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All Journal Jurnal Ilmiah Matrik Aptekmas : Jurnal Pengabdian Kepada Masyarakat
Qois Al Qorni
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PELATIHAN PEMBELAJARAN DASAR PEMROGRAMAN MENGGUNAKAN BAHASA PYTHON Qois Al Qorni; Deka Putra Pamungkas; Suluh Arif Wibowo; Muhammad Fachrurrozi Syawalludin; Teo Yulio Sihotang; Ery Hartati
Aptekmas Jurnal Pengabdian pada Masyarakat Vol 6 No 2 (2023): Aptekmas Volume 6 Nomor 2 2023
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36257/apts.v6i2.6754

Abstract

In today's digital era, basic programming skills are in high demand in the workplace. Many companies are looking for employees who have basic programming skills to develop more sophisticated applications and technologies. Therefore, it is important for SMK students to have basic programming skills in order to compete in the world of work. This effort can help improve the basic programming skills of SMK children so that they can compete in the increasingly tight world of work and prepare themselves for a better future. This activity involves the stages of pre-test, material delivery, discussion, and post-test. The results show that the students are very happy with this training, which shows that in the first and second questions, the students get new knowledge with a simple explanation carried out by the speaker when conducting training, referring to the initial question before programming training, and after carrying out the training process, the students have 100% gained knowledge. Community service activities entitled "Basic Programming Learning Training Using Python Language" at SMK Bina Cipta Palembang have been successfully implemented. The training participants responded positively to this activity. The socialization of basic programming using Python has provided new knowledge for participants, which can increase creativity and knowledge in utilizing Python. The results of this training provide benefits and new knowledge for students
Pendekatan Algoritma Naïve Bayes dan Support Vector Machine dalam Menganalisis Tanggapan Terhadap Penutupan Tik Tok Shop Fandi kurniawan; Qois Al Qorni
Jurnal Ilmiah Matrik Vol. 25 No. 3 (2023): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/jurnalmatrik.v25i3.2732

Abstract

The development of information technology, especially in social media such as TikTok, has had a significant impact on people's shopping behavior patterns. Sentiment analysis is aimed at understanding general views regarding the closure of the TikTok Shop, describing positive or negative opinions. The algorithms used are Naïve Bayes and Support Vector Machine (SVM) to analyze responses to the closure of the TikTok Shop. The research methodology involves the process of crawling the Twitter dataset with the keyword "Tik Tok Shop", data cleaning, sentiment labeling, model building, and performance testing. The results of the sentiment analysis are parsed and analyzed to describe the general sentiment towards the closure of the Tik Tok Shop. The conclusion results show that the Naïve Bayes algorithm achieved an accuracy level of 97.91%, with positive recall of 100%, positive precision of 96.30%, negative recall of 95.42%, and negative precision of 100%. Meanwhile the SVM algorithm achieved an accuracy of 91.29%, with a positive recall of 100%, positive precision of 86.19%, negative recall of 80.92%, and negative precision of 100%. Overall, Naïve Bayes provides the highest accuracy results of 97.91%, while SVM provides an accuracy of 91.29%.
Co-Authors Awalludin, Nur Deka Putra Pamungkas Fandi kurniawan Hartati, Ery Suluh Arif Wibowo Teo Yulio Sihotang