Article Per Year (5 Year)
p-Index From 2020 - 2025
0.817
P-Index
This Author published in this journals
All Journal Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) BAREKENG: Jurnal Ilmu Matematika dan Terapan Journal of Science and Technology Mathematics and Applications (MAp) Journal
Ul Hasanah, Fitri Rahmah
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Environmental Science Mathematics Mechanical Engineering Medicine & Pharmacology Physics Transportation

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
APLIKASI TEOREMA HUKUM LEMAH BILANGAN BESAR PADA PEMBUKTIAN TEOREMA APROKSIMASI WEIERSTRASS Ul Hasanah, Fitri Rahmah; Putri, Darvi Mailisa
MAp (Mathematics and Applications) Journal Vol 3, No 2 (2021)
Publisher : Universitas Islam Negeri Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (316.943 KB) | DOI: 10.15548/map.v3i2.3354

Abstract

Teorema aproksimasi weierstrass dinyatakan sebagai fungsi kontinu pada selang tertutup dan terbatas yang daoat didekati dengan barisan suku banyak. Salah satu pembuktian teorema ini dengan menggunakan polinomial Bernstein ). Oleh karena,  dimana  untuk ukuran  cukup besar maka ) dirumuskan menjadi , dimana berlaku hukum lemah bilangan besar dengan . Oleh karena itu, dalam tulisan ini dibahas pembuktian teorema aproksimasi weierstrass dengan hukum lemah bilangan besar.Kata Kunci: bilangan besar, Weierstrass, polinomial Bernstein.
Pemodelan Harga Saham Menggunakan Geometric Brownian Motion Ul Hasanah, Fitri Rahmah; Putri, Darvi Mailisa
JOSTECH: Journal of Science and Technology Vol 2, No 1: Maret 2022
Publisher : UIN Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/jostech.v2i1.3801

Abstract

Stocks are something that is still interesting to this day to be discussed. Because the price tends to fluctuate, it is necessary to make predictions for the future in order to reduce losses for investors. Geometric Brownian Motion is a model for predicting stock prices by conducting a study through stock return data obtained. Stock return data is required to meet the assumptions of Geometric Brownian Motion. After that, the average value and volatility of the stock return data of PT. Aneka Tambang Tbk. from January 04th to June 30th 2021 amounted to  -0,002376925 and 0,0212161. Through stock return parameters and data generation with a standard normal distribution, a model that is very close to the actual stock price data is obtained.
Pemodelan Indeks Pembangunan Manusia (IPM) dengan Regresi Logit dan Probit Putri, Darvi Mailisa; Ul Hasanah, Fitri Rahmah; Jannah, Miftahul; Hasibuan, Lilis Harianti
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 10 No 2 (2022): VOLUME 10 NOMOR 2 TAHUN 2022
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v10i2.31438

Abstract

Penelitian ini mengkaji tentang variabel yang mempengaruhi Indeks Pembangunan Manusia (IPM) di provinsi Sumatera Barat. Regresi logit dan probit menjadi model yang akan diterapkan pada kasus ini. Berdasarkan kedua model diketahui bahwa variabel Usia Harapan Hidup (UHH) adalah variabel yang mempengaruhi Indeks Pembangunan Manusia (IPM) secara signifikan. Model regresi probit menjadi model terbaik melalui pemilihan nilai Akaike’s Information Criterion (AIC) terkecil.
COMPARISON OF DOUBLE EXPONENTIAL SMOOTHING AND FUZZY TIME SERIES MARKOV CHAIN IN FORECASTING FOREIGN TOURIST ARRIVALS Putri, Darvi Mailisa; Afrimayani, Afrimayani; Hasibuan, Lilis Harianti; Ul Hasanah, Fitri Rahmah; Jannah, Miftahul
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1817-1828

Abstract

Foreign tourist arrivals are one of the factors that make a positive contribution to a country's economy, especially the addition of foreign exchange. This activity is important for the tourism industry and the government to make policies for progress in the tourism sector. This research aims to forecast data on foreign tourist arrivals, especially land routes. This data set, which is a monthly time series covering the period from January 2018 to October 2023, is sourced from the Central Statistics Agency (BPS). The DES technique is a method that quickly adapts to changes in data patterns and can lessen the impacts of random fluctuations, resulting in more stable estimates. Meanwhile, the FTS-MC approach can handle large data variations by utilizing fuzzy sets. Furthermore, combining fuzzy time series with Markov Chains increases forecast accuracy by taking into account state transitions and probability. The research demonstrates that the DES method produces the MAPE value of 0.108530 or 10% which is obtained from the alpha value of 0.9 and beta 0.2. The MAPE 0.108530 means that the ability of the forecasting model is classified as a good category. In the FTS-MC method, the forecast data is close to the actual data. This is indicated by the MAPE value obtained of 0.086850 or 8%, which means that the ability of the forecasting model is very good. Based on the analysis of the two methods, it is concluded that the FTS-MC method is better applied to data on land-based foreign tourist arrivals.
Co-Authors Afrimayani, Afrimayani Darvi Mailisa Putri Hasibuan, Lilis Harianti Miftahul Jannah