Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal Jurnal Mantik ALMUISY: Journal of Al Muslim Information System
Wahyuning Naja, Naella Nabila Putri
Unknown Affiliation
Computer Science & IT Economics, Econometrics & Finance Languange, Linguistic, Communication & Media

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

Found 2 Documents
Search

 1 
Impact of Palestine-Israel conflict on multinational stock prices use neural network and support vector machine comparison Andriani, Wresti; Gunawan, Gunawan; Wahyuning Naja, Naella Nabila Putri
Jurnal Mantik Vol. 8 No. 1 (2024): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v8i1.5196

Abstract

One form of prolonged geopolitical event is the conflict between Palestine and Israel, which has complex historical, political, and religious roots in the Middle East. This research aims to determine whether this conflict influences the share prices of the companies Unilever, McDonald's, and KFC. These three large companies are known as allies of one of the disputing countries. The method used by the Neural Network is compared with Support Vector Machine to find the best accuracy using RMSE and MAE. The greater the error value, the more affected the company is by this geopolitical factor. As a result, the accuracy of the SVM method is better than NN; the company most affected is KFC, with the RMSE value of 0.111, MAE of 0.020, followed by Unilever with RMSE 0.034, MAE 0.025 then McDonald's with RMSE 0.026 and MAE 0.116, is expected to help investors choose to invest in the company McDonald’s then Unilever.
Integrasi Sistem Cerdas Berbasis AI untuk Penyaluran Bantuan Langsung Tunai yang Tepat Sasaran Andriani, Wresti; Wahyuning Naja, Naella Nabila Putri
ALMUISY: Journal of Al Muslim Information System Vol. 4 No. 1 (2025): ALMUISY: Journal of Al Muslim Information System
Publisher : STMIK Al Muslim

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

Abstract

Penelitian ini mengembangkan sistem cerdas berbasis AI untuk penyaluran Bantuan Langsung Tunai (BLT) yang tepat sasaran menggunakan algoritma Decision Tree, K-Nearest Neighbors (KNN), dan Naive Bayes. Evaluasi awal menunjukkan akurasi rata-rata model berada di bawah 50%, dengan AUC terbaik sebesar 0.47 pada Naive Bayes. Setelah optimasi menggunakan Particle Swarm Optimization (PSO), algoritma KNN menunjukkan peningkatan terbaik dengan AUC sebesar 0.51, sementara Decision Tree mencapai AUC sebesar 0.49. Sistem ini memanfaatkan data seperti penghasilan, kondisi kesehatan, dan status tempat tinggal untuk menentukan kelayakan penerima BLT. Penelitian ini membuktikan bahwa penggunaan metode AI dengan optimasi mampu meningkatkan efisiensi dan akurasi dalam mendistribusikan BLT secara lebih tepat sasaran, memberikan kontribusi signifikan pada perbaikan sistem bantuan sosial.
Co-Authors Andriani, Wresti Gunawan Gunawan