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Astari Prakasiwi, Degita
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Computer Science & IT Decision Sciences, Operations Research & Management

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PENERAPAN ARTIFICIAL NEURAL NETWORK DAN LEAFLET.JS DALAM MEMBANGUN APLIKASI PEMETAAN DESA TERTINGGAL DAN KELUARGA PRA SEJAHTERA PADA KECAMATAN BATHIN III ULU KABUPATEN BUNGO PROVINSI JAMBI: ARTIFICIAL NEURAL NETWORK, BACKPROPAGATION, MAPPING, LEAFLET.JS, UNDERDEVELOPED VILLAGE Pariyadi; Astari Prakasiwi, Degita
FORTECH (Journal of Information Technology) Vol. 2 No. 2 (2018): Fortech (Journal Of Information Technology)
Publisher : LP2M STMIK Nurdin Hamzah Jambi

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Abstract

Lagging villages are areas that are generally located in districts that are relatively underdeveloped and have relatively underdeveloped populations compared to other regions on a national scale. Batin III Ulu District Bungo has 9 (nine) villages which have promising space potential including abundant forest resources, natural tourism, agricultural land and plantations. Village development has not yet had an optimal impact and there are still disadvantaged families in each village in Bathin III Ulu Subdistrict. Development of application mapping of disadvantaged villages and underprivileged families in Bathin III Ulu Subdistrict, Bungo District, Jambi Province is a qualitative research that aims to support the government in accelerating the implementation of services for underdeveloped villages and underprivileged families. Automated learning stage to determine mapping of disadvantaged villages and underprivileged families through the application of Artificial Neural Network (ANN) as an adaptive system to model complex relationships between input and output to find patterns in the data and collaboration with Leaflet.Js as a library used for making thematic spatial maps that can emphasize priority objects to be addressed immediately. The application is built on a web-based basis so that users can easily access it anywhere and anytime as a reference in determining future development policies.
SISTEM PAKAR MENDIAGNOSA PENYAKIT IKAN ARWANA (SCLEROPAGES FORMOSUS) UNTUK MEMINIMALISIR PENYEBARAN HAMA DAN PENYAKIT MENGGUNAKAN METODE FORWARD CHAINING: EXPERT SYSTEM, DISEASE, SCLEROPAGES FORMOSUS, FORWARD CHAINING Astari Prakasiwi, Degita; Wiranata, Ardi
FORTECH (Journal of Information Technology) Vol. 2 No. 2 (2018): Fortech (Journal Of Information Technology)
Publisher : LP2M STMIK Nurdin Hamzah Jambi

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Abstract

Unit Pelaksana Teknis Dinas Balai Benih Ikan Daerah (UPTD BBID) Provinsi Jambi is a place for freshwater fish cultivation including arwana. UPTD BBID are diagnosing disease in arwana fish by the help of the employee who are expert in diagnosing the diseases. But this method is difficult and needs time. So, this research aims to build an expert system application to diagnose Arwana fish (scleropages formosus) disease by using forward chaining method. The use of this application expected can minimize the spread of pests and diseases in arwana fish. This application is built using Microsoft Visual Basic Net and MySQL database. The results of consultation tests with this system indicate that the system is able to determine the disease, causes, and prevention and solution based on symptoms previously answered by employees.
Co-Authors Cecep Kusmana Pariyadi