Analisis Perbandingan Sebelum Dan Saat Pandemi Covid-19 Pada Klasifikasi Likuiditas Lq45 Saham Syariah Dengan Metode Regresi Logistik Biner Dan Smote-Regresi Logistik Biner

Setyaratih, Salsabila Puteri (2022) Analisis Perbandingan Sebelum Dan Saat Pandemi Covid-19 Pada Klasifikasi Likuiditas Lq45 Saham Syariah Dengan Metode Regresi Logistik Biner Dan Smote-Regresi Logistik Biner. Other thesis, Institut Teknologi Sepuluh Nopember.

Text 06211840000082-Undergraduate_Thesis.pdf Restricted to Repository staff only Download (2MB) | Request a copy

Abstract

Pandemi COVID-19 tidak hanya berdampak pada kesehatan saja tetapi juga berdampak pada perekonomian negara, salah satu dampaknya adalah pada dunia investasi saham. Pasar modal terpengaruh dan menyebabkan terjadinya perubahan waktu perdagangan di Bursa Efek Indonesia sehingga hal ini merupakan kabar buruk yang menyebabkan investor lebih tertarik untuk menjual kepemilikan sahamnya. Saham syariah memiliki ketahanan yang baik ketika perekonomian sedang mengalami krisis, dikarenakan pasar modal syariah mempunyai kemampuan yang lebih baik untuk menyesuaikan diri dari gangguan krisis eksternal. Sehingga saham syariah merupakan pilihan yang tepat untuk melakukan investasi. Selain saham syariah di BEI terdapat saham konvensional yakni indeks LQ45. Indeks LQ45 merupakan salah satu indeks saham yang sangat popular dan berpengaruh di Bursa Efek Indonesia karena perusahaan-perusahaan yang masuk di indeks tersebut rata-rata memiliki kinerja perusahaan yang baik. Pada penelitian ini akan melakukan analisis perbandingan sebelum dan sesudah pandemi COVID-19 pada klasifikasi likuiditas LQ45 saham Syariah dengan Metode Regresi Logistik Biner dan Smote-Regresi Logistik Biner. Didapatkan hasil bahwa pada periode sebelum (1 September 2019) dan saat (2 September 2021) pandemi metode yang terbaik adalah Smote-Regresi Logistik Biner dan proporsi pembagian data training dan testing terbaik yakni dengan presentase 80:20. Variabel signifikan pada periode sebelum dan saat pandemi yakni earning per share. Nilai adjusted Odds ratio pada periode sebelum pandemi lebih besar. Proporsi perusahaan Indeks Saham Syariah Indonesia (ISSI) yang masuk sebagai anggota LQ45 sebelum pandemi tidak berbeda signifikan dibandingkan pada periode saat pandemi. Pada studi simulasi didapatkan hasil bahwa metode SMOTE Regresi Logistik Biner cenderung lebih baik.
==============================================================================================================================
The COVID-19 pandemic does not only have an impact on health but also has an impact on the country's economy, one of which is world investment. The capital market affects and causes changes in trading times on the Indonesia Stock Exchange so this is bad news that causes investors to be more interested in selling their ownership. Sharia stocks have good resilience when the economy is in crisis, because the sharia capital market has a better ability to adapt to external crisis disturbances. So that sharia stocks are the right choice for investing. In addition to sharia stocks on the IDX, there are conventional stocks, namely the LQ45 index. The LQ45 index is one of the most popular and influential stock indices on the Indonesia Stock Exchange because the companies listed on the index generally have good company performance. In this study, we will conduct a comparative analysis of before and during COVID-19 pandemic in classification of sharia stock LQ45 liquidity using binary logistics regression and smote binary logistics regression methods. It was found that in the period before (1 September 2019) and during the pandemic (2 September 2021) the best method was the Binary Logistic Smote-Regression and the proportion of the best training and testing data distribution with a percentage of 80:20. Significant variables in the period before and during the pandemic is earnings per share. The adjusted Odds ratio in the period before the pandemic was greater. The proportion of Indonesian Sharia Stock Index (ISSI) companies that were included as members of LQ45 before the pandemic was not significantly different from during the period during the pandemic. The simulation study shows that the SMOTE Binary Logistics Regression method tends to be better.

Item Type:	Thesis (Other)
Additional Information:	RSSt 519.536 Set a-1 2022
Uncontrolled Keywords:	COVID-19, Regresi Logistik Biner, Saham Syariah, SMOTE Regresi Logistik Biner. COVID-19, Binary Logistics Regression, Sharia Stocks, SMOTE Binary Logistics Regression.
Subjects:	H Social Sciences > HA Statistics
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User:	Mr. Marsudiyana -
Date Deposited:	11 Jun 2026 03:23
Last Modified:	11 Jun 2026 03:23
URI:	http://repository.its.ac.id/id/eprint/133726

Actions (login required)

View Item