IMPLEMENTASI ALGORITMA FP-GROWTH DALAM MENENTUKAN ITEMSET PLATFORM-GAME YANG PALING SERING DIGUNAKAN DEVELOPER UNTUK MERILIS GAME

HERDIANA, MUHAMMAD DIFA (2023) IMPLEMENTASI ALGORITMA FP-GROWTH DALAM MENENTUKAN ITEMSET PLATFORM-GAME YANG PALING SERING DIGUNAKAN DEVELOPER UNTUK MERILIS GAME. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

Software development and game technology have experienced rapid advancements in the last few decades. Along with this progress, the gaming industry has become one of the most promising and profitable industries in the world. Modern games released by various developers can now be accessed through various platforms such as Computers/PCs, gaming consoles, and other devices. It is essential for game developers and companies to understand market trends and consumer preferences in choosing platforms for game releases.One of the effective methods of data analysis is the FP-Growth (Frequent Pattern Growth) algorithm. This algorithm is used to discover frequently occurring patterns in a dataset known as large transactional data efficiently and effectively. In the context of this research, the dataset is extracted from one of the Metacritic websites, consisting of a database or collection of data that records the platforms used by developers for game releases. Based on a support value of 5% in the FP-Growth algorithm, six itemsets are generated, ranked by their support values from highest to lowest. Thus, it can be concluded that the most frequently used game platforms by game developers are Switch, PC, Playstation 5, Xbox, and Game Boy Advance.Based on the results of the itemsets and the support threshold value obtained from the application of the FP-Growth algorithm, it can be inferred that the algorithm's performance is excellent in determining relevant itemsets Kata Kunci: Game, Platform Game, FP-Growth, Itemset Pengembangan perangkat lunak dan teknologi game telah mengalami perkembangan pesat dalam beberapa dekade terakhir. Seiring dengan kemajuan ini, industri game telah menjadi salah satu industri yang paling menjanjikan dan menguntungkan di dunia. Game-game modern yang dirilis oleh berbagai developer kini dapat diakses melalui berbagai platform seperti Komputer/PC, konsol game, dan perangkat lainnya. penting bagi developer dan perusahaan game untuk memahami tren pasar dan preferensi konsumen dalam memilih platform untuk merilis game. Salah satu metode analisis data yang telah terbukti efektif adalah Algoritma FP Growth (Frequent Pattern Growth). Algoritma ini digunakan untuk menemukan pola sering muncul dalam dataset yang disebut data transaksi besar dengan cepat dan efisien. Dalam konteks penelitian ini, dataset yang diambil dari salah satu website Metacritic berupa database atau kumpulan data yang mencatat platform-platform yang digunakan oleh developer dalam merilis. Berdasarkan nilai support 5% pada algoritma FP-Growth menghasilkan 6 itemset dengan penilaian berdasarkan nilaipport dari yang paling tinggi hingga terendah, maka dapat disimpulkan platform-game yang paling sering digunakan oleh developer game yaitu Switch, PC, Playstation 5, Xbox, dan Game Boy Advance. Berdasarkan hasil dari itemset dan nilai support threshold yang dihasilkan dari penerapan algoritma Fp-Growth, maka disimpulkan bahwa performa dari algoritma tersebut sangat baik dalam menentukan itemset yang relevan. Kata Kunci: Game, Platform Game, FP-Growth, Itemset

Item Type: Thesis (S1)
Call Number CD: FIK/INFO. 23 195
NIM/NIDN Creators: 41519010056
Uncontrolled Keywords: Game, Platform Game, FP-Growth, Itemset
Subjects: 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 003 Systems/Sistem-sistem
000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 003 Systems/Sistem-sistem > 003.5 Computer Modeling and Simulation/Model dan Simulasi Komputer
000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika
000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika > 004.1 General Works on Specific Types of Computers/Karya Umum tentang Tipe-tipe Khusus Komputer
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: CALVIN PRASETYO
Date Deposited: 04 Nov 2023 02:42
Last Modified: 04 Nov 2023 02:42
URI: http://repository.mercubuana.ac.id/id/eprint/83819

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