Smartphone Selection Recommendation System for Streaming
Needs Using the TOPSIS Method
Dublin Core
Title
Smartphone Selection Recommendation System for Streaming
Needs Using the TOPSIS Method
Needs Using the TOPSIS Method
Subject
Digital Marketing; SWOT; PEST; Business Model Canvas.
Description
Choosing the optimal smartphone for streaming needs is a challenge for users amidst the rapid development of technology and the variety
of choices on the market. The need for high performance in streaming, such as large battery capacity, adequate RAM, fast processor, highquality screen, and stable network support, drives the need for an objective and measurable recommendation system. This study aims to
develop a smartphone selection recommendation system using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)
method that focuses on streaming activity needs. The research process involves the stages of problem identification, collecting datasets from
various trusted sources, preprocessing data to ensure completeness and consistency, and implementing the TOPSIS method through data
normalization, weighting criteria, determining positive and negative ideal solutions, to calculating preference scores and alternative
rankings. The dataset used includes 252 smartphones from popular brands in Indonesia such as Samsung, Oppo, Vivo, Apple, Realme, and
Xiaomi, with specifications relevant to streaming. The results of the TOPSIS method implementation show that smartphones such as the
iQOO Z9 Turbo Endurance, Redmi Turbo4, and Neo7 SE are ranked at the top with high preference scores, indicating the best combination
of price, battery capacity, RAM, and network connectivity. The recommendation categories are arranged based on market segments, such
as flagship, mid-range, budget-friendly , and based on each brand, to provide flexibility in selection. In general, Vivo, Xiaomi, and Realme
dominate the best category, while Samsung and Oppo remain competitive in the middle class, and Apple maintains its stability in the premium
ecosystem. The recommendation system is expected to help users make faster and more precise decisions according to technical needs and
budget constraints in choosing a smartphone for high-quality streaming activities.
of choices on the market. The need for high performance in streaming, such as large battery capacity, adequate RAM, fast processor, highquality screen, and stable network support, drives the need for an objective and measurable recommendation system. This study aims to
develop a smartphone selection recommendation system using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)
method that focuses on streaming activity needs. The research process involves the stages of problem identification, collecting datasets from
various trusted sources, preprocessing data to ensure completeness and consistency, and implementing the TOPSIS method through data
normalization, weighting criteria, determining positive and negative ideal solutions, to calculating preference scores and alternative
rankings. The dataset used includes 252 smartphones from popular brands in Indonesia such as Samsung, Oppo, Vivo, Apple, Realme, and
Xiaomi, with specifications relevant to streaming. The results of the TOPSIS method implementation show that smartphones such as the
iQOO Z9 Turbo Endurance, Redmi Turbo4, and Neo7 SE are ranked at the top with high preference scores, indicating the best combination
of price, battery capacity, RAM, and network connectivity. The recommendation categories are arranged based on market segments, such
as flagship, mid-range, budget-friendly , and based on each brand, to provide flexibility in selection. In general, Vivo, Xiaomi, and Realme
dominate the best category, while Samsung and Oppo remain competitive in the middle class, and Apple maintains its stability in the premium
ecosystem. The recommendation system is expected to help users make faster and more precise decisions according to technical needs and
budget constraints in choosing a smartphone for high-quality streaming activities.
Creator
Firdan Gusmara Kusumah a
, Rifki Miftah Fauzi b*
, Rifki Miftah Fauzi b*
Source
https://jurnal.unsil.ac.id/index.php/jaisi/article/view/15567/4228
Publisher
https://jurnal.unsil.ac.id/index.php/jaisi/article/view/15567/4228
Date
mei 2025
Contributor
Fajar bagus W
Format
PDF
Language
English
Type
Text
Files
Collection
Citation
Firdan Gusmara Kusumah a
, Rifki Miftah Fauzi b*
, “Smartphone Selection Recommendation System for Streaming
Needs Using the TOPSIS Method,” Repository Horizon University Indonesia, accessed January 2, 2026, https://repository.horizon.ac.id/items/show/9711.
Needs Using the TOPSIS Method,” Repository Horizon University Indonesia, accessed January 2, 2026, https://repository.horizon.ac.id/items/show/9711.