Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal CALL Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen
Fahmi, Syahrul
Unknown Affiliation
Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Languange, Linguistic, Communication & Media

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

Found 2 Documents
Search

 1 
Data Mining Menggunakan Multiple Regression untuk Prediksi Harga Saham Netflix Dona Ariyatma, Rama; Fahmi, Syahrul
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 13 No 2 (2023): September 2023
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33020/saintekom.v13i2.419

Abstract

Investing in the stock market is an important and fascinating endeavor, especially when we observe significant increases in certain stocks. Currently, Netflix stock is one of the rising stars and sought after by investors. However, along with the potential for high profits, there are certainly risks of losses that need to be anticipated. To mitigate these risks, an investor must make predictions about future stock prices. One method that can be used is data mining, a data processing technique used to discover patterns in data. In this study, data mining was conducted using the multiple regression algorithm to predict the future price of Netflix stock. Python and Jupyter Notebook were used as tools to process the data, which was collected from January 4, 2010, to March 30, 2023, totaling 3334 data points. After data processing, the model yielded a score of 0.99%, indicating a highly reliable model. Additionally, evaluation using RMSE resulted in a value of 3.73, and MAE had a value of 2.80, both derived from 1334 testing data points. With accurate prediction results and the evaluation conducted, an investor can use these findings as a reference when deciding whether to buy or sell Netflix stock.
A STUDY OF ENGLISH FOOD AND BEVERAGE LEXICONS AT RESTAURANTS AND CAFES IN KUDUS CITY Fahmi, Syahrul; Riyono, Ahdi; Utomo, Slamet
CALL: Journal of Critical Theory, Art, Language, and Literature Vol. 7 No. 1 (2025): CALL
Publisher : Universitas Islam Negeri Sunan Gunung Djati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/call.v7i1.38531

Abstract

This research aims to analyze lexicon choices, word formation, and reference in English culinary lexicon on food and beverage menus in restaurants and cafes in Kudus City. A descriptive qualitative method was employed, collecting data from 25 establishments, Focusing on lexical choices, word formation processes, and references. Semantic theory and morphological analysis were used to interpret the data. The results show that the lexicon contained in the beverage menu is more diverse than the food menu, as beverage variants are used more on menus than food. In addition, compounding is the dominant word formation process found in the menu. The findings illustrate the influence of local culture in the choice of words used on food and beverage menus, as well as showing creative trends in word formation through compounding. This research contributes to the understanding of how the English culinary lexicon is adapted in local cultural contexts and how word formation processes reflect communication needs in the culinary industry, so that people can mention menu names without changing the pronunciation.
Co-Authors Ahdi Riyono Dona Ariyatma, Rama Utomo, Slamet