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All Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Komtika (Komputasi dan Informatika) JURNAL PEMBELAJARAN DAN MATEMATIKA SIGMA (JPMS) TECHSI - Jurnal Teknik Informatika
Fajriana Fajriana
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Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Mathematics Other

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Journal : JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING

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Information System for Predicting Fisheries Outcomes Using Regression Algorithm Multiple Linear Nurdin Nurdin; Fajriana Fajriana; Maryana Maryana; Ama Zanati
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 5, No 2 (2022): Issues January 2022
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v5i2.6023

Abstract

Bireuen is one of the regencies in Aceh province which has quite a lot of potential for marine and fishery resources, both capture fisheries and aquaculture, because some areas in this district are coastal areas supported by several fish landing bases (PPI), namely PPI Kuala Jangka, Kuala Jeumpa, Peudada, Jeunip, Pandrah, and Bate Iliek which are supporting sectors of the regional economy. The importance of this research is so that the Department of Food Security, Maritime Affairs and Fisheries can estimate the catch of fish in the coming year so that it can be used in terms of policies to increase the fishery production sector. The method used in information systems research to predict fishery results Multiple Linear Regression Algorithm using two independent variables (X), namely, the number of motorized boats (X1), the number of rainy days (X2) and one dependent variable, namely the number of fish caught (Y). ). The steps taken in this research are data collection, calculation of each variable, completion of the elimination method, substitution to get constant values, coefficients and inserting constants and coefficients into the Multiple Linear Regression equation. Based on data obtained from 2016, 1017, 2018, 2019 and 2020 using the Multiple Linear Regression algorithm, the prediction results of the Tangka fishery in Bireuen Regency in 2021 are 12,813.88 tons.
Classification of Determination the Recipients of the Program Keluarga Harapan (PKH) Using K-Nearest Neighbor Algorithm Fajriana Fajriana
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 6, No 1 (2022): Issues July 2022
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v6i1.7543

Abstract

Classification is one method of data mining techniques for classifying data by system according to predetermined rules. In this study, the algorithm used was K-Nearest Neighbor (KNN) algorithm and the data used in this study was the community data obtained from Kantor Desa Gampong Uteun Geulinggang, Dewantara, in Aceh Utara. The main focus of this study was to analyzing and applying K-NN algorithm in a web-based system to classify data on beneficiaries of the Program Keluarga Harapan (PKH) in Gampong Uteun Geulinggang, Dewantara, Aceh Utara. This study used 16 (sixteen) criterias, namely house status, floor area, floor type, gas cylinder, refrigerator, air conditioner, water heater, television, jewelry/gold (10 grams), computer/laptop, bicycle, motorcycle, car, cow, buffalo and goat. The data was classified into 3 classes, namely worthy, not unworthy and very unworthy. The results of this study with a value of k = 3, obtained a precision value of 97%, recall value of 95% and the accuracy value of 97%.
Co-Authors Aklimawati Aklimawati Ama Zanati Aris Munandar Aryandi Aryandi Bustami Bustami Erna Isfayani Fadlisyah Fadlisyah Gunawan, Chichi Rizka Hayatun Nufus Maryana Maryana Nurdin Nurdin Nurdin Nurdin Rizal Rizal