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All Journal Jurnal Dedikasi ARRUS Journal of Mathematics and Applied Science VARIANSI: Journal of Statistics and Its Application on Teaching and Research Journal of Mathematics, Computation and Statistics (JMATHCOS)
Muhammad Kasim Aidid
Universitas Negeri Makassar
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Mathematics Physics Other

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Manajemen Referensi dengan Aplikasi Zotero Muhammad Kasim Aidid; M. Nadjib Bustan; Ruliana Ruliana
DEDIKASI Vol 22, No 2 (2020): Jurnal Dedikasi
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/dedikasi.v22i2.16120

Abstract

Based on the situation analysis, a Community Partnership Program (PKM) activity is proposed to train the use of reference management software for teachers in which SMA Negeri 4 Pinrang Regency is the partner. The identified problems are: (1) Lack of skills in using reference manager software, (2) Zotero as open source software is unknown, (3) The need for the ability to use reference manager software that can be applied in writing scientific papers. The material is presented through zoom meetings in plenary and in groups according to the schedule. In the plenary presentation of the material, material on basic concepts in research and writing of scientific papers was presented then continued with the provision of material on the use of Zotero in writing scientific articles. Some of the requirements to become a participant are: (1) having an interest in learning the basic concepts of reference management, (2) having never attended a similar training. (3) must attend all training activities. From the PKM activities that have been carried out as well as the team's internal survey, it can be concluded that in the implementation of this activity: (1) Participants become literate and skilled in operating the Zotero software, (2) The Zotero menu is well known to PKM participants, (3) Participants have the ability to use Zotero in writing scientific articles.
APPLICATION OF MULTIVARIATE ADAPTIVE REGRESSION SPLINES (MARS) TO MODEL THE FACTORS AFFECTING THE PERCENTAGE OF POOR POPULATION IN INDONESIA Nur Shanty; Ruliana; Muhammad Kasim Aidid
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 7 No. 03 (2025)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm518

Abstract

Poverty is one of the social and economic problems that Indonesia continues to face today. The Multivariate Adaptive Regression Spline (MARS) is a nonparametric regression model that estimates the functional relationship between the response variable and predictor variables when the relationship form is unknown. This study aims to estimate the parameters of the Multivariate Adaptive Regression Spline (MARS) method for the percentage of poor population in Indonesia and to identify the factors that significantly affect the percentage of poor population. The results of this study found that the best model was obtained with a combination of BF = 21, MI = 1, and MO = 3, with GCV = 0,3102717. Based on the MARS model, the variables that significantly affect the percentage of the poor population are the percentage of formal workers (x3), percentage of households with access to proper sanitation (x4), and Gini Ratio (x7) with a coefficient of determination (????²) of 81,44%.
Implementation of Support Vector Regression (SVR) and Double Exponential Smoothing (DES) for Forecasting BRI Stock Prices Sitti Masyitah Meliyana; Muhammad Kasim Aidid; Amaliyah Rahmadhani
ARRUS Journal of Mathematics and Applied Science Vol. 5 No. 2 (2025)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience4282

Abstract

This study aims to forecast the closing stock prices of BRI using Support Vector Regression (SVR) and Double Exponential Smoothing (DES) methods. The data used in this research is secondary data obtained from the Yahoo Finance website, covering the period from January 2020 to November 2023. The analytical steps using the SVR method involve selecting the optimal model by applying Grid Search Optimization to various kernels (linear, polynomial, radial, and sigmoid). The best-performing model was found to be the radial kernel with parameters ? = 0.1, C = 100, and ? = 10, yielding a Mean Absolute Percentage Error (MAPE) of 0.2431%, which was then used for forecasting. For the DES method, the steps involved parameter determination and minimizing the MAPE value, followed by smoothing calculations and forecasting. The optimal parameters obtained were ? = 0.89 and ? = 0.01, resulting in a MAPE value of 1.4832%. Based on the comparison of MAPE values, it can be concluded that the SVR method with a radial kernel (? = 0.1, C = 100, ? = 10) provides the most accurate forecasts for BRI closing stock prices, with the lowest MAPE of 0.2431%.
Penerapan Metode Generalized Space Time Autoregressive (GSTAR) Untuk Memprediksi Sebaran Covid-19 di Pulau Jawa Maria Dominggo Wea; aswi; Muhammad Kasim Aidid
Journal of Mathematics, Computations and Statistics Vol. 7 No. 1 (2024): Volume 07 Nomor 01 (April 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i1.1944

Abstract

Virus Corona merupakan keluarga besar virus (antara hewan dan manusia) yang ditularkan secara zoonik dan menimbulkan gejala ringan hingga berat. Kasus COVID-19 terus bertambah secara global dan berfluktuasi, termasuk di Indonesia dan sebaran kasus infeksi virus terbesar di Pulau Jawa. Penelitian ini bertujuan untuk memprediksi sebaran kasus COVID-19 di Pulau Jawa dengan data spasial yaitu 6 provinsi sehingga menggunakan model ruang waktu yaitu Model Generalized Space Time Autoregressive (GSTAR). Matriks pembobot yang digunakan adalah invers jarak dan queen contiguity. Tahapan pembentukan model terdiri dari uji stasioneritas data, penentuan urutan ruang-waktu, penggunaan kedua matriks pembobot, estimasi parameter dengan Ordinary Least Square, uji kesesuaian model dengan uji asumsi white noise dan uji asumsi normalitas, perhitungan Root Mean Square Error (RMSE), pemilihan model terbaik dengan matriks pembobotan queen contiguity yang menghasilkan nilai RMSE terkecil, peramalan berdasarkan model GSTAR terbaik, dan pemetaan total hasil peramalan. Model GSTAR terbaik yang dihasilkan adalah GSTAR (1;1) I(1) dengan menggunakan matriks pembobotan queen contiguity dengan nilai RMSE terkecil. Hasil peramalan dan pemetaan berdasarkan hasil ramalan total kasus COVID-19 di Pulau Jawa pada tanggal 1 April 2022 – 7 April 2022 menunjukkan bahwa hampir semua provinsi mendekati nilai pada data aktual dilihat dari plot dan peta sebaran.
Co-Authors Amaliyah Rahmadhani Aswi, Aswi M. Nadjib Bustan Maria Dominggo Wea Nur Shanty Ruliana Sitti Masyitah Meliyana R.