ANALISIS SENTIMEN MENGENAI KENAIKAN HARGA BAHAN BAKAR MINYAK (BBM) MENGGUNAKAN METODE NAIVE BAYES DAN SUPPORT VECTOR MACHINE

REJEKI, FERDI (2023) ANALISIS SENTIMEN MENGENAI KENAIKAN HARGA BAHAN BAKAR MINYAK (BBM) MENGGUNAKAN METODE NAIVE BAYES DAN SUPPORT VECTOR MACHINE. S1 thesis, Universitas Mercu Buana Jakarta.

[img]
Preview
Text (HAL COVER)
01 COVER.pdf

Download (360kB) | Preview
[img]
Preview
Text (ABSTRAK)
02 ABSTRAK.pdf

Download (30kB) | Preview
[img] Text (BAB I)
03 BAB 1.pdf
Restricted to Registered users only

Download (64kB)
[img] Text (BAB II)
04 BAB 2.pdf
Restricted to Registered users only

Download (69kB)
[img] Text (BAB III)
05 BAB 3.pdf
Restricted to Registered users only

Download (65kB)
[img] Text (BAB IV)
06 BAB 4.pdf
Restricted to Registered users only

Download (59kB)
[img] Text (BAB V)
07 BAB 5.pdf
Restricted to Registered users only

Download (26kB)
[img] Text (DAFTAR PUSTAKA)
08 DAFTAR PUSTAKA.pdf
Restricted to Registered users only

Download (38kB)
[img] Text (LAMPIRAN)
09 LAMPIRAN.pdf
Restricted to Registered users only

Download (1MB)

Abstract

The increase in world oil prices was influenced by the war between Russia and Ukraine in Europe, which caused a huge financial shock to the world economy. As a result of this war, oil prices rose almost all over the world. The increase in world oil prices is expected to have a significant impact on the condition of the Indonesian economy. High oil prices turned out to be unprofitable for any country, including the whole world in Asia, especially for our country. The increase in fuel prices is due to high world market prices for crude oil and domestic scarcity compared to demand. The amount of fuel subsidies of almost 520 trillion is very large and swallows the state budget, so the government considers subsidized and non- subsidized fuel prices very urgent. Do a very careful and accurate calculation to calculate the amount of fuel price increase in the country. The increasing impact of simultaneous and exponential increase in fuel prices will have an impact on price inflation on Indonesia's macroeconomic fundamentals. On the Twitter platform, there are often various kinds of public responses that they throw about the increase in fuel prices in Indonesia is negative or positive. In this study, sentiment analysis of public opinion on Twitter to increase fuel prices using Bayes algorithm and Support Vector Machine Using RapidMiner and Python tools. The experimental results show that the Support Vector Machine algorithm is higher than the algorithm of Naive Bayes by giving the highest accuracy value of 90%. Keywords: Fuel Prices, Sentiment Analysis, Naïve Bayes, Support Vector Machine Kenaikan harga minyak dunia dipengaruhi oleh perang antara Rusia dan Ukraina di Eropa, yang menyebabkan guncangan finansial yang besar terhadap ekonomi dunia. Akibat perang ini, harga minyak naik hampir di seluruh dunia. Kenaikan harga minyak dunia diperkirakan akan berdampak signifikan terhadap kondisi perekonomian Indonesia. Harga minyak yang tinggi ternyata tidak menguntungkan bagi negara manapun, termasuk seluruh dunia di Asia, apalagi bagi negara Indonesia. Kenaikan harga BBM disebabkan tingginya harga pasar dunia untuk minyak mentah dan kelangkaan domestik dibandingkan dengan permintaan. Besaran subsidi BBM yang hampir 520 triliun sangat besar dan menelan anggaran negara, sehingga pemerintah menganggap harga BBM bersubsidi dan non-subsidi sangat mendesak. Meningkatnya dampak kenaikan harga BBM secara simultan dan eksponensial akan berdampak pada inflasi harga terhadap fundamental ekonomi makro Indonesia. Pada platform Twitter, sering dijumpai berbagai macam tanggapan masyarakat yang mereka lontarkan mengenai kenaikan harga BBM di Indonesia yang memiliki opini sentimen negatif, positif atau netral. Pada penelitian ini dilakukan analisa sentimen terhadap opini masyarakat dari media sosial Twitter terhadap kenaikan harga BBM menggunakan Algoritma Naïve Bayes dan Support Vector Machine dengan menggunakan tools RapidMiner dan Python. Hasil eksperimen menunjukan bahwa algoritma Support Vector Machine menghasilkan performa yang jauh lebih bagus daripada algoritma Naïve Bayes dengan memberikan nilai akurasi sebesar 90%. Kata Kunci: Subsidi BBM, Sentimen, Naïve Bayes, Support Vector Machine

Item Type: Thesis (S1)
Call Number CD: FIK/INFO. 23 034
NIM/NIDN Creators: 41519010214
Uncontrolled Keywords: Subsidi BBM, Sentimen, Naïve Bayes, Support Vector Machine
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
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
500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik > 518.1 Algorithms/Algoritma
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: ADELINA HASNA SETIAWATI
Date Deposited: 14 Apr 2023 07:26
Last Modified: 14 Apr 2023 07:26
URI: http://repository.mercubuana.ac.id/id/eprint/76524

Actions (login required)

View Item View Item