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All Journal Inovate : Jurnal Ilmiah Inovasi Teknologi Informasi
Zuyyinal Haqqul Barir , Much
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Computer Science & IT

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SISTEM INFORMASI GEOGRAFIS PEMETAAN LAHAN PERTANIAN BAWANG MERAH DENGAN METODE K-MEANS CLUSTERING BERBASIS WEBSITE (Studi Kasus di Kabupaten Nganjuk) Zuyyinal Haqqul Barir , Much; Imam Agung, Achmad; Mashuri, Chamdan
Inovate Vol 4 No 1 (2019): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v4i1.752

Abstract

Geographic Information system (GIS) is a type of system that can be used for mapping the garlic farm land.The system consists of hardware, software, geographic location and human resources that can effectivelyprocess and display geographic information data. Agricultural land is an economic resource that isrelatively permanent availability, but its needs continue to increase due to development needs. The purposeof this research is tobuild SIG -based GIS Website and M-energy method of K-means Clustering for themapping of garlic farmland . The method used In this research is qualitative and uses K-means Clusteringfor GIS. This method is used for grouping data that has similarity variables. This method generates severaliterations that have clustervalues. Of These iterations used the least cluster value to determine theagricultural Land Mapping group. The result of this research is a geographic information system that canmap the garlic farm land. GIS testing was conducted on land in 20 sub-districts in Nganjuk district withconsideration of 3 variables and the test count 4 times. From The test results, the average number ofconformity calculation is obtained by 93,51% between manual counting result and counting result usingSIG.Keywords: K-means, Clustering, shallots, land mapping.
MENENTUKAN EFEKTIVITAS PEMBELAJARAN ONLINE MENGGUNAKAN ALGORITMA ANGGLOMERATIVE HIERARCHICAL CLUSTERING Kadek Dwi Nuryana , I; Zuyyinal Haqqul Barir , Much; Ikhwan Muhammad , Zainal
Inovate Vol 8 No 1 (2023): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v8i1.6302

Abstract

The clustering method is a method that can group to produce modeling processes, as well as analyze data with a partition system. In classifying student personalities, we use the Agglomerative Hierarchical Clustering (AHC) Algorithm. AHC is a data grouping technique that divides data into groups based on their similarity. This study aims to classify student personalities in lectures based on E-Learning with the AHC method. In this study, the score calculation was carried out in three processes following the hierarchical cluster process which was carried out in three processes. This process is carried out three times with the aim of observing the development of particle distribution during the hierarchical cluster process. It can be seen that the first score produced a value of 0.54, then the second score produced a value of 0.51, while the last one produced a value of 0.54. Then it takes the last value to determine how well it is spread. It can be seen from the last value that the resulting value is above 0 and close to 1 so that it can be said that the distribution of the particles is fairly good. Keywords : AHC, Clustering, Optimization, Personality, PSO, Student.
Co-Authors Achmad Imam Agung Ikhwan Muhammad , Zainal Kadek Dwi Nuryana , I Mashuri, Chamdan