PENGARUH PENGGUNAAN MODEL PEMBELAJARAN KOOPERATIF TIPE JIGSAW TERHADAP HASIL BELAJAR MAHASISWA

Abstrak:            Tujuan penelitian ini adalah untuk mengetahui pengaruh penggunaan model pembelajaran kooperatif tipe jigsaw terhadap hasil belajar aljabar linier mahasiswa. Adapun populasi dalam penelitian ini adalah seluruh mahasiswa semester III Program studi Fisika, Fakultas Sains dan Teknologi,  Universitas Islam Negeri Sumatera Utara. Sedangkan sampel dalam penelitian  ini adalah mahasiswa Fis 1 semester III yang berjumlah 38 mahasiswa. Penelitian ini menggunakan metode experimental design dengan jenis pretest dan posttest one group design. Penelitian ini mengambil desain eksperimen yang hanya melibatkan satu kelompok tanpa kelompok pembanding. Dari hasil penelitian diperoleh bahwa   >  yaitu 55,53 > 4,11 maka persamaan garis regresi tersebut menunjukkan signifikan dan dapat disimpulkan bahwa terdapat terdapat pengaruh model pembelajaran koperatif tipe jigsaw  terhadap hasil belajar aljabar linier mahasiswa semester III Program studi Fisika, Fakultas Sains dan Teknologi,  Universitas Islam Negeri Sumatera Utara. Kata Kunci:Model Pembelajaran Kooperatif Tipe Jigsaw, Hasil Belajar, Aljabar Linier Abstract:The purpose of this study was to determine the effect of using the type of jigsaw cooperative learning model on student linear algebra learning outcomes. The population in this study were all third semester students of Physics Study Program, Faculty of Science and Technology, State Islamic University of North Sumatra. While the sample in this study were 38 students of the third semester of Fiscal 1. This study used experimental design with the type of pretest and posttest one group design. This study took an experimental design involving only one group without a comparison group. From the results of the study, it was found Fcount > Ftable that 55.53> 4.11, the regression line equation shows significant and it can be concluded that there is an effect of the jigsaw cooperative learning model on the learning outcomes of the third semester students of the Physics Study Program, Faculty of Science and Technology, State Islamic University of North Sumatera. Keywords:Jigsaw Type Cooperative Learning Model, Learning Outcomes, Linear Algebr

Penggunaan Metode Classification Analysis Regression Trees dan Iterative Dichotomizer 3 Dalam Mengklasifikasikan Pasien Hipertensi Di Rumah Sakit Umum Daerah Dr. Pirngadi KotaMedan

Abstract:  Hypertension is a deadly disease wihtout any symptoms. The high cases of hypertension in Indonesian poses a challenge for health development in Indonesia because treating people with hypertension takes a long time and costs a lot. To find out the factors that influence hypertensive patients and reduce the death rate, an intelligent system is needed to classify hypertensive patients early. The methods used for Classification Analysis Regression Trees and Iterative Dechotomizer 3. The results of this study show that the Classification Analysis Regression Trees method produces an accuracy of 93,75%. Meanwhile, the Iterative Dechotomizer 3 method produces a low accuracy of 87,5%. So the Classification Analysis Regression Trees method is better at classifying hypertensive patients than the Iterative Dichotomizer 3 method. Variables that effect it are produced by the classification analysis regression trees  method namely diastolic blood pressure and iterative dichotomizer 3 namely heredity as parent node.Abstrak: Hipertensi merupakan salah satu penyakit yang mematikan tanpa disertai gejala. Tingginya kasus hipertensi di Indonesia menyebabkan tantangan bagi pembangunan kesehatan di Indonesia karena perawatan penderita hipertensi membutuhkan waktu yang lama dan biaya yang tidak sedikit. Untuk mengetahui faktor yang mempengaruhi pasien hipertensi serta mengurangi angka kematian diperlukan sistem cerdas untuk mengklasifikasikan pasien hipertensi secara dini. Metode yang digunakan untuk pengklasifikasian yaitu Classification Analysis Regression Trees dan Iterative Dichotomizer 3. Adapun hasil dari penelitian ini diperoleh bahwa metode Classification Analysis Regression Trees menghasilkan akurasi sebesar 93,75%. Sedangkan metode Iterative Dichotomizer 3 menghasilkan akurasi yang rendah yaitu 87,5%. Sehingga Metode Classification Analysis Regression Trees lebih baik dalam mengklasifikasikan pasien hipertensi dibandingkan metode Iterative Dichotomizer 3. Variabel yang mempengaruhinya yang dihasilkan oleh metode Classification Analysis Regression Trees yaitu tekanan darah diastolik dan Iterative Dichotomizer 3 yaitu Keturunan sebagai parent node.                

SISTEM PENDUKUNG KEPUTUSAN UNTUK SELEKSI KARYAWAN BARU DENGAN MENGGUNAKAN METODE FUZZY TSUKAMOTO

In running an agency/company, competent employees are one of the keys to achieving a company goal. The role of the decision support system will help staffing to achieve the objectives of the selection process for new prospective employees without compromising the criteria set by the company. The purpose of this study was to determine the application of the Tsukamoto fuzzy method in the process of selecting new prospective employees. The advantages of the Tsukamoto fuzzy method are that it is intuitive and can provide responses based on inaccurate and ambiguous information. The ranking of expert results and Tsukmaoto's FIS was compared using Rank Spearman. The correlation test value of 0.818623 indicates that the Tsukamoto fuzzy has produced an accurate solution

PERAMALAN TINGKAT PRODUKSI KAKAO TAHUN 2021 DI PROVINSI SUMATERA UTARA DENGAN METODE DOUBLE EXPONENTIAL SMOOTHING BROWN

Cocoa production in North Sumatera Province from 2007 to 2018 tends to decline. The low cocoa production in North Sumatera Province is below optimal conditions which impact on the economic sector, so forecasting is necessary in order to support the development of the upcoming cocoa industry in North Sumatera Province. The purpose of this study was to determine the amount of cocoa production in 2021 in North Sumatera Province using the double exponential smoothing brown method. With parameter values  and values  obtaining the form of the equation for forecasting the level of cocoa production in 2021 in North Sumatera Province using double exponential smoothing brown is . Form the research result, the amount of cocoa production in 2021 in North Sumatera Province obtained tons

ANALISIS PENJUALAN DAN PERSAINGAN AIR MINERAL KEMASAN BOTOL SELAMA PANDEMI COVID-19 DI KOTA MEDAN MENGGUNAKAN RANTAI MARKOV ORDE DUA

Markov chain is a method used to identify variables in the present, which is based on past variables in order to obtain an estimate of the probability of these variables in the future. The CoVid-19 virus outbreak has also had a negative impact on economic problems, because this pandemic resulted in a decrease in sales of mineral water. in bottles that experienced a decline in sales results during the COVID-19 pandemic. The formulation of the problem of how companies compete during Covid-19 which continues to experience a decline in sales? . Based on the results of this study, there is a large chance of a second order transition, namely AQUA products in September, which is 61%, an increase of 0.39% from October, in October it was 61.39, a decline of 0.02% so that in November it was 61.37% while Le Mineral products in September were 39%, decreased 0.39% from October, October was 38.61%, experienced a fix in November so November was 38.61%

ANALISIS PENGENDALIAN PERSEDIAAN MENGGUNAKAN METODE MIN-MAX DAN ECONOMIC ORDER QUANTITY (EOQ)

Penelitian ini bertujuan untuk menentukan jumlah pemesanan buah-buahan yang lebih ekonomis dengan membandingkan antara metode Min-Max dan Metode Economic Order Quantity (EOQ) guna melihat metode mana yang lebih efektif digunakan. Dalam penelitian ini digunakan data primer dengan menyebarkan kuisioner, lalu merata-ratakan data, sehingga didapat pemesanan ekonomis dengan menggunakan metode Min-Max pada buah jeruk yaitu 427,5kg/pekan, buah mangga yaitu 582,5kg/pekan, pada buah markisah yaitu 146kg/pekan, pada buah kesemek yaitu 180,25kg/pekan dan pada buah lainnya yang terdiri dari buah salak, terong belanda dan alpukat yaitu 273,75kg/pekan. Sedangkan pemesanan ekonomis dengan menggunakan metode EOQ pada buah jeruk yaitu 160,71kg/pekan, buah mangga yaitu 156,15kg/pekan, buah markisah yaitu 147,20kg/pekan, buah kesemek yaitu 124,94kg/pekan dan buah lainnya yang terdiri dari buah salak, terong belandan dan alpukat yaitu 122,98kg/pekan. Sedangkan yang digunakan pada Pasar Buah Berastagi pada buah jeruk yaitu 542,5kg/pekan, buah mangga yaitu 370,63kg/pekan, pada buah markisah yaitu 395,63kg/pekan, pada buah kesemek yaitu 304,38kg/pekan dan pada buah lainnya yang terdiri dari buah salak, terong belanda dan alpukat yaitu 391,25kg/pekan Dari perhitungan diatas didapat total persediaan buah-buahan menggunakan perhitungan Min-Max sebesar 1.610kg dan perhitungan menggunakan EOQ sebesar 711,97kg lebih ekonomis dibandingkan dengan perhitungan yang digunakan Pasar Buah Berastagi sebesar 1613,125

Gold Price Prediction Using the Fuzzy Time Series Saxena-Easo Method

Gold is an investment that has the smallest risk compared to other investment methods, but every time the price of gold always fluctuates. This fluctuation will make it difficult for investors, the government, or those who need gold price data to see how the prospects for gold investment are going forward. To overcome this, a prediction or forecast is made. One of the forecasting methods developed with fuzzy theory is the Saxena-Easo fuzzy time series method. In this study, this method will be used to predict gold prices in the period 17 August 2021 to 31 December 2021. The purpose of this study is to determine the value of gold prices for the period 17 August 2021 to 31 December 2021 and to determine the accuracy of the fuzzy time series method. Saxena Easo. While the parameter used to measure forecasting accuracy is MAPE, if this parameter is in the range of 10% to 20% then the forecasting result is good, and if the parameter is below 10% then the forecast result is very good. The results of forecasting gold prices in the period 17 August – 31 December 2021 have a value that tends to increase and the MAPE obtained is 0.024277%. Therefore, it can be said that the prediction results for certain parameters are very good

PERBEDAAN PENGARUH MODEL PEMBELAJARAN KOOPERATIF TIPE STUDENTS TEAMS ACHIEVEMENT DIVISION (STAD) DAN TIPE MAKE A MATCH TERHADAP HASIL BELAJAR MATEMATIKA SISWA DI KELAS X MADHARASAH ALIYAH EX PGA UNIVA MEDAN TAHUN PELAJARAN 2015/2016

The purpose of this research is to know the difference of result learningstudent mathematics taught with the Model of cooperative learning withtype of Students Teams Achievement Division (STAD) and type ofMake A Match In Class of X Madrasah Aliyah EX PGA UNIVA at.2015/2016. This research is quantitative research with the type ofexperiment research. The population is all students of class of XMadrasah Aliyah EX PGA UNIVA at 2015/2016 amounting to 99student amounting to 4 class. Instrument test used to know the resultlearn the student is multiple choice tes in the form of test of early andtest of result of learning. In this research, researcher succeed to obtain;get to test the normalitas of at experiment class 1 to assess the pre-tesgot by value LHitung = 0,172 and assess the pos-tes got by value LHitung =0,172 of while at class of Ekperimen II to assess the pre-tes got byvalue LHitung = 0,131 and assess the pos-tes of value LHitung = 0,117,later; then for the value of second LTabel of group is 0,173, meaningpopulation have normal distribution. To test the homogeneity assessthe pre-tes obtained by FHitung = 1,764 and assess the pos-tes obtained byFHitung = 1,93, while for the FTabel = 1,984 of, meaning second ofhomogeneous sampel. While to test the hypothesis t got by value ofthitung = 4,09 and ttabel = 2,011. meaning thitung>ttabel that is 4,09 > 2,011.Therefore, H0 refused and HA accepted meaning that there aredifference of result of learning student taught with the model ofcooperative learning of type student teams achievement division(STAD) with the model of study of Make A match of at items ofMathematics Logic in class of X MAS of Project Univa

Application of Simple Multi-Attribute Rating Technique Exploiting Rank (SMARTER) Method In Seed Selection Superior Corn in Silau Mangi Village

Agriculture is one of the important sectors in Indonesia. Most of Indonesia's population depends on the agricultural sector,one of which is corn farmers. Cultivation of corn plants starts from choosing quality seeds. Determination of quality cornseeds aims to increase productivity and quality of production. Various efforts can be made to increase corn production suchas the use of superior corn seeds. Efforts to increase corn production are still experiencing several obstacles, such as the lackof understanding of farmers in determining superior corn seeds. This study aims to apply the SMARTER method in selectingsuperior maize seeds in order to increase maize production. The Simple Multi Attribute Rating Technique Exploiting Rank(SMARTER) method is one of the methods in a decision support system whose solution is by using Rank Order Centroid(ROC) weighting on each criteria and sub-criteria. The results of the research carried out obtained five criteria that were usedas an assessment in the selection of corn seeds, namely resistance to pests, seed size, production yield, environmentaladaptation and harvest tim

IMPLEMENTATION OF THE GENERALIZED SPACE TIME AUTOREGRESSIVE (GSTAR) MODEL IN THE CASE OF THE SPREAD OF CORONAVIRUS IN THE DISTRICT CITY OF NORTH SUMATRA

Corona Virus Disease 2019 (COVID-19) is a new virus that can be transmitted and the worst impact is death. Covid-19 first appeared in Wuhan, China and eventually spread throughout the world, one of which was North Sumatra Province. The spread of Covid-19 cases was quite rapid, until finally the World Health Organization (WHO) declared the Covid-19 case a pandemic. Based on the conditions that occurred, this final project discusses the prediction of positive cases of Covid-19 in five locations in North Sumatra using the Generalized Space Time Autoregressive (GSTAR) model. Considering that Covid-19 spreads very easily, it does not only depend on time but also the proximity between locations, so the GSTAR model is quite good to use in predicting it, assuming the parameters between locations are heterogeneous. The estimation used is OLS with inverse distance weight. This study aims to determine the best GSTAR model and forecast positive cases of Covid-19 at five locations in North Sumatra. The results show that the best GSTAR model in this study is -OLS with an inverse weight of distance with forecasting results for the next 10 days in May 2022