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All Journal Equivalent : Journal of Economic, Accounting and Management Electronic Integrated Computer Algorithm Journal
Sinaga, Kristin
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Social Sciences

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Sentiment Analysis of Hate Speech against DPR-RI on Twitter Using Naive Bayes and KNN Algorithms Munthe, Joy Lousia Brigitha; Sinaga, Kristin; Santi Prayudani
Electronic Integrated Computer Algorithm Journal Vol. 2 No. 1 (2024): VOLUME 2, NO 1: OCTOBER 2024
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/enigma.v2i1.39

Abstract

According to surveys, the rise in social media users has resulted in an increase of hate speech, and Twitter is one of the most popular platforms for this type of speech. The tweet feature on Twitter enables users to make repeated instances of hate speech, making Twitter data very intriguing to analyze. This study aims to investigate whether a tweet contains hate speech towards the Indonesian House of Representatives (DPR-RI). The research employed crawling techniques to gather data from Twitter using the Twitter API feature. The Naïve Bayes algorithm was applied, and the results were compared with the accuracy of the K-Nearest Neighbor. After preprocessing, the total data obtained was 1,494, with 956 test data and 538 training data. The study revealed that Twitter users' sentiment towards DPR-RI was 49.2% positive and 50.8% negative sentiment when tested using Naïve Bayes. Meanwhile, KNN showed 23.4% positive and 76.6% negative sentiment. The high negative sentiment in both classifiers suggests that Twitter users frequently express hate speech towards DPR-RI. Naïve Bayes algorithm showed the highest prediction accuracy at 98.32%, while the K-Nearest Neighbor algorithm had an accuracy of only 62.84%.
Analyzing The Impact Of Employee Competence, Organizational Climate, and Physical Work Environment On Worker Productivity in Palm Oil Manufacturing Sitorus, Ezekiel Berliantoro; Panjaitan, Maludin; Purba, Jon Henri; Sinaga, Kristin
Equivalent : Journal of Economic, Accounting and Management Vol. 3 No. 2 (2025): Equivalent : Journal of Economic, Accounting and Management
Publisher : CV. Doki Course and Training

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61994/equivalent.v3i2.1428

Abstract

This study examines the influence of employee competence, organisational climate, and work environment on work performance at PT Perkebunan Nusantara IV Pasir Mandoge Palm Oil Factory. A quantitative method with an associative design was employed, involving 120 employees selected from a population of 172 using the Slovin formula with a 5% margin of error. Data were collected through five‑point Likert scale questionnaires and analysed using multiple linear regression with standard classical assumption tests in IBM SPSS Statistics. The results indicate that employee competence, organisational climate, and work environment each have positive and significant partial effects on work performance, with t‑values of 2.276, 3.213, and 3.787, respectively, all exceeding the critical value of 1.980. Simultaneously, these three variables significantly affect work performance, as shown by an F‑statistic of 9.934, greater than the critical value of 2.68. The coefficient of determination (R‑square) of 0.204 shows that 20.4% of the variation in work performance is explained by these variables, while 79.6% is attributed to other factors. The findings highlight that the work environment has the strongest association with work performance, underscoring the importance of supportive organisational conditions to enhance employee productivity and engagement.
Co-Authors Jon Henri Purba, Jon Henri Maludin Panjaitan Munthe, Joy Lousia Brigitha Prayudani, Santi Sitorus, Ezekiel Berliantoro