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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Pythagoras: Jurnal Matematika dan Pendidikan Matematika CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Mahasiswa Matematika Jurnal POINTER Jurnal Sains Dan Teknologi (SAINTEKBU) BAREKENG: Jurnal Ilmu Matematika dan Terapan Journal of Research in Mathematics Trends and Technology Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi
Endang Wahyu Handamari
Department Of Mathematics, University Of Brawijaya, Malang, Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Library & Information Science Mathematics Mechanical Engineering Physics Transportation

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METODE LEAST SQUARE ESTIMATION UNTUK MENCARI PARAMETER FUNGSI RELIABILITAS DALAM MENENTUKAN PERSEDIAAN SUKU CADANG HAMMER UNIGRATOR F. Laua, Deni Putra Lurenso; Handamari, Endang Wahyu
Jurnal Mahasiswa Matematika Vol 1, No 4 (2013)
Publisher : Jurnal Mahasiswa Matematika

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KOMBINASI METODE AHP DAN METODE CUT OFF POINT DALAM PEMILIHAN SISTEM INFORMASI MANAJEMEN DI RSUI MADINAH KASEMBON MALANG Jannah, Liwaul; Handamari, Endang Wahyu
Jurnal Mahasiswa Matematika Vol 1, No 4 (2013)
Publisher : Jurnal Mahasiswa Matematika

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ESTIMASI PARAMETER DATA TERSENSOR TIPE II BERDISTRIBUSI WEIBULL PADA ANALISIS UJI HIDUP Moko, Endri Bitlas; Handamari, Endang Wahyu
Jurnal Mahasiswa Matematika Vol 1, No 5 (2013)
Publisher : Jurnal Mahasiswa Matematika

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BALANCED INCOMPLETE BLOCK DESIGN (BIBD) DAN SYMMETRIC BALANCED INCOMPLETE BLOCK DESIGN (SBIBD) Rasikhun, Hady; Marsudi, Marsudi; Handamari, Endang Wahyu
Jurnal Mahasiswa Matematika Vol 2, No 1 (2014)
Publisher : Jurnal Mahasiswa Matematika

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SEBARAN STASIONER PADA SISTEM BONUS-MALUS SWISS DENGAN BANYAKNYA PENGAJUAN KLAIM BERDISTRIBUSI BINOMIAL NEGATIF Rosyidah, Tri Hastuti Nur; Handamari, Endang Wahyu
Jurnal Mahasiswa Matematika Vol 2, No 1 (2014)
Publisher : Jurnal Mahasiswa Matematika

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PENENTUAN MODEL PREMI DENGAN METODE INDIVIDUAL LEVEL PREMIUM PADA ASURANSI DANA PENSIUN Nurcahyani, Lia; Handamari, Endang Wahyu
Jurnal Mahasiswa Matematika Vol 2, No 2 (2014)
Publisher : Jurnal Mahasiswa Matematika

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APROKSIMASI DISTRIBUSI UMUM WAKTU PELAYANAN UNTUK MODEL LALU LINTAS JARINGAN SELULER Ning Setyowati, Citra Ayu; Handamari, Endang Wahyu
Jurnal Mahasiswa Matematika Vol 2, No 4 (2014)
Publisher : Jurnal Mahasiswa Matematika

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Prediksi Profil Asam Amino Pada Family Protein Menggunakan Hidden Markov Model Endang Wahyu Handamari; Kwardiniya A; Mila Kurniawaty; Emilia S I
Jurnal POINTER Vol 2, No 2 (2011): Jurnal Pointer - Ilmu Komputer
Publisher : Ilmu Komputer, Universitas Brawijaya

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ABSTRAK Sequence  alignment adalah metode dasar dalam analisis sekuens, yang  merupakan proses penyusunan atau penjajaran dua atau lebih sequence primer sehingga persamaan sequence - sequence tersebut tampak nyata. Salah satu kegunaan  metode ini adalah untuk  memprediksi karakteristik dari suatu protein, yaitu memprediksi struktur atau fungsi protein yang belum diketahui menggunakan protein yang telah diketahui informasi struktur atau informasi fungsinya jika protein tersebut memiliki kesamaan sequence dengan sequence yang terdapat dalam database. Protein merupakan makromolekul yang menyusun lebih dari separuh bagian dari sel.  Protein merupakan  rantai dari gabungan 20 jenis asam amino, di mana setiap jenis protein mempunyai jumlah dan sequence asam amino yang khas. Metode yang dapat diterapkan untuk sequence  alignment di samping algoritma genetika adalah  metode yang berhubungan dengan Hidden Markov Model (HMM). Hidden Markov Model (HMM)  merupakan bentuk pengembangan dari rantai Markov, yang dapat diterapkan dalam kasus yang tidak dapat diamati secara langsung. Sebagai observed state untuk sequence  alignment adalah sequence asam amino dalam tiga kategori yaitu : deletion(1), insertion(2) dan match(3),  sedangkan  untuk hidden state adalah residu asam amino, yang  dapat menentukan  family protein  bersesuaian dengan observasi O .               Implementasi melalui perangkat lunak HMM terhadap sequence asam amino telah dilakukan namun perlu diuji keakuratan  terhadap data sebenarnya melalui PDB (Protein Data Bank). ABSTRACT Sequence alignment is the basic method in sequence analysis,  which is the process of  two or more primer  sequences  so  that  the  equation sequences are apparent.  One of  the  usefulness  of  this  method to predict the characteristics of a protein, which predicts the structure or function of unknown proteins using known protein structure information  if the information  these proteins have sequence similarity to sequences contained in the data base. Proteins are  macromolecules  which  make up more  than half of  the cell. Proteins  are  chains  of a combination of  20 kinds of amino acids,  where each type protein  has  a number of proteins and amino acid sequences are typical.   The  method  can be  applied  to sequence  alignment besides  the genetic algorithm is a method associated with the Hidden Markov Model  (HMM). Hidden Markov Model (HMM) is a form of development of Markov chains, which can be applied in cases that can not be observed directly. As observed state for sequence alignment is the sequence of amino acids into three categories namely: deletion (1), insertion (2) and match (3), while for the hidden state is an amino acid residue, which can determine the family of proteins corresponding to the observation O. Implementation through HMM software for  the amino acid sequence has been done but needs to be tested against actual data accuracy through the PDB  (Protein Data Bank).
Klasifikasi Protein Berdasarkan Frekuensi Warna RGB Dengan Metode Naïve Bayes Classifier Endang Wahyu Handamari
Jurnal POINTER Vol 1, No 1 (2010): Jurnal Pointer - Ilmu Komputer
Publisher : Ilmu Komputer, Universitas Brawijaya

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ABSTRAK Pengklasifikasian enzim  berdasarkan frekuensi warna RGB,  dimana satu atau lebih frekuensi warna RGB terbesar yang didapat melalui  Discrete Cosine Transform, dipakai sebagai  atribut. Metode pangklasifikasian ini bertujuan untuk memprediksi kelas  sebuah gambar struktur enzim dengan cara mengklasifikasikan gambar tersebut ke dalam salah satu kelas dari beberapa kelas yang tersedia pada  database. Metode untuk melakukan proses klasifikasi ini adalah metode Naive Bayes Classifier, dengan asumsi bahwa setiap atribut bersifat independent. Hasil dari 47 data gambar struktur enzim diperoleh kesalahan minimal 8 pada kombinasi atribut 12 merah(R), 12 hijau(G) dan 12 biru(B) Kata kunci: Atribut, Discrete Cosine Transform, Naive Bayes Classifier     ABSTRACT Classification of enzyme according to frequency of RGB color, one or more the most frequency of RGB color which is got from Discrete Cosine Transform is used as attribute. This classification method has purpose to predict the class of enzyme structure picture by classifying the picture into one of the several classes that available on database. Method for doing this classification process is Naive Bayes Classifier method, with the assumption that each attribute is independent. The result which is got by using 47 data of enzyme structure picture makes at least 8 fault on attribute combination of 12 red (R), 12 green (G) and 12 blue (B).   Keywords: Attribute, Discrete Cosine Transform, Naive Bayes Classifier
Usage Pattern Exploration of Effective Contraception Tool Endang Wahyu Handamari
Journal of Research in Mathematics Trends and Technology Vol. 1 No. 1 (2019): Journal of Research in Mathematics Trends and Technology (JoRMTT)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jormtt.v1i1.750

Abstract

Determination of methods or contraception tool used by acceptors to support the Family Planning (“Keluarga Berencana”) is a problematic. In choosing methods or contraception tool, the acceptor must consider several factors, namely health factor, partner factor, and contraceptive method. Each method or contraception tool which is used has its advantages or disadvantages. Although it has been considering the advantages and disadvantages, it is still difficult to control fertility safely and effectively. Consequently acceptor change the method or a contraception tool that is used more than once. In order acceptors get the appropriate contraception tool then the patterns of changing in the usage of effective methods or contraception tool is determined. One of the methods that can be used to look for the patterns of changing in the usage of contraception tool is data mining. Data mining is an interesting pattern extraction of large amounts of data. A pattern is said to be interesting if the pattern is not trivial, implicit, previously unknown, and useful. The patterns presented should be easy to understand, can be applied to data that will be predicted with a certain degree, useful, and new. The early stage before applying data mining is using k nearest neighbors algorithm to determine the factors shortest distance selecting the contraception tool. The next step is applying data mining to usage changing data of method or contraception tool of family planning acceptors which is expected to dig up information related to acceptor behavior pattern in using the method or contraception tool. Furthermore, from the formed pattern, it can be used in decision making regarding the usage of effective contraception tool. The results obtained from this research is the k nearest neighbors by using the Euclidean distance can be used to determine the similarity of attributes owned by the acceptors of Family Planning to the training data is already available. Based on available training data, it can be determined the usage pattern of contraceptiion tool with the concept of data mining, where the acceptors of Family Planning are given a recommendation if the pattern is on the training data pattern. Conversely, if the pattern is none match, then the system does not provide recommendations of contraception tool which should be used.
Co-Authors Ambarwani, Ajeng Pambuko Arifin, Maulana Muhamad Arvianti, Aurellia A’la, Kevina Alal Edy Santoso Emilia S I F. Laua, Deni Putra Lurenso Fakih, Biastadias Sabirina Feby Indriana Yusuf Hady Rasikhun Imam Nurhadi Purwanto Indah Resti Ayuni Suri Jannah, Liwaul Karim, Corina Kwardiniya Andawaningtyas Mahmudi, Wayan Firdaus Marji Marji Marsudi, Marsudi Mila Kurniawaty Moko, Endri Bitlas Mukti, Donny Hanggoro Ning Setyowati, Citra Ayu Novitasari, Novitasari Nuraini, Safitri Ana Nurcahyani, Lia Pramoedyo Henny, Pramoedyo Rinaldy, Fawzan Rosyidah, Tri Hastuti Nur Sa'adah, Umu Saifullah, Mohammad Dicky Setyowati, Nur Fitriana Shankar, Aldyan Situmorang, Boy Nathanael Yundari, Yundari