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Penerapan Hidden Markov Model (HMM) dan Mel-Frequency Cesptral Coefficients (MFCC) pada E-Learning Bahasa Madura untuk Anak Usia Dini Ubaidi, Ubaidi; Dewi, Nindian Puspa
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 6: Desember 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020722477

Abstract

Bahasa Madura is a regional language used in Madura island. This language has many variations of pronunciation and dialect that makes it not easy to learn, even by the local people especially children. There hasn’t been any interesting learning media to learn Bahasa Madura so far. In fact, a fun learning activity is needed to help children to enhance their ability in pronouncing animals’ names, numbers, fruits and things in Bahasa Madura. Thus, it’s considered important to create Bahasa Madura e-learning by implementing the recognition of voice patterns in order to make it easier for the children to learn Bahasa Madura which has several variations of pronunciation only for one single object. This Bahasa Madura e-learning application for young learners is used to introduce Bahasa Madura vocabularies by recognizing the voice pattern recordings which have been processed through MFCC technique as the extracted voice features and HMM as the learning techniques. The implementation of MFCC and HMM as the learning tool to introduce the pronunciation of regional language vocabularies especially Bahasa Madura has never been done before. Therefore, this research is expected to help the young learners to be able to pronounce Bahasa Madura vocabularies properly.  In this study, a number of young learners’ voices were recorded and were set as the trial data. Only the proper voice data that were used—voice data that were considered to be pronounced correctly. The trial method was done through one-single model and multi-model. After doing several simultaneous trials, the result showed the accuracy level. The average accuracy level for one-single model system was 73% (with the highest accuracy reached 75%) and the average accuracy level for multi-model system was 80% (with the highest accuracy reached 81%).
Peramalan Harga Bahan Proyek Menggunakan Metode Least Square (Studi Kasus : CV Rizky Mulya) Dewi, Nindian Puspa; Listiowarni, Indah
J-TIFA Vol 2 No 1: Maret 2019
Publisher : Universitas Muhammadiyah Maluku Utara (Prodi Teknik Informatika)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (422.367 KB) | DOI: 10.52046/j-tifa.v2i1.240

Abstract

Rancangan Anggaran Belanja, atau yang bisa disingkat sebagai RAB, merupakan sebuah perencanaan anggaran yang digunakan oleh perusahaan kontraktor untuk merancang anggaran yang dibutuhkan untuk bahan dalam sebuah proyek yang dikerjakan. Penyusunan RAB untuk pengerjaan proyek mendatang, erat kaitannya dengan peramalan harga bahan-bahan proyek itu sendiri. Sehingga diperlukan sebuah sistem peramalan harga bahan proyek dengan menggunakan metode least square pada CV Rizky Mulya. Metode Least Square merupakan metode peramalan yang tergantung pada trend dan musim, artinya naik dan turunnya harga sebuah bahan tersebut dipengaruhi oleh waktu tertentu. Dengan menggunakan metode least square, akurasi pada sistem mencapai akurasi maksimal mencapai 90% pada tahun 2014 sampai 2016. Sistem peramalan ini akan dibangun dengan menggunakan bahasa pemograman PHP, yang didukung dengan menggunakan mySQL sebagai manajemen basis data.