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All Journal Building of Informatics, Technology and Science KERN : Jurnal Ilmiah Teknik Sipil
Kusumaningtyas, Dyah Ayu
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Civil Engineering, Building, Construction & Architecture Computer Science & IT

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Agglomerative Hierarchical Clustering (AHC) Method for Data Mining Sales Product Clustering Lubis, Ridha Maya Faza; Huang, Jen-Peng; Wang, Pai-Chou; Khoifin, Kiki; Elvina, Yuli; Kusumaningtyas, Dyah Ayu
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3569

Abstract

Supermarkets are Indonesian terms that refer to large stores or supermarkets that offer a variety of daily needs such as food, drinks, cleaning products, household appliances, clothing, and so on. In contrast to stalls or small shops, supermarkets have a larger size and provide a variety of products. Because of this, many people prefer to shop for their daily needs at the supermarket rather than at the nearest shop because the existence of the supermarket makes it easier for consumers to buy various products in one place without having to move to another store. However, sales in supermarkets also pose a problem, namely how to sort or group products that are not selling well so they can be replaced with products that are selling better or reduce the number of suppliers. This is where data mining or data analysis techniques that use business intelligence are needed. The research was conducted to classify the best-selling products in supermarkets using the Agglomerative Hierarchical Clustering (AHC) method, in which alternatives with the same matrix or distance are grouped into certain clusters. In applying the AHC method, the number of clusters formed is 3. There are three different clusters, namely cluster 0, cluster 1, and cluster 2, each with a different alternative group. Each cluster has a different number of products and a different percentage. Cluster 0 is the cluster with the highest number of products and the largest percentage, namely 45% with a total of 9 products, followed by cluster 2, and cluster 1 has the smallest number of products and percentage, namely 0.30% with a total of 6 products and 0 .25% with a total of 5 products. In addition, sales data for several products each month are grouped based on certain price ranges
Analisa Perbandingan Salinitas dengan Kadar Klorofil- di Wilayah Perairan Sumenep Menggunakan Metode Regresi Linier dan Uji-T Kusumaningtyas, Dyah Ayu; Wibisana, Hendrata; Zainab, Siti
KERN : Jurnal Ilmiah Teknik Sipil Vol. 6 No. 2: Oktober 2020
Publisher : Program Studi Teknik Sipil, Fakultas Teknik, Universitas Pembangunan Nasional "Veteran" Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/kern.v6i2.35

Abstract

Indonesia merupakan negara dengan wilayah perairan yang luas, wilayah perairannya mencapai 77% dari total wilayah Indonesia. Wilayah perairan di indonesia banyak dimanfaatkan sebagai ladang perekonomian masyarakat, juga sebagai sarana kebutuhan non ekonomi lain. Banyaknya aktivitas yang dilakukan di wilayah perairan, serta faktor alam lain seperti gelombang, angin, dan lain sebagainya dapat memengaruhi banyak hal di perairan tersebut, misalnya salinitas dan kadar klorofil-a. Pada penelitian ini menggunakan citra satelit aqua modis tahun 2020 dengan mengambil data bulan Januari hingga April sebagai fokus penelitian. Penelitian ini mengerucutkan semua data penelitian menjadi hanya satu macam model matematika terbaik untuk setiap gelombangnya yang dapat digunakan dalam memperhitungkan nilai salinitas pada perairan Sumenep. Dari hasil korelasi nilai salinitas tersebut didapatkan nilai koefisien korelasi (r) sebesar 0,195. Setelah itu dilakukan analisa perbandingan dengan metode uji-T pada Program Microsoft Excel. Perbandingan dilakukan dengan variabel bebas kadar klorofil-a. Hasil yang didapat adalah hubungan antara salinitas dan kadarklorofil-a bersifat positif, atau berbanding lurus. Sedangkan untuk tingkat hubungannya termasuk dalam kategori hubungan yang lemah dengan nilai r sebesar 0,195. Secara periodik terjadi penurunan rerata antara salinitas dengan kadar klorofil-a.
Co-Authors Elvina, Yuli Hendrata Wibisana Huang, Jen-Peng Kiki Khoifin, Kiki Lubis, Ridha Maya Faza Siti Zainab, Siti Wang, Pai-Chou