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All Journal Saber: Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi
Mugi Nasikhatun Solikhah
Universitas Pamulang
Computer Science & IT

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Penerapan Metode Fuzzy Mamdani Berbasis Web untuk Menganalisis Pola Multitasking Generasi Z dalam Konsumsi Konten Hiburan Digital Mugi Nasikhatun Solikhah; Shandi Noris
SABER : Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi Vol. 4 No. 4 (2026): Oktober: Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi
Publisher : STIKes Ibnu Sina Ajibarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59841/saber.v4i4.4313

Abstract

The rapid advancement of digital technology has encouraged Generation Z to consume digital entertainment content simultaneously with studying or working, potentially creating diverse multitasking patterns. This study aims to identify Generation Z's multitasking patterns in consuming digital entertainment content while studying or working and to implement Mamdani Fuzzy Logic for automated classification. A quantitative approach was employed using purposive sampling with a 5-point Likert-scale questionnaire. The instrument comprised 16 validated items covering four input variables: Multitasking Intensity, Focus and Distraction, Productivity Impact, and Psychological Aspects, involving 53 Generation Z respondents. Data were collected online via Google Forms distributed through WhatsApp groups, Instagram Stories, and Google Classroom between December 2024 and January 2025. Data were analyzed through fuzzification, IF–THEN inference using 81 fuzzy rules, MAX aggregation, and Centroid defuzzification. The results show that 27 respondents (50.94%) were classified as Distractive, 25 (47.17%) as Neutral, and 1 (1.89%) as Productive. System verification was conducted by comparing manual spreadsheet calculations with the web-based system outputs for all 53 respondents. The classification results provide an overview of the multitasking patterns identified in the study and demonstrate the application of Mamdani Fuzzy Logic for automated classification through a web-based system.
Co-Authors Noris, Shandi