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Variansi : Journal of Statistics and Its Application on Teaching and Research
Published by Universitas Negeri Makassar
ISSN : -     EISSN : 26847590     DOI : https://doi.org/10.35580/variansiunm
Core Subject : Economy, Health, Science, Education,
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Mathematics Public Health
VARIANSI: Journal of Statistics and Its application on Teaching and Research memuat tulisan hasil penelitian dan kajian pustaka (reviews) dalam bidang ilmu dasar ataupun terapan dan pembelajaran dari bidang Statistika dan Aplikasinya dalam pembelajaran dan riset berupa hasil penelitian dan kajian pustaka.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 45 Documents
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Pendekatan persamaan struktural pada model regresi error spasial (Kasus: PDRB Sulawesi Selatan) Muhammad Kasim Aidid; Zulkifli Rais; Muhammad Fahmuddin S
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 3, No 3 (2021)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm26380

Abstract

The spatial autocorrelation model studied in the framework of structural equations is the spatial error regression model. The results of this study are applied to South Sulawesi's Gross Regional Domestic Product (GRDP) data. For parameter estimation using open source software Mx. To implement the spatial error model in SEM, two new sets of weighted spatial variables need to be formed, namely W based on the dependent variable (PW) and ηW based on the independent variable (PW) and ξW based on the independent variable (QW). Since in the case of the latent model, the variables P and Q cannot be observed directly, then ηW and ξW are directly defined by the observation variables (indicators) Y yW and Y xW which are related to each other as Yy and Yx to η and ξ. obtained a model that represents the spatial error in SEM. By using South Sulawesi GRDP data where y represents the per capita GRDP in the Regency/City, x1 and x2 respectively represent the value of the Mining sector and the building sector in the Regency/City. XW1 represents first-order contiguity spatially lagged for trade and XW2 represents first-order contiguity spatially lagged for agriculture. yW denotes spatially lagged first-order contiguity for GRDP. (1−λ)γ0 represents the unit variable coefficient. From the model it can be stated that GRDP (y) is influenced by several sectors in the economy such as mining (x1) and building (x2). In addition, there is a location effect (Spatial Effect) that affects the GRDP in South Sulawesi. Based on the final results obtained, it is known that λ = 0,16 which indicates that there is a dependency on the GRDP data in South Sulawesi in 2008 between one district/city and another district/city based on the spatial correction. Areas that are centers of mining and construction in South Sulawesi are mutually dependent, causing dependence on GRDP data, this can be seen in the positive covariance value between mining lagged, and building lagged, and lagged GRDPKeywords: Effect Spatial, Error Spatial, SEM, GRDP
ANALISIS PELUANG PENYEBARAN COVID-19 MENGGUNAKAN RANTAI MARKOV DI SULAWESI SELATAN M. Nadjib Bustan; Ruliana Ruliana; Muhammad Kasim Aidid
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 3, No 2 (2021)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm25170

Abstract

Virus Corona sudah menyebar ke seluruh negera termasuk salah satunya di Indonesia. Karena transmisi Covid-19 dari manusia ke manusia telah dikonfirmasi dan mobilitas manusia juga merupakan faktor penguat persebaran Covid-19, sehingga diperlukan suatu informasi yaitu data harian Covid-19 yang berguna untuk melihat laju persebaran Covid-19. Oleh karena itu, diperlukan suatu pendekatan untuk menganalisis peluang penyebaran covid-19 di setiap wilayah sehingga pengambilan keputusan menjadi tepat. Pada penelitian ini, dilakukan analisis dengan rantai markov diskrit untuk memprediksi peluang penyebaran Covid-19 pada kabupaten/kota di Sulawesi Selatan. Penelitian ini adalah penelitian yang bersifat kuantitatif dengan menggunakan konsep stokastik. Pada bagian awal dilakukan kajian sumber-sumber pustaka dengan cara mengumpulkan data atau informasi yang berkaitan dengan masalah, mengumpulkan konsep pendukung yang diperlukan dalam menyelesaikan masalah, sehingga didapatkan suatu ide mengenai bahan dasar pengembangan upaya pemecahan masalah.  Hasil penelitian menunjukkan bahwa pada saat pengamatan (28 Agustus 2021) di Sulawesi Selatan (Sulsel), Kota Makassar menjadi daerah dengan peluang penyebaran yang paling tinggi, sedangkan Kabupaten Bantaeng dengan peluang penyebaran terendah. Pada hasil analisis dengan rantai Markov, terlihat bahwa terjadi penurunan peluang infeksi untuk setiap Kabupaten/Kota di Sulawesi Selatan dan cenderung menjadi homogen.Keywords: covid-19, Markov chain, peluang bersyarat
PERBANDINGAN METODE PCA-SVM DAN SVM UNTUK KLASIFIKASI INDEKS KEPUASAN MASYARAKAT TERHADAP LAYANAN PENDIDIKAN DI KABUPATEN JENEPONTO Nur Ikhwana; Muhammad Nusrang; Sudarmin Sudarmin
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 3, No 3 (2021)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm22988

Abstract

Support Vector Machine (SVM) is one of the classification methods used to find the best hyperplane by maximizing the distance between classes. SVM aims to build a model that can predict the given test data. The SVM method can be implemented easily and the testing time is short, but it needs to reduce the computation burden. One way that can be done is to perform feature extraction to get the main characteristics of the data. The method that can be used to extract features is Principal Component Analysis (PCA). PCA is used to reduce the dimensions of data which are generally used in numerical scale data. If the data in the study used categorical data, then the PCA used was Nonlinear PCA. The data used in this study is the Community Satisfaction Survey data in Jeneponto Regency. This study compares the PCA-SVM and SVM methods for the classification of the Jeneponto Regency Community Satisfaction Index. The overall PCA-SVM classification results are better than SVM with 100% accuracy.
Pengelompokan Daerah Penyebaran Demam Berdarah Dengue Alam Dengan Menggunakan Algoritma K-Means Di Kota Makassar Zulkifli Rais; Misveria Villa Waru
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 3, No 2 (2021)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm25657

Abstract

This study proposes the k-means method to map the endemic areas of dengue fever in the city of Makassar. Data were obtained from the health department based on the number of patients affected by dengue hemorrhagic fever (DHF) in every sub-district in Makassar City. The k-means method has mapped the area into 3 groups. These results indicate that group 1, which is the area that has the highest number of DHF sufferers, is Rappocini, Panakukang, and Manggala villages. Furthermore, Tamalate and Biringkanaya villages are members of group 2. And group 3 is an area that has a low number of dengue patients, namely Mamajang, Makassar, Tamalanrea, Mariso, Ujung Pandang, Bontoala, Tallo, Ujung Tanah, Wajo. Keywords: k-means, dengue hemorrhagic fever (DHF)
Analisis Kruskal-Wallis Terhadap Kemampuan Numerik Siswa Andi Quraisy; Wahyuddin Wahyuddin; Nur Hasni
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 3, No 3 (2021)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm29957

Abstract

This study aims to determine the differences in the numerical abilities of students from 4 classes, namely classes A, B, C, and D. The population in this study were students of class VII SMP Muhammadiyah 1 Makassar with a total sample of 57 students. The data collection technique used a numerical ability test instrument, then the data obtained were analyzed using descriptive analysis and Kruskal-Wallis nonparametric analysis. The results of the descriptive analysis obtained that the average value of the numerical abilities of students in grades A, B, C, and D was not much different, namely 76.13; 78.4; 76.57; 77.23. Meanwhile, the results of the Kruskal Wallis analysis showed that there was no significant difference in the grades of A, B, C, and D numerical abilitiesKeywords: Mann-Whitney test, Non-parametric test,  Problem Based Learning Model

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