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MILANG Journal of Mathematics and Its Applications
Published by Institut Pertanian Bogor
ISSN : -     EISSN : 29635233     DOI : https://doi.org/10.29244/milang.18.1
Core Subject : Education,
Mathematics
MILANG Journal of Mathematics and Its Applications, originally established in 2002 as the Journal of Mathematics and Its Applications (ISSN 1412-677X), transitioned to online publishing in 2018 and was renamed in 2022 to reflect its broadened scope. The name MILANG, a Sundanese word meaning “to count,” also stands for the journal’s key focus areas: Mathematics in Informatics, Life Sciences, Actuarial Science, Natural Sciences, and Graph Theory. This journal, published twice a year in June and December by the Department of Mathematics, IPB University, embraces an open access policy, making all articles freely available upon publication to support the global dissemination of innovative mathematical research.
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 6 No. 2 (2007): Journal of Mathematics and Its Applications" : 5 Documents clear
DINAMIKA MODEL VAKSINASI VIRUS INFLUENZA DENGAN PERUBAHAN LAJU PEMBERIAN VAKSINASI KUSNANTO, A.
MILANG Journal of Mathematics and Its Applications Vol. 6 No. 2 (2007): Journal of Mathematics and Its Applications
Publisher : School of Data Science, Mathematics and Informatics, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jmap.6.2.1-8

Abstract

Dalam tulisan ini, disajikan dinamika populasi model virus influenza dari Alexander dengan pengubahan laju pemberian vaksinasi. Model memiliki dua titik tetap yaitu titik tetap tanpa penyakit dan titik tetap endemik. Banyaknya titik tetap endemik dipengaruhi oleh suatu persamaan kuadrat sehingga keberadaannya bergantung pemilihan nilai parameter. Pada saat titik tetap ini ada dua, kestabilannya titik tetap ini akan dipengaruhi oleh suatu parameter yang merupakan tingkat vaksinasi. Jika nilai ini diperbesar, maka populasi yang rentan akan semakin membesar sedangkan populasi terinveksi akan semakin kecil. Penggambaran dinamika populasi model akan dilakukan dengan bantuan software Maple.
ALGORITMA PENGENDALI KONKURENSI TERDISTRIBUSI (DROCC) BUKHARI, F.
MILANG Journal of Mathematics and Its Applications Vol. 6 No. 2 (2007): Journal of Mathematics and Its Applications
Publisher : School of Data Science, Mathematics and Informatics, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jmap.6.2.9-22

Abstract

Penelitian ini memperkenalkan algoritma pengendalian konkurensi untuk sistem basis data terdistribusi atau dikenal dengan sebutan DROCC (Distributed Read commit Order Concurrency Control), karena algoritma DROCC merupakan pengembangan algoritma ROCC (Read commit Order Concurrenct Control) yang diperkenalkan oleh Shi dan Perizzo untuk sistem basis data terpusat. Sama halnya dengan ROCC, algoritma DROCC mengurut eksekusi transaksi tanpa menggunakan mekanisme locking, tetapi menggunakan struktur Read Commit queue (RC-queue) untuk mengurut akses terhadap basis data lokal dan menggunakan struktur serial graph untuk mengurut transaksi secara global. Proses validasi pada algoritma DROCC terdiri dari proses validasi lokal dan proses validasi global. Proses validasi lokal DROCC merupakan penyempurnaan proses validasi ROCC. Sedangkan proses validasi global memanfaatkan struktur serial graph yang dibangkitkan dari RC-queue. Pada penelitian ini mekanisme penghapusan transaksi yang sudah tervalidasi juga dirancang.Algoritma DROCC memiliki feature, (i) optimistik, setiap request langsung dieksekusi tanpa penundaan yang berarti, (ii) bebas deadlock baik lokal maupun global, (iii), masing-masing situs memiliki full autonomy.
PENDUGAAN PARAMETER DERET WAKTU HIDDEN MARKOV SATU WAKTU SEBELUMNYA SETIAWATY, B.; SANTOSO, D. H.
MILANG Journal of Mathematics and Its Applications Vol. 6 No. 2 (2007): Journal of Mathematics and Its Applications
Publisher : School of Data Science, Mathematics and Informatics, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jmap.6.2.23-36

Abstract

Pendugaan parameter deret waktu Hidden Markov satu waktu sebelumnya dilakukan mengunakan Metode Maximum Likelihood dan pendugaan ulang menggunakan metode Expectation Maximization. Dari kajian ini diperoleh algoritme untuk menduga parameter model.
FORMULASI LAGRANGE UNTUK MENGGAMBARKAN GERAK GELOMBANG INTERNAL DI ATMOSFIR JAHARUDDIN, J.
MILANG Journal of Mathematics and Its Applications Vol. 6 No. 2 (2007): Journal of Mathematics and Its Applications
Publisher : School of Data Science, Mathematics and Informatics, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jmap.6.2.37-46

Abstract

Dengan menggunakan metode asimtotik, diturunkan persamaan gerak gelombang internal yang sesuai pada lapisan atmosfir. Persamaan gerak ini merupakan kombinasi antara persamaan Korteweg-de vries (KdV) dan persamaan Benjamin-Ono (BO). Persamaan KdV-BO muncul sebagai suatu kondisi terselesaikan dari suatu masalah nilai batas. Koefisien dari persamaan KdV-BO dinyatakan dalam bentuk integral dari suatu fungsi yang muncul pada pendekatan linear gelombang. 
CONSISTENCY OF KERNEL-TYPE ESTIMATORS FOR THE FIRST AND SECOND DERIVATIVES OF A PERIODIC POISSON INTENSITY FUNCTION MANGKU, I W.; SYAMSURI, S.; HERNIWAT, H.
MILANG Journal of Mathematics and Its Applications Vol. 6 No. 2 (2007): Journal of Mathematics and Its Applications
Publisher : School of Data Science, Mathematics and Informatics, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jmap.6.2.47-55

Abstract

We construct and investigate consistent kernel-type estimators for the first and second derivatives of a periodic Poisson intensity function when the period is known. We do not assume any particular parametric form for the intensity function. More- over, we consider the situation when only a single realization of the Poisson process is available, and only observed in a bounded interval. We prove that the proposed estimators are consistent when the length of the interval goes to infinity. We also prove that the mean-squared error of the estimators converge to zero when the length of the interval goes to infinity.1991 Mathematics Subject Classification: 60G55, 62G05, 62G20.

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