Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal Jurnal INKOM Teknik dan Ilmu Komputer
Maria Ariesta
Unknown Affiliation
Computer Science & IT

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
MENGELOLA RISIKO PROYEK PENGEMBANGAN SOFTWARE Putro, Endi; Ariesta, Maria
Teknik dan Ilmu Komputer vol. 1 no. 4 Oktober-Desember 2012
Publisher : Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Software Development is considered as a project due to the budget and time restrictions applied to it.  In software development project, risk refers to an event that is not in the plan which may occur and result in the project loss. The methodology used to manage the project risks include giving weigth to the matrix that draws together the project management activities and questions generated based on the risk factors of software development projects. The results of these matrixes are used to anticipate the risks that might appear during the project implementation.  Keywords: project, risk, managing
Web-Based Decision Support Systems Application of Stock Recommendation Using Bayesian Methods Sevani, Nina; Ariesta, Maria
INKOM Journal Vol 8, No 1 (2014)
Publisher : Pusat Penelitian Informatika - LIPI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (923.021 KB) | DOI: 10.14203/j.inkom.302

Abstract

We propose an application that can support traders by providing recommendation about the right stock transaction. The expected impact from this application is to reduce the risk of loss, even achieve the maximum profit for traders who use this application. Recommendation that resulted by application is based on Bayesian methods calculation and four technical analysis indicators that most commonly used by stock experts, i.e. Bollinger Bands, Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI), and Stochastic Oscillator. Methodology used in this paper consists of data collection, data analysisa, application design, implementation, and testing. From the results of application testing, the accuracy of the application is 87,37%.
Co-Authors Endi Putro Nina Sevani