Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
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All Journal Indonesian Journal of electronics, electromedical engineering, and medical informatics Teknomekanik
Tri Lestari
Department of Information Technology, Politeknik Negeri Padang, Indonesia
Computer Science & IT Control & Systems Engineering Engineering Mechanical Engineering

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Data Communication Stability Test a Data Acquisition System (DAQ) for Inpatient Rooms Sentagi Sesotya Utami; Winny Setyonugroho; Iman Permana; Tri Lestari; Muhammad Dian Saputra Taher; Gilang Ari Widodo; Akhmad Khanif
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 5 No 1 (2023): February
Publisher : Department of electromedical engineering, Health Polytechnic of Surabaya, Ministry of Health Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v5i1.268

Abstract

In inpatient services, patient beds are usually limited by curtains or partitions to maintain the patient's safety. At the time of data collection, the barrier or barrier is considered to the effectiveness of the results and validation of medical device sensor data. This study aims to explain the results of the reliability testing of Bluetooth and the internet on hardware and CovWatch applications. This study is action research; comparison is used using devices (tools) with different specifications. Testing internet and Bluetooth connectivity from the CovWatch unit and applications installed on the Samsung A01 devices, Redmi Note 10 and Oppo A57, have mixed results. Hardware CovWatch and Samsung A01 are considered the best in acquiring vital sign data, while Redmi Note 10 and OPPO A57 are not good because some data cannot be obtained so that it does not appear on the monitor unit.
Comparative analysis of the least squares method and double moving average technique for forecasting product inventory Surfa Yondri; Dwiny Meidelfi; Tri Lestari; Fanni Sukma; I.S Mutia
Teknomekanik Vol. 7 No. 1 (2024): Regular Issue
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/teknomekanik.v7i1.29672

Abstract

The cosmetics industry necessitates efficient inventory management to balance customer demand with stock control. This case study explores how Liza Cosmetics Shop optimized inventory for Lip Cream Implora 01, a popular product, using data-driven forecasting techniques. Traditional trend-based methods often resulted in inaccurate forecasts. This study proposed implementing the SDLC Waterfall Model to apply two forecasting techniques: Least Squares and Double Moving Average. Historical sales data (April 2021 - June 2022) was analyzed to identify demand patterns, seasonality, and trends. The Least Squares method was chosen for its suitability in capturing stable, linear relationships between sales and time, while the Double Moving Average method catered to data exhibiting both long-term trends and short-term fluctuations. Rigorous testing using white-box and black-box methods ensured the accurate functionality and system behavior of the implemented models. The Mean Absolute Percentage Error (MAPE) determined the method best suited for predicting July 2022 demand. This case study contributes insights into data-driven inventory management in cosmetics, highlighting benefits such as optimized stock levels, reduced costs, and enhanced customer satisfaction through improved demand fulfillment. This studys’ limitations including unforeseen marketing campaigns and economic fluctuations impacting forecasts were acknowledged. Despite these challenges, the study emphasizes the potential of data-driven techniques to optimize inventory management and meet customer demands effectively.
Co-Authors Akhmad Khanif Dwiny Meidelfi Fanni Sukma Gilang Ari Widodo I.S Mutia Iman Permana Muhammad Dian Saputra Taher Surfa Yondri Utami, Sentagi Sesotya Winny Setyonugroho