cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
jurnalmantik@gmail.com
Editorial Address
Mathematics Department, Faculty of Science and Technology UIN Sunan Ampel Surabaya Jl. A. Yani no 117 Surabaya, Jawa Timur, Indonesia
Location
Kota surabaya,
Jawa timur
INDONESIA
Jurnal Matematika: MANTIK
Published by Universitas Islam Negeri Sunan Ampel
ISSN : 25273159     EISSN : 25273167     DOI : 10.15642/mantik
Core Subject : Education,
Mathematics
Jurnal Matematika MANTIK is a mathematical journal published biannually by the Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya. Journal includes research papers, literature studies, analysis, and problem-solving in Mathematics (Algebra, Analysis, Statistics, Computing and Applied).
Arjuna Subject : -
Articles 119 Documents
 1   2   3   4   5 
Klasifikasi Menggunakan Metode Hybrid Bayessian-Neural Network (Studi Kasus: Identifikasi Virus Komputer) Dian C Rini; Yuniar Farida; Dwi Puspitasari
Jurnal Matematika MANTIK Vol. 1 No. 2 (2016): Mathematics and Applied Mathematics
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (354.93 KB)

Abstract

Virus komputer merupakan suatu program yang menginfeksi komputer terutama pada saat komputer sedang beroperasi dan menjadi momok bagi pengguna komputer. Virus komputer dapat menggandakan dirinya sendiri dan menyebar dengan cara menyisipkan dirinya pada program dan data lainnya. Efek negatif virus komputer adalah memperbanyak dirinya sendiri, yang membuat sumber daya pada komputer terutama penggunaan memori menjadi berkurang secara signifikan. Diperlukan suatu penangkal atau antivirus dalam mencegah penyebaran yang lebih jauh dalam sistem komputer. Pada penelitian ini, dilakukan suatu identifikasi virus dengan menggabungkan dua metode yaitu Naïve Bayes Classifier dengan Neural Network. Fitur virus didapatkan dari mengkodekan ciri-ciri dari virus. Untuk klasifikasi awal digunakan metode Naïve Bayes Classifier untuk membagi dua jenis fitur, yaitu virus dan bukan virus. Setelah masuk kedalam jenis virus, maka diklasifikasikan kedalam dua jenis virus yaitu trojan atau worm menggunakan salah satu metode neural network (perceptron). Hasil sistem setelah dilakukan uji coba didapatkan recognition rate tertinggi yaitu sebesar 94.12%.
VEKTOR PRIORITAS DALAM ANALYTICAL HIERARCHY PROCESS (AHP) DENGAN METODE NILAI EIGEN Moh. Hafiyusholeh; Ahmad Hanif Asyhar
Jurnal Matematika MANTIK Vol. 1 No. 2 (2016): Mathematics and Applied Mathematics
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (374.221 KB)

Abstract

Pada Penelitian ini dikaji metode nilai eigen yang digunakan untuk mengkonstruksivektor prioritas model pengambilan keputusan yang dikenal dengan Analytical Hierarchy Process (AHP). AHP merupakan suatu metode pengambilan keputusan yang berdasarkan pada keragaman kriteria. Melalui metode nilai eigen ini diperoleh λ_mak≥n, dengan λ_mak adalah nilai eigen maksimum dan n adalah ukuran matriks. Untuk membatasi apakah suatu keputusan yang telah diambil dengan AHP sudah valid atau belum, bisa diverifikasi dengan menggunakan indeks konsistensi.
Metode Historis untuk Perhitungan Value at Risk pada Model Generalized Autoregressive Conditional Heteroscedacity in Mean Alfi Reny Kusumaningtyas; Abdul Aziz
Jurnal Matematika MANTIK Vol. 2 No. 1 (2016): Mathematics and Applied Mathematics
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (928.514 KB) | DOI: 10.15642/mantik.2016.2.1.1-6

Abstract

Investment is a commitment of the placement of the data on an object or a few investments with expectations will benefit in the future. The main motive is to seek investment gain or profit in a certain amount, but behind the good side there is one side that can harm or the risk of, for it required a measurement of risk where methods of value at risk (VaR) is very popular is widely used by the financial industry worldwide. Three main method on calculation of VaR historical method, parametric method and Monte Carlo method. So, the selected calculation of VaR GARCH-M model with historical simulation method on Bank Mandiri Tbk closing stock in 2005-2010. This research aims to know the calculation of VaR model GARCH-M through the historical method and implementation model GARCH-M on the computation of VaR via simulation on closing stock Bank Mandiri Tbk. Historical method approach is a model calculation of VaR is determined by the value of the past (historical) or return generated by simulation (repetition) of data used. The measures undertaken that explains the historical simulation method VaR models in the estimation of GARCH-M with a normal distribution, then apply GARCH-M in case of loss obtained by investors after investing with the help of Minitab software, E-views software and Matlab software.
PERBANDINGAN PENGKLUSTERAN DATA IRIS MENGGUNAKAN METODE K-MEANS DAN FUZZY C-MEANS Fitria Febrianti; Moh. Hafiyusholeh; Ahmad Hanif Asyhar
Jurnal Matematika MANTIK Vol. 2 No. 1 (2016): Mathematics and Applied Mathematics
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (150.672 KB)

Abstract

Indonesia with abundant natural resources, certainly have a lot of plants are innumerable. To clasify the plants into different clusters can use several methods. Methods used are K-Means and Fuzzy C-Means. However, this methods have difference. Not only in terms of algorithms, but in terms of value calculation on the root mean square error (RMSE) also different. To calculate the value of RMSE there are two indicators are required, namelt the training data and the checking data. Of discussion, the Fuzzy C-Means method has RMSE values smaller than the K-Means method, namely on 80 training data and 70 checking data with RMSE value 2,2122E-14. This indicates that the Fuzzy C-Means method has a higher level of accuracy than the K-Means method
APLIKASI METODE ADAMS BASHFORTH-MOULTON (ABM) PADA MODEL PENYAKIT KANKER Kuzairi Kuzairi; Tony Yulianto; Lilik Safitri
Jurnal Matematika MANTIK Vol. 2 No. 1 (2016): Mathematics and Applied Mathematics
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (410.098 KB)

Abstract

Cancer is a deadly disease that is characterized by the growth of abnormal cells, the growth is ongoing, forming a tumor. Tumors are divided into two parts, namely benign and malignant tumors. Malignant tumors are a general term for cancer. The disease of cancer has a mathematical model in the form of a system of differential equations, for it required a method to obtain the solution of the system of differential equations. The method used is the method of numerical methods Bashforth Adams Moulton (ABM) order one, two, three, and four. From the results of this study concluded that the method ABM order three better than the method ABM first order, second order and fourth order at issue models of cancer, It can be seen in the graphic simulation using ABM order three, it shows that increasing time population of immune effector cells (E) and a population of effector molecules (C) increased and then stabilized. The population of immune effector cells (E) stabilized at 33.3336, while the population of the effector molecule (C) is stable in the scope of the numbers 33,333, 33,333 are said to be in scope for changes in population effector molecule (C) can not be known with certainty. While the population of cancer cells (T) remains at 0 at each iteration (stable) remains in a state that is free of cancer
METODE LOGIKA FUZZY SEBAGAI EVALUASI DISTRIBUSI DAYA LISTRIK BERDASARKAN BEBAN PUNCAK PEMBANGKIT TENAGA LISTRIK Fifi D. Rosalina; Yuniar Farida; Abdulloh Hamid
Jurnal Matematika MANTIK Vol. 2 No. 1 (2016): Mathematics and Applied Mathematics
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (358.001 KB)

Abstract

Evaluation of peak load on the power system is raised very influential on the development of electric power availability in the various provinces. By reviewing the peak load for a year, can be implemented for the evaluation of power generation as a simulation of the electrical energy supply for the future. Evaluating the peak load also depends on several factors such as installed capacity, power capacity, and production at some plants systems. It can be the control of the forces generated on each such PLTA, PLTU, PLTG, and PLTS. Fuzzy logic method is an effective method that can be applied to evaluate peak loads with high accuracy. Thus the fulfillment of the electricity will be met with the desired reliability level. The evaluation of the resulting output can be used as a control for the security of the power system. With the results obtained is the highest error rate reached 60%, and has done training and testing data is as much as 4x to test the parameters of the membership function has been determined by the highest recognize result of 12.5%
APLIKASI GRAPH COLORING PADA PENJADWALAN PERKULIAHAN DI FAKULTAS SAINS DAN TEKNOLOGI UIN SUNAN AMPEL SURABAYA Devi Saidatuz Zaenab; Deasy Alfiah Adyanti; Aris Fanani; Nurissaidah Ulinnuha
Jurnal Matematika MANTIK Vol. 2 No. 1 (2016): Mathematics and Applied Mathematics
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (379.359 KB)

Abstract

In the academic environment there are various problems, one of problem is scheduling of courses at the university level. These problems are affected by the allocation of time (Conformity of SKS with each course), the availability of classrooms, and many study program. In the study preparation lecture schedules in this time, the parameters used, among others: second semester students in each Study Program, Number of Study Program, availability of classrooms, Lectures, number of credits a day of each study program at the Faculty of Science and Technology. This research is aimed as an alternative in formulating scheduling system when the faculty there is an imbalance between the lecture hall, many Study Program, and the number of credits taken each Study Program. Based on the analysis of Graph Coloring and Edge Coloring at case of scheduling Study Program Faculty of Science and Technology State Islamic University Sunan Ampel Surabaya, which has 6 Programs and 5 lecture room with three simulated combinations of input data, obtained scheduling unchanged (consistent) and results scheduling does not overlap / collision, both in the lecture room, and the time of the lecture.
PENGKLASTERAN LAHAN SAWAH DI INDONESIA SEBAGAI EVALUASI KETERSEDIAAN PRODUKSI PANGAN MENGGUNAKAN FUZZY C-MEANS Nur Afifah; Dian Candra Rini Novitasari; Ahmad Lubab
Jurnal Matematika MANTIK Vol. 2 No. 1 (2016): Mathematics and Applied Mathematics
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (180.695 KB)

Abstract

The number of rice field in Indonesia is decreasing due to development of residential areas and buildings. Consequently, it reduces foodstuff availability and government should import it from other. Increasing food production and minimizing imported food can be started by clustering fields as an evaluation. This clustering is approached by Fuzzy C-Means. Training and Testing data are implemented on Matlab and yield three categories, wide, medium and narrow field. Moreover, the most potential field is East Java, Central Java, and West Java
PENERAPAN METODE EXPONENTIAL SMOOTHING UNTUK PERAMALAN JUMLAH KLAIM DI BPJS KESEHATAN PAMEKASAN Faisol Faisol; Sitti Aisah
Jurnal Matematika MANTIK Vol. 2 No. 1 (2016): Mathematics and Applied Mathematics
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (178.967 KB)

Abstract

Time series model is the model used to predict the future using past data, one example of a time series model is exponential smoothing. Exponential smoothing method is a repair procedure performed continuously at forecasting the most recent data. In this study the exponential smoothing method is applied to predict the number of claims in the health BPJS Pamekasan using data from the period January 2014 to December 2015, the measures used to obtain the output of this research there are four stages, namely 1) the identification of data, 2) Modeling, 3) forecasting, 4) Evaluation of forecasting results with RMSE and MAPE. Based on the research methodology, the result for the period 25 = 833.828, the 26 = 800.256, period 27 = 766.684, a period of 28 = 733.113, period 29 = 699.541, and the period of 30 = 655, 970. Value for RMSE = 98.865 and MAPE = 7.002, In this case the moving average method is also used to compare the results of forecasting with double exponential smoothing method. Forecasting results for the period 25 = 899.208, the 26 = 885, 792, 27 = 872.375 period, a period of 28 = 858.958, period 29 = 845.542, and the period of 30 = 832.125. Value for RMSE = 101.131 and MAPE = 7.756. Both methods together - both have very good performance because the value of MAPE is below 10%, but the method of exponential smoothing has a value of RMSE and MAPE are smaller than the moving average method.
PENARAPAN METODE GOAL PROGRAMMING UNTUK MENGOPTIMALKAN BEBERAPA TUJUAN PADA PERUSAHAAN DENGAN KENDALA JAM KERJA, PERMINTAAN DAN BAHAN BAKU Fauziyah Fauziyah
Jurnal Matematika MANTIK Vol. 2 No. 1 (2016): Mathematics and Applied Mathematics
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (130.877 KB)

Abstract

The company has multiple objectives that want to be achieved, which are maximizing selling, maximizing production and minimizing the cost production without reducing the quality of the product. The objective contains different aspects and so often incompatible with each other. To provide an optimal solution with respect to those objectives of some predetermined goals, the applied method that used is goal programming. The goal programming show that it is run by using the LINDO program. The result of the goal programming method can maximize the total selling and total production by minimize cost. The result showed that the define objectives achieved optimally

Page 2 of 12 | Total Record : 119

 1   2   3   4   5 

Filter by Year

2015 2022


Reset
Filter By Issues
All Issue Vol. 8 No. 2 (2022): September - November Vol. 8 No. 1 (2022): April - June Vol. 7 No. 2 (2021): Mathematics and Applied Mathematics Vol. 7 No. 1 (2021): Mathematics and Applied Mathematics Vol. 6 No. 2 (2020): Mathematics and Applied Mathematics Vol. 6 No. 1 (2020): Mathematics and Applied Mathematics Vol. 5 No. 2 (2019): Mathematics and Applied Mathematics Vol. 5 No. 1 (2019): Mathematics and Applied Mathematics Vol. 4 No. 2 (2018): Mathematics and Applied Mathematics Vol. 4 No. 1 (2018): Mathematics and Applied Mathematics Vol. 3 No. 2 (2017): Mathematics and Applied Mathematics Vol. 3 No. 1 (2017): Mathematics and Applied Mathematics Vol. 2 No. 1 (2016): Mathematics and Applied Mathematics Vol. 1 No. 2 (2016): Mathematics and Applied Mathematics Vol. 1 No. 1 (2015): Matematika dan Terapan More Issue