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Richki Hardi
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Jl. Letjend. TNI. Z.A Maulani No. 9 Damai Bahagia, Kota Balikpapan, Kalimantan Timur 76114
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Multica Science and Technology
Published by Universitas Mulia
ISSN : -     EISSN : 27762386     DOI : https://doi.org/10.47002/mst.v1i1
Core Subject : Science,
Computer Science & IT Energy Library & Information Science Physics
Focus and Scope The journal covers all aspects of science and technology, that is: Science: Bioscience & Biotechnology; Chemistry; Food Technology; Applied Biosciences and Bioengineering; Environmental; Health Science; Mathematics; Statistics; Applied Physics; Biology; Pharmaceutical Science; etc. Technology: Artificial Intelligence; Computer Science; Computer Network; Data Mining; Web; Language Programming; E-Learning & Multimedia; Information System; Internet & Mobile Computing; Database; Data Warehouse; Big Data; Machine Learning; Operating System; Algorithm; Computer Architecture; Computer Security; Embedded system; Cloud Computing; Internet of Thing; Robotics; Computer Hardware; Geographical Information System; Virtual Reality; Augmented Reality; Multimedia; Computer Vision; Computer Graphics; Pattern & Speech Recognition; Image processing; ICT interaction with society; ICT application in social science; ICT as a social research tool; ICT in education
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
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Search results for , issue "Vol 2 No 2 (2022): Multica Science and Technology" : 5 Documents clear
FRUIT IMAGE CLASSIFICATION USING DEEP LEARNING ALGORITHM: SYSTEMATIC LITERATURE REVIEW (SLR) Mirwansyah, Dedy; Arief Wibowo
Multica Science and Technology Vol 2 No 2 (2022): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v2i2.356

Abstract

Systematic literature review (SLR) research studies various classification models with deep learning algorithms on fruit with digital images. In recent years, computer vision and processing techniques are increasingly useful in the fruit industry, especially for quality and color inspection, sizing, and shape sorting applications. Research in this area demonstrates the feasibility of using a machine computer vision system to improve product quality. Utilizing deep learning in the field of image processing or digital image processing, Image Processing is used to assist humans in recognizing and/or classifying objects quickly, and precisely, and can process large amounts of data simultaneously. Classifying fruit through a computerized system using deep learning algorithms with CNN, MASK-RCNN, FASTER-RCNN, and SSD models. Developed on the multilayer perceptron (MLP) layer, the algorithm is processed into two-dimensional data, to the image and is capable of classifying images with larger classes.
APPLICATION OF MACHINE LEARNING IN PREDICTING CHILDREN'S NUTRITIONAL STATUS WITH MULTIPLE LINEAR REGRESSION MODELS Mutammimul Ula; Ananda Faridhatul Ulva; Mauliza; Muhammad Abdullah Ali; Yumna Rilasmi Said
Multica Science and Technology Vol 2 No 2 (2022): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v2i2.363

Abstract

Forecasting is an important part of making plans and making decisions that can predict future events. Forecasting techniques in this study used multiple linear regression. This study aims to predict the number of cases of child nutritional status in children in each region. The purpose of this study was to see the results of predicting the number of children's nutritional status in each region and to make it easier to predict children's nutrition. The research method includes the analysis of the system built and the design of machine learning applications using the Multiple Linear Regression method. Then the system built can help predict the nutritional status of children in Aceh quickly, precisely, and accurately. The data used is data on the nutritional status of children in 2018, 2019, and 2020. Based on the results of forecasting for 2021 based on data obtained in previous years, the predicted results of total nutritional status in 2021 are 449,0912126. The results of this study indicate that the linear regression method obtains the best model results by being able to predict the implementation of machine learning.
APPLICATION OF WEB-BASED APRIORI ALGORITHM FOR DRUG INVENTORY AT KHAIRI FARMA PHARMACY ZIDAN, Muhamad Nur Zidan; Rika Ismayanti; Nariza Wanti Wulan Sari
Multica Science and Technology Vol 2 No 2 (2022): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v2i2.365

Abstract

Inventory has a very important role in increasing sales and service to consumers. The purpose of this study was to determine the information and sales patterns in the form of association rules at a certain period that can provide advice to the pharmacy in managing drug inventory. The algorithm used in this study is a priori to determine the results of sales patterns in the form of association rules. Association rules are obtained by implementing an apriori data mining algorithm to a website-based system using laravel and the resulting calculation results are in the form of Drug Association rules purchased simultaneously. With a minimum support value of 2, there are 214 items in 1 – the itemset that passes the minimum support and 9 association rules formed from all transactions of 519 data with a confidence value of more than 30%. From the resulting Association rules, there are Association rules with the highest confidence value of 66.67% in the form of ketotifen and cupanol pairs purchased simultaneously.
DISINFECTAN STERILIZATION ROOM TO PREVENT MICROCONTROLLER BASED COVID-19 Vidy Vidy; Muhammad Safii
Multica Science and Technology Vol 2 No 2 (2022): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v2i2.570

Abstract

Microcontroller-based Disinfectant Room is a tool that functions for self-sterilization from the Covid-19 virus. This covid-19 outbreak has been rampant in Indonesia since the end of 2019, to prevent the spread of the covid-19 virus in every region in Indonesia, check the temperature, wash hands, and spraying disinfectant liquid. There are still many areas that still use manual spraying of disinfectant liquid, so a tool is needed that aims to facilitate the automatic self-sterilization process. This tool aims to create a disinfectant chamber tool that uses an ultrasonic sensor as an object detector and an Arduino Uno as a controller. The output used in this study is a relay module that is connected to a 12V DC water pump that will spray disinfectant liquid through a mist nozzle. This tool is effective in detecting objects with a distance of 80 cm – 170 cm in front of the sensor.
PLANNING AND INFORMATION SYSTEM DEVELOPMENT STRATEGY USING THE WARD AND PEPPARD METHOD (A CASE STUDY OF CV XYZ) Ahmad Alfi Adianur Giansyah; Sumardi Sumardi; Mundzir Mundzir; Linda Fauziyah Ariyani
Multica Science and Technology Vol 2 No 2 (2022): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v2i2.630

Abstract

To remain competitive globally, businesses must adapt dynamically to changing trends. In response, the necessary action is to implement the use of information technology. While CV XYZ currently has an information system in place, only certain parts of the organization have adopted it, leaving others untouched. Data was gathered through interviews and observations to assess the business environment and the company's information system environment. This research employs the Ward and Peppard method, which includes SWOT analysis, Value Chain analysis, Porter's Five Forces analysis, and McFarlan's Strategic Grid analysis. The study provides strategic recommendations and examines the internal environment, the company's external information systems, and proposed information systems such as HRD information system, After Service information system, Supplier information system, customer service information system, administration information system, and promotion information system. In the McFarlan Strategic Grid mapping, all of these are deemed a priority and feasible for implementation.

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