Article Per Year (5 Year)
p-Index From 2019 - 2024
0.408
P-Index
This Author published in this journals
All Journal Jurnal Nasional Teknik Elektro dan Teknologi Informasi Proceeding Applied Business and Engineering Conference
Nazifa Hayati
Politeknik Caltex Riau
Religion Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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

Found 2 Documents
Search

 1 
Coarse-Grained Sentiment Analysis Berbasis Natural Language Processing – Ulasan Hotel Warnia Nengsih; M. Mahrus Zein; Nazifa Hayati
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 1: Februari 2021
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1387.91 KB) | DOI: 10.22146/jnteti.v10i1.548

Abstract

Sentiment analysis is a method for obtaining data from various platforms available on the internet. Advances in technology enable the machine to recognize a term that is considered a positive opinion and vice versa. These data and opinions play an important role as product, services, or other topic feedback. Without the need to obtain an opinion directly from the public, the provider has obtained an important evaluation to develop themselves. Hospitality business is a field related to services, providing services to customers. Indicators of business continuity also depend on customer feedback and serve as a reference for strategic policy. Sentiment analysis techniques based on Natural Language Processing are expected to overcome these problems. In this study, the prediction uses a temporary Random Forest (RF) classifier to summarize the quality of the classifier then it can be done using the Receiver Operating Characteristic (ROC) curve. The ROC curve is a good graphic to summarize the quality of the classifier. The higher the curve is above the diagonal line, the better the prediction, with the ROC Curve value of 0.90. The result shows that positive reviews are more than the negative reviews, i.e., 68% and 32%, respectively.
RANCANG BANGUN DASHBOARD BUSINESS INTELLIGENCE UNTUK VISUALISASI DATA PASIEN (STUDI KASUS: PUSKESMAS PAKAN KAMIS) Nazifa Hayati; Dini Nurmalasari
ABEC Indonesia Vol. 9 (2021): 9th Applied Business and Engineering Conference
Publisher : Politeknik Caltex Riau

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

Abstract

The Public Health Center (Puskesmas) is a technical implementation unit of the district / city office which is responsible for carrying out health development in a work area. One of the existing community health centers is the Pakan Kamis puskesmas. Based on the interviews conducted, the puskesmas still experienced difficulties in seeing the pattern of disease spread, drug use patterns and patient development, because the process of recapping and calculating data was still done manually. This causes the puskesmas management to have difficulty in analyzing data and obtaining information for decision making. Therefore, a web-based business intelligence dashboard was created that can visualize patient data related to these problems. This Business Intelligence dashboard is built using the PHP programming language and MySQL database. From the results of user satisfaction testing, it was found that 97% of the business intelligence system dashboard for visualizing patient data was in accordance with the needs and could assist the health center in monitoring the pattern of disease spread, patient usage and development, as well as assisting the health center in analyzing data to make appropriate decisions. and efficient. Keywords: Puskesmas Pakan Kamis, Patient Data, Visualization, Dashboard, Business Intelligence
Co-Authors M. Mahrus Zein Nurmalasari, Dini Warnia Nengsih