In Multivariate regression, we need to assess normality assumption simultaneously, not univariately. Univariate normal distribution does not guarantee the occurrence of multivariate normal distribution [1]. So we need to extend the assessment of univariate normal distribution into multivariate methods. One extended method is skewness and kurtosis as proposed by Mardia [2]. In this paper, we introduce the method, present the procedure of this method, and show how to examine normality assumption in multivariate regression study case using this method and expose the use of statistics software to help us in numerical calculation. Received February 20, 2021Revised March 8, 2021Accepted March 10, 2021
The need for medicinal raw materials is increasing, in line with the increasing of traditional medicine utilization. Sangketan (Achyranthes aspera) is one of the potential medicinal plants, considering this plant contains active compounds that are beneficial for health. Triterpenoids are one of the main secondary metabolites of Sangketan. The purpose of this study was to determine the optimal combination of growing media, that could support the extract production from Sangketan. In Sangketan cultivation, given treatment at growing media composition of soil + rice husk charcoal, with comparison 1:1; 1:2 and 2:1. Whereas the fertigation uses goat manure fertilizer, with a concentration of 1 kg per 5 liters of water, dose of 60 ml per plant every two weeks. Sangketan is harvested after 4-5 months, then qualitative analysis is performed of resulting extracts. The research data was applied using simplex lattice design (SLD), to obtain the optimal combination of growing media. Qualitative data of Sangketan extract containing triterpenoid compounds, have been analyzed by chloroform and concentrated H2SO4 reagents, characterized by a reddish brown layer. Sangketan resulting extracts was applied using SLD, obtained the equation Y = 8.94 (Charcoal) + 11.585 (Soil) + 14.26 (Charcoal.Soil). The triterpenoid compound in Sangketan extract was proven using thin layer chromatography, showed marker compounds in form of gray spot under UV light 254 nm at Rf value 0.65.
The linear regression model is employed when it is identified a linear relationship between the dependent and independent variables. In some cases, the relationship between the two variables does not generate a linear line, that is, there is a change point at a certain point. Therefore, themaximum likelihood estimator for the linear regression does not produce an accurate model. The objective of this study is to presents the performance of simple linear and segmented linear regression models in which there are breakpoints in the data. The modeling is performed onthe data of depth and sea temperature. The model results display that the segmented linear regression is better in modeling data which contain changing points than the classical one.Received September 1, 2021Revised November 2, 2021Accepted November 11, 2021
Pemanfaatan data sebagai alat untuk memahami kondisi lingkungan dan kesehatan di wilayah merupakan hal yang harus dikembangkan di era informasi saat ini. Pengetahuan mengenai pengolahan data juga perlu dikembangkan oleh semua kalangan. Sebagai salah satu sekolah negeri yang terletak di Mojolaban, Sukoharjo, guru dan siswa SMPN 1 Mojolaban merupakan bagian dari masyarakat yang memerlukan pengetahuan tentang analisis dan visualisasi data. Profil kesehatan Kabupaten Sukoharjo yang diterbitkan oleh Dinas Kesehatan merupakan salah satu sumber informasi kesehatan yang dari tahun ke tahun dapat diakses oleh publik. Visualisasi data merupakan salah satu metode penyampaian informasi yang dipelajari dalam statistika. Pelatihan Excel yang diberikan bertujuan untuk memberikan pemahaman terkait penerapan metode statistika dengan Excel serta visualisasinya agar masyarakat dapat lebih memahami tentang kondisi kesehatan di wilayah Kabupaten Sukoharjo. Materi yang dibahas meliputi pengorganisasian data, statistik deskriptif, analisis regresi, pivot, pengenalan chart dan pembuatan dasbor. Hasil dari pelatihan yang diberikan, peserta pelatihan mampu membuat dasbor berisikan diagram yang menampilkan kondisi kesehatan dasar di Sukoharjo.
Kemampuan mengolah data menjadi kebutuhan di masa kini, apalagi dengan banyaknya data yang tersedia yang dapat diakses secara bebas. Statistika dapat digunakan untuk membantu masyarakat dalam menjelaskan dan memahami gambaran tentang kejadian bencana alam. Karanganyar, yang terletak di Provinsi Jawa Tengah, merupakan salah satu kabupaten di Indonesia yang rawan bencana alam. Oleh karena itu, diperlukan visualisasi data sebagai upaya untuk memberikan pemahaman kepada masyarakat tentang bencana alam yang terjadi di wilayah Kabupaten Karanganyar. Pemetaan bencana alam dengan Geoda dapat memberikan informasi kondisi kecamatan-kecamatan di Karanganyar yang rawan bencana alam. Untuk menyusun peta, diperlukan data bencana alam serta file peta wilayah. Setelah program Geoda terinstal, peta dapat disusun melalui menu toolbar, mengurutkan kolom kode kabupaten, create project file, dan map. Peta spasial menunjukkan bahwa tanah longsor sering terjadi di wilayah Kabupaten Karanganyar bagian timur yang berbatasan dengan Kabupaten Magetan di Jawa Timur, kebakaran di bagian tengah, dan angin ribut di bagian utara.
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