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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA JURIKOM (Jurnal Riset Komputer) Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) KLIK: Kajian Ilmiah Informatika dan Komputer
Alwis Nazir
Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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Journal : KLIK: Kajian Ilmiah Informatika dan Komputer

 1 
Penerapan Algoritma Fuzzy C-Means untuk Melihat Pola Penerima Beasiswa Bank Indonesia Agung Surya Maulana; Alwis Nazir; Lestari Handayani; Iis Afrianty
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 3 No. 6 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v3i6.788

Abstract

Scholarship is a program in the form of financial assistance aimed at individuals to continue their education with the aim of helping reduce the financial burden during the study period, especially in difficult situations, so that it can help expedite the learning process. Based on data related to scholarship recipients obtained in 2020, 2021 and 2022, analysis is needed to see the characteristics of Bank Indonesia scholarship recipients because Bank Indonesia does not yet know this, this was said directly by the Bank Indonesia Scholarship supervisor. The method needed for grouping data is data mining with the Fuzzy C-Means algorithm and using a computerized system, namely the RapidMiner application. This study uses the Cumulative Grade Point Average (GPA), Semester, and Study Program variables. The research results obtained were at Riau University for three years, the pattern formed was students of the Faculty of Social and Political Sciences with a large GPA of 3.5. At Sultan Syarif Kasim Riau State University, Riau Muhammadiyah University, and Lancang Kuning University have the same pattern, namely students with a GPA above 3.5. Then at the Dumai College of Technology, namely Informatics Engineering students with a large GPA of 3.5
Pengelompokan Produk Berdasarkan Data Persediaan Barang Menggunakan Metode Elbow dan K-Medoid Nurafni Syahfitri; Elvia Budianita; Alwis Nazir; Iis Afrianty
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 3 (2023): Desember 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i3.1525

Abstract

Inventory has a very important role in the company, because it indirectly influences the company's income. If a company does not have inventory, it will experience the risk of not being able to fulfill consumer desires. One data mining technique that can help in processing data to obtain useful information is clustering. The aim of this research is to group inventory of goods, by attributes, initial quantity, quantity sold, and quantity available. Management of inventory data using data mining techniques with the elbow and K-Medoid methods. Then the data that has been grouped can make it easier for stores to determine inventory carefully in terms of procuring stock of goods or products. The results of this research are the use of the elbow method in determining the optimal number of clusters using Python at point 7 (cluster). The clustering results using the k-medoid method with elbow show 7 clusters using the RapidMiner tool. Cluster 0 has 145 products, cluster 1 has 135 products, cluster 2 has 200 products, cluster 3 has 76 products, cluster 4 has 101 products, cluster 5 has 208 products, and cluster 6 has 135 products. Where cluster grouping is based on initial quantity, sold quantity and available quantity with the same or similar value. Clustering results using the k-medoid method without elbows, the clustering process uses 3 clusters with the RapitMiner tool. Cluster 0 has 169 products, cluster 1 has 410 products, and cluster 2 has 421 products. Cluster 0 grouping is based on quantity sold and available quantity, the value is the same, cluster grouping 1 is based on greater quantity sold, and cluster grouping 2 is based on greater quantity available. From the two analysis results it can be seen that the analysis using the k-medoid method with elbows is quite good because in determining the optimal number of clusters using the elbow method and the clustering results in grouping inventory are more effective.
Co-Authors Adrian Maulana Agung Surya Maulana Ana Komaria Baskara Beni Basuki Eka Pandu Cynthia Elin Haerani Elvia Budianita Fadhilah Syafria Ferdian Arya Dinata Fitri Insani Fitria Novitasari Ihda Syurfi Iis Afrianty Iwan Iskandar Jasril Jasril Lestari Handayani Lili Rahmawati Lola Oktavia Muhammad Fikry Muhammad Irsyad Muhammad Rifaldo Al Magribi Nining Nur Habibah Nur Iza Nurafni Syahfitri Pizaini . Pizaini Pizaini Qurrata A'yuni Reski Mai Candra Reski Mei Candra Risna Lailatun Najmi Sabar Mulyati Said Nurfan Hidayad Tillah Sephia Pratista Siska Kurnia Gusti Suwanto Sanjaya Yusra Yusra Yusril Hidayat