Garuda - Garba Rujukan Digital

Masrizal Masrizal

Universitas Labuhanbatu

Author-ID : 2728639

Aerospace Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Public Health Social Sciences Other

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Evaluation of Machine Learning Using The K-NN Algorithm to determine The Quality of Meat before consumption Feronika Feronika; Masrizal Masrizal; Ibnu Rasyid Munthe
Jurnal Riset Informatika Vol 5 No 2 (2023): Priode of March 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i2.467

Meat is one of the sources of animal protein for humans, and one of the requirements that must be met so that the human body does not lack protein, especially animal; this protein can be obtained from beef, chicken, and other meats, but the most important thing here is the content contained in meat, whether it has been contaminated with chemicals, e.g., chicken that has been injected with chemicals that cause the chicken to look fat, or beef whose flexibility has decreased and the pH is getting more acidic. This research tries to predict meat quality by looking at two parameters: flexibility and acidity. The programming language used is R Language, using the k-NN method or Algorithm to determine the meat's condition suitable for consumption. In detail, it will be processed in Machine Learning using the k-NN Algorithm; there are two criteria for consumption of meat, namely good or not good for consumption; in detail, the output will be explained using a specific graph using a plot function, and array data will be specifically classified to represent values. The value of 2 variables, namely feasible or not suitable for consumption.

A Real-Time Web Information System Based on A Global Positioning System for Monitoring Environmental Pollution Eko Gustriyadi; Volvo Sihombing; Masrizal Masrizal; Puput Dani Prasetyo Adi Adi
Jurnal Riset Informatika Vol. 5 No. 1 (2022): December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.204

This research will discuss monitoring pollution in waterways in real time based on GPS. A website-based information system is an essential factor for information media, not only database-based but can be communicated with GPS. GPS is a satellite system that can determine the point of an area with Longitude and Latitude parameters. The Global Positioning System is one of the parameters used in this study. Longitude and Latitude are the primary keys to getting the point in a particular area or point. In research, this location is used in sensor or environmental pollution monitoring. In this paper, we try to review the projects carried out and perform analysis, management, and governance on the server and local host. The program is made by developing the FrontEnd and BackEnd sides. Development can be done on Desktop-based programming and then extended to Mobile by manipulating and modifying programs using Javascript, JSON, and other building scripts for better performance and suitable for deployment on various platforms such as Mobile-based. This system is very efficient in determining various parameters, for example, the environmental pollution factor. From testing, the GPS data is not perfect, all data can be sent, but the accuracy of GPS data can reach 96%. This is due to data errors during uplinking and downlinking data.

Evaluation of Machine Learning Using the K-NN Algorithm To Determine the Quality of Meat Before Consumption Feronika Feronika; Masrizal Masrizal; Ibnu Rasyid Munthe
Jurnal Riset Informatika Vol. 5 No. 2 (2023): March 2023
Publisher : Kresnamedia Publisher

Meat is one of the sources of animal protein for humans, and one of the requirements that must be met so that the human body does not lack protein, especially animal; this protein can be obtained from beef, chicken, and other meats, but the most important thing here is the content contained in meat, whether it has been contaminated with chemicals, e.g., chicken that has been injected with chemicals that cause the chicken to look fat, or beef whose flexibility has decreased and the pH is getting more acidic. This research tries to predict meat quality by looking at two parameters: flexibility and acidity. The programming language used is R Language, using the k-NN method or Algorithm to determine the meat's condition suitable for consumption. In detail, it will be processed in Machine Learning using the k-NN Algorithm; there are two criteria for consumption of meat, namely good or not good for consumption; in detail, the output will be explained using a specific graph using a plot function, and array data will be specifically classified to represent values. The value of 2 variables, namely feasible or not suitable for consumption.

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Journal : Jurnal Riset Informatika