[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-126460-id":3,"doc-seo-126460-113":31,"detail-sidebar-cat-0-id-113":93},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},126460,962084925290,"Ophelia","https://ap-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45",54,"Penelitian & Laporan","Volatilitas Pasar Saham Syariah Indonesia - Periode Pandemi COVID-19 dan Pasca Pandemi: Studi Komparasi Machine Learning dan Metode Statistik","Pandemi COVID-19 memicu ketidakstabilan pasar keuangan global, termasuk pasar saham syariah di Indonesia, sehingga volatilitas indeks syariah seperti Jakarta Islamic Index (JII) dan Indeks Saham Syariah Indonesia (ISSI) mengalami perubahan sepanjang periode pandemi dan masa pemulihan pascapandemi. Analisis volatilitas diperlukan untuk memahami tingkat risiko pasar dan menilai efektivitas model prediksi. Penelitian ini membandingkan Random Forest Regressor berbasis pembelajaran mesin dengan metode statistik Naïve Persistence, menggunakan data harga penutupan harian yang ditransformasikan menjadi log return mingguan serta volatilitas rolling standar deviasi. Evaluasi dilakukan dengan RMSE dan MAE.","Volatilitas Pasar Saham Syariah Indonesia Periode Pandemi COVID-19 dan Pasca Pandemi: Studi Komparasi Machine Learning dan Metode  \nStatistik  \nGilang Gumelar, Mirza Kalyana Musthofa, Muhammad Ridho Lifandri  \npresident university, Indonesia  \n[Email: Gilang.gumelar@president.ac.id](Email: Gilang.gumelar@president.ac.id)*, [Mirza.Musthofa@student.president.ac.id](Mirza.Musthofa@student.president.ac.id), [Muhammad.Lifandri@student.president.ac.id](Muhammad.Lifandri@student.president.ac.id)  \n\n| Kata Kunci:\u003Cbr>Perkiraan Deret Waktu, prediksi volatilitas, Pembelajaran Mesin, Hutan Acak,\u003Cbr>Model statistik dasar | Abstrak |\n| --- | --- |\n|  | Pandemi COVID-19 telah menimbulkan ketidakstabilan pada pasarkeuangan global, termasuk pasar saham syariah di Indonesia. Perubahan kondisi ekonomi selama pandemi dan periode pemulihan pasca pandemi memengaruhi dinamika volatilitas indeks sahamsyariah seperti Jakarta Islamic Index (JII) dan Indeks Saham Syariah Indonesia (ISSI) . Analisis volatilitas menjadi penting untuk memahami tingkat risiko pasar serta mengevaluasi efektivitasmetode prediksi yang digunakan dalam memodelkan perilaku pasarsaham. Penelitian ini bertujuan untuk menganalisis dinamika volatilitas indeks saham syariah Indonesia pada periode pandemi dan pasca pandemi serta membandingkan kinerja model prediksi volatilitas menggunakan pendekatan Machine Learning Random Forest Regressor dan metode statistik Naïve Persistence. Penelitian menggunakan data harga penutupan harian indeks JII dan ISSI yang kemudian ditransformasikan menjadi log return mingguan dandihitung volatilitasnya menggunakan rolling standar deviasi. Prosespemodelan dilakukan dengan pembagian data deret waktu untuk training dan testing, sedangkan evaluasi model menggunakan metrik Root Mean Squared Error (RMSE) dan Mean Absolute Error (MAE) . Hasil penelitian menunjukkan bahwa volatilitas pasar saham syariahmeningkat secara signifikan pada periode pandemi dan menurun pada periodepascapandemi. Model Machine Learning menunjukkan kinerja yang lebih baik dalam memprediksi volatilitas pada kondisipasar yang bergejolak, sedangkan metode statistik lebih efektif ketika kondisi pasar relatif stabil. Temuan ini menunjukkan bahwapemilihan model prediksi volatilitas perlu mempertimbangkan karakteristik kondisi pasar yang berbeda. |\n| Keywords: | Abstract |\n| Time Series forecasting, | The COVID-19 pandemic has caused significant instability in global |\n| volatility prediction, | financial markets, including the Islamic stock market in Indonesia. |\n| Machine Learning, | Changes in economic conditions during the pandemic and the post- |\n| Random Forest, | pandemic recovery period have influenced the volatility dynamics of |\n| baseline statistical model. | Islamic stock indices such as the Jakarta Islamic Index (JII) and the Indonesia Sharia Stock Index (ISSI). Volatility analysis is essential to understand market risk and to evaluate the effectiveness of predictive models used to analyze stock market behavior. This study aims to analyze the volatility dynamics of Indonesian Islamic stock indices during the pandemic and post-pandemic periods and to |\n\ncompare the performance of volatility prediction models using the Machine Learning Random Forest Regressor approach and the statistical Naïve Persistence method. The study uses historical daily closing price data of JIIandISSI, which are transformed into weekly log returns and used to calculate volatility through rolling standard deviation. The modeling process applies a time-series data split for training and testing, while model performance is evaluated using Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). The results show that the volatility of Islamic stock indices increased significantly during the pandemic and gradually declined in the postpandemic period. The Machine Learning model performs better in predicting volatility during highly volatile market conditions, whereas the statistical method provides more accura","cbCaijfLQrB4Qnmx","https://ap.wps.com/l/cbCaijfLQrB4Qnmx","pdf",556319,6,1,13,"Indonesian","id",113,"# Pendahuluan\n## Latar belakang indeks syariah JII dan ISSI\n## Dampak pandemi dan karakteristik pergerakan harga","[{\"question\":\"Apa tujuan penelitian mengenai volatilitas pasar saham syariah Indonesia?\",\"answer\":\"Menganalisis dinamika volatilitas indeks saham syariah Indonesia selama pandemi dan pascapandemi, serta membandingkan kinerja model prediksi volatilitas.\"},{\"question\":\"Data apa yang digunakan untuk memprediksi volatilitas JII dan ISSI?\",\"answer\":\"Data harga penutupan harian JII dan ISSI ditransformasikan menjadi log return mingguan, lalu volatilitas dihitung menggunakan rolling standar deviasi.\"},{\"question\":\"Bagaimana hasil perbandingan model Machine Learning dan metode statistik?\",\"answer\":\"Volatilitas meningkat signifikan saat pandemi dan menurun pada pascapandemi. Model Machine Learning lebih baik pada kondisi pasar yang bergejolak, sedangkan metode statistik lebih efektif ketika pasar relatif stabil.\"}]","Volatilitas Pasar Saham Syariah Indonesia - Periode Pandemi COVID-19 dan Pasca Pandemi: Studi Komparasi Machine Learning dan Metode Statistik | PDF",1785905177,20,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":88,"head_meta":90,"extra_data":92,"updated_unix":29},"volatility-of-indonesias-sharia-stock-market-covid-19-pandemic-to-post-pandemic-comparative-study-of-machine-learning-and-statistical-methods","",{"@graph":37,"@context":87},[38,55,70],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,52],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":48},"https://docshare.wps.com/id/document/","Document",2,{"item":50,"name":12,"@type":44,"position":51},"https://docshare.wps.com/id/document/penelitian-laporan/",3,{"item":53,"name":13,"@type":44,"position":54},"https://docshare.wps.com/id/document/volatility-of-indonesias-sharia-stock-market-covid-19-pandemic-to-post-pandemic-comparative-study-of-machine-learning-and-statistical-methods/126460/",4,{"url":53,"name":13,"@type":56,"author":57,"headline":13,"publisher":59,"fileFormat":62,"inLanguage":24,"description":14,"dateModified":63,"datePublished":64,"encodingFormat":62,"isAccessibleForFree":65,"interactionStatistic":66},"DigitalDocument",{"name":9,"@type":58},"Person",{"url":42,"name":60,"@type":61},"DocShare","Organization","application/pdf","2026-08-17","2026-08-05",true,{"@type":67,"interactionType":68,"userInteractionCount":20},"InteractionCounter",{"@type":69},"ViewAction",{"@type":71,"mainEntity":72},"FAQPage",[73,79,83],{"name":74,"@type":75,"acceptedAnswer":76},"Apa tujuan penelitian mengenai volatilitas pasar saham syariah Indonesia?","Question",{"text":77,"@type":78},"Menganalisis dinamika volatilitas indeks saham syariah Indonesia selama pandemi dan pascapandemi, serta membandingkan kinerja model prediksi volatilitas.","Answer",{"name":80,"@type":75,"acceptedAnswer":81},"Data apa yang digunakan untuk memprediksi volatilitas JII dan ISSI?",{"text":82,"@type":78},"Data harga penutupan harian JII dan ISSI ditransformasikan menjadi log return mingguan, lalu volatilitas dihitung menggunakan rolling standar deviasi.",{"name":84,"@type":75,"acceptedAnswer":85},"Bagaimana hasil perbandingan model Machine Learning dan metode statistik?",{"text":86,"@type":78},"Volatilitas meningkat signifikan saat pandemi dan menurun pada pascapandemi. Model Machine Learning lebih baik pada kondisi pasar yang bergejolak, sedangkan metode statistik lebih efektif ketika pasar relatif stabil.","https://schema.org",{"og:url":53,"og:type":89,"og:title":13,"og:site_name":60,"og:description":14},"article",{"robots":91,"canonical":53},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":94},[95,100,104,108,112,116,118,122,126,130,134],{"id":96,"doc_module":4,"doc_module_name":47,"category_name":97,"show_sort_weight":98,"slug":99},55,"Agama & Spiritualitas",60,"religion-spirituality",{"id":101,"doc_module":4,"doc_module_name":47,"category_name":102,"show_sort_weight":98,"slug":103},48,"Cerita & Novel","story-novel",{"id":105,"doc_module":4,"doc_module_name":47,"category_name":106,"show_sort_weight":98,"slug":107},56,"Gaya Hidup","lifestyle",{"id":109,"doc_module":4,"doc_module_name":47,"category_name":110,"show_sort_weight":98,"slug":111},51,"Komik","comic",{"id":113,"doc_module":4,"doc_module_name":47,"category_name":114,"show_sort_weight":98,"slug":115},53,"Layanan Kesehatan","healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":98,"slug":117},"research-report",{"id":119,"doc_module":4,"doc_module_name":47,"category_name":120,"show_sort_weight":98,"slug":121},49,"Sastra","literature",{"id":123,"doc_module":4,"doc_module_name":47,"category_name":124,"show_sort_weight":98,"slug":125},52,"Teknologi","technology",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":128,"show_sort_weight":98,"slug":129},50,"Ujian","exam",{"id":131,"doc_module":4,"doc_module_name":47,"category_name":132,"show_sort_weight":98,"slug":133},57,"Umum","general",{"id":135,"doc_module":4,"doc_module_name":47,"category_name":136,"show_sort_weight":4,"slug":137},181,"Formulir","formulir"]