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Yanuar, Ferra
Universitas Andalas
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Generalized Linear Models in Determining Factors Affecting the Number of Community Visits to Health Service with Bayesian Inference Approach Selfinia, Selfinia; Devianto, Dodi; Yanuar, Ferra
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 7, No 3 (2023): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v7i3.15186

Abstract

Public health plays an important role in achieving the Sustainable Development Goals (SDGs) set by the United Nations. The SDGs are a series of global targets and commitments aimed at addressing various challenges facing the world today, such as poverty, hunger, gender inequality, climate change, and others. Public health, as one of the important aspects of the SDGs, is closely linked to several sustainable development goals. Efforts made to achieve the SDGs in the health sector are to improve health services. The objective of this study was to identify factors that influence the number of community visits to health services. The data used is a small sample size as one hundred community respondents in Padang City, West Sumatra Province. In this study, the number of respondents' visits to health service was the measured variable, while the predictor variables consisted of five variables, namely the status of the implementation of clean and healthy living behavior, health history, distance to health services, type of insurance owned, and consumption patterns. The generalized linear models is used to identify predictor variables that have significance using the Bayesian inference approach. It was found that there are two predictor variables that are significant in influencing the number of community visits to health services, namely the consumption patterns of respondents and the health history of respondents. These two variables have a very dominant effect on the number of visits to health service facilities in Padang City. This result indicates the community has to pay attention to their consumption patterns and living behavior to prevent periodic disease outbreaks and take care of their health history factors.
Pemodelan dan Peramalan Volatilitas Memori Panjang pada Return Saham ANTM Studi Komparatif Model GARCH dan FIGARCH Rafulta, Elfa; Yanuar, Ferra; Devianto, Dodi; Maiyastri
Lattice Journal : Journal of Mathematics Education and Applied Vol. 5 No. 1 (2025): Juni 2025
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/lattice.v5i1.9525

Abstract

This study aims to model and forecast the volatility of ANTM stock returns using FIGARCH and GARCH models to capture both short- and long-memory dynamics. Daily return data spanning from January 1, 2014, to December 31, 2024, were analyzed after stationarity confirmation via ADF test. A mean model was estimated using MA (4), followed by conditional variance modeling with GARCH (1,1) and FIGARCH (1, d,1). Diagnostic tests confirmed the presence of heteroskedasticity and long memory, justifying FIGARCH usage. The FIGARCH (1, d,1) model indicated significant long-memory effects (d = 0.461007), while GARCH (1,1) effectively captured short-term volatility clustering. Forecast performance comparison showed that although both models yielded equal RMSE (0.029000), GARCH (1,1) performed better in terms of MAE (0.019531 vs. 0.019529) and MAPE (192.0809 vs. 192.3617). However, FIGARCH demonstrated superior ability in modeling persistent volatility patterns with smoother conditional variance distribution and better long-term uncertainty estimation. These findings suggest that while GARCH is preferable for short-term predictive accuracy, FIGARCH offers more robust insights into long-term volatility persistence, making it suitable for strategic financial risk management.   Penelitian ini bertujuan untuk memodelkan dan meramalkan volatilitas return saham ANTM menggunakan model GARCH dan FIGARCH guna menangkap dinamika volatilitas jangka pendek dan panjang. Data return harian dari 1 Januari 2014 hingga 31 Desember 2024 dianalisis setelah melalui uji stasioneritas ADF. Model rata-rata ditentukan menggunakan MA (4), dilanjutkan dengan pemodelan varian bersyarat menggunakan GARCH (1,1) dan FIGARCH (1, d,1). Uji diagnostik menunjukkan adanya heteroskedastisitas dan efek memori panjang, mendukung penggunaan model FIGARCH. Hasil estimasi menunjukkan bahwa model FIGARCH (1, d,1) memiliki nilai d = 0,461007, mengindikasikan adanya efek long memory yang signifikan, sedangkan GARCH (1,1) efektif dalam menangkap klaster volatilitas jangka pendek. Evaluasi kinerja peramalan menunjukkan kedua model memiliki nilai RMSE yang sama (0,029000), namun GARCH (1,1) lebih unggul dalam MAE (0,019531 vs. 0,019529) dan MAPE (192,0809 vs. 192,3617). Meskipun demikian, FIGARCH menunjukkan keunggulan dalam menangkap pola volatilitas jangka panjang yang stabil. Dengan demikian, GARCH cocok untuk akurasi prediksi jangka pendek, sementara FIGARCH lebih direkomendasikan untuk estimasi risiko jangka panjang dalam pengelolaan keuangan strategis.
Co-Authors Abdi Mulya Admi Nazra AMALIA DWI PUTRI Amalia Dwi Putri ANGGUN CITRA DELIMA ANNISA RAHMADIAH Arfarani Rosalindari Arrival Rince Putri Asdi, Yudiantri Astari Rahmadita ATIKAH RAHMAH PUTRI Azmi Arsa Bahri, Susila Baqi, Ahmad Iqbal Boby Canigia Budi Rudianto Catrin Muharisa Cichi Chelchillya Candra Cichi Chelchillya Candra Cici Saputri Cintya Mukti Des Welyyanti Deva, Athifa Salsabila Devianto, Dodi Dila Mulya Dina Monica DINIE ANEFI HAJARA Efendi Efendi Elfa Rafulta Ermanely Ermanely Fadilla Nisa Uttaqi Fajriyah, Rahmatika Farhah Anggana Febriyuni, Rahmi Firdawati, Firdawati FITARI RESMALANI Fitri Aulia FITRI SABRINA Gusmanely Z Harahap, Vika Pradinda Haripamyu Haripamyu Hasibuan, Lilis Harianti Hazmira Yozza Helmi, Monika Rianti Ihsan Kamal Ikhlas Pratama Sandi Indah Pratiwi Izzati Rahmi HG Izzati Rahmi HG Jenizon Jenizon Kamarni, Neng Kartini Aboo Talib @Khalid Khatimah, Havifah Husnatul Lilis Harianti Hasibuan Livia Amanda M. Pio Hidayatullah M. Rizki Oktavian Maiyastri Maiyastri, Maiyastri Majbur, Ridha Fauza Mardha Tillah Mawanda Almuhayar MEILINA DINIARI Melisa Febriyana Mesi Oktafia Meutia Fikhri MIFTAHUL JANNAH HB Mira Serma Teti Mita Oktaviani Muhammad Iqbal Muhammad Qolbi Shobri Muharisa, Catrin Mutiara Fara Nabilla Nadia Cindi Eka Putri Nadiah Ramadhani NADYA PUTRI ALISYA Nadya Putri Alisya Narwen Narwen Nayla Desviona Nova Noliza Bakar Noverina Alfiany Nurmaylina Zaja Nurwijayanti Qalbi, Latifatul Radhiatul Husna RAHMI HG, IZZATI Rahmi, Fatihatur Ramadhani, Eza Syafri Religea Reza Putri Rescha, Ratna Vrima Resti Mustika Sari Resti Nanda Yani Riau, Ninda Permata Ridhatul Ilahi Riri Lestari Riri Lestari Rudiyanto Rudiyanto, Rudiyanto SAIDAH . Sani, Ridha Fadhila Saputri, Ovi Delviyanti Sari, Putri Trisna Sarmada Sarmada Sarmada, Sarmada Selfinia, Selfinia SHINTA MUTIA KARNEVA Shinta Wulandari SHINTA YULIANA Silvia . SILVIA YUNANDA Sisi Andriani Siti Juriah SITI LATHIFAH IRMA SUMINDANG YUZAN Surya Puspita Sari, Surya Puspita Susi Marisa Syafwan, Mahdhivan Syauqi, Irfan Tari Adriana Musana Tasya Abrari Tasya Abrari Uswatul Hasanah VIKI ANDRIANI Widya Wijayanti WINDA LIDYA Winda Oktari WULANDARI, FRILIANDA Wulandari, Sintya wulandari, sisca Yanita Yanita Yosika Putri Yulmiati Yulmiati Yurinanda, Sherli Zahratul Aini Zetra, Aidinil Zetra, Aidinil Zulakmal, Zulakmal Zulhazizah .