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Richki Hardi
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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 4 Documents
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Search results for , issue "Vol. 2 No. 1 (2022): Multica Science and Technology" : 4 Documents clear
APPLICATION OF INTELLIGENT SYSTEM WITH BACKPROPAGATION MODEL IN CLOUD IMAGE CLASSIFICATION Mulyadi Mulyadi; Ichwan, Muhammad; Rizka, Muhammad; Ula, Mutammimul
Multica Science and Technology (ACCREDITED-SINTA 5) Vol. 2 No. 1 (2022): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v2i1.323

Abstract

The clouds have different patterns on each type and each type has different properties. The introduction of the type, shape, and nature of the cloud is indispensable in the weather forecasts so that the clouds can be classified. There are several methods used in the image classification process that is the method of the artificial neural network Backpropagation. The method of Backpropagation is one of the methods used for the classification process, in this research Backpropagation used on the training and testing process for the introduction of cloud imagery aimed at determining the type of cloud, before the second These stages are carried out imagery through the preprocessing process. From the training conducted using the Backpropagation method shows that this method generates the best weight value and saves that value into the database to do the testing process using a neural network Backpropagation. In addition, Backpropagation also has the ability to reduce errors by continuously correcting the weight until reaching the maximum target. Data used for training data as many as 92 cloud type image with each type of 10 imagery. In this study obtained a system success rate of 60.6%.
IMPLEMENTATION OF MACHINE LEARNING USING THE K-NEAREST NEIGHBOR CLASSIFICATION MODEL IN DIAGNOSING MALNUTRITION IN CHILDREN Mutammimul Ula; Ananda Faridhatul Ulva; Ilham Saputra; Mauliza Mauliza; Ivan Maulana
Multica Science and Technology (ACCREDITED-SINTA 5) Vol. 2 No. 1 (2022): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v2i1.326

Abstract

The problem faced today is the lack of nutrition for children which causes stunting. One way to prevent stunting problems is to provide input to the community in Aceh for the importance of providing adequate nutrition for children. This study classifies toddlers who are identified as stunting with the K-NN model technology which is modeled in machine learning, the results are grouped. The purpose of this study was to determine the detection of malnutrition in toddlers and to classify data on malnutrition in toddlers using the k-means clustering method and the system that was built could be used as a reference to monitor the growth and development of children. Then in classifying malnutrition in children based on the results of the nutritional status criteria in toddlers, it can be known based on the index of Body Weight for Age (W/U), Height for Age (TB/U), and Weight for Height (W/TB). by entering data values ??from weight, height and gender of toddlers. The purpose of this study was to determine the detection of malnutrition under five at the Cut Meutia Hospital Kab. North Aceh. The process in the initial data analysis of Mr. ID, baby's name, gender, age, weight (kg), height (cm), the data to be classified for training data are 40 children in each region / village. In the assessment of nutritional status, it is classified as Malnutrition less than 3 SD or 70%, Malnutrition - 3 SD to < - 2 SD or 80%, Good Nutrition -2 SD to +2 SD, Over Nutrition >+2 SD. The results of the final score obtained are euclidean distance with a value of 1.3 with a ranking of malnutrition, age 1.6 months, weight (weight) 0.852, TB (height) 4.556 with euclidean distance with a value of 1.3 with a low ranking. For the second test data, age is 2.8 months, BB (weight) 0.222, TB (height) 4.556 with Euclidean distance with a value of 1.3 with a good rating of 0.778. The results of this study can be classified in children to children for each region in each region, village and sub-district of each Puskesmas in North Aceh Regency
THE EFFECT OF FIELD WORK PRACTICES ON WORK INTEREST OF CLASS XII STUDENTS OF ACCESS NETWORK ENGINEERING SKILLS COMPETENCE AT SMK NEGERI 5 TELKOM BANDA ACEH Husnizar Husnizar; Fathiah, Fathiah; Agus Fachruzi
Multica Science and Technology (ACCREDITED-SINTA 5) Vol. 2 No. 1 (2022): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v2i1.327

Abstract

Education is a foundation for improving the quality of human resources. Quality education will be able to produce superior human resources from every aspect of life. One of the educations that is responsible for creating quality human resources is Vocational High School (SMK) education. Vocational learning load includes Face-to-face (TM) School Practice (PS) activities and Practical Activities in DU/DI. Field work practices can train and support the skills that students have learned while at school, so that they can be developed in the world of work. But apart from that, there are some SMKs that pay less attention to the implementation of the field work practice. The discrepancy between the material studied at school and what is faced by students in DU/DI. This study aims to determine how much influence field work practices have on the work interest of class XII students of Access Network Engineering Skills Competence at SMK Negeri 5 Telkom Banda Aceh. This study uses a quantitative approach with the method used is Ex Post Facto. The subjects of this study were 48 students of the Access Network Engineering Department. The instrument used is a questionnaire. The results of this study indicate that there is a positive influence between field work practices and work interest of class XII students of Access Network Engineering expertise competence at SMKN 5 Telkom Banda Aceh by 39.8%, while 60.2% is influenced by other factors. This study uses a quantitative approach with the method used is Ex Post Facto. The subjects of this study were 48 students of the Access Network Engineering Department. The instrument used is a questionnaire. The results of this study indicate that there is a positive influence between field work practices and work interest of class XII students of Access Network Engineering expertise competence at SMKN 5 Telkom Banda Aceh by 39.8%, while 60.2% is influenced by other factors. This study uses a quantitative approach with the method used is Ex Post Facto. The subjects of this study were 48 students of the Access Network Engineering Department. The instrument used is a questionnaire. The results of this study indicate that there is a positive influence between field work practices and work interest of class XII students of Access Network Engineering expertise competence at SMKN 5 Telkom Banda Aceh by 39.8%, while 60.2% is influenced by other factors.
THE UTILIZATION OF COMPLEX PROPORTIONAL ASSESSMENT (COPRAS) IN DETERMINING THE SELECTION OF THE BEST SPEAKER Muhammad Rafli Nur Alam; Richki Hardi; Sumardi Sumardi
Multica Science and Technology (ACCREDITED-SINTA 5) Vol. 2 No. 1 (2022): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v2i1.629

Abstract

Decision-making in choosing the appropriate sound system involves numerous considerations to achieve acceptable outcomes or quality. There are many critical factors influencing the selection of speaker models, such as the required program features, brand, design, power, and price. In this study, we introduce the Complex Proportional Assessment (COPRAS) method as a solution for making effective and high-quality decisions when selecting the best alternatives based on predefined criteria. The COPRAS method is employed to analyze various different alternatives and estimate their utility values. The case study presented in this research involves identifying the best alternatives according to the criteria within the context of sound systems. The COPRAS method aids in evaluating alternatives by taking into account the relative weights of each relevant attribute. Consequently, the use of the COPRAS method in selecting the best sound system has proven to be effective and beneficial. This method assists in addressing complexity, enhancing objectivity, and yielding more informative and accurate decisions.

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