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All Journal eCo-Buss Journal of Innovation Research and Knowledge
Lorio Purnomo
Universitas Bina Nusantara
Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Health Professions Law, Crime, Criminology & Criminal Justice Social Sciences

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Macro-Environmental Analysis Throughout Covid-19 Pandemic Using Pestel Framework: A Study in Indonesian Multi-Industry Siti Paramadita; Lorio Purnomo; Stefanus Rumangkit
eCo-Buss Vol. 7 No. 1 (2024): eCo-Buss
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/eb.v7i1.1446

Abstract

To become competitive, companies cannot rely solely on their internal factors. Macro-environmental factors have become essential for companies. These factors can be analyzed using PESTEL analysis, which shows how political, economic, social, technological, environmental, and legal aspects can affect the industry. This study examines the PESTEL framework for three industries affected by COVID-19: aviation, education, and technology. The method used is case studies where the PESTEL framework analyzes the industrial competitiveness of those three industries. The results show that each sector has different characteristics and that PESTEL factors have various effects. This study gives insights into what kind of macro-environmental factors are crucial for the industries and how companies should act to maintain their competitiveness in the industry. Additionally, risk analysis is used within this study to help companies raise their business performance and function better amidst the COVID-19 pandemic. The findings reveal that political and environmental factors significantly impact the aviation industry, social and technological factors influence the education sector, and economic and technological factors drive the e-commerce industry. This comprehensive analysis highlights the need for tailored strategies for each industry to navigate external challenges effectively. The limitation of this study is the lack of primary data. Therefore, future research using surveys or interviews can enrich this study. By understanding these dynamics, companies can develop more robust strategies to thrive in a post-pandemic world.
PORTOFOLIO OPTIMAL SAHAM INDEKS INFOBANK15 PASCA PANDEMI BERAKHIR DI INDONESIA Tofik; Lorio Purnomo; Anggha Dipa Pratama; Shandra Widiyanti; Anton Kurniawan
Journal of Innovation Research and Knowledge Vol. 4 No. 12: Mei 2025
Publisher : Bajang Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53625/jirk.v4i12.10195

Abstract

Penelitian ini bertujuan untuk mengetahui kombinasi saham apa saja yang dapat menjadi portofolio optimal saham menggunakan metode Single Index Model pada indeks infobank15 pasca pandemi. Selain itu, belum banyak penelitian tentang portofolio optimal dengan metode Single Index Model pada indeks saham infobank15 serta indeks saham lainnya yang merupakan hasil kerja sama Bursa Efek Indonesia dengan sejumlah perusahaan media. Jenis penelitian ini adalah analisis kuantitatif dan menggunakan data historis secara bulanan seperti harga saham penutupan dan Indeks Harga Saham Gabungan, serta suku bunga acuan. Tujuannya adalah untuk mengetahui nilai Excess Return to Beta dan Cut Off Point untuk dapat menentukan saham mana yang paling cocok untuk portofolio dan proporsi sahamnya. Populasi dalam penelitian adalah saham-saham yang terdaftar dalam indeks infobank15 mulai dari Juni 2023 hingga Desember 2024 yang berjumlah 18 saham. Teknik pengambilan sampel menggunakan metode purposive sampling seperti memilih saham yang konsisten masuk indeks infobank15 selama periode penelitian berturut-turut. Jumlah saham yang dapat diambil sebagai sampel dalam penelitian ini tercatat 13 saham. Hasil penelitian menunjukkan bahwa saham-saham pembentuk portofolio optimal menggunakan metode Single Index Model pada indeks infobank15 terdapat empat saham yaitu PNBN dengan proporsi 57,11%, BRIS 27,71%, BNGA 13,25%, dan ARTO dengan proporsi 1,93%.
Co-Authors Anggha Dipa Pratama Anton Kurniawan Shandra Widiyanti Siti Paramadita Stefanus Rumangkit Tofik