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Journal of Mathematics: Theory and Applications
Published by Universitas Sulawesi Barat
ISSN : 26859653     EISSN : 27222705     DOI : https://doi.org/10.31605/jomta
Core Subject : Education,
Mathematics
JOMTA Journal of Mathematics Theory and applications is a national journal intended as a communication forum for mathematicians and other scientists from many practitioners who use mathematics in the research. JOMTA Journal of Mathematics Theory and applications disseminates new research results in all areas of mathematics and their applications. Besides research articles, the journal also receives survey papers that stimulate research in mathematics and their applications. The scope of the articles published in this journal deal with a broad range of mathematics topics, : Numerical Analysis Modeling and Simulation Logic Geometry and Topology Discrete Mathematics and Combinatorics Control and Optimization Applied Mathematics Analysis Algebra and Number Theory Computational Mathematics Statistics and Probability
Arjuna Subject : Matematika - Matematika Terapan
Articles 5 Documents
 1 
Search results for , issue "Volume 4, Nomor 1, 2022" : 5 Documents clear
K-Means Clustering dan Principal Component Analysis (PCA) Dalam Radial Basis Function Neural Network (RBFNN) Untuk Klasifikasi Data Multivariat Hayqal Hazmi Qastari Hayqal; Oni Soesanto; Yuana Sukmawaty
Journal of Mathematics: Theory and Applications Volume 4, Nomor 1, 2022
Publisher : Program Studi Matematika Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1089.188 KB) | DOI: 10.31605/jomta.v4i1.1757

Abstract

Pada penelitian ini dilakukan uji simulasi data berskala besar sehingga diperlukan metode yang handal untuk permasalahan klasifikasi salah satunya adalah Radial Basis Function Neural Network (RBFNN). Untuk training data RBFNN menggunakan struktur khusus yang melibatkan dimensi tinggi pada hidden layer. Dengan struktur RBFNN yang khusus tersebut maka seringkali menimbulkan permasalahan karena hidden layernya terlalu besar, sehingga diperlukan penambahan metode penyederhaan jaringan seperti PCA dan K-Means Clustering. Metode PCA digunakan untuk mereduksi dimensi input pada RBFNN sedangkan metode K-Means Clustering digunakan untuk penentuan inisialisasi center awal pada RBFNN. Pada hasil percobaan metode PCA dihasilkan komponen utama ke-1 dan ke-2 dengan masing-masing mewakili 55.2288% dan 27.3108% dari seluruh variabilitas, secara kumulatif kedua komponen utama menyatakan sebesar 82.5396% dan hasil percobaan perulangan iterasi di metode penelitian ini didapatkan hasil rata-rata proses akurasi PC dan Klas terbaik berada pada PC-2 Klas-3 dengan akurasi di atas 90% untuk proses training dan testing dengan akurasi kesalahan klasifikasi di bawah 10%.
Penerapan Metode Extreme Gradient Boosting (XGBOOST) pada Klasifikasi Nasabah Kartu Kredit Sri Elina Herni Yulianti; Oni Soesanto; Yuana Sukmawaty
Journal of Mathematics: Theory and Applications Volume 4, Nomor 1, 2022
Publisher : Program Studi Matematika Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (546.128 KB) | DOI: 10.31605/jomta.v4i1.1792

Abstract

Bad credit card is a problem of inability of credit card users to pay credit card bills that can cause losses to both parties concerned. In order to avoid losses caused by bad credit cards, the provider must conduct a careful analysis of prospective or old customers using credit cards. This study aims to classify bad credit card customers using machine learning techniques, namely classification techniques. One of the classification techniques used is the XGBoost method which is useful for regression analysis and classification based on the Gradient Boosting Decision Tree (GBDT), the XGBoost method has several hyperparameters that can be configured to improve the performance of the model. Hyperparameter tuning method used is grid search cross validation which is then validated using 10-Fold Cross Validation. XGBoost hyperparameters configured include n_estimators, max_depth, subsample, gamma, colsample_bylevel, min_child_weight and learning_rate. Based on the results of this study proves that the use of algorithms with hyperparameter tuning can improve the performance of eXtreme Gradient Boosting algorithm in the process of classification of credit card customers with an accuracy of 80.039%, precision of 81.338% and a recall value of 96.854%. Keywords: XGBoost, classification, Accuracy, Precision, Recall
Some Fixed Point Results on Multiplicative Metric Spaces Ahmad Ansar; Muh. Akbar Idris
Journal of Mathematics: Theory and Applications Volume 4, Nomor 1, 2022
Publisher : Program Studi Matematika Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (305.488 KB) | DOI: 10.31605/jomta.v4i1.1845

Abstract

In this paper, we first discussed some results about multiplicative metric spaces to support the main results. The aim of this paper is to present fixed point some result that satisfied some generalized of contraction mapping related to multiplicative metric spaces. Furthermore, some examples are given to support results
Penerapan Algoritma Branch and Bound dalam Optimalisasi Produk Tenun Sa’be (Studi Kasus: Toko Sutera Mandar Kec. Campalagian) Nurjanna Nurjanna; Darma Ekawati; Fardinah Fardinah
Journal of Mathematics: Theory and Applications Volume 4, Nomor 1, 2022
Publisher : Program Studi Matematika Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (436.813 KB) | DOI: 10.31605/jomta.v4i1.1858

Abstract

Setiap pelaku usaha atau pelaku ekonomi pasti melakukan prinsip ekonomi yaitu dengan modal yang sedikit mampu menghasilkan keuntungan maksimal, mengakibatkan munculnya masalah optimasi meliputi meminimumkan biaya atau memaksimumkan keuntungan dengan kapasitas sumber daya yang ada. Penelitian ini bertujuan untuk mengetahui optimalisasi produk tenun sa’be Toko Mandar Sutera menggunakan algoritma Branch and Bound. Metode yang digunakan dalam penelitian ini adalah algoritma Branch and Bound. Dalam penelitian ini diambil 11 jenis sarung, yakni sapeq, sapeq bocoq, pucuk, kotak-kotak, burberry, bunga kaiyang, arjuna, kucing garong, sandeq, lontara, dan malolo. Upaya optimalisasi keuntungan produk tenun sa’be memiliki beberapa kendala, yaitu persedian, bahan baku, waktu pembutan, jumlah karyawan, dan kapasitas gudang. Solusi awal diperoleh dengan menggunakan metode simpleks. Apabila hasilnya bernilai non integer maka dilanjutkan dengan algoritma Branch and Bound untuk mendapatkan solusi yang integer. Berdasarkan hasil penelitian diperoleh bahwa untuk mengoptimalkan produk tenun sa’be dengan keuntungan maksimal, maka Toko Mandar Sutera memproduksi produk jenis sapeq sebanyak 2 buah, burberry sebanyak 2 buah dan lontara sebanyak 1 buah dengan keuntungan produksi sebesar Rp460.000,00 per bulan
Hubungan Kemampuan Numerik Dan Kemampuan Verbal Siswa dalam Pembelajaran Matematika Andi Quraisy
Journal of Mathematics: Theory and Applications Volume 4, Nomor 1, 2022
Publisher : Program Studi Matematika Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (363.254 KB) | DOI: 10.31605/jomta.v4i1.1878

Abstract

This research was conducted with the aim of knowing the relationship or correlation between numerical abilities and verbal abilities of UPTD students at SMP Negeri 3 Sinjai. This study is a quantitative research with a research sample of 67 students. The sampling method used is Cluster Random Sampling. The data collection technique in this study used a numerical ability questionnaire and a verbal ability questionnaire. Data were analyzed by descriptive statistics and inferential statistics using correlation analysis. The results indicated that the average value of students' numerical ability was above the value of verbal ability, namely 68.05 for numerical ability and 55.68 for verbal ability, while based on the results of the calculation of correlation analysis techniques, the correlation coefficient value (r) was 0.33. The correlation of the two variables is in the weak category. These results suggest that there is a significant positive relationship between numerical ability and verbal ability. The higher the numerical ability, the higher the verbal ability. Conversely, the lower the numerical ability, the lower the verbal ability.

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