Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal International Journal Of Science, Technology & Management (IJSTM) International Journal of Economics, Accounting, and Management
Gunawan, Yogi
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 Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Transportation

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

Found 2 Documents
Search

 1 
Sentiment Analysis of Twitter towards the 2024 Indonesian Presidential Candidates Using the Naïve Bayes Algorithms Gunawan, Yogi; Purnama, Iwan; Rohani, Rohani
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.v5i4.1154

Abstract

The increasing use of social media (Twitter) has made it a platform for the public to express their views on the Indonesian presidential candidate in the 2024 elections. The sentiment expressed through comments on Twitter provides important insights into the public perception of the candidates. However, given the volume and speed at which information is disseminated on social media, manual analysis of this sentiment becomes impractical. Therefore, the use of the Naïve Bayes algorithm for automatic sentiment analysis is considered essential to understanding voter support and preferences. The study aims to analyze Twitter users' sentiments towards three Indonesian presidential candidates in 2024, Anies, Ganjar, and Prabowo, using the Naïve Bayes algorithm. We categorize the results of this analysis into three sentiment categories: positive, negative, and neutral. The methods used in the study involved collecting Twitter comment data related to the three candidates, pre-processing data, labeling data, applying the Naïve Bayes algorithm for the classification of sentiment, and evaluation of the performance of the algorithm performed by calculating the level of accuracy. The results of the research showed that the Naïve Bayes algorithm was able to classify sentiments with fairly high precision, namely 75.54% for Anies, 82.74% for Ganjar, and 75.24% for Prabowo. The conclusion of this study is that sentimental analysis using the Naïve Bayes algorithm can provide significant insights into voter preferences and support. The sentimental data generated can serve as a strong foundation for decision-makers to design campaign strategies that are more effective and responsive to public perception. This research also opens up opportunities for further development in the use of sentimental analysis techniques in politics and campaigns.
Quality Control Management in Processed Beef Production in MSMEs (PT XYZ) Rangga Mahardika; Azmi, Nadia Aurin; Oktavia, Berliana; Giofadli Nugraha, Muhamad; Gunawan, Yogi; Rahman, Fatul; Selma Agnia Elfath, Amadea; Novintri, Riska
International Journal of Economics Accounting and Management Vol. 2 No. 2 (2025): IJEAM - July 2025
Publisher : PT. INOVASI TEKNOLOGI KOMPUTER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60076/ijeam.v2i2.1330

Abstract

This study focuses on the design and implementation of a quality control management system for the production of rendang at PT XYZ, a local SME. The objective of this research is to analyze and design an integrated quality control system using Statistical Process Control (SPC) tools, including P-control charts and Fishbone diagrams. Data collection was carried out through direct observation, interviews with the owner, and documentation of production records from February 2025. The study found that although the production process was within statistical control limits, there were still variations in product quality, especially in taste and aroma, as well as packaging issues. This research emphasizes the importance of a structured quality management system to enhance product consistency and reduce defects. Recommendations for improvement include formalizing standard operating procedures (SOPs), conducting regular worker training, and adopting modern equipment to ensure more uniform production conditions. The findings of this study provide practical insights for SMEs in the food processing industry to improve product quality and operational efficiency, while also contributing to the development of quality management systems in the local food production industry
Co-Authors Azmi, Nadia Aurin Giofadli Nugraha, Muhamad Iwan Purnama Novintri, Riska Oktavia, Berliana Rahman, Fatul Rangga Mahardika Rohani Rohani Selma Agnia Elfath, Amadea