Article Per Year (5 Year)
p-Index From 2021 - 2026
0.659
P-Index
This Author published in this journals
All Journal Jurnal Paradigma Ekonomika JAIS (Journal of Applied Intelligent System) Jurnal Manajemen Sistem Informasi
Sophia, Aya
Unknown Affiliation
Computer Science & IT Economics, Econometrics & Finance

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Penerapan Data Mining dalam Pengelompokan Uang Kuliah Tunggal (UKT) Menggunakan Metode K-Means Pada Universitas Jambi Sophia, Aya; Jasmir, Jasmir
Jurnal Manajemen Sistem Informasi Vol 9 No 1 (2024): MANAJEMEN SISTEM INFORMASI
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jurnalmsi.2024.9.1.1692

Abstract

UKT is a single tuition fee borned by each undergraduate student at a state university in Indonesia, to be paid every semester. At Jambi University, 8 UKT groups apply to students based on the level of the student's economic condition. Determining the UKT group for new students manually is less effective because it really depends on the assessment of the assessor, the criteria for economic conditions are quite a lot, the potential for subjectivity, and the amount of data is quite large. This study grouped new students into 8 UKT groups by applying data mining using the k-Means method. The k-Means method performs clustering based on the similarity of data on student economic conditions. K-Means analysis was performed using Rapidminer and SPSS tools. The results show that there are 7 variables/attributes of economic condition parameters that can be used in k-means analysis, including: total parent/guardian income including additional income, parent/guardian employment, electricity bills, parent status, land and building tax bills, housing conditions, and the number of dependents who are still at school. The results show that between the interpretation of the k-means analysis and the real data, there was a similarity in determining the UKT group above 50% in both Rapidminer and SPSS. Thus it can be concluded that the k-Means method can be applied to support decision making in determining UKT groups for students.
Analisis persistensi inflasi di Provinsi Jambi Sophia, Aya; Safri, Muhammad; Achmad, Erni
Jurnal Paradigma Ekonomika Vol. 17 No. 3 (2022): Jurnal Paradigma Ekonomika
Publisher : Program Studi Ekonomi Pembangunan Fakultas Ekonomi dan Bisnis Universitas Jambi

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

Abstract

This study aims to analyze the inflation persistence level in Jambi Province and the factors that influence it. By using the univariate autoregressive (AR) model, the persistence level is measured in general, disaggregation, commodity groups, and selected commodities. Multiple regression models are used for the factors that influence inflation. The observation period is January 2019 to December 2021. The results show that the persistence of general inflation in Jambi Province was low. However, high persistence was in core inflation and administered prices, 9 commodity groups, and several commodities contributing to inflation and deflation. High persistence in several commodities caused by supply side factors (changes in global commodity prices, rising prices of imported raw materials, and tariff adjustment policies by the Government). Inflation persistence is also influenced by expectations dominated by backward looking, as well as the demand side (the COVID-19 pandemic, credit growth, and the BI7DRR interest rate).
Optimization Of The Simple Additive Weighting Method Using The Entropy Method In Tourist Recommendation Decision Support Sophia, Aya
(JAIS) Journal of Applied Intelligent System Vol. 8 No. 3 (2023): Journal of Applied Intelligent System
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i3.9407

Abstract

Travel recommendations are ideas or suggestions of cool places to see while traveling. Depending on the interests and preferences of each visitor, these tourist attractions can be nature tourism, beach tourism, cultural tourism or other interesting places to visit. Tourism recommendations can be offered based on criteria including scenic beauty, street access, distance traveled, children's entertainment venues, ticket prices, menu variations, parking, places to relax, toilets, prayer rooms. Therefore, tourism recommendations are needed for tourists to determine the tourist destinations they want to visit. The SAW method is applied to decision making using many criteria, and to avoid subjectivity in determining the criteria weights, the Entropy method is used. The results of this study indicate that the ranking results from the optimization of the SAW method with the entropy method in supporting tourism recommendation decisions.
Co-Authors Erni Achmad Jasmir, Jasmir Muhammad Safri, Muhammad