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All Journal EDUMATIC: Jurnal Pendidikan Informatika Jurnal Muria Pengabdian Masyarakat
Artiarno, Andrean Maulana
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Computer Science & IT Education Social Sciences

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Penerapan Digital Branding Dalam Meningkatkan Upaya Pemasaran Pada UMKM Abon Lele Desa Dersalam Octavia, Putri Nabila; Damayanti, Anisa Iqlima; Sumartono, Thalia Chandra Dewi; Afariyanto, Vigo Ade; Kusuma, Chrestella Putu Holy; Maharani, Shinta Fanindia; Jayasanti, Renny Adi; Artiarno, Andrean Maulana
Jurnal Muria Pengabdian Masyarakat Vol 2, No 1 (2025): Januari
Publisher : Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/jmpm.v2i1.14620

Abstract

Muria Kudus University's Thematic KKN Program focuses on branding MSMEs, including shredded lele MSMEs in Dersalam Village which are managed by local residents. The main issue faced is the lack of knowledge and skills in promoting shredded catfish products, making it difficult to compete in the wider market. The focus of this service is to improve community capabilities in branding and product promotion strategies. The aim of the service is to strengthen the identity and appeal of shredded catfish products through training and assistance in digital and offline marketing. The methods used include branding workshops, creating promotional content, and using social media. The results of the service show an increase in public awareness and ability to market products, an increase in sales of shredded catfish, and the introduction of products to a wider market. This program has succeeded in having a positive impact on the economic development and independence of the Dersalam Village community.
K-Means Clustering untuk Segmentasi Pelanggan: Mengungkap Pola Pembelian Strategi Pemasaran pada Sektor Ritel Artiarno, Andrean Maulana; Setiaji, Pratomo; Nugraha, Fajar
Jurnal Pendidikan Informatika (EDUMATIC) Vol 9 No 2 (2025): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v9i2.30336

Abstract

Digital transformation has posed new challenges for retail companies in understanding consumer behavior due to the increasing volume of data and continuously changing preferences. This study aims to uncover purchasing patterns among retail customers and to provide data-driven marketing strategies through customer segmentation using the K-Means Clustering algorithm. This research adopts a quantitative exploratory approach using 3,900 synthetic entries from the Kaggle platform, representing retail transactions. The analysis focuses on variables such as age, gender, product category, location, purchase amount, and transaction frequency. The analytical process includes data preprocessing, dimensionality reduction using PCA, and segmentation with the K-Means algorithm. The optimal number of clusters was determined using the Elbow Method and Silhouette Score, while the quality of the clustering was evaluated using internal metrics, namely the Calinski-Harabasz Score (491.47) and the Davies-Bouldin Score (2.02). These values indicate a well-structured and reliable clustering result. Our findings reveal five distinct customer segments with varying characteristics, ranging from teenagers with small and periodic purchases to high-value adult customers who transact infrequently. These insights serve as the foundation for developing marketing strategies such as loyalty programs, seasonal promotions, and exclusive approaches.
Co-Authors Afariyanto, Vigo Ade Damayanti, Anisa Iqlima Fajar Nugraha Jayasanti, Renny Adi Kusuma, Chrestella Putu Holy Maharani, Shinta Fanindia Octavia, Putri Nabila Pratomo Setiaji Sumartono, Thalia Chandra Dewi