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All Journal KLOROFIL: Jurnal Ilmu Biologi dan Terapan AL-ULUM: JURNAL SAINS DAN TEKNOLOGI G-Tech : Jurnal Teknologi Terapan Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika KLOROFIL: Jurnal Ilmu Biologi dan Terapan International Journal of Basic and Applied Science Journal of Mathematics and Scientific Computing With Applications Innovative: Journal Of Social Science Research Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika SATIN - Sains dan Teknologi Informasi JME
Sajaratud Dur
Universitas Islam Negeri Sumatera Utara
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Immunology & microbiology Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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Penilaian Prestasi Kerja Karyawan PT. Perkebunan Nusantara IV Medan Dengan Metode Simple Additive Weighting (SAW) Winda Risfani Nst; Sajaratud Dur; Hendra Cipta
Innovative: Journal Of Social Science Research Vol. 3 No. 4 (2023): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v3i4.4185

Abstract

Penilaian prestasi kerja karyawan adalah satu dari berbagai peranan penting untuk perusahaan. Ini dilaksanakan untuk melakukan evaluasi, motivasi dan meningkatkan hasil kerja karyawan, dimana kinerja tersebut digunakan untuk menentukan karyawan yang berprestasi. Penelitian ini menggunakan 5 kriteria yaitu komitmen, Integrasi, professional, inovatif, dan disiplin. Simple Additive Weighting (SAW) diterapkan dalam menetapkan nilai bobot masing-masing atribut, diteruskan dengan membuat rangking untuk menyeleksi setiap alternative yang diberikan. Metode ini bisa memudahkan mengambil keputusan guna memperoleh nilai paling besar yang menjadi alternatif terbaik. Penelitian ini dilaksanakan pada 37 responden. Berdasarkan hasil penelitian menunjukan bahwa ini dapat memberi alternatif keputusan terbaik dalam pengambilan keputusan untuk menilai kinerja karyawan.
PEMODELAN GEOGRAPHICALLY WEIGHTED REGRESSION TERHADAP FAKTOR-FAKTOR YANG MEMPENGARUHI ANGKA PUTUS SEKOLAH MENENGAH KEJURUAN DI PROVINSI SUMATERA UTARA Sajaratud Dur; Hendra Cipta; Nurul Aprilla Rizki
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 3 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i3.422

Abstract

The proportion of kids who are of school age but are no longer enrolled or did not complete their education at a certain level is known as the dropout rate. The majority of dropouts are from vocational high schools. One of the reasons why students leave school is because the causes of dropouts are not accurately identified. This issue persists in the field of education. One issue with geographic heterogeneity is dropout. the development of geographical effects or spatial heterogeneity as a result of variations in each region's features and the connection between their distances. Geographically Weighted Regression (GWR) is one technique for analyzing spatially heterogeneous issues. The fixed kernel's weighting function and the adaptive kernel's weighting function in this research are both gaussian. The goal of this research was to choose the most appropriate model to utilize for the GWR model on the variables influencing the dropout rate for vocational high schools in North Sumatra Province. For each North Sumatra district or city, a distinct model is generated by this study. As compared to the multiple linear regression model with Ordinary Least Square (OLS) and the GWR model with fixed kernel weighting function gaussian, the GWR model with the adaptive weighting function of the gaussian kernel is the best model used to model the factors that influence the dropout rate for vocational high schools in North Sumatra Province. This is because it has the smallest AIC value of 321.7397 and the highest of 0.9756.
MULTIVARIATE SINGULAR SPECTRUM ANALYSIS MODEL IN FORECASTING RED CHILI AND CAYENNE PEPPER PRICES Radita Rahma; Rina Filia Sari; Sajaratud Dur
AL ULUM: JURNAL SAINS DAN TEKNOLOGI Vol 10, No 1 (2024)
Publisher : UPT Publication and Journal Management, Islamic University of Kalimantan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/jst.v10i1.14281

Abstract

North Sumatra is one of the provinces that contributes the most prominent agricultural commodities of red chilies and cayenne peppers in Indonesia. This study aims to determine the outcomes of price forecasts for cayenne and red chilies in the province of North Sumatra. The method used is multivariate singular spectrum analysis. Results were grouped into six groups based on 12 eigenvectors with a forecast length of 9 monthly periods. Further, the level of accuracy was obtained from MAPE for each variable, with the highest MAPE being 30% for the curly red chili, 27.55% for the big red chili, and the lowest at 23.44% for mixed cayenne pepper. So, the price forecast for red chilies and cayenne peppers in North Sumatra Province for October 2023 to June 2024 using the Multivariate Singular Spectrum Analysis model is included in the forecast category with reasonable capabilities.
ANALISIS DIAGNOSTIK VARIABEL CUACA UNTUK ESTIMASI POLA CURAH HUJAN DI MEDAN MENGGUNAKAN MODEL BAYESIAN VECTOR AUTOREGRESSIVE Winda Yuniar Ambarita; Sajaratud Dur; Silvia Harleni
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 3 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i3.470

Abstract

The territory of Indonesia is located in a strategic position in the tropics. Indonesia is in a position where the equator passes, making it vulnerable to changes in weather and climate. Big cities are increasingly facing many global challenges, so that the effects of climate change are causing urban areas to become more vulnerable to disasters. The city of Medan is one of the big cities that has been recognized as having different characteristics from the surrounding climate, which still has quite a lot of natural elements. Various community activities in Medan City can change the composition of the atmosphere which causes changes in the characteristics of the microclimate which will affect the weather and climate. Weather and climate have a dynamic relationship with other weather elements such as air humidity, air temperature and rainfall. Weather and climate patterns often do not match the pattern they should and are difficult to predict. The main elements of weather are temperature and rainfall, knowing the temperature and rainfall of an area can be used as material to describe the weather in that area. In expressing rainfall in an area, the relationship between air humidity, air temperature and wind direction and speed is very influential. Knowing the pattern of rainfall is very important to do in several activities. So that a diagnostic analysis of weather variables is needed to estimate rainfall patterns in the city of Medan using the bayesian vector autoregressive (BVAR) model. The estimation results using the Bayesian Vector Autoregressive (BVAR) model for Medan City found that the highest rainfall occurred in September at 571.87 mm and the lowest occurred in January at 54.59 mm with a method accuracy rate of 4.75% which indicates that the use of the BVAR method in estimation is very accurate
MULTIVARIATE SINGULAR SPECTRUM ANALYSIS MODEL IN FORECASTING RED CHILI AND CAYENNE PEPPER PRICES Radita Rahma; Rina Filia Sari; Sajaratud Dur
AL ULUM: JURNAL SAINS DAN TEKNOLOGI Vol 10, No 1 (2024)
Publisher : UPT Publication and Journal Management, Islamic University of Kalimantan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/jst.v10i1.14281

Abstract

North Sumatra is one of the provinces that contributes the most prominent agricultural commodities of red chilies and cayenne peppers in Indonesia. This study aims to determine the outcomes of price forecasts for cayenne and red chilies in the province of North Sumatra. The method used is multivariate singular spectrum analysis. Results were grouped into six groups based on 12 eigenvectors with a forecast length of 9 monthly periods. Further, the level of accuracy was obtained from MAPE for each variable, with the highest MAPE being 30% for the curly red chili, 27.55% for the big red chili, and the lowest at 23.44% for mixed cayenne pepper. So, the price forecast for red chilies and cayenne peppers in North Sumatra Province for October 2023 to June 2024 using the Multivariate Singular Spectrum Analysis model is included in the forecast category with reasonable capabilities.
Co-Authors Fajari Husnul Walid Fakhraini Zahra Afifa Hasni Indah Sari Hasyim Hawari Lubis Hasyim Lubis Hendra Cipta Heni Pujiastuti Ismail Husein, Ismail Jumianti Ritonga Leni Widiarti Lia Lestari Nurul Aprilla Rizki Nurul Khoiriah Hasibuan Radita Rahma Rakhmawati, Fibri Regina Kuswoyo Rima Aprilia Rina Filia Sari Silvia Harleni Winda Risfani Nst Winda Yuniar Ambarita