Results 41 to 50 of about 12,226 (126)

Penerapan Metode Fuzzy Time Series Berbasis Algoritma Novel Dalam Memprediksi Indeks Harga Konsumen Di Provinsi Lampung

Titian Ilmu: Jurnal Ilmiah Multi Sciences
Indeks Harga Konsumen (IHK) menjadi indikator ekonomi yang digunakan sebagai standar untuk mengukur nilai dari rata-rata perubahan harga barang dan jasa yaitu berupa inflasi dan deflasi di tingkat konsumen.
Ahmad Muhaimin, Reni Permata Sari, Ma’rufah Hayati   +2 more
doaj   +1 more source

Performance of Holt-Winters exponential smoothing method in forecasting Indonesian inflation levels

Majalah Ilmiah Matematika dan Statistika
Forecasting inflation data is an important part of economic decision making. Periodic updates are needed considering changes in external factors that affect the inflation rate.
Agista Marshanda, Harmi Sugiarti
doaj   +1 more source

Improved prediction of soil shear strength using machine learning algorithms: interpretability analysis using SHapley Additive exPlanations

Frontiers in Earth Science
The soil’s shear strength is an important parameter that is used frequently throughout the design phase of construction. The conventional method of calculating shear strength in a laboratory is more expensive and time-consuming.
Mahmood Ahmad, Mahmood Ahmad, Mohammad Al Zubi, Hamad Almujibah, Mohanad Muayad Sabri Sabri, Jawad Bashir Mustafvi, Shay Haq, Tariq Ouahbi, Abdullah Alzlfawi   +8 more
doaj   +1 more source

A Comparison of Forecasting Method of Number of Customer Accounts that use the Service Internet Banking using Box-Jenkins Method and Holt’s method [PDF]

Warasan Witthayasat Lae Theknoloyi Mahawitthayalai Mahasarakham, 2019
The purpose of this research was to study and compare the forecasting methods for number of customer accounts that use the service internet banking by using Box-Jenkins method and Holt’s method.
Kanya Bowornchockchai
doaj  

Exploring PM2.5 and PM10 ML forecasting models: a comparative study in the UAE

Scientific Reports
Particulate Matters PM $$_{2.5}$$ and PM $$_{10}$$ present a major health and environmental concern in urban regions. This research compares machine learning and time series models, such as Decision Tree (DT), Random Forest (RF), Support Vector ...
Waad Abuouelezz, Nazar Ali, Zeyar Aung, Ahmed Altunaiji, Shaik Basheeruddin Shah, Derek Gliddon   +5 more
doaj   +1 more source

Wind speed prediction in some major cities in Africa using Linear Regression and Random Forest algorithms

Journal of Nigerian Society of Physical Sciences
Globally, wind energy if properly harnessed, could serve as a source of energy generation in Africa. This study compared the performance of two Machine Learning (ML) algorithms (Linear regression and Random Forest) in predicting wind speed in five major
Timothy Kayode Samson, Francis Olatunbosun Aweda   +1 more
doaj   +1 more source

Comparative Analysis of Machine Learning Models for Predicting Contaminant Concentration Distributions in Hospital Wards

Buildings
As the distribution of indoor contaminants is often heterogeneous, the traditional Wells–Riley equation is inadequate for accurately assessing the infection risk to indoor personnel.
Chonggang Zhou, Yunfei Ding
doaj   +1 more source

Evaluating The Accuracy of Gridded Climate Datasets for Precipitation, Surface Air Temperature, and Sea Surface Temperature in Central Java, Indonesia

Indonesian Journal of Applied Physics
Studies of climate information that rely on accurate and reliable data are essential in hydrometeorological monitoring, early warning, and climate change impacts in areas with varied topography and limited observation data, such as Central Java ...
Iis Widya Harmoko, Muhammad Zainuri, Anindya Wirasatriya, Supari Supari   +3 more
doaj   +1 more source

Comparison Airport Traffic Prediction Performance Using BiGRU and CNN-BiGRU Models

JOIN: Jurnal Online Informatika
COVID-19 pandemic has significantly disrupted the aviation industry, highlighting the critical need for accurate airport traffic predictions. This study compares the performance of BiGRU and CNN-BiGRU models to enhance airport traffic forecasting ...
Willy Riyadi, Jasmir, Xaverius Sika
doaj   +1 more source

COMPARISON OF ARIMA, LSTM, AND GRU MODELS FOR FORECASTING SALES OF HIT AEROSOL PRODUCTS

Pilar Nusa Mandiri
A more accurate forecasting model, such as LSTM, can significantly enhance business efficiency by providing more reliable predictions of future sales, allowing for better inventory management, optimized production schedules, and more precise distribution
Nendi Sunendar, Yan Rianto
doaj   +1 more source