PENERAPAN KONSEP NON-BLOCKING PADA APLIKASI ANALISIS SENTIMEN TRENDING TOPIC TWITTER

Pradipta, Raka Yuda (2025) PENERAPAN KONSEP NON-BLOCKING PADA APLIKASI ANALISIS SENTIMEN TRENDING TOPIC TWITTER. S1 thesis, Universitas Mercu Buana Jakarta - Menteng.

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Abstract

Penelitian ini bertujuan untuk mengevaluasi penerapan konsep non-blocking pada aplikasi analisis sentimen Trending Topic Twitter dengan menggunakan Node.js. Konsep non-blocking diimplementasikan untuk mengoptimalkan kinerja aplikasi dalam mengonsumsi API sentimen tanpa memblokir eksekusi proses yang berjalan. Penelitian ini tidak hanya memfokuskan pada algoritma sentimen, melainkan lebih menitikberatkan pada efisiensi penggunaan sumber daya dan waktu proses. Data eksperimen diperoleh melalui serangkaian percobaan dengan variasi jumlah worker (pemroses). Hasil percobaan menunjukkan bahwa dengan satu worker, waktu proses meningkat secara linear seiring dengan jumlah data tes, sedangkan rata-rata penggunaan CPU dan memori cenderung stabil. Dengan penambahan worker, terlihat peningkatan kinerja dalam hal waktu proses yang lebih efisien, meskipun terjadi kenaikan sejumlah kecil penggunaan CPU dan memori. Dengan satu worker, penggunaan CPU dan memori relatif stabil, sementara peningkatan jumlah worker menyebabkan penurunan waktu proses secara signifikan. Hal ini mengindikasikan bahwa penerapan konsep non-blocking, terutama dengan lebih dari satu worker, dapat meningkatkan efisiensi dan responsivitas aplikasi. Penelitian ini memberikan wawasan terhadap potensi penggunaan konsep non-blocking pada aplikasi analisis sentimen dengan skala yang lebih besar, terutama pada platform berbasis Node.js. Hasil eksperimen dapat menjadi dasar bagi pengembang untuk mempertimbangkan penerapan konsep non-blocking dalam pengembangan aplikasi serupa guna meningkatkan kinerja dan responsivitas. This research aims to evaluate the implementation of the non-blocking concept in the Twitter Trending Topic sentiment analysis application using Node.js. The nonblocking concept is implemented to optimize the application's performance in consuming sentiment API without blocking the execution of running processes. The study not only focuses on sentiment algorithm but also emphasizes resource usage efficiency and processing time. Experimental data was obtained through a series of trials with variations in the number of workers (processors). The results indicate that with one worker, processing time increases linearly with the number of test data, while the average CPU and memory usage tends to remain stable. Adding a second worker shows improved performance in terms of more efficient processing time, although there is a slight increase in both CPU and memory usage. With one worker, CPU and memory usage remain relatively stable, while an increase in the number of workers results in a significant reduction in processing time. This suggests that the implementation of the non-blocking concept, especially with more than one worker, can enhance the efficiency and responsiveness of the application in consuming sentiment data from the Twitter API. This research provides insights into the potential use of the non-blocking concept in sentiment analysis applications on a larger scale, especially on Node.js-based platforms. The experimental results can serve as a foundation for developers to consider implementing the non-blocking concept in the development of similar applications to enhance performance and responsiveness.

Item Type: Thesis (S1)
NIM/NIDN Creators: 41519110143
Uncontrolled Keywords: Non-Blocking, Twitter, Sentimen, Blocking, Nodejs Non-Blocking, Twitter, Sentiment, Blocking, Nodejs
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 > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: OKTAFIYANI AZ ZAHRO
Date Deposited: 26 Feb 2025 04:44
Last Modified: 26 Feb 2025 04:44
URI: http://repository.mercubuana.ac.id/id/eprint/94455

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