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All Journal International Journal of Evaluation and Research in Education (IJERE) Electronic Journal of Graph Theory and Applications (EJGTA) Jurnal Matematika & Sains AKSIOMA JURNAL PENDIDIKAN MATEMATIKA Jurnal Elemen Indonesian Journal of Applied Statistics Journal of Mathematics and Mathematics Education (JMME) JTAM (Jurnal Teori dan Aplikasi Matematika) JCES (Journal of Character Education Society) Indonesian Journal of Combinatorics Budapest International Research and Critics in Linguistics and Education Journal (Birle Journal) International Journal of Science and Society (IJSOC)
Diari Indriati
Universitas Sebelas Maret, Surakarta, Indonesia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Neuroscience Nursing Physics Public Health Social Sciences Transportation Other

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Journal : Indonesian Journal of Applied Statistics

 1 
Penerapan Generalized Cross Validation dalam Model Regresi Smoothing Spline pada Produksi Ubi Jalar di Jawa Tengah Trionika Dian Wahyuningsih; Sri Sulistijowati Handajani; Diari Indriati
Indonesian Journal of Applied Statistics Vol 1, No 2 (2018)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v1i2.26250

Abstract

Sweet Potato is a useful plant as a source carbohydrates, proteins, and is used as an animal feed and ingredient industry. Based on data from the Badan Pusat Statistik (BPS), the production fluctuations of the sweet potato in Central Java from year to year are caused by many factor. The production of sweet potato and the factors that affected it if they are described into a pattern of relationships then they do not have a specific pattern and do not follow a particular distribution, such as harvest area, the allocation of subsidized urea fertilizer, and the allocation of subsidized organic fertilizer. Therefore, the production model of sweet potato could be applied into nonparametric regression model. The approach used for nonparametric regression in this study is smoothing spline regression. The method used in regression smoothing spline is generalized cross validation (GCV). The value of the smoothing parameter (λ) is chosen from the minimum GCV value. The results of the study show that the optimum λ value for the factors of harvest area, urea fertilizer and organic fertilizer are 5.57905e-14, 2.51426e-06, and 3.227217e-13 that they result a minimum GCV i.e 2.29272e-21, 1.38391e-16, and 3.46813e-24. Keywords: Sweet potato; nonparametric; smoothing spline; generalized cross validation.
Co-Authors Adinata, Yuda candri Ainun Rahma Firdausy Akrom, Akrom Alghofari, Abdul Rouf Bowo Winarno Budiyono Budiyono Budiyono Budiyono Dhani Nur Hendrayanto Eka Aprilia Enyta Ramadisae Putri Hidayat, Noor Imam Sujadi Indah E. Wijayanti Irfan Setiawan Isnaini Rosyida Isnaini Rosyida, Isnaini Kiki A. Sugeng Krida Singgih Kuncoro Martini, Titin Sri Monika Agnes Henny Kinanti Muhammad Bilal Nugroho Arif Sudibyo Purjiyo Purjiyo Putranto Hadi Utomo Riyadi Riyadi S Slamin Sri Sulistijowati Handajani Sujadi, Imam Tri Atmojo Kusmayadi Trionika Dian Wahyuningsih Triyanto Triyanto Vika Yugi Kurniawan W. Widodo Wijayanti, Dian Eka