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INDONESIA
JOURNAL OF APPLIED INFORMATICS AND COMPUTING
ISSN : -     EISSN : 25486861     DOI : 10.3087
Core Subject : Science,
Journal of Applied Informatics and Computing (JAIC) Volume 2, Nomor 1, Juli 2018. Berisi tulisan yang diangkat dari hasil penelitian di bidang Teknologi Informatika dan Komputer Terapan dengan e-ISSN: 2548-9828. Terdapat 3 artikel yang telah ditelaah secara substansial oleh tim editorial dan reviewer.
Arjuna Subject : -
Articles 5 Documents
Search results for , issue "Vol 1 No 2 (2017): Desember 2017" : 5 Documents clear
Penerapan Replikasi Data pada Aplikasi Ticketing Menggunakan Slony PostgreSQL Defriyanuar Dhining; Yeni Rokhayati; Dwi Ely Kurniawan
Journal of Applied Informatics and Computing Vol 1 No 2 (2017): Desember 2017
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (964.866 KB) | DOI: 10.30871/jaic.v1i2.472

Abstract

Nowadays, almost every company use web aplication to do their business activity. Besides multi-platform it also easier for installation and maintenance. Other that web application need a fast and reliable internet connection. It is necessity to make a server in local area network with syncronize database from one server to another server. Syncronize database will run using replication server database. Database replication can use many tool, one of them is Slony that is specially create for PostgreSQL. Replication database can also to pretend stopping application when there is bad internet connection. Replication database is one of stanby server tecknic because down server. Database synchronize will be buid using PHP programming language and PostgreSQL database with Slony which is open source at all, so it will reduce the cost of installation and maintenance.
Prediksi Kelayakan Operasional Mesin Rivet Menggunakan Regresi Linear Berganda Yeni Rokhayati; Nur Setyo Utomo; Sartikha Sartikha
Journal of Applied Informatics and Computing Vol 1 No 2 (2017): Desember 2017
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (264.497 KB) | DOI: 10.30871/jaic.v1i2.473

Abstract

Mesin rivet merupakan suatu mesin yang digunakan dalam penyambungan plat berbahan aluminium. Upaya untuk mengetahui kelayakan mesin rivet di PT. XYZ selama ini dilakukan dengan melihat hasil yang dikeluarkan oleh mesin tersebut. Seringkali terjadi ketika mesin sudah menghasilkan banyak barang, namun hasilnya tidak memenuhi standar kualitas yang baik. Ini disebabkan oleh tidak diketahuinya kelayakan kondisi pengoperasian mesin rivetnya. Salah satu cara untuk mengetahui kelayakan operasi mesin rivet tanpa harus menunggu hasil penyambungan adalah dengan memprediksinya dari faktor-faktor yang berpengaruh besar, yaitu kesesuaian tekanan hidrolik, waktu penyambungan, dan diameter punch dari mesin rivetnya. Oleh karena melibatkan variabel lebih dari satu, maka metode regresi linier berganda digunakan dalam membuat model prediksi kelayakan mesin rivet ini. Pengujian hipotesis, penghitungan koefisien determinasi dan korelasi dilakukan untuk menguji kelayakan model prediksinya. Selain itu, guna mempermudah dalam mengetahui hasil prediksi kelayakan mesin rivetnya, sebuah aplikasi berbasis desktop dirancang menggunakan pemodelan Unified Modelling Languag (UML) dan dikembangkan menggunakan bahasa pemrograman Java.
Identifikasi Fitur Laptop beserta Orientasinya dengan Metode Apriori dan Lexicon-Based Try Satria Amanattullah; Hilda Widyastuti; Festy Winda Sari
Journal of Applied Informatics and Computing Vol 1 No 2 (2017): Desember 2017
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (888.631 KB) | DOI: 10.30871/jaic.v1i2.508

Abstract

Perkembangan laptop saat ini sangat pesat. Para produsen menggunakan media sosial misalnya fan page di Facebook untuk mempromosikan produknya. Semakin banyaknya pilihan membuat seseorang kesulitan dalam menentukan suatu laptop bagus atau tidak, direkomendasikan atau tidak. Review-review dan komentar-komentar yang ada di fan page tentang merek-merek laptop baru bisa dijadikan sebagai pengetahuan untuk menentukan apakah laptop baru tersebut bagus atau tidak. Jumlah review dan komentar yang ada di fan page sangat banyak sehingga diperlukan proses otomatisasi. Untuk keperluan tersebut digunakan opinion mining mencakup identifikasi target opini dan penentuan orientasinya. Identifikasi target opini digunakan untuk mengetahui fitur-fitur laptop yang dibicarakan dalam sebuah komentar sedangkan penentuan orientasi digunakan untuk menentukan apakah komentar bersifat positif atau negatif. Data yang digunakan untuk penelitian ini diambil dari data fans page Facebook yang kemudian dianalis menggunakan metode Apriori untuk menghasilkan fitur laptop sebagai target opini dan metode Lexicon-based untuk menentukan orientasi fitur laptop, apakah berorientasi positif atau negatif. Penelitian juga menghasilkan kesimpulan dari data review dan komentar yang telah diproses.
Analisis Koefisien Cepstral Emosi Berdasarkan Suara Ismail Mohidin; Frangky Tupamahu
Journal of Applied Informatics and Computing Vol 1 No 2 (2017): Desember 2017
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1024.129 KB) | DOI: 10.30871/jaic.v1i2.523

Abstract

Abstract - The speech signal carries some sort of information, which consists of the intent to be conveyed, who speaks the information, and the emotional information that shows the emotional state of the utterance. One of the characteristics of human voice is the fundamental frequency. In this study the selection of features and methods of classification and recognition is important to recognize the emotional level (anger, sadness, fear, pleasure and neutral) contained in the dataset, this research proposes design through two main processes of training and introduction recognition). Experiments conducted using the Indonesian emotion voice dataset and the Mel-Frequency Cepstrum Coefficients (MFCC) algorithm were used to extract features from sound emotion. MFCC produces 13 cepstral coefficients of each of the sound emotion signals. This coefficient is used as an input of classification of emotional data from 250 data sampling.
Modeling Infant Mortality Rate with Multivariate Adaptive Regression Spline Approach Hendra H Dukalang
Journal of Applied Informatics and Computing Vol 1 No 2 (2017): Desember 2017
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (728.268 KB) | DOI: 10.30871/jaic.v1i2.524

Abstract

The most important thing in human life is health, because of it is the rights of national foundation that should be fullfiled. This contains on Millenium Development Goals (MDGs) which had elapsed on December 2015, and was replaced by Sustainable Development Goals (SDGs). SDGs in the aspect of Mother and Child’s Health mentioned in its third purpose namely: ensuring the health life and supporting welfare for all ages. Kota Gorontalo is the capital of Gorontalo Province which has become the center ofactivities either in the part of economics or all sectors including health development, as one of them is to reduce the Infant Mortality Rate. The Infant Mortality Rate can be defined as the number of babies who died since the birth phase until the approximately age of one year of babies in the area at a certain period, then divided with the total per 1000 successful birth in that year. This research is aimed to analyze the relationship between infant mortality and its affecting factors by using MARS Method. The result of this research showed that the best MARS MODEL is a combination of BF = 16, MI = 3, MO = 3, with with a GVC value of 0,732. Therefore, the variable that have significant effect towards infant mortality in Gorontalo City is the percentage of childbirth which was helped by the healthcare provider (X1), the percentage of giving Vitamin A to the babies (X5), the percentage of pregnant mother who received TT2(X7), the percentage of basic inclusive imunitation on babies (X4) and the percentage of babies which was given breast milk exclusively at the age of 0-5 months (X2).

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