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PENINGKATAN KESADARAN MASYARAKAT TERHADAP KEBERSIHAN DAN MENGEMBANGKAN UMKM DI KELURAHAN BAKALANKRAJAN Achyunda Putra, Firnanda Al-Islama Achyunda Putra; Arief, Rizza Muhammad; Arifin, Yulia Natasya Farah Diba
RAMBIDEUN : Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 2 (2024): Rambideun: Jurnal Pengabdian Kepada Masyarakat
Publisher : LPPM Universitas Al Muslim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51179/pkm.v7i2.2414

Abstract

Improving cleanliness is one way to optimize public health. This community service activity has the theme of cleanliness and development of MSMEs, which is carried out by KKN students in Bakalankrajan Village. Students helped develop 2 MSME products and held a "Shining Village" competition to increase the enthusiasm and awareness of residents in cleaning the environment. This activity aimed to increase residents' awareness and initiative towards environmental cleanliness in Bakalankrajan Village. From the results of the "Shining Village" competition, Unmer KKN 2023 students will support and help the village that gets the lowest score. This activity used implementation methods in the form of socialization, by distributing posters, holding competitions, assessing and processing scale data, and service in the form of community service. From the results of the service activities, it can be seen that residents are starting to keep their environment clean after the Shining Village" competition program and updating the logo and catalog design for the Jamu and Sago Tempe Chips MSMEs to maximize their products visibility.
Segmentasi Pelanggan E-Commerce Berdasarkan Pola Pembatalan dan Pengembalian Pesanan Menggunakan K-Means Arifin, Yulia Natasya Farah Diba; Zubair, Anis
JUSIFOR : Jurnal Sistem Informasi dan Informatika Vol 4 No 2 (2025): JUSIFOR - Desember 2025
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/jusifor.v4i2.8887

Abstract

This study examines e-commerce customer segmentation based on cancellation and return behaviors using K-Means clustering as a proof-of-concept. Using the Pakistan E-Commerce Dataset (2017), we performed preprocessing, behavioral feature engineering (Cancellation Rate, Return Rate, Average Order Value, Discount Sensitivity, Preferred Payment Method, and Total Orders), Min–Max normalization, and K-Means modeling. Cluster number validation relied on the Elbow Method, Silhouette Score, and PCA visualization. Results indicate K = 3 stable clusters: Price-Sensitive Customers (69.48%) high per-order value but price-sensitive; Loyal Customers (13.55%), high frequency and low CR/RR; and High-Risk Customers (16.97%), high return rate with low value contribution. The findings demonstrate K-Means’ effectiveness in identifying cancellation/return patterns and provide a conceptual basis for risk management and further analysis.