Implementasi Support Vector Regression pada Prediksi Inflasi Indeks Harga Konsumen
DOI:
https://doi.org/10.30812/matrik.v19i1.511Keywords:
SVM, RBF, Linear, InflationAbstract
Inflation reflects an increase in the prices of these items as well as those used by the Indonesian government, especially Bank Indonesia, in determining monetary policy. An indicator that can be obtained by Bank Indonesia in measuring inflation is the Consumer Price Index. This study discusses inflation prediction using the SVR method. Inflation test data issued by Bank Indonesia. As a comparison material for the kernel used in the SVR method using two kernels, namely Linear and Radial Base Function. The error rate evaluation results show that linear kernels produce better values, with a MAPE rate of 8.70% and MSE of 0.0037
Downloads
Downloads
Published
Issue
Section
How to Cite
Similar Articles
- Fadhilah Dwi Ananda, Yoga Pristyanto, Analisis Sentimen Pengguna Twitter Terhadap Layanan Internet Provider Menggunakan Algoritma Support Vector Machine , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 20 No. 2 (2021)
- Rizki Rino Pratama, Analisis Model Machine Learning Terhadap Pengenalan Aktifitas Manusia , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 19 No. 2 (2020)
- Firda Yunita Sari, Maharani sukma Kuntari, Hani Khaulasari, Winda Ari Yati, Comparison of Support Vector Machine Performance with Oversampling and Outlier Handling in Diabetic Disease Detection Classification , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 22 No. 3 (2023)
- Wahyu Styo Pratama, Didik Dwi Prasetya, Triyanna Widyaningtyas, Muhammad Zaki Wiryawan, Lalu Ganda Rady Putra, Tsukasa Hirashima, Performance Evaluation of Artificial Intelligence Models for Classification in Concept Map Quality Assessment , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 24 No. 3 (2025)
- Sucipto Sucipto, Didik Dwi Prasetya, Triyanna Widiyaningtyas, Educational Data Mining: Multiple Choice Question Classification in Vocational School , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 23 No. 2 (2024)
- Dewa Ayu Kadek Pramita, Ni Wayan Sumartini Saraswati, I Putu Dedy Sandana, Poria Pirozmand, I Kadek Agus Bisena, Optimizing Hotel Room Occupancy Prediction Using an Enhanced Linear Regression Algorithms , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 24 No. 1 (2024)
- Syahril Efendi, Poltak Sihombing, Sentiment Analysis of Food Order Tweets to Find Out Demographic Customer Profile Using SVM , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 21 No. 3 (2022)
- Rofik Rofik, Roshan Aland Hakim, Jumanto Unjung, Budi Prasetiyo, Much Aziz Muslim, Optimization of SVM and Gradient Boosting Models Using GridSearchCV in Detecting Fake Job Postings , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 23 No. 2 (2024)
- Annisa Nurul Puteri, Suryadi Syamsu, Topan Leoni Putra, Andita Dani Achmad, Support Vector Machine for Predicting Candlestick Chart Movement on Foreign Exchange , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 22 No. 2 (2023)
- Putu Tisna Putra, Anthony Anggrawan, Hairani Hairani, Comparison of Machine Learning Methods for Classifying User Satisfaction Opinions of the PeduliLindungi Application , MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer: Vol. 22 No. 3 (2023)
You may also start an advanced similarity search for this article.