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Jurnal Kajian Matematika dan Aplikasinya
Published by Universitas Negeri Malang
ISSN : -     EISSN : 27227650     DOI : -
Core Subject : Education,
Mathematics
The aim of this journal publication is to disseminate research results and new theories that have been achieved in the area of mathematics. Jurnal Kajian Matematika dan Aplikasinya (JKMA) particularly focuses on the main issues in the development of the sciences of mathematics, in the fields of algebra, analysis, applied mathematics, combinatorics, computational sciences, geometry, and statistics.
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol 3, No 1 (2022): January" : 5 Documents clear
ALGORITMA GENERAL VARIABLE NEIGHBORHOOD SEARCH PADA CAPACITATED VEHICLE ROUTING PROBLEM WITH TIME WINDOWS DAN IMPLEMENTASINYA Ulil Ilmi Fadila; Sapti Wahyuningsih; Darmawan Satyananda
Jurnal Kajian Matematika dan Aplikasinya (JKMA) Vol 3, No 1 (2022): January
Publisher : UNIVERSITAS NEGERI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um055v3i12022p1-7

Abstract

The Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) is one of the variants of the Vehicle Routing Problem (VRP), which is the problem of determining the optimal route from the depot to the consumer which is located spread out with different requests. In CVRPTW problem solving considers capacity and time constraints. Determining the optimal route can reduce costs and energy spent during the distribution process. The General Variable Neighborhood Search (GVNS) algorithm can be applied to the CVRPTW problem. The GVNS algorithm is an improvement on the VNS algorithm using RVND. The GVNS algorithm starts with finding the initial solution, continues with perturbation, and then the repair procedure is carried out. Perturbation and improvements to the GVNS algorithm are performed repeatedly according to the predetermined IterMax. The GVNS algorithm for CVRPTW will be implemented using the Borland Delphi 7.0 programming language. The product in the form of this application can be used more practically to solve CVRPTW problems using the GVNS algorithm.Keywords: Capacitated Vehicle Routing Problem with Time Windows (CVRPTW), General Variable Neighborhood Search (GVNS) Algorithm, Randomized Variable Neighborhood Descent (RVND)
PERAMALAN PENJUALAN JUMLAH KRIPIK DI SNACK CENTER MENGGUNAKAN METODE TRIPLE EXPONENTIAL SMOOTHING Siti Nurul Afiyah; Nur Lailatul Aqromi
Jurnal Kajian Matematika dan Aplikasinya (JKMA) Vol 3, No 1 (2022): January
Publisher : UNIVERSITAS NEGERI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um055v3i12022p8-14

Abstract

Snack Center is a gift center that offers various kinds of products to consumers who have a lot of untapped sales transaction data to support business and services. In addition, the goods arrangement system is carried out without standardization so that the goods cannot be run. In order to make the sales process more optimal, a chip sales forecasting system was made using the triple exponential smoothing method at the Batu City Snack Center by entering the data that has been obtained. The data is the result of sales in the previous period. In the triple exponential smoothing method, three smoothing calculations are carried out, then determine the alpha value to compare the smallest error percentage level. From the results of the data that has been tested with a sales forecasting system for chips with sales data from 2020-2021, the forecast value for recommendations for the next month, namely January 2022, is 30 packs of chips at alpha parameter 0.3 with least MAPE 9.598 percent.Keywords: Chips sale, forecasting, triple exponential smoothing
ALGORITMA GRAVITIONAL EMULATION LOCAL SEARCH PADA CVRP DAN IMPLEMENTASINYA Febri Nur Azis; Sapti Wahyuningsih; Darmawan Satyananda
Jurnal Kajian Matematika dan Aplikasinya (JKMA) Vol 3, No 1 (2022): January
Publisher : UNIVERSITAS NEGERI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um055v3i12022p23-29

Abstract

Permasalahan optimalisasi distribusi dapat dipecahkan dengan menggunakan algoritma pada varian Vehicle Routing Problem (VRP). Salah satu varian dari VRP adalah Capacitated Vehicle Routing Problem (CVRP) yaitu dengan tambahan kendala kapasitas kendaraan yang identik. Algoritma Gravitational Emulation Local Search (GELS) dapat digunakan untuk menentukan solusi CVRP. Algorima GELS merupakan gabungan dari algoritma genetika dan local search (best improvement local search). Pada artikel ini dibahas langkah algoritma dan diimplementasikan ke dalam computer menggunakan aplikasi Borland Delphi 7.  Input program berupa ukuran populasi, probabilitas crossover, probabilitas mutasi, maksimum iterasi, kapasitas kendaraan, banyaknya titik, dan permintaan setiap customer. Output berupa hasil rute dengan jarak yang ditempuh serta divisualisasi rutenya dengan gambar graph. .Diberikan contoh penyelesaian permasalahan dengan contoh 7 titik terdiri dari satu depot dan enam customer. Hasil tampilan program berupa matrik bobot titik, permintaan, dan hasil berupa rute optimal. Aplikasi program GELS pada CVRP secara praktis dapat digunakan untuk penyelesaian optimasi distribusi.
PENERAPAN ANALISIS DISKRIMINAN LINIER ROBUST DALAM PENGKLASIFIKASIAN INDEKS KEPEDULIAN TERHADAP ISU KEPENDUDUKAN (IKIK) Nabilatul Fahma; Trianingsih Eni Lestari
Jurnal Kajian Matematika dan Aplikasinya (JKMA) Vol 3, No 1 (2022): January
Publisher : UNIVERSITAS NEGERI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um055v3i12022p30-36

Abstract

Abstract Robust linear discriminant analysis is used to classify data that contains outlier by replacing classical parameters in linear discriminant analysis with robust parameters. This study aims to classify the Index of Concern for Population Issues (IKIK) of 34 provinces in 2020 into two categories namely target fulfilled IKIK and target not fulfilled IKIK using robust linear discriminant analysis. The independen variabels used are quantity dimensions (X_1), quality dimensions (X_2), mobility dimensions (X_3), and environment dimensions (X_4). The results obtained are 17 provinces were categorized as target fulfilled IKIK, 17 provinces as target not fulfilled IKIK. There are 2 robust discriminant functions formed, each for target fulfilled and target not fulfilled IKIK. The accuracy of the robust linear discriminant functions formed is 97,06%, the APER value of the discriminant functions is 2,94% and the PressQ value = 30,11 is greater than the value of (Chi_(3,0.05)^2) = 7.81. This shows that the discriminant functions can classify observations accurately.Keywords: classification, Index of Concern for Population Issues, robust discriminant analysis
PENERAPAN MACHINE LEARNING UNTUK PREDIKSI PENYAKIT STROKE Denis Eka Cahyani
Jurnal Kajian Matematika dan Aplikasinya (JKMA) Vol 3, No 1 (2022): January
Publisher : UNIVERSITAS NEGERI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um055v3i12022p15-22

Abstract

Stroke is a global health problem and one of the leading causes of adult disability. Early detection and prompt treatment are needed to minimize further damage to the affected brain area and complications to other parts of the body. Machine learning techniques can be used to predict stroke detection. Machine learning algorithms such as Naive Bayes, Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Decision Tree are compared in this study to obtain the best performance in predicting stroke. The implementation stages in this research consist of the pre-processing data, the application of the algorithm and the evaluation and analysis. The Naïve Bayes algorithm obtains better Accuracy, Precision, Recall, and F1-Measure values compared to other algorithms. The values of Accuracy, Precision, Recall, and F1-Measure obtained by Naïve Bayes are 93.93%, 88.23%, 93.93%, and 91.00%, respectively. So the conclusion of this study is that the Naïve Bayes algorithm has the best performance compared to the SVM, KNN and Decision Tree algorithms in predicting stroke.Keywords: decision tree, klasifikasi, k-nearest neighbor, naïve bayes, stroke, support vector machine 

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