Implementasi K-Means Clustering Terhadap Mahasiswa yang Menerima Beasiswa Yayasan Pendidikan Battuta di Universitas Battuta Tahun 2020/2021 Studi Kasus Prodi Informatika

Harahap, Baginda; Rambe, Aripin

doi:10.36987/informatika.v9i3.2185

Cited by 2 publications

(2 citation statements)

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“…Beberapa penelitian terkait yang menggunakan K-Means Clustering adalah pengelompokan pemeroleh beasiswa dari Yayasan untuk mahasiswa dengan menggunakan algoritma K-Means Clustering yang diimplementasikan menggunakan RapidMiner. Hasil penelitian menunjukkan 3 kategori beasiswa Yayasan, yaitu 50%, 60%, dan 100% [15]. Dalam penelitian lain terkait rekomendasi calon mahasiswa yang mendapatkan beasiswa Yayasan dengan algoritma K-Means Clustering.…”

Section: Pendahuluanunclassified

Penerapan Algoritma K-Means Clustering untuk Mengetahui Pola Penerima Beasiswa Bank Indonesia (BI)

A'yuni,

Nazir,

Handayani

et al. 2023

JoSYC

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Bank Indonesia Scholarships are a type of scholarship sourced from Bank Indonesia for students from selected State Universities, Private Universities, and Polytechnics. From the data on scholarship recipients who have passed the selection from 2020, 2021, 2022 universities in Riau, it is necessary to look for the behavior patterns of scholarship recipien because Bank Indonesia does not yet have a pattern. To find the pattem from scholarship recipients using the method of data mining with K-Means Clustering algorithm. The parameters used are 4, namely study program, semester, GPA, and level. The results of the study using RapidMiner showed that cluster 0 was dominated by students from the Commerce Shipping Management study program, who were in semester 5 and D3 level. Cluster 1 is dominated by students from the Accounting and Management study program, in semester 7, with GPA greater than or equal to 3.51, and S1 level. Cluster 2 is dominated by students from the Nursing study program, in semester 5, with GPA greater than or equal to 3.51, and D3 level. Cluster 3 is dominated by students from the International Relations study program, in semester 7, with GPA greater than or equal to 3.51, and S1 level. Cluster 4 is dominated by students from the Informatics Engineering study program, in semester 5, with GPA greater than or equal to 3.51, and S1 level. It show that the recipients of Bank Indonesia scholarships are dominated by students with high GPA scores or equal to 3.51. In addition, it is also dominated by students who are at the S1 level. Tests were carried out using DBI with k=5 resulting in a validity value of 0.121.

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Section: Pendahuluanunclassified

Penerapan Algoritma K-Means Clustering untuk Mengetahui Pola Penerima Beasiswa Bank Indonesia (BI)

A'yuni,

Nazir,

Handayani

et al. 2023

JoSYC

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“…Salah satu penelitian yang dilakukan oleh Baginda Harahap dan Arifin Rambe dengan menggunakan Algoritma K-Means, Dalam penelitian ini digunakanlah K-Means Clustering untuk menyeleksi mahasiswa dalam menerima beasiswa tersebut, yaitu 50%, 60% dan 100%. Sehingga penelitian ini sangat cocok untuk digunakan dalam menyeleksi calon mahasiswa baru yang mendapatkan beasiswa dari Yayasan Pendidikan Battuta [6].…”

Section: Pendahuluanunclassified

Penerapan Data Mining Untuk Menentukan Strategi Penjualan Pada Toko Raja Komputer Menggunakan Metode Clustering

Wahyuni

Utamajaya²

2022

Jur. Ris. Kom.

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Toko Raja Computer Balikpapan is one of the laptop sales shops engaged in electronics with main products such as laptops, PC computers, and other accessories. Where the company every day must meet the needs of consumers and sales to be able to make the right decisions in determining the strategy. To be able to do this, Toko Raja Computer requires sales strategies to be able to attract buyers and increase company profits or revenues. In this study, data mining analysis was carried out by clustering techniques using the K-Means method. From the results of the research conducted, the results obtained from 1044 datasets of the Raja Computer sales list in 2021. So the results of clustering on the sales transaction data were 4 clusters of which there were 398 data following cluster 0, 363 data following cluster 1, 145 data following cluster 2 , and 138 data follow cluster 3, which means that clusters 0 and 1 are defined as products that must pay attention to the supply with the highest number, while clusters 2 and 3 are products with stock supply below clusters 0 and 1.

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Implementasi K-Means Clustering Terhadap Mahasiswa yang Menerima Beasiswa Yayasan Pendidikan Battuta di Universitas Battuta Tahun 2020/2021 Studi Kasus Prodi Informatika

Cited by 2 publications

References 0 publications

Penerapan Algoritma K-Means Clustering untuk Mengetahui Pola Penerima Beasiswa Bank Indonesia (BI)

Penerapan Algoritma K-Means Clustering untuk Mengetahui Pola Penerima Beasiswa Bank Indonesia (BI)

Penerapan Data Mining Untuk Menentukan Strategi Penjualan Pada Toko Raja Komputer Menggunakan Metode Clustering

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