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All Journal Jurnal Informatika Universitas Pamulang Infotronik : Jurnal Teknologi Informasi dan Elektronika
Gunawansyah
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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PREDIKSI PERTUMBUHAN UMKM DI KOTA BANDUNG MENGGUNAKAN METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE Sri Hanifah, Nurul; Gunawansyah
Infotronik : Jurnal Teknologi Informasi dan Elektronika Vol 9 No 2 (2024): Vol 9 No 2 Tahun 2024
Publisher : Universitas Sangga Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32897/infotronik.2024.9.2.3839

Abstract

This study aims to predict the number of micro, small, and medium enterprises (MSMEs) in Bandung City using the ARIMA (AutoRegressive Integrated Moving Average) method. MSMEs play a crucial role in the local economy, particularly in creating jobs and driving economic growth. Predicting the number of MSMEs is important for understanding future trends to support better planning and policy-making. The data used in this study includes the number of MSMEs in Bandung City from 1990 to 2023. The ARIMA method was chosen for its ability to handle time series data with seasonal patterns and trends and for providing accurate predictions based on historical data. The ARIMA (2,1,0) prediction model was selected as the best model, with model evaluation results showing an MAE value of 666.9431 and a MAPE value of 7.55%. The accuracy of this study using the ARIMA (2,1,0) model is 92.45%. Based on the research findings, the AutoRegressive Integrated Moving Average (ARIMA) method can be used to predict the number of Micro, Small, and Medium Enterprises (MSMEs) in Bandung City.
Pengaruh Smoothing Data Terhadap Hasil Prediksi Volume dan Ritasi Sampah di Kota Bandung Menggunakan Metode Regresi Linear Gunawansyah; Ihsan Fauzi
Jurnal Informatika Universitas Pamulang Vol 9 No 3 (2024): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v9i3.43271

Abstract

The waste problem is very important in big cities, especially Bandung. The population, people's lifestyles and waste management that has not been carried out professionally are a challenge in itself. One of the preparatory steps to deal with the waste problem is to predict the development of waste volume. In this study, a statistical time series approach, namely the linear regression method, is used to predict the volume and transportation of waste in the city of Bandung. In the prediction process, data processing before being used in the prediction process plays an important role, one of which is data smoothing. A process to smooth the data using the moving average method with intervals of 2.3 and 4 and moving averages with weights of 242 and 12421 will be used to see its effect on the prediction results. Scenario 1 of the data used is all monthly data in the dataset time range and scenario 2 uses the same month's data for each year to predict the results of the month in the following year. The results of the volume and transportation predictions of waste between the best results from the Smoothing method and the results without going through the data smoothing process in scenario 1 show less significant results, namely less than 1%, while in scenario 2 it shows quite significant results, namely around 10% when compared to the actual data. Patterns and data ranges affect the final result from scenarios above.
Co-Authors Ihsan Fauzi Sri Hanifah, Nurul