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All Journal Jurnal Penelitian Pendidikan IPA (JPPIPA) KLOROFIL: Jurnal Ilmu Biologi dan Terapan JOURNAL OF SCIENCE AND SOCIAL RESEARCH AL-ULUM: JURNAL SAINS DAN TEKNOLOGI Jurnal Biogenerasi 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 Journal of Pharmaceutical and Sciences. JME
Sajaratud Dur
Universitas Islam Negeri Sumatera Utara
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing 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.
Selulosa Bakteri Terimpregnasi Nanopartikel Perak dari Sari Pelepah Kelapa Sawit dan Sifat Antimikrobanya Wardatul Husna Irham; Syarifah Yusra; Hari Gunawan; Marzuti Isra; Sajaratud Dur
Jurnal Penelitian Pendidikan IPA Vol 11 No 12 (2025): December
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i12.13390

Abstract

Palm oil frond sap (NPS), rich in fermentable sugars and essential minerals, is a renewable substrate for the production of biocompatible biomaterials. This study aims to review the utilization of  of OPFJ as a culture medium for BC biosynthesis, its functionalization with silver nanoparticles (AgNPs), and the potential of the resulting composite’ for wound dressing applications. The method used was a literature review by collecting the latest and most recent journals, recording and analyzing the results of the utilization of OPFJ with AgNPs. The results showed   that OPFJ-based BC exhibits nanofibrillar morphology, high crystallinity, and good mechanical stability. The incorporation of AgNPs enhances antimicrobial activity against both Gram-positive and Gram-negative bacteria, providing a dual-functional dressing material. Nonetheless, limitations persist in silver release control, cytotoxicity management, and large-scale production. Future studies should focus on pretreatment optimization of OPFJ, green synthesis of AgNPs, and in vivo evaluations to ensure clinical viability.
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.
INDUKSI TUNAS Musa paradisiaca L. MENGGUNAKAN KOMBINASI IBA DAN BAP SERTA AIR KELAPA Nadiatul Firdha; Sajaratud Dur; Irda Nila Selvia
Jurnal Biogenerasi Vol. 11 No. 2 (2026): April - Juni 2026
Publisher : Universitas Cokroaminoto Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30605/qqtxmd98

Abstract

Pisang kepok (Musa paradisiaca L.) menjadi komoditas unggulan Indonesia yang memiliki nilai ekonomi dan gizi tinggi. Namun, perbanyakan bibit secara konvensional seringkali lambat dan rentan terhadap penyakit. Penelitian ini bertujuan untuk mengetahui pengaruh kombinasi zat pengatur tumbuh (ZPT) IBA (Indole Butyric Acid) dan BAP (Benzylaminopurine) serta penambahan air kelapa terhadap induksi tunas pisang kepok secara in vitro. Metode penelitian menggunakan Rancangan Acak Lengkap (RAL) non-faktorial dengan empat perlakuan: A1 (MS + IBA 2 mg/L + BAP 3 mg/L), A2 (MS + IBA 3 mg/L + BAP 2 mg/L), B1 (MS + IBA 2 mg/L + BAP 3 mg/L + Air Kelapa 15%), dan B2 (MS + IBA 3 mg/L + BAP 2 mg/L + Air Kelapa 15%). Hasil penelitian menunjukkan bahwa perlakuan memberikan pengaruh nyata terhadap jumlah tunas, namun berpengaruh tidak nyata terhadap waktu muncul tunas, tinggi tunas, diameter tunas, jumlah daun, dan bobot basah eksplan. Perlakuan B1 merupakan media yang paling optimal untuk menginduksi jumlah tunas terbanyak (1,67 tunas), tinggi tunas tertinggi (3,32 cm), diameter tunas terbesar (1,42 cm), dan jumlah daun terbanyak (2,11 daun). Secara keseluruhan, kombinasi sitokinin yang lebih tinggi (BAP 3 mg/L) dibandingkan auksin (IBA 2 mg/L) didukung oleh penambahan air kelapa 15% memberikan hasil pertumbuhan  lebih stabil dan optimal pada fase induksi tunas pisang kepok.
Pengaruh Konsentrasi dari Gliserol Terhadap Plastik Biodegradable Berbahan Pati dari Kulit Singkong Leni Widiarti; Sajaratud Dur; Aisyah Rafiqah Azla Siregar
Journal of Pharmaceutical and Sciences JPS Volume 8 Nomor 4 (2025)
Publisher : Fakultas Farmasi Universitas Tjut Nyak Dhien

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36490/journal-jps.com.v8i4.1072

Abstract

Indonesia is the second-largest producer of plastic waste in the world, while conventional plastics require a long time to decompose and may generate harmful emissions. Therefore, the development of biodegradable bioplastics has become increasingly important. Abundant cassava peels have potential as a starch source, with glycerol serving as a plasticizer and chitosan as a reinforcing agent. This study aimed to analyze the effect of varying glycerol concentrations (0, 2, 4, 6, and 8 mL) on the functional group characteristics and thermal properties of cassava peel starch–chitosan-based bioplastics. The bioplastics were synthesized by blending starch and chitosan at an 8:2 ratio, followed by the addition of glycerol at different concentrations. Characterization was conducted using Fourier Transform Infrared (FTIR) spectroscopy and Differential Scanning Calorimetry (DSC). FTIR results indicated no formation of new functional groups; however, shifts and broadening of the –OH absorption bands were observed, suggesting physical interactions through hydrogen bonding among starch, chitosan, and glycerol. DSC analysis revealed that glycerol concentration significantly affected the thermal properties of the bioplastics, with the highest melting temperature (Tm) obtained at 6 mL glycerol (160.67 °C) and the lowest at 8 mL glycerol (129.33 °C). The formulation containing 8 mL glycerol exhibited the highest fusion enthalpy (321.73 J/g). These findings indicate that the addition of 6 mL glycerol provides the most optimal plasticization condition with the highest thermal stability, whereas higher glycerol concentrations result in over-plasticization. The optimal formulation shows potential for further development as an environmentally friendly packaging material.
MODEL MATEMATIKA PERKIRAAN PECANDU NARKOTIKA DI BNNP SUMUT DENGAN PROGRAM REHABILITASI MENGGUNAKAN METODE MONTE CARLO Fikri Nur Ardiansyah; Sajaratud Dur; Rima Aprilia
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 7 No. 3 (2024): August 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i3.2135

Abstract

Penyalahgunaan narkoba adalah salah satu masalah kesehatan dan sosial paling serius di dunia, dan menjadi fokus perhatian pemerintah. Meningkatnya kasus penyalahgunaan narkoba berarti jumlah pecandu narkoba di Indonesia terus bertambah. Untuk mengatasi masalah ini, pemerintah memperkenalkan program untuk mencegah peningkatan pecandu narkoba, program rehabilitasi. Model Matematika dengan faktor rehabilitasi merupakan salah satu cara efektif untuk menganalis pecandu dan pengguna narkotika di Sumatera Utara. Model matematika penyebaran pecandu narkotika dari White dan Comikey dengan menambahkan kelas populasi yang berhenti dari pengguna narkotika (R) dan selanjutnya dilakukan penambahan pada setiap kelas populasi sehingga penambahan variabel model berupa kelas populasi rentan yang diberikan program rehabilitasi (Se), kelas populasi penguna narkotika yang diberi program rehabilitasi (Ue) dan kelas populasi berhernti dari pengguna narkotika yang diberikan program rehabilitasi (Re). Rehabilitasi yang dimaksud dapat dilaksanakan dalam bentuk sosialisasi atau penangganan untuk para pencandu dan penyalahgunaan narkotika. Untuk itu diperlukan sistem pendekatan yang ilain, isalah isatunya idengan menggunakan imodel isimulasi dasar metode Monte Carlo adalah melakukan pengujian pada elemen-elemen probalitiasi melalui sampel angka random. Hasilnya perkiraan jumlah penyalahgunaan pada tahun 2019 dan 2020 di Badan Narkotika Nasional Provinsi Sumatera Utara adalah 1638 orang, 1726 orang. Jumlah perkiraan penyalahgunaan narkotika tersebut naik dari jumlah penyalahgunaan narkotika dengan program rehabilitasi pada tahun 2019 yang jumlah penyalahgunaan narkotika 1638 orang. Jumlah penyalahgunaan narkotika dengan program rehabilitasi pada tahun 2019, 2020, 2021 menaik sekitar 5%.
Co-Authors Aisyah Rafiqah Azla Siregar Fajari Husnul Walid Fakhraini Zahra Afifa Fikri Nur Ardiansyah Hari Gunawan Hasni Indah Sari Hasyim Hawari Lubis Hasyim Lubis Hendra Cipta Heni Pujiastuti Irda Nila Selvia Ismail Husein, Ismail Jumianti Ritonga Leni Widiarti Lia Lestari Marzuti Isra Nadiatul Firdha Nurul Aprilla Rizki Nurul Khoiriah Hasibuan Radita Rahma Rakhmawati, Fibri Regina Kuswoyo Rima Aprilia Rina Filia Sari Silvia Harleni Syarifah Yusra WARDATUL HUSNA IRHAM Winda Risfani Nst Winda Yuniar Ambarita