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All Journal JAM : Jurnal Aplikasi Manajemen Jurnal Teknologi Informasi dan Ilmu Komputer Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Performance Revenue: Jurnal Manajemen Bisnis Islam JOURNAL OF RESEARCH IN MANAGEMENT Abdimas Galuh : Jurnal Pengabdian Kepada Masyarakat Terbuka Journal of Economics and Business Jurnal Aplikasi Bisnis dan Komputer Malcom: Indonesian Journal of Machine Learning and Computer Science The Eastasouth Management and Business J-Icon : Jurnal Komputer dan Informatika JURNAL KARYA ILMIAH MULTIDISIPLIN Management Studies and Business Journal The Eastasouth Journal of Social Science and Humanities
Anggraeni, Ade Irma
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Nursing Public Health Social Sciences Other

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Journal : JURNAL KARYA ILMIAH MULTIDISIPLIN

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Pengembangan Aplikasi Simulasi Investasi Reksadana Dengan Algoritma Machine Learning Prophet Halimah, Siti; Qur’ania, Arie; Anggraeni, Irma; Rama Putra, Gustian
Jurnal Karya Ilmiah Multidisiplin (JURKIM) Vol. 4 No. 3 (2024): Jurnal Karya Ilmiah Multidisiplin (Jurkim)
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/jurkim.v4i3.23550

Abstract

Investment is a crucial foundation in financial management that opens opportunities to achieve long-term financial goals. One mutual fund investment platform at a PT is innovating to create a platform tailored to the needs of Generation Z users. However, the platform is currently still under improvement and/or renewal due to functional deficiencies such as the frontend and backend display, as well as the lack of an investment simulation feature that allows investors to predict mutual fund investments. This research focuses on adding an investment simulation feature using a Machine Learning algorithm that can automate the detection of trends and seasonality in mutual fund products. The method used in the website development is the Agile method in the System Development Life Cycle (SDLC). In conducting this research, an analysis of the platform's weaknesses and deficiencies was carried out to compare the website platform to be developed with another platform. Based on the analysis that has been carried out, the development of the platform's functionality and the addition of features were made, namely, updating the latest display on each page and the investment simulation feature. This research uses the PHP programming language and the Laravel framework as well as Firebase as its database. The programming implementation results in a platform that can predict mutual fund product simulations that can be used by investors, thus easily attracting Generation Z to invest in the website platform.
Co-Authors Adi, Pramono Hari Alisa Tri Nawarini, Alisa Tri Anisa, Ayi Arie Qur’ania Asep Denih Aziezah, Aiz Nur Candra Nuraini, Candra Choerunnisa, Mita Daing Nasir Ibrahim Darajat, Muhamad Alif Ibnu Delia, Dini Dewandaru, Wicky Fadilah, Asep Muhamad Fajriandini, Nurul Bintang Farohah, Nisa Lailatul fatimah Fatimah Fiqri, Fahmi Noor Hafizh, Naufal Fadhil HAKIM, WIDYATAMA LUKMAN NUR Hamzah, Rizki Maulana Haryadi - ISKANDAR, GILANG BAGASKARA Jadmiko, Purbo Mei Rani Amalia Muhammad Zakiy Musthafa, Burhanuddin Muzaki, Ilzam Najmudin Nufitri, Titi Nuraini, Sella NURFITRI, TITI Putri, Cindy Monica Salsabila Qur’ania, Arie Rama Putra, Gustian Ratno Purnomo Runanto Saputri, Cita Suci Setiabudi, Shayla Azmi Shopiana, Nasywa Siti Halimah Sudarto Sudarto Sufiatul Maryana Susanto, Is SWANDARUJATI, MAXIMILIAN SYADINA, KHANSA PUTRI Syafitri, Tiara Septiana Triyadi, Iqbal wandarujati, Maximilian Wijaya, Rohmatullah Sony