Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal International Journal Of Science, Technology & Management (IJSTM) Jurnal Pranata Biomedika
Syahputra, Arief
Unknown Affiliation
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Medicine & Pharmacology Transportation

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Comparative Analysis of Naïve Bayes and K-Nearest Neighbors Algorithms in Predicting Public Interest in Electric Motorcycles Syahputra, Arief; Zuhri Harahap, Syaiful; Nasution , Marnis
International Journal of Science, Technology & Management Vol. 5 No. 4 (2024): July 2024
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v5i4.1134

Abstract

Concerns about global warming and the need for sustainable transport solutions have led to the emergence of electric vehicles as an alternative to conventional vehicles. These vehicles offer cleaner and more efficient transportation, especially in urban areas. However, high costs in some countries, such as Indonesia, hinder their adoption. Electric motorcycle companies use previously recorded data to predict customer interest in purchasing their products. Based on these forecasts, business owners make decisions about the quantity of goods to supply. Researchers are increasingly using machine learning algorithms to study consumer behavior and predict demand for a variety of products, including electric motorcycles. The researchers have used this data-based method to analyze large amounts of consumer data, including online survey responses and reviews, as well as other sources. The study aims to perform a comparative analysis of the performance of the Naïve Bayes and K-Nearest Neighbors algorithms to predict public interest in electric motorcycles in Labuhanbatu district. We will perform a comparative analysis based on the performance evaluation matrix (accuracy, precision, recall, and f1 score) to determine the most suitable algorithm. The phases of the research methods included: data collection, exploratory data analysis, data preprocessing, splitting data, implementation of naïve bayes and k-nearest neighbors, and evaluation. The results showed that Naïve Bayes achieved an accuracy of 31.13%, precision of 83.33%, recall of 4.63%, and f1-score of 8.77%. In contrast, K-Nearest Neighbors attains an accuracy of 71.52% and a precision of 71.52%, recall 100%, and f1 score of 83,40%. According to the research results, K-nearest neighbors showed much better results in terms of accuracy, recall, and F1 scores. These results demonstrate that K-nearest neighbor is more effective in detecting public interest in electric motorcycles, and it strikes a better balance between identifying all positive cases and avoiding predictive errors.
“PERBEDAAN HASIL PEMERIKSAAN TOTAL PROTEIN MENGGUNAKAN SAMPEL SERUM DAN PLASMA EDTA” Munabari, Faiza; Syahputra, Arief
Jurnal Pranata Biomedika Vol 3, No 2: September 2024
Publisher : Universitas Katolik Soegijapranata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24167/jpb.v3i2.5108

Abstract

Kadar total protein didalam darah dapat diketahui dengan pemeriksaan dilaboratorium klinik. Pemeriksaan total protein dapat menggunakan darah vena yang dibuat plasma atau serum. Bahan sampel yang dapat digunakan untuk pemeriksaan total protein yaitu serum, plasma, cairan serebrospinal dan urine. Pemeriksaan menggunakan sampel plasma dapat menyebabkan kadar total protein menjadi lebih tinggi 3 – 5 % karena pengaruh fibrinogen dalam plasma. Penelitian ini bertujuan untuk mengetahui perbedaan kadar total protein dengan menggunakan sampel serum dan plasma.Penelitian dilakukan dengan menggunakan metode Biuret. Dalam pemeriksaan total protein ini yang sering digunakan adalah metode Biuret karena lebih mudah dikerjakan dan hasilnya bersesuaian dengan metode Kjeldahl. Jenis penelitian ini observasi analitik dengan menggunakan 30 sampel.Dari hasil penelitian didapatkan rata - rata kadar total protein dengan sampel serum 77,36 g/dl. Sedangkan rata - rata kadar total protein dengan sampel plasma EDTA adalah 81,30 g/dl. Dari hasil analisis uji beda pada kedua variabel (Serum dan Plasma EDTA) didapatkan P-value ( P-value 0,05 ) yang artinya Ho ditolak dam ha diterima sehingga dapat disimpulkan bahwa ada perbedaan yang signifikan.Dari hasil penelitian didapatkan hasil bahwa terdapat perbedaan yang bermakna antara kadar total protein dengan sampel serum dan plasma EDTA dimana kadar dalam plasma lebih tinggi dari pada serum. Bagi tenaga analis hendaknya dalam pemeriksaan total protein sebaiknya menggunakan serum sebagai sampelnya.
Co-Authors Munabari, Faiza Nasution , Marnis Zuhri Harahap, Syaiful