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All Journal SisInfo : Jurnal Sistem Informasi dan Informatika Jurnal Ilmiah Ekonomi dan Manajemen
Sindrawati Sindrawati
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Computer Science & IT Other

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Penerapan Algoritma K-Means Clustering pada Data Nilai Siswa untuk Menentukan Kelompok Penerima Beasiswa Sindrawati Sindrawati; Dodi Syaripudin; Agung Rachmat Raharja
SisInfo Vol 6 No 2 (2024): SisInfo
Publisher : Universitas Informatika dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37278/sisinfo.v6i2.900

Abstract

To prevent school mistakes in determining class XII students who are entitled to receive scholarships, prevention can be done by using data mining techniques so that the school can determine decisions accurately and quickly. Clustering is a data mining technique that functions to group a number of data or objects into clusters (groups) so that each cluster will contain data that is as similar as possible and different from objects in other clusters. The method used is CRISP-DM, through the business understanding process, data understanding, data modeling, deployment, assessment, and preparation. The K-Means algorithm is the one used to construct clusters. K-Means is a non-hierarchical technique for clustering data that divides student data into multiple clusters according to how similar the data is. A total of 109 data points were used, including majors and grades in English, Indonesian, and mathematics. The three clusters that were created are as follows: the first cluster has 26 pupils, the second has 46 kids, and the third has 37 students. Based on the clusters that were generated, the study's findings can be utilized to inform decisions about which scholarship recipients should be grouped..
PENGARUH HARGA DAN KUALITAS PRODUK TERHADAP KEPUTUSAN PEMBELIAN MASKARA O TWO O PADA PLATFROM E-COMMERCE SHOPEE Nuriddini Sri Rizki; Sindrawati Sindrawati
JURNAL ILMIAH EKONOMI DAN MANAJEMEN Vol. 4 No. 4 (2026): April
Publisher : CV. KAMPUS AKADEMIK PUBLISING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/jiem.v4i4.9730

Abstract

This study aims to analyze the effect of price and product quality on the decision to purchase O Two O mascara on the Shopee e-commerce platform. Technological developments have changed consumer behavior in online shopping, where ease of access, promotions, and product reviews influence consumer choices. The research method used is quantitative with a positivistic approach, involving 104 respondents selected through purposive sampling. Data were collected through an online questionnaire and analyzed using multiple linear regression to test the influence of price and product quality variables on purchasing decisions. The results of the study indicate that product quality has a positive and significant effect on purchasing decisions, while price, although positive, is not significant. This indicates that consumers prioritize durability, reliability, and the results of O Two O mascara makeup over price variations in their purchasing decisions. The implications of this study emphasize the importance of manufacturers maintaining product quality and packaging design to retain consumer trust, while pricing strategies can be optimized to attract new consumers without compromising quality perception. This study provides insights for cosmetics manufacturers and e-commerce marketers to understand consumer behavior and formulate effective marketing strategies in the context of digital commerce.
Co-Authors Agung Rachmat Raharja Dodi Syaripudin Nia Sumiati Nuriddini Sri Rizki