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Pradina, Selomita
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Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Mechanical Engineering Veterinary

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PEMODELAN OPTIMASI PEMILIHAN PRODUK PADA PLATFORM E-COMMERCE SHOPEE BERBASIS FORMULASI ALJABAR LINIER Pradina, Selomita; Akbar, Syeren Kyla
(JITEK)Jurnal Ilmiah Teknosains Vol 11, No 2/Nov (2025): Jitek
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jitek.v11i2/Nov.25515

Abstract

The development of e-commerce in Indonesia has changed consumer decision-making patterns, particularly on the Shopee platform, which offers a wide selection of products at competitive prices. However, the multitude of alternatives often makes it difficult for consumers to determine the best product that balances price, quality, and seller reputation. This study aims to develop a linear algebra-based product selection optimization model with a linear programming approach to help consumers make rational, data-driven decisions. Four main factors were analyzed: price, shipping costs, ratings, and reviews. Data were obtained through a questionnaire survey of 100 Shopee user respondents and actual product data in the fashion category. The results show that reviews (0.2819) and ratings (0.2698) have a dominant influence compared to price (0.2283) and shipping costs (0.2200). This optimization model is able to transform qualitative variables into measurable quantitative values, resulting in optimal product recommendations based on a balance between digital trust and economic efficiency. This approach provides a unique contribution in applying linear algebra concepts to the analysis of digital consumer behavior on e-commerce platforms.
Analisis Persepsi Pengguna Terhadap Penggunaan Fitur Dark Mode Dalam Mengurangi Kelelahan Mata Pada Sistem Operasi Pradina, Selomita; Akbar, Syeren Kyla
(JITEK)Jurnal Ilmiah Teknosains Vol 12, No 1/Now (2026): Vol.12 No. 1 Mei 2026
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jitek.v12i1/Now.27590

Abstract

Meningkatnya durasi paparan layar perangkat digital memicu risiko gangguan visual seperti Computer Vision Syndrome (CVS). Fitur dark mode hadir sebagai antarmuka alternatif untuk mengurangi kelelahan mata, namun efektivitasnya secara subjektif masih sering diperdebatkan. Penelitian ini bertujuan untuk menganalisis persepsi pengguna terhadap penggunaan fitur dark mode dalam mengurangi kelelahan mata pada sistem operasi. Metode yang digunakan adalah deskriptif kuantitatif dengan pendekatan survei berani terhadap 50 responden pengguna aktif perangkat digital di Indonesia. Hasil penelitian menunjukkan bahwa 84% responden telah mengadopsi mode gelap , dengan 46% di antaranya menggunakan fitur ini secara konsisten setiap hari. Keluhan visual saat menggunakan mode cahaya berada pada kategori tinggi (mean 3,97), dengan indikator silau sebagai keluhan utama (mean 4,12). Sebaliknya, persepsi terhadap efektivitas dark mode berada pada kategori tinggi (mean 4,04), di mana aspek kenyamanan mata memperoleh skor tertinggi (mean 4,18). Sebanyak 82% responden menilai mode gelap lebih nyaman daripada mode terang . Mayoritas pengguna (58%) termotivasi oleh faktor fungsional kesehatan mata alih-alih sekadar tren estetika. Penelitian ini menyimpulkan bahwa mode gelap telah menjadi kebutuhan fungsional yang efektif bagi pengguna dengan intensitas paparan layar yang tinggi.  
PEMODELAN OPTIMASI PEMILIHAN PRODUK PADA PLATFORM E-COMMERCE SHOPEE BERBASIS FORMULASI ALJABAR LINIER Akbar, Syeren Kyla; Pradina, Selomita
(JITEK)Jurnal Ilmiah Teknosains Vol 11, No 2/Nov (2025): Jitek
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jitek.v11i2/Nov.25515

Abstract

The development of e-commerce in Indonesia has changed consumer decision-making patterns, particularly on the Shopee platform, which offers a wide selection of products at competitive prices. However, the multitude of alternatives often makes it difficult for consumers to determine the best product that balances price, quality, and seller reputation. This study aims to develop a linear algebra-based product selection optimization model with a linear programming approach to help consumers make rational, data-driven decisions. Four main factors were analyzed: price, shipping costs, ratings, and reviews. Data were obtained through a questionnaire survey of 100 Shopee user respondents and actual product data in the fashion category. The results show that reviews (0.2819) and ratings (0.2698) have a dominant influence compared to price (0.2283) and shipping costs (0.2200). This optimization model is able to transform qualitative variables into measurable quantitative values, resulting in optimal product recommendations based on a balance between digital trust and economic efficiency. This approach provides a unique contribution in applying linear algebra concepts to the analysis of digital consumer behavior on e-commerce platforms.
Co-Authors Akbar, Syeren Kyla