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Geographically Weighted Spline Nonparametric Regression dengan Fungsi Pembobot Bisquare dan Gaussian Pada Tingkat Pengangguran Terbuka Di Pulau Kalimantan Ilmi, Hillidatul; Sifriyani; Prangga, Surya
J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 14 No 2 (2021): Jurnal Ilmiah Teori dan Aplikasi Statistika
Publisher : Fakultas Sains dan Teknologi Univ. PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/jstat.vol14.no2.a4470

Abstract

Geographically weighted spline nonparametric regression merupakan pengembangan regresi nonparametrik untuk data spasial dengan estimator parameter bersifat lokal setiap lokasi pengamatan yang diaplikasikan pada kasus tingkat pengangguran terbuka. Tingkat pengangguran terbuka menjadi alat ukur kualitas kesejahteraan di suatu wilayah yang mengindikasikan besarnya persentase penduduk usia kerja yang aktif secara ekonomi. Tujuan penelitian ini yaitu untuk mengidentifikasi faktor-faktor yang mempengaruhi tingkat pengangguran terbuka 56 Kabupaten/Kota di Kalimantan. Metode yang digunakan adalah geographically weighted spline nonparametric regression dengan pembobot fungsi kernel eksponensial. Model terbaik geographically weighted spline nonparametric regression dengan pembobot fungsi kernel eksponensial pada orde 1 titik knot 1 dengan nilai R-Square sebesar 86,410 persen, nilai AIC sebesar 12,152, nilai RMSE sebesar 0,584 serta nilai CV terkecil adalah fungsi kernel bisquare sebesar 77,175. Adapun faktor-faktor yang berpengaruh signifikan terhadap tingkat pengangguran terbuka yaitu tingkat partisipan angkatan kerja, jumlah penduduk, indeks pembangunan manusia, harapan lama sekolah dan upah minimum.
Analysis Of The Effect Of Net Profit, Operational Cash Flow, Free Cash Flow, Previous Year Cash Dividends On Cash Dividends In The Indonesia Stock Fatia Fatimah; Sifriyani; Deni sunaryo; Etty Puji lestari
International Journal of Science, Technology & Management Vol. 3 No. 1 (2022): January 2022
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v3i1.450

Abstract

This study aims to determine the analysis of the effect of net income, operating cash flow, free cash flow, cash dividends in the previous year, on cash dividends. This study uses a food and beverage sub-sector research design. The research population amounted to 18 companies for 5 years from 2014-2018 and were picked up by 7 companies in a row to publish their financial statements. The method used in this data analysis using multiple linear regression analysis. Based on the results of the study, it can be concluded that: net income has no effect on cash dividends, operating cash flow has no effect on cash dividends, free cash flow has no effect on cash dividends, previous year's cash dividends have an effect on cash dividends.recommendations The company should pay attention to the cash dividend payments in previous years as an independent variable that affects the current year's cash dividend. Because the company will be attractive to shareholders whose preferences are related to dividend payout and stability. Investors want a stable dividend as a source of income embedded in shares that are paid the same amount of dividends every period. For further researchers, it is better to add the number of samples in the observation period of 6 years or 7 years, adding other variables such as Analyzing the relationship between Net profit, Operating Cash Flow with cash dividends, or Effect of accounting profit, cash profit, Free Cash Flow, Operating Cash Flow, leverage and current ratio to cash dividend. and can expand the research sample, not only to manufacturing companies but to more than one type of company.