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All Journal JURNAL PENDIDIKAN TAMBUSAI Journal of Mathematics, Computation and Statistics (JMATHCOS)
Kevin Alifviansyah
IPB University
Mathematics Social Sciences

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Market Segmentation of Smartphones in Tokopedia Using Fuzzy C-Means Clustering Reyuli Andespa; Muh. Sunan; Maisa Salsabila; Anwar Fitrianto; Kevin Alifviansyah
Jurnal Pendidikan Tambusai Vol. 9 No. 3 (2025): Desember
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

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Abstract

Penelitian ini bertujuan untuk menganalisis segmentasi pasar smartphone pada platform e-commerce Tokopedia dengan menggunakan algoritma Fuzzy C-Means (FCM). Dataset diperoleh melalui proses web scraping terhadap 428 produk smartphone, yang mencakup variabel harga, rating, volume penjualan, nama toko, dan lokasi penjual. Tahapan analisis meliputi data cleaning, eksplorasi deskriptif, penentuan jumlah klaster optimal menggunakan metode Elbow, serta penerapan algoritma FCM untuk membentuk segmen pasar yang homogen. Hasil penelitian mengidentifikasi tiga klaster optimal, yaitu: Budget, Mid-range, dan Premium. Segmen Budget terdiri dari 337 produk dengan rata-rata harga Rp1.623.426, rating rata-rata 4,81, dan volume penjualan rata-rata 301 unit. Segmen Mid-range mencakup 20 produk dengan rata-rata harga Rp3.462.007, rating 2,25, dan penjualan 22 unit. Sementara itu, segmen Premium berisi 102 produk dengan rata-rata harga Rp6.434.597, rating 4,92, dan penjualan 201 unit. Temuan ini menunjukkan bahwa konsumen Tokopedia cenderung lebih menyukai smartphone yang terjangkau namun tetap berkualitas, sementara segmen Mid-range menghadapi tantangan dalam hal positioning dan daya saing pasar.
Clustering of Central Java Districts Based on Educational Indicators: A Comparison of K-Means and Hierarchical Methods Muhammad Syafiq; Nabila Fida Millati; Muh Akbar Idris; Anwar Fitrianto; Kevin Alifviansyah; Erfiani Erfiani
Journal of Mathematics, Computations and Statistics Vol. 9 No. 1 (2026): Volume 09 Issue 01 (March 2026)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/xen35m31

Abstract

This study aims to cluster districts and municipalities in Central Java based on educational indicators and to compare the clustering performance of K-Means and Hierarchical methods. The analysis uses secondary data from the Statistical Publication of Education in Central Java Province 2024, covering eight indicators related to educational facilities, participation, and attainment. The data were standardized, explored using descriptive statistics, and analyzed using K-Means and Hierarchical clustering methods. The evaluation results show that both methods produced broadly comparable clustering structures. However, Hierarchical Clustering demonstrated slightly stronger performance in terms of cluster separation and compactness, with a higher Silhouette Index (0,591) and Dunn Index (0,320) and a lower Davies–Bouldin Index (0,501) compared with K-Means (SI 0,584, Dunn 0,225, DBI 0,562). Meanwhile, K-Means produced a more balanced partition and a higher Calinski–Harabasz Index (48,63) than Hierarchical Clustering (44,30). The clustering results reveal a clear pattern of educational disparities across the region. A small group consisting of Sukoharjo Regency and the cities of Semarang, Surakarta, Salatiga, and Magelang forms a higher-performing cluster characterized by stronger educational indicators, while most rural districts belong to a lower-performing group. These findings indicate that educational disparities in Central Java remain spatially concentrated and highlight the need for targeted policies to strengthen educational investment and improve progression to higher levels of education in less developed districts.
Co-Authors Erfiani Erfiani Fitrianto, Anwar Maisa Salsabila Muh Akbar Idris Muh. Sunan Muhammad Syafiq Nabila Fida Millati Reyuli Andespa