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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan
Berny Pebo Tomasouw
Jurusan Matematika FMIPA Universitas Pattimura
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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DETEKSI PENYALAHGUNAAN NARKOBA DENGAN METODE TWIN BOUNDED SVM Berny Pebo Tomasouw; Yopi Andry Lesnussa
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 15 No 4 (2021): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (476.137 KB) | DOI: 10.30598/barekengvol15iss4pp753-760

Abstract

Twin Bounded SVM (TB-SVM) is an improvement of the Twin SVM method and has advantages in classification problems compared to standard SVM. In this research, linear TB-SVM and nonlinear TB-SVM methods will be applied to detect drug use based on 23 symptoms experienced. The training and testing data is divided into three partition data schemes (60/40 scheme, 70/30 scheme and 80/20 scheme) in order to determine the best level of accuracy that can be obtained. The test results show that the nonlinear TB-SVM with the RBF kernel has a better accuracy rate than the linear TB-SVM, that is 80% at 60/40 scheme, 90% at 70/30 scheme, and 95% at 80/20 scheme.
MATRIKS SCORE DAN APLIKASINYA DALAM PENGAMANAN PESAN RAHASIA Berny Pebo Tomasouw; Glevi E. Mado; Elvinus R. Persulessy
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 12 No 2 (2018): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (228.926 KB) | DOI: 10.30598/vol12iss2pp107-116ar623

Abstract

The exchange of general information or confidential information between two persons through a medium does not guarantee its safety. This makes the sender of information and the recipient of information needs to be vigilant. In this case, the role of data encoding is very important. One of the most commonly used and recognized data encryption is cryptography. Cryptography is a technique for encrypting data through the process of encryption and decryption process by using certain keys so as generate new data that is secret. One of the cryptography is the security of secret messages using the Score matrix. The score matrix is defined as a symmetric matrix with elements of complex number and is a diagonal matrix.
PENGELOMPOKKAN DAN PEMETAAN KARAKTERISTIK KEMISKINAN DI KABUPATEN MALUKU BARAT DAYA PROVINSI MALUKU DENGAN MENGGUNAKAN SELF-ORGANIZING MAP DAN ANALISIS BIPLOT Zeth Arthur Leleury; Berny Pebo Tomasouw
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 13 No 2 (2019): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (210.024 KB) | DOI: 10.30598/barekengvol13iss2pp093-106ar810

Abstract

Berdasarkan hasil survei sosial ekonomi nasional (SUSENAS) BPS Provinsi Maluku menunjukkan bahwa kabupaten Maluku Barat Daya (MBD) merupakan kabupaten yang memiliki persentase tingkat kemiskinan tertinggi di provinsi Maluku dengan persentase tingkat kemiskinan 30,18 persen. Penelitian ini bertujuan untuk melakukan pengelompokkan desa/kecamatan di Kabupaten MDB guna melihat karakteristik kemiskinan pada setiap cluster. Selain itu, juga dilakukan pemetaan karakteristik kemiskinan untuk setiap desa/kecamatan di Kabupaten MBD sebagai upaya untuk mengetahui keragaman karakteristik kemiskinan. Metode pengelompokkan yang digunakan adalah algoritma jaringan syaraf tiruan Self Organizing Map (SOM) dan Biplot. Hasil penelitian memperlihatkan bahwa hasil pengelompokkan terbaik adalah dengan metode Biplot karena memiliki rasio yang lebih kecil. Adapun hasil pengelompokkan 17 kecamatan di kabupaten MBD terbagi dalam 4 cluster yakni cluster 1 terdiri kecamatan Pulau-Pulau Terselatan, Letti dan Moa; cluster 2 terdiri dari kecamatan Pulau-Pulau Babar dan Babar Timur; cluster 3 terdiri dari kecamatan Pulau Masela, Mdona Hyera, Kepulauan Romang, Damer, Wetar, dan Wetar Barat; sedangkan cluster 4 terdiri dari kecamatan Wetar Utara, Wetar Timur, Kisar Utara, Lakor, Dawelor Dawera dan Pulau Wetang. Ada 11 faktor yang mempengaruhi sehingga cluster 4 tergolong dalam cluster dengan karakteristik kemiskinan tertinggi. Sedangkan ada 4 faktor yang mempengaruhi sehingga cluster 3 tergolong dalam cluster dengan karakteristik kemiskinan cukup tinggi.
PENYELESAIAN SISTEM PEMBENTUKAN SEL PADA HYDRA MENGGUNAKAN METODE BEDA HINGGA SKEMA EKSPLISIT Y. Sambono; Zeth Arthur Leleury; Berny Pebo Tomasouw; Dorteus L. Rahakbauw
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 14 No 4 (2020): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (859.505 KB) | DOI: 10.30598/barekengvol14iss4pp481-490

Abstract

Mathematical models that describes the pattern of cell formation in hydra are expressed in a system of equations known as the Meinhardt model. This model is a continuous model in the form of diffusion equations. Thus, one of the studies which can be applied to Meinhardt equation is discretization. The finite difference model is a numerical method that can describe the discrete form of a continuous differential form. The method used in this study is finite different methods implementing explicit scheme. The advantage of the explicit scheme is easier to use for solving non-linear partial differential equations. This method used finite forward difference for derivatives of 𝑡 and finite centre difference for derivatives of 𝑥 at theactivator 𝑎(𝑥, 𝑡) and inhibitor 𝑏(𝑥, 𝑡). The Steps conducted by analyzing Meinhardt equation andcontinued with discretization such that earn the solution of system cell formation in hydra. According to the research its found that the activator cell population graphic have cell growth disposed ascend by the unit time, be different with the inhibitor cell population disposed descend of cell growth by the unit time.
Co-Authors Dorteus L. Rahakbauw Elvinus R. Persulessy Glevi E. Mado Y. Sambono Yopi Andry Lesnussa Zeth Arthur Leleury, Zeth Arthur