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All Journal JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) Jurnal Algoritma
Ilham Nur Ramdani
Universitas budi luhur
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Perbandingan Algoritma Single Exponential Smoothing Dan Simple Moving Average Dalam Peramalan Penjualan Kopi Ilham Nur Ramdani; Nawindah
Jurnal Ilmiah Teknologi Infomasi Terapan Vol. 11 No. 2 (2025)
Publisher : Universitas Widyatama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33197/jitter.vol11.iss2.2025.2431

Abstract

Increasingly fierce competition, operational management, especially raw material management, has become a major challenge for many businesses. Therefore, companies or businesses that want to achieve maximum profits need a good and accurate sales prediction strategy for the coming period. Good predictions not only help in anticipating market needs, but also optimize inventory management to minimize the risk of losses due to excess or shortage of stock. The use of good forecasting algorithms is the main key so that companies can analyze historical data in depth to identify relevant patterns and trends so that they can improve operational efficiency. This research aims to compare two forecasting algorithm methods, namely Exponential Smoothing and Moving Average, in determining which method is superior in terms of sales prediction accuracy. The data used in this research comes from historical sales of Kopi Cucu Eyang Coffee Shop. Performance evaluation of the two algorithms was carried out using three main metrics, Mean Absolute Deviation (MAD), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE). The research results show that the Moving Average method is superior in MAPE accuracy with an average of 23%. On the other hand, Single Exponential Smoothing shows superiority in balancing MAD and MSE in certain products. It is hoped that this research can provide useful recommendations to improve inventory management efficiency and support better business decision making.
Analisis Komparatif Overhead Kinerja CPU pada Lingkungan Bare Metal, Docker Container, dan KVM Virtual Machine Berbasis Linux Ubuntu Ammanda Putri Nurhalizah; Ilham Nur Ramdani; Imelda Imelda
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.3411

Abstract

Virtualization and containerization technologies are key solutions for improving the efficiency of modern computing infrastructure. This study aims to analyze a comparison of CPU performance overhead across three computing environments: Bare Metal, Docker Containers, and KVM Virtual Machines running on Ubuntu 24.04 LTS. Testing was conducted using Sysbench with the Events Per Second (EPS) metric as an indicator of throughput, with Bare Metal serving as the baseline. The results show that Docker Containers exhibit near-native performance with an overhead of -4.44%, indicating a slight performance improvement over the baseline due to efficient resource management. Conversely, the KVM Virtual Machine experienced a significant performance drop with an overhead of 81.78%. These findings suggest that containers are more efficient in utilizing CPU resources, while KVM Virtual Machines offer higher system isolation at the cost of reduced performance. This study provides a quantitative evaluation to serve as a basis for selecting computing technologies based on performance and isolation requirements.
Co-Authors Ammanda Putri Nurhalizah Imelda, Imelda nawindah