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Unnes Journal of Mathematics
Published by Universitas Negeri Semarang
ISSN : 22526943     EISSN : 24605859     DOI : https://doi.org/10.15294/ujm
Core Subject : Education,
Mathematics
Unnes Journal of Mathematics (UJM) publishes research issues on mathematics and its apllication. The UJM processes manuscripts resulted from a research in mathematics and its application scope, which includes. The scopes include research in: 1. Algebra 2. Analysis 3. Discrete Mathematics and Graph Theory 3. Differential Equation 4. Geometry 5. Mathematics Computation, 6. Statistics.
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 234 Documents
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IMPLEMENTASI METODE AHP-WP PADA SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN GURU TELADAN (Studi Kasus: Yayasan Abadiyah Kuryokalangan) Rifan, Slamet; Arini, Florentina Yuni; Alamsyah, Alamsyah
Unnes Journal of Mathematics Vol 5 No 1 (2016)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ujm.v5i1.13106

Abstract

This research proposed an application of MADM (Multi Attribute Decision Making) in the problems of the exemplary teacher selection with assessment criteria: the preparation of teaching material, lesson plan, application of learning, mastery of the learning material, the use of learning resource/media and the discipline in teaching. In this research, AHP (Analytical Hierarchy Process) method’s was used for weighting the criteria and testing the consistency toward pairwise comparison matrix. If the matrix has been consistent then it can be continued to WP (Weighted Product) method’s process in implementing rank to determine the best alternative. The methods of this research include preliminary studies, data collection phase, system development phase and conclusion. From the results of the ranking in this system, it was found that the teacher got the highest score was teacher with code of teacher: A05 with score 0.0195981, so that the teacher was a recommendation teacher that was selected as an exemplary teacher.
METODE FUZZY TOPSIS MADM SEBAGAI ALTERNATIF PENGAMBILAN KEPUTUSAN MENENTUKAN PENERIMA BEASISWA PPA BERBASIS WEB Halim, Bravura Candra; Alamsyah, Alamsyah; Sugiman, Sugiman
Unnes Journal of Mathematics Vol 5 No 1 (2016)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ujm.v5i1.13107

Abstract

This study examines the decision making to determine the scholarship recipients Improving Academic Achievement (PPA) at the State University of Semarang (UNNES) with details of criteria that include student GPA, number of credits taken, the value of student affairs, and the income of parents. The decision making process admission PPA UNNES scholarship implemented with the programming language of PHP with MySQL database and calculations using the method of Fuzzy TOPSIS Multiple-Attribute Decision Making (MADM). The results of reception system PPA UNNES scholarship in this study is a ranking by 50 students of the value of the preferences of the applicants and then taken by students who ranked top 10 of the results of ranking of preferences for recommended escapes in scholarship acceptance PPA UNNES. Based on these results it can be concluded that a web-based decision support systems can be built using TOPSIS Fuzzy MADM with the structure of the programming language PHP and MySQL as a Database Management System (DBMS). In the development of future systems, can be done by adding other data supporting the selection of scholarship PPA
PERBANDINGAN AKURASI MODEL ARCH DAN GARCH PADA PERAMALAN HARGA SAHAM BERBANTUAN MATLAB Sunarti, Sunarti; Mariani, Scolastika; Sugiman, Sugiman
Unnes Journal of Mathematics Vol 5 No 1 (2016)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ujm.v5i1.13108

Abstract

This article aims to get model data stock Unilever Indonesia Tbk. use the model ARCH and GARCH as well as comparing forecasting accuracy of the result of the next five days ahead model ARCH and GARCH on the stock Unilever Indonesia Tbk. use MATLAB. The methods used are design application forecasting uses GUI MATLAB, next model ARIMA Box-Jenkins, identification ARCH effect, forecasting use the model ARCH and GARCH, and compares the results second forecasting model that is based on the value of RMSE. On residual ARIMA best namely ARIMA(1,1,1) detected the effects ARCH so that data can modeled ARCH and GARCH. Model ARCH and GARCH best respectively namely ARCH(3) and GARCH(1,1). Based on value RMSE be seen that model best for forecasting the next five days ahead of data Unilever Indonesia Tbk. produced bymodels GARCH(1,1) because it has value RMSE smallest with equation conditional mean and conditional variance
ANALISIS VOLATILITY FORECASTING SEMBILAN BAHAN POKOK MENGGUNAKAN METODE GARCH DENGAN PROGRAM R Larasati, Enggar Niken; Hendikawati, Putriaji; Zaenuri, Zaenuri
Unnes Journal of Mathematics Vol 5 No 1 (2016)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ujm.v5i1.13109

Abstract

commodities, namely oil, sugar, eggs, flour, rice, chili, milk, onions, and chicken with GARCH models using the program R 2.11.1.The first step is, to test the data stationary nine basic commodities price increases, stationary data already analyzed using ARIMA method. From the analysis using ARIMA, were estimated several models. To determine the best ARIMA model, conducted a comparison of some of the models that have been in the estimation of the model are then selected by a significant parameter value, the value of ^ 2 is the smallest, smallest AIC value and the largest value of log likelihood. The residual value of the best ARIMA model that will be used to determine the GARCH model to the data of nine price increases of basic commodities. Having obtained the best GARCH model, it will be forecasting the smallest value of standard error and approach the original data.Forecasting results on nine basic price increase in 2015 with the best ie GARCH GARCH (1,1) for the rise in oil prices, chili, onions, chicken and wheat flour, GARCH (2,1) for the price of sugar, milk, rice and eggs. Garch best models have a standard error values are smaller and tend to be closer to the original data. By using the GARCH method, it will be forecasting the rise in prices of daily necessities in 2015.
ANALISIS MODEL THRESHOLD GARCH DAN MODEL EXPONENTIAL GARCH PADA PERAMALAN IHSG Susanti, Susanti; Zaenuri, Zaenuri; Mariani, Scolastika
Unnes Journal of Mathematics Vol 5 No 1 (2016)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ujm.v5i1.13111

Abstract

The purpose of this research were to know (1) the best model among TGARCH model and EGARCH model on predicting JCI value in BEI (2) the results forecasting JCI value in BEI using the best model for a few days later. This reseacrh focused on analysis of TGARCH and EGARCH models in forecasting JCI value. Procedure which used in this research were formulate problem, collecting data, analysis data dan conclusion. Data collected with documentation method that is collected secondary data and literature. Software EVIEWS 6 used as a analysis tool of JCI data. This research result in conclusions that is (1) The best model among models TGARCH and EGARCH models on predicting JCI value in BEI is TGARCH model (2) The results forecasting JCI value in BEI use TGARCH model for day 42th is 5112.81 and for day 43th until day 50th obtained 5112.82 (constant).
MODEL LINEAR GOAL PROGRAMMING PADA PENJADWALAN PERAWAT UGD RUMAH SAKIT UMUM DAERAH KOTA SEMARANG Ichsan, Nur; Dwijanto, Dwijanto; Arifudin, Riza
Unnes Journal of Mathematics Vol 5 No 1 (2016)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ujm.v5i1.13114

Abstract

Scheduling of emergency room is quite a complicated issue for each hospital, including the RSUD Kota Semarang. Many methods can be used in the scheduling of nurses, including the Linear Goal Programming (LGP). The purpose of this study was to determine the form of the LGP model and comparison between manual scheduling and LGP model. The method used in this study is by changing the scheduling rules into a form of LGP models, then the model is solved with LINGO 14. In this model, the hospital rules should not be violated is called major constraints, while the rules may be violated at any time is called additional constraints. Additional constraints is a policy made by the head nurse to schedule in accordance with the conditions and needs of nurses. In this study there are 7 major constraints and 5 additional constraints. Based on calculations, obtained the nurse schedule for 31, 30, 29, and 28 days. From the analysis, LGP schedule for 31 days, 30 days, 29 days, and 28 days to meet all of the major constraints and additional constraints. While in manual schedule, the main constraints are met as much as 5 constraints. Then for the additional constraints are not met for all. From the analysis, LGP models can also be applied to the scheduling of nurses in the other room.
IMPLEMENTASI FRACTIONAL BROWNIAN MOTION DENGAN PARAMETER HURST UNTUK DATA PAJAK HOTEL Nugroho, Samuel Defri; Mariani, Scolastika
Unnes Journal of Mathematics Vol 5 No 1 (2016)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ujm.v5i1.13115

Abstract

Fractional Brownian Motion (FBM) is general Brownian Motion (BM) that impact for construction tax hotel, this can instrument for decision. the trouble is how to do value best implementation estimate FBM and BM with Hurst parameter for tax hotel. How to do impact matlab program for that. data can uses is data tax hotel in Semarang. Purpose research is know value estimate FBM and BM and impact that with matlab program. Process construction is input Hurst [0,1], Δt, and N to estimate Hurst output value estimate, this value input to FBM and BM (H=0.5) process, output this value construction finance for covarians Hurst and bias Hurst for finaly value RMSE (Root Mean Square Error).
MODEL EPIDEMI SEIV PENYEBARAN PENYAKIT POLIO PADA POPULASI TAK KONSTAN Umam, Yanuar Chaerul; Kharis, Muhammad; Supriyono, Supriyono
Unnes Journal of Mathematics Vol 5 No 2 (2016)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ujm.v5i2.13117

Abstract

Polio (Poliomyelitis) is a highly contagious disease caused by the polio virus from the genus Enterovirus and family Picorna Viridae. Polio considered dangerous because it can lead to complications, brain damage that causes paralysis of the internal organs, paralysis in the legs, muscles and even death. In this paper,it will be studied mathematical models for the spread of polio that does not cause the death. The mathematical model that is used in this paper is SEIV epidemis models with the recruitmen - death. The analysis includes the determination of the equilibrium point and the associated stability analysis of the equilibrium point. Simulation models are given as a form of approach are the values of the parameters are given as a check on the results of analyzes performed. Vaccination is done can affect the spread of measles in the population
APLIKASI MOBILE LEARNING BERBASIS ANDROID Wibowo, Eric Adie; Arifudin, Riza
Unnes Journal of Mathematics Vol 5 No 2 (2016)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ujm.v5i2.13119

Abstract

The purpose of this article is to design and implement mobile learning applications based on Android at SMAN 5 Semarang. Applications developed using prototype method, the process of software development activities include the design needs analysis, implementation, and testing. Applications created with features that include viewing the content, news, download materials, assignments, and grades. Testing was conducted using Blackbox test and testing by the user. The final results reveal that the application can be implemented properly in android device with type mobile phones and tablets that have a version of 2.3 Gingerbread to 4.3 Jelly Bean with a variety of screen sizes
PERBANDINGAN TAKSIRAN VALUE AT RISK DENGAN PROGRAM R DAN MATLAB ANALISIS INVESTASI SAHAM MENGGUNAKAN METODE GARCH Sari, Fenny Tunjung; Mariani, Scolastika
Unnes Journal of Mathematics Vol 5 No 2 (2016)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ujm.v5i2.13120

Abstract

Value at Risk (VaR) became a popular statistical method used to measure the risk investing. When estimating it require forecasting volatility. One of methods for modeling the heteroscedastic volatility called Generalized Autoregressive Conditional Heteroscedasticity (GARCH). The goal of this research are compare the result estimated it, by R program and MATLAB program, and then comparing accuracy of them. This research used data index March 4, 2013 to October 1, 2014. The result show that the forecasting it with probability 95% and 15-days horizon on R program is -0,2224606 then MATLAB program is -0,215263. While the result of calculation Mean Square Error (MSE) respectively R and MATLAB programs are 0,0003623 and 0,0003609. MATLAB program is the best level of accuracy in forecasting variansi. They have been modeling the volatility of LQ45 stock index to estimate it, using GARCH(1,1) model

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