ANN (forecasting) memiliki persentase rata–rata sebesar 78,12% dan 60,95%.Kata kunci : Profil Kanal (C), ferosemen, Artificial Neural Network, Backpropagation.</text>
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            <description>The file format, physical medium, or dimensions of the resource</description>
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                <text>application/pdf</text>
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            <description>An unambiguous reference to the resource within a given context</description>
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                <text>http://jurnal.unsyiah.ac.id/JTS/article/view/1020</text>
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            <description>A language of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="51293">
                <text>eng</text>
              </elementText>
            </elementTextContainer>
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                <text>Jurnal Teknik Sipil</text>
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              <elementText elementTextId="51297">
                <text>http://jurnal.unsyiah.ac.id/JTS/article/view/1020/961</text>
              </elementText>
            </elementTextContainer>
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              <elementText elementTextId="51299">
                <text>Jurnal Teknik Sipil; Vol 2, No 2 (2013): Volume 2, Nomor 2, januari 2013; 117 - 126</text>
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              <elementText elementTextId="51301">
                <text>2088-9321</text>
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                <text>APLIKASI ARTIFICIAL NEURAL NETWORK (ANN) UNTUK MEMPREDIKSI PERILAKU LENTUR PROFIL KANAL (C) FEROSEMEN</text>
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