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All Journal Jurnal Manajemen Teori dan Terapan Zeta - Math Journal Ecopreneur.12 Mathvision : Jurnal Matematika Business and Finance Journal Community Development Journal Community Development Journal: Jurnal Pengabdian Masyarakat Indonesia Berdaya Pattimura International Journal of Mathematics (PIJMath) Semanggi: Jurnal Pengabdian kepada Masyarakat
Puspandam Katias
Department Of Management, Universitas Nahdlatul Ulama Surabaya
Arts Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Health Professions Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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Journal : Pattimura International Journal of Mathematics (PIJMath)

 1 
Unscented Kalman Filter and H-Infinity for Travel Company Stock Price Estimation Katias, Puspandam; Susanto, Ismanto Hadi; Herlambang, Teguh; Anshori, Mohamad Yusak
Pattimura International Journal of Mathematics (PIJMath) Vol 1 No 2 (2022): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (414.728 KB) | DOI: 10.30598/pijmathvol1iss2pp81-88

Abstract

The travel and hotel industry is one of the industries experiencing rapid growth. As the population grows, the need for travel and accommodation services gets higher. This is one of the factors contributing a rapid increase in such service industry. Competition in the economy and business world is getting tougher from year to year both within a country and abroad. Considering that Indonesia is a country comprised of many islands with a variety of natural beauty, it has the very potential for tourist resort attraction. This kind of thing leads to the growth of the Hotel and Travel industry to support tourism development. With such rapid service industry development, supported by promising business opportunities, investors for such sector are encouraged. The right way to reduce risk for investors interested is to develop a system for estimating the stock prices. Therefore, in this study, the stock price estimation method applied for travel companies adopted Advanced Kalman Filter, a comparison of H-Infinify and Unscented Kalman Filter (UKF) as a chart for investors to take into consideration in their investment decision making. The simulation results showed that the UKF method had higher accuracy than the H-Infinify method with an error by the UKF of 3.2% and that by the H-Infinify of 9.6%.
Implementation Fuzzy and Extended Kalman Filter for Estimation of High and Low Stock Price Travel Company Santoso, Ismanto Hadi; Katias, Puspandam; Herlambang, Teguh; Anshori, Mohamad Yusak; Adinugroho, Mukhtar
Pattimura International Journal of Mathematics (PIJMath) Vol 2 No 1 (2023): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol2iss1pp17-24

Abstract

Competition in the business world is getting tougher from year to year both within a country and abroad. There are a large number of companies competing with one another, especially entering the free market share in Asia, namely the Asean Economic Community (AEC). In the current development of modern economy, Indonesia is making efforts to increase its economic growth. For this, developments in any fields are made. Among others is the service industry such as accommodation, travel, and transportation services. Considering that Indonesia is a country comprised of many islands with a variety of natural beauty, it has the very potential for tourist resort attraction. This kind of thing leads to the growth of the Travel, tourism and hotel industry to support development of tourism. With such rapid service industry development, supported by promising business opportunities, investors for such sector are encouraged. The right way to reduce risk for investors interested is to develop a system for estimating the stock prices. Therefore, in this study, the high and low stock price estimation method applied for travel companies adopted developed Kalman Filter, a comparison of two Kalman Filter development methods, namely Extended Kalman Filter (EKF) and Fuzzy Kalman Filter (FKF) as a chart for investors to take into consideration in their investment decision making. The simulation results showed that the EKF method had higher accuracy than the FKF method with an error by the EKF of 3.5% and that by the FKF of 8.9%.
Co-Authors Achmad Affandi Ajizah, Silvia Amri Rasyid, Reizano Farisi, Rizaldi Al Fatikhasari, Niken Fidita, Denis Fredo Karismawan Fredo Karismawan FUJI RAHAYU Herlambang, Teguh - Isqi, Isye Fadiata Iyori Kharisma Muhammad Karya, Denis Fidita Macap, Siti Rahayu Moch. Sahri Mohamad Yusak Anshori Mughni, Ahmad Syafiq Muhammad Rodhiyallah Muhammad, Iyori Kharisma Niken Savitri Primasari Nurul Khomsiyah Primasari, Niken Savitri Putri, Nadita Mutiara Rahayu, Fuji Riansyah, Denny Fitrah Af Riyan Sisiawan Putra Rodhiyallah, Muhammad Santoso, Ismanto Hadi Susanto, Fajar Annas Susanto, Ismanto Hadi Teguh Herlambang Yudianto, Firman