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FORECASTING THE INFLATION RATE IN INDONESIA USING ARIMA-GARCH MODEL Toha Saifudin; Suliyanto Suliyanto; Fitriana Nur Afifa; Aini Divayanti Arrofah; Doni Muhammad Fauzi; Fachriza Yosa Pratama; Isryad Yoga Adyatma
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss2pp0955-0970

Abstract

Inflation is a key economic indicator that affects purchasing power, economic growth, and financial stability. Accurate forecasting is essential for policymakers to implement effective monetary and fiscal policies. However, traditional models like ARIMA (Autoregressive Integrated Moving Average) mainly capture general trends and often fail to address inflation volatility. This study enhances inflation forecasting accuracy by applying the ARIMA-GARCH hybrid model, which combines trend estimation with volatility modelling. Focusing on Indonesia’s inflation patterns using recent data, it addresses a gap in existing research. This type of research uses quantitative methods, and the data were obtained from the official website of Bank Indonesia. The dataset consists of 240 monthly Indonesian inflation data points spanning from September 2004 to August 2024. The ARIMA (0,1,1)-GARCH (2,0) model is used to analyze inflation trends and volatility dynamics. The model evaluation shows strong predictive performance, with a Mean Absolute Percentage Error (MAPE) of 2.73% and Root Mean Squared Error (RMSE) of 0.74 for training data. Testing data results in a MAPE of 18.95% and RMSE of 0.702, which remains within an acceptable range. These findings highlight the importance of incorporating volatility modelling in inflation forecasting to enhance economic decision-making. A reliable forecast mitigates economic uncertainty, thereby providing a stronger foundation for achieving long-term economic growth. This study contributes by demonstrating the practical application of ARIMA-GARCH in Indonesia’s inflation modelling, providing valuable insights for policymakers in managing inflation-related risks.
Stock Price Modelling of Ciputra Development Tbk. (CTRA) Using Fourier Series Ika Purnamasari; Toha Saifudin; Sri Wahyuningsih; M. Fariz Fadillah Mardianto
Journal of Applied Informatics and Computing Vol. 10 No. 3 (2026): June 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i3.13093

Abstract

Stock price data generally show fluctuating and dynamic patterns, making the forecasting process challenging in time series analysis. In addition, stock forecasting is also related to economic activity and investment development that support economic growth. This study applies the Fourier series model to predict daily stock prices of Ciputra Development Tbk (CTRA) during January-December 2025 by considering the Fourier parameter (K). The Fourier series estimator consists of two models, namely a model with trend component and a model without trend component. The data were divided into training and testing sets using an 85:15 ratio. Model selection was performed using Generalized Cross validation (GCV), while model performance was evaluated using Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE). The results show that the Fourier series model with a trend component outperformed the model without trend component. The optimal model was obtained at K=20 with a minimum GCV value of 357.7702. The model produced a training MAPE of 1.2804% and RMSE of 14.9427, while the testing MAPE and RMSE were 5.0640% and 53.6083, respectively, indicating good predictive accuracy and generalization performance.
MODELLING MATHEMATICS LEARNING OUTCOMES USING A MULTIPREDICTOR SEMIPARAMETRIC REGRESSION APPROACH BASED ON SPLINE ESTIMATOR Titania Faisha Purnama; Nur Chamidah; Toha Saifudin
JP2M (Jurnal Pendidikan dan Pembelajaran Matematika) Vol 11, No 1 (2025)
Publisher : Universitas Bhinneka PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jp2m.v11i1.6999

Abstract

Education is one of the points of Indonesia's SDGs which is stated in goal number 4. Mathematics is one of the subjects that contributes to the realizing national education goals. In the independent curriculum, the success of the learning process at school can be seen from the criteria for achieving learning objectives. In this article, we analyzed students’ mathematics learning outcomes using a multi predictor semiparametric regression approach and interpreted the results with Spline estimator. The results shows that the differences between the types of classes greatly influence outcomes in learning mathematics, where social classes experienced a decrease of 2.435 percent compared to science classes. To increase outcomes in learning mathematics, the percentage of learning motivation must be more than 88 percent. Apart from that, high or low IQ cannot determine whether students’ mathematics learning outcomes. Furthermore, by combining linear and nonlinear components in the model effectively, the overall accuracy based on the MAPE value is 7.87 percent, so that the model can be predict the actual value high accurately. Thus, the multi predictor semiparametric regression approach based on spline estimator can explain the mathematics learning outcomes model very well.
Co-Authors Abdul Aziz Aditya Syarifudin Akbar Aflaha, Nabila Shafa Aini Divayanti Arrofah Aisharezka, Mutiara Aisyah, Arlisya Shafwan Al Hasri, Ilham Maulana Alfi Nur Nitasari Alfredi Yoani Alpandi, Gaos Tipki Ameliatul 'Iffah Ana, Elly Andini Putri Mediani Angga Kusuma Bayu Viargo Angga Kusuma Bayu Viargo Aniq Atiqi Any Tsalasatul Fitriyah Ardi Kurniawan Ardi Kurniawan Ariani, Fildzah Tri Januar Aulia, Niswa Faizah Auliyah, Nina Ayuning Dwis Cahyasari Azis, Aurelia Islami Azizah, Khansa Belindha Ayu Ardhani Bryan Given Christiano Ginzel Chaerobby Fakhri Fauzaan Purwoko Christopher Andreas Dewanti, Maria Setya Dewanty, Sanda Insania Diah Puspita Ningrum Dita Amelia Dita Amelia Dita Amelia, Dita Doni Muhammad Fauzi Dwika Maya Harsanti Easyfa Wieldyanisa, Ezha Elly Pusporani Erfiana Erfiana Fachriza Yosa Pratama Faiza, Atikah Fajrina, Sofia Falasifah, Sabrina Fatmawati Fatmawati Fauziah, Nathania Fa’iqotus Zuqna Dwi Syauqie Felix Reba Fina Insyiroh Firmansyah, Mochamad FIRMANSYAH, MOCHAMMAD Fitriana Nur Afifa Fitriani, Mubadi'ul Fortunata, Regina Gaos Tipki Alpandi Gaos Tipki Alpandi Hardiansyah, Fernanda Rizky Hasyim, Maylita Herdianto, Muhammad Hendra Ika Purnamasari Ilma Amira Rahmayanti Indrasta, Irma Ayu Insania Dewanty, Sanda Isryad Yoga Adyatma Johanna Tania Victory Jovansha Ariyawan Khairian, Farhan Aldan Kholidiyah, Azizatul Leni Sartika Panjaitan Lensa Rosdiana Safitri M. Fariz Fadillah Mardianto Maelcardino Christopher Justin Mahadesyawardani, Arinda Maharani, Prima Makhbubah, Karina Rubita Marisa Rifada Marpaung, Josua Ronaldo Davico Marshanda Aprilia Marwanda, Nadia Dwi Mediani, Andini Putri Mia Khoirunnisa Mochamad Firmansyah Mochamad Rasyid Aditya Putra Mohammad Noufal Ubadah Muhammad Rosyid Ridho Az Zuhro Mutiara Aisharezka Nabila Nurdin Nahar, Muhammad Hafidzuddin Naufal Ramadhan Al Akhwal Siregar Naura, Sheila Sevira Asteriska Novianti, Dita Aris Nugraha, Galuh Cahya Nur Chamidah Nur Chamidah Nur chamnidah Nur Rahmah Miftakhul Jannah Nurrohmah, Zidni 'Ilmatun Panjaitan, Leni Sartika Puspasari, Laili Raaulia Gita Nafsi Rahayu, Rizky Dwi Kurnia Ramadhani, Azzah Nazhifa Wina Ramadhanty, Devira Thania Ramadhina, Fidela Sahda Ilona Recylia, Rien Rimuljo Hendradi Risky Wahyuningsih Sa'idah, Andini Sabrina Salsa Oktavia Safitri, Lensa Rosdiana Salma Bethari Andjani Sumarto Salsabila, Fatiha Nadia Sa’idah Zahrotul Jannah Sediono, Sediono Sentosa, Martha Ayu Setyawan, Muhammad Daffa Bintang Shalwa Oktavrilia Kusuma Siagian, Kimberly Maserati Siti Maghfirotul Ulyah Sri Wahyuningsih Sugha Faiz Al Maula Suliyanto Suliyanto Suliyanto Syaugi Sungkar, Salman Teguh Susanto Teguh Susanto Tiani Wahyu Utami Titania Faisha Purnama Trisa, Nadya Lovita Hana Valida, Hanny Verina Tita Nabila Victory, Johanna Tania VITA FIBRIYANI Wahyuli, Diana Widyawati, Ayu Wieldyanisa, Ezha Easyfa Wulandari, Indana Zulfa Yan Dwi