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All Journal Asia-Pacific Management and Business Application Jati: Jurnal Akuntansi Terapan Indonesia JEMA: Jurnal Ilmiah Bidang Akuntansi dan Manajemen Fair Value: Jurnal Ilmiah Akuntansi dan Keuangan Data Science: Journal of Computing and Applied Informatics J-SAKTI (Jurnal Sains Komputer dan Informatika) International Journal of Advanced Science Computing and Engineering Economic and Finance in Indonesia
Patria, Harry
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Social Sciences

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Bayesian Regression for Predicting Price Empirical Evidence in American Real Estate Patria, Harry
Data Science: Journal of Computing and Applied Informatics Vol. 7 No. 1 (2023): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v7.i1-10082

Abstract

The two foremost aims of classical regression are to assess the structure and magnitude of the relationship between variables. Despite the aforementioned benefits, unlike classical regression, which only offers a point estimate and a confidence interval, Bayesian regression offers the whole spectrum of inferential solutions. The results of this study demonstrate the Bayesian approach's suitability for regression tasks and its advantage in accounting for additional a priori data, which often strengthens studies. Using data from Boston Housing provided by from UCI ML Repository, this study proves that the prior distributions have the benefit of producing analytical, closed-form conclusions, which eliminates the need to use numerical techniques like Markov Chain Monte Carlo (MCMC). Second, software implementations are offered together with formulas for the posterior outcomes that are supplied, clarified, and shown. The assumptions supporting the suggested approach are evaluated in the third step using Bayesian tools. Prior elicitation, posterior calculation, and robustness to prior uncertainty and model sufficiency are the three processes that are essential to Bayesian inference.
Price Prediction with Bayesian Inference and Visualization: Empirical Evidence in India Real Estate Patria, Harry
Data Science: Journal of Computing and Applied Informatics Vol. 7 No. 2 (2023): Data Science: Journal of Computing and Applied Informatics (JoCAI)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jocai.v7.i2-11434

Abstract

Classical regression serves two primary purposes: evaluating the structure and strength of the relationship between variables. However, while classical regression provides only a point estimate and confidence interval, Bayesian regression offers a comprehensive range of inferential solutions. This study demonstrates the suitability of the Bayesian approach for regression tasks and its advantage in incorporating additional a priori information, which can strengthen research. To illustrate, we utilized data from the Indian Housing dataset provided by the Kaggle Repository. We found that prior distributions produce analytical, closed-form conclusions, eliminating the need for numerical techniques like Markov Chain Monte Carlo (MCMC). Furthermore, this study provides software implementations, along with formulas for the posterior outcomes that are explained and presented clearly. In the third step, Bayesian tools were employed to evaluate the assumptions that underlie the proposed approach. Specifically, the essential processes of Bayesian inference - prior elicitation, posterior calculation, and robustness to prior uncertainty and model sufficiency - were assessed.
The Role of Leadership and Decision-Making under Crisis: A bibliometric analysis and scientific evolution from 1962 to 2020 Patria, Harry
APMBA (Asia Pacific Management and Business Application) Vol. 10 No. 1 (2021)
Publisher : Department of Management, Faculty of Economics and Business, Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.apmba.2021.010.01.3

Abstract

The unprecedented importance of leadership and decision-making under recent pandemic and economic crises boosts the development of this research domain. This study shed light on the published works of leadership and decision-making under crises which have had the greatest contribution and evolutionary scientific paths over the decades, which are: (1) inspect the scientific anatomy of earlier works and their main structures; (2) scrutinize the scientific trends and the evolutionary path, and (3) recognize theoretical and practical implications. This study generates its analysis based on R programming language with a package of ‘bibliometrix’ (a) multidimensional data analysis, (b) intellectual structure and network analysis, (c) conceptual structure and factorial analysis, (d) strategic diagrams and evolution maps, and (e) historical citation network and research collaboration across the world. From this bibliometric study covering 692 articles published in the academic journal from 1962 to 2020, the findings open up an opportunity of how leaders overcome plausible crises by making the right decision through organizational resources, technological capability, people management. Subsequently, the findings can explain the way decisions are made so that prevent the potential crisis in the stage of planning and lessening the harm in the stage of crisis intervention. For theoretical contributions, it appears that future research needs to explore the emerging themes of data mining, artificial intelligence, information system, and information management. In the era of the COVID-19 pandemic, healthcare and crisis management are likely to be addressed by unleashing cutting-edge digital technology such as Artificial Intelligence (AI), Machine Learning (ML), and Internet of Things (IoT).
Analisis Optimasi Portofolio Sebelum dan Sesudah Covid19: Studi pada Perusahaan Sektor Kesehatan di Bursa Efek Indonesia Syarif, Allevia; Zulfikri, Fahmi; Tryanda, Dendy; Patria, Harry
Jati: Jurnal Akuntansi Terapan Indonesia JATI Vol 5, No 1: March 2022
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jati.v5i1.13239

Abstract

Tujuan dari adanya riset ialah guna membentuk portofolio yang optimal pada perusahan sektor kesehatan dari tahun 2019 sampai 2020 dengan menggunakan model Teori Portofolio Modern dan untuk menganalisa risiko dan keuntungan yang dihasilkan portofolio yang optimal sebelum dan sesudah Covid-19. Selain itu untuk menguji pengaruh Covid-19 pada harga saham selama 8 bulan, sebelum dan setelah adanya pengumuman Covid-19 di Indonesia, sehingga bisa merumuskan keputusan berinvestasi. Penggunaan sampelnya dengan memakai 12 perusahaan sector kesehatan yang secara konsisten ada di BEI dan tidak melakukan stock split dengan jumlah observasi adalah 3984 harga saham selama periode Juli 2019 sampai November 2020. Berdasarkan hasil penelitian, investasi optimal, tiga saham yang memiliki tangensi yang tinggi adalah HEAL, SIIDO, dan DVLA, akan tetapi HEAL dan DVLA juga memiliki nilai varians yang tinggi. Hasil empiris penelitian ini berimplikasi pada investor dan pengembangan teori portofolio optimal pada secktor kesehatan.
Co-Authors Aromy, Verry Dina B, Yanuardhi Arief Daulay, Iman Taufiq Dina Anggraeni, Dina Djuwita A. Rahim Fadillah, Lukman Farih, Imaduddin Heri Hermawan Margono, Hanif Nur Fauzi Nadira, N Nugraha, Raditya Hari Nugroho, Antonius Agung Prasetyo, Heru Budi Prasetyohadi, Latif Rahim, Djuwita A. Satya, Candra Harry Sugiyanto, Kris Syarif, Allevia Tryanda, Dendy Yuwono, Eko Zam Zam, M. Irwan Zulfikri, Fahmi