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All Journal JIKSI (Jurnal Ilmu Komputer dan Sistem Informasi) Forum Agribisnis
Elvin Elvin
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Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Mathematics Other

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ANALISIS PEMASARAN IKAN KOI (KASUS DI DESA BABAKAN, KECAMATAN CISEENG, KABUPATEN BOGOR) Elvin Elvin; Wahyu Budi Priatna
Forum Agribisnis Vol 8 No 1 (2018): FA VOL 8 NO 1 MARET 2018
Publisher : Magister Science of Agribusiness, Department of Agribusiness, FEM-IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/fagb.8.1.97-116

Abstract

Koi is a prospective fishery commodity that make a positive contribution to Indonesia National GDP. Subdistrict Ciseeng especially in Babakan Village became one of the areas that make a positive contribution because there is a koi farmers, but has a different price level koi farmers with the consumer level. The purpose of this research is to analyze the institution, functioning, marketing channels and efficiency of marketing channels koi. Methods of data collection using purposive sampling to farmers and marketing agencies using snowball sampling. The results showed marketing agencies involved include farmers, village merchants, merchant shops and suppliers with functions exchange, physical and facility in nine koi marketing channels in Babakan Village. The efficiency of marketing channels occurs in channels VII because it has a lower marketing margins, the farmer's share is higher and the ratio of benefits to costs relatively with sales volume 210 tail.
KLASIFIKASI CITRA IKAN MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK Elvin Elvin; Chairisni Lubis
Jurnal Ilmu Komputer dan Sistem Informasi Vol 10, No 1 (2022): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v10i1.17827

Abstract

Fish Image Classification Using Convolutional Neural Network is an application that helping classification process. The application is used by user for knowing an information about what is the name of fish species from image that visitor captured. The application is designed by Python programming language. Method of designing the application using System Development Life Cycle. The method used in training model is Convolutional Neural Network, Data used in training process are the species data set is more than 10 species and each species is more than 1000 images, The data collected has been divided into training data and test data. In training process, Fish Image Classifiation Program produce a train loss value of 0.189203, validation loss value of 0.033459 and accuracy value of 0.991029. The evaluation process is carried out using a Confusion Matrix where the diagonal data is the correct prediction data, while the other data is the wrong prediction. By evaluating the Confusion Matrix, predicted accuracy reaches 99.1%precision and recall is 0.98. The resulting accuracy is very good accuracy so that it can predict the image inputted by the user accurately.
Co-Authors Chairisni Lubis Wahyu Budi Priatna