Receivable Dan Inventory Financing Sebagai Determinan Profitabilitas: Analisis Laporan Keuangan PT. Bank Syariah Indonesia (BSI) KCP Krakatau TBK Tahun 2020-2024
Keywords:
Pembiayaan, Pembiayaan Utang, Pembiayaan Persediaan, Laporan Keuangan, ProfitabilitasAbstract
This study's goal is to investigate to how financing and inventory financing affect Bank Syariah Indonesia's (BSI) Tbk's profitability. The significance of finance as the primary revenue stream for Islamic banks serves as the study's backdrop. Data from BSI's financial statements for the years 2020–2024 are used in this quantitative research. The research results show that profitability is positively and significantly influenced by the receivables financing variable. Profitability is also positively and significantly influenced by the inventory financing variable. In general, profitability is influenced by both inventory financing and receivables financing.
References
[1] Sitepu, A. I. B., & Tanjung, D. Y. H. (2020). Rancang Bangun Aplikasi Pemesanan dan Penjualan Berbasis Web dan Android pada Toko YT. Wall Interior. Jurnal Mahasiswa Fakultas Teknik dan Ilmu Komputer, 1(1), 816-828.
[2] Nasution, R. S., Verina, W., & Tanjung, M. R. (2020). Rancang Bangun Aplikasi Pemilihan Pegawai Berprestasi Dengan Metode Profile Matching Berbasis Android Pada BPJS Ketenagakerjaan. Jurnal Mahasiswa Fakultas Teknik dan Ilmu Komputer, 1(1), 666-680.
[3] Marsudi, D. A., & Rosnelly, R. (2020). Implementasi Linear Congruent Method Dalam Permainan Kuis Musik Berbasis Android. Jurnal Mahasiswa Fakultas Teknik dan Ilmu Komputer, 1(1), 857-869.
[4] Manullang, A. S., Puspasari, R., & Verina, W. (2020). Penyandian Database Menggunakan Metode Base64 Dan Rot13. Jurnal Mahasiswa Fakultas Teknik dan Ilmu Komputer, 1(1), 283-292.
[5] Veropoulos, K., Campbell, C., & Learmonth, G. (1998). Image processing and neural computing used in the diagnosis of tuberculosis. IEE Colloquium on Intelligent Methods in Healthcare and Medical Applications (Digest No. 1998/514), 8/1-8/4.
[6] Forero, M. G., Sroubek, F., & Cristobal, G. (2004). Identification of tuberculosis bacteria based on shape and color. Real-Time Imaging, 10, 251-262.
[7] Costa, M., Filho, F. C., Sena, J., Salem, J., & de Lima, M. (2008). Automatic identification of mycobacterium tuberculosis with conventional light microscopy. Proc. 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2008, 382-385
[8] Wang, W., Qin, Z., Rong, S., Rong, X., & Song, Y. (2008). A kind of method for selection of optimum threshold for segmentation of digital color plane image. 9th International Conference on Computer-Aided Industrial Design and Conceptual Design, 959 – 961.
[9] Forero, M. G., Cristobal, G., & Borrego, J. A. (2003). Automatic identification techniques of tuberculosis bacteria. SPIE Proceedings of the Applications of Digital Image Processing XXVI, 5203, 71-81.
[10] Veropoulos, K., Learmonth, G., Campbell, C., Knight, B., & Simpson, J. (1999). Automated identification of tubercle bacilli in sputum: A preliminary investigation. Analytical and Quantitative Cytology and Histology, 21(4), 277–281
[11] Wilkinson, M. (1996). Rapid automatic segmentation of fluorescent and phase-contrast images of bacteria. Fluorescence Microscopy And Fluorescent Probes. New York, NY: Plenum Press.
