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All Journal JSAI (Journal Scientific and Applied Informatics) Jurnal Teknologi Informasi dan Pendidikan Paradoks : Jurnal Ilmu Ekonomi Jurnal Informatika Polinema (JIP)
Salim, M
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Library & Information Science Social Sciences

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Analysis of Cyberbullying on Social Media Using A Comparison of Naïve Bayes, Random Forest, and SVM Algorithms Ahmad, Sulistiawati Rahayu; Insani, Nur; Salim, M
Jurnal Teknologi Informasi dan Pendidikan Vol. 17 No. 1 (2024): Jurnal Teknologi Informasi dan Pendidikan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtip.v17i1.807

Abstract

Social media allows the public, especially the younger generation, to access information and knowledge or communicate with others online. Unfortunately, the phenomenon of bullying has evolved into cyberbullying, encompassing various forms of violence such as taunting, insults, intimidation, or harassment carried out by young individuals through digital technology or social media platforms. Therefore, considering the available data, there is a need for a method to classify text comments on social media, whether they fall into the category of cyberbullying or not. One of the methods used is the creation of a cyberbullying classification model using a Support Vector Machine (SVM), Random Forest (RF), and Naive Bayes algorithms. This research aims to analyze cyberbullying in social media by comparing three different algorithms, namely Naïve Bayes, Random Forest, and SVM. The research results show that in the classification analysis, the Support Vector Machine (SVM) model performed the best, with an accuracy of 85%, precision of 79.93%, and recall of 94.29%. The Naive Bayes model also provided satisfactory results, with an accuracy of around 82.19%, precision of 81.29%, and recall of 85.10%. Meanwhile, the Random Forest (RF) model had a lower accuracy of approximately 73.15%, with a precision of 74.05% and a recall of 77.79%.
The Relationship Between Employee Motivation, Creativity and Performance Z, Nurhaeda; Maryadi, Maryadi; Salim, M; Kitta, Syafruddin
Paradoks : Jurnal Ilmu Ekonomi Vol. 7 No. 4 (2024): Agustus - Oktober
Publisher : Fakultas Ekonomi, Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57178/paradoks.v7i4.991

Abstract

This research explores the relationship between employee motivation, creativity, and performance, focusing on the interaction between intrinsic and extrinsic motivations and the role of organizational strategies, leadership support, and resource availability in enhancing motivation and creativity. Using a qualitative case study approach, the study involves semi-structured interviews, focus groups, and document analysis with employees and leaders from a mid-sized technology company. Thematic analysis was employed to identify key themes related to motivation, creativity, and performance. The findings reveal that intrinsic motivation significantly enhances creative productivity, while extrinsic rewards complement intrinsic motivation when aligned with employees' values. Transformational leadership and a supportive organizational culture are crucial in fostering an environment conducive to creativity. Adequate resources and well-designed workspaces that encourage collaboration further boost motivation and creativity. Training programs focused on creative problem-solving and developing a growth mindset also play a vital role. This study provides valuable insights for managers and policymakers on creating environments that foster innovation and sustain high levels of employee engagement. Organizations can enhance creativity and performance by understanding the interplay between different motivational factors and the importance of supportive leadership and resources. Future research should consider mixed-method approaches and diverse organizational contexts to validate and expand upon these findings.
Analisis Pemahaman Literasi Digital Siswa Terhadap UU ITE Dan Norma Agama Pada MAN Kepulauan Selayar Al Imran, Abdul Ma'arief; Maro, Muhammad Ihsan; Ardiansyah, Mursyid; Salim, M; Ahmad, Sulistiawati Rahayu
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7595

Abstract

The research focused on MAN Kepulauan Selayar students' level of understanding of the Electronic Information and Transaction Law (UU ITE) and how religious norms influence their attitudes to using digital technology. Selayar Islands, with its distinctive social, cultural, and spiritual characteristics, provides a relevant context for exploring digital literacy in an area with unique educational challenges. Using descriptive methods, a multiple choice test was used to measure students' understanding of the ITE Law. In contrast, a Likert scale questionnaire was used to assess the influence of religious norms on their attitudes. The data obtained were analyzed quantitatively to provide a comprehensive picture of students' digital literacy. The results showed that the average score of students' understanding of the ITE Law was 74, which was classified as a High category. Ranking analysis revealed that class XII students had the highest score of 80.77 (High category), followed by class XI with a score of 74.83 (High category), and class X with a score of 66.4 (Medium category). In addition, the average percentage of students' answers in the questionnaire shows a value of 79.42%, which is classified as Influential in reflecting the influence of religious norms on students' attitudes toward using digital technology. This finding shows that although students' level of understanding of the ITE Law is relatively good, there are differences in the level of understanding between grades. In addition, religious norms have a significant influence on students' attitudes toward the responsible use of digital technology.
Implementasi Backward Chaining untuk Mendeteksi Tingkat Stres Belajar Siswa SMK Kamase, Hamka Witri; Salim, M; Pnua, Salma
Jurnal Informatika Polinema Vol. 11 No. 3 (2025): Vol. 11 No. 3 (2025)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v11i3.7245

Abstract

Stres belajar merupakan salah satu permasalahan psikologis yang umum dialami siswa, terutama di tingkat Sekolah Menengah Kejuruan (SMK) yang memiliki beban akademik dan praktik kejuruan secara bersamaan. Keterbatasan waktu dan sumber daya menyebabkan proses deteksi tingkat stres secara manual oleh guru Bimbingan Konseling (BK) menjadi tidak optimal. Penelitian ini bertujuan untuk mengembangkan sebuah sistem pakar berbasis web yang mampu mendeteksi tingkat stres belajar siswa SMK secara cepat dan akurat menggunakan algoritma backward chaining. Penelitian ini menggunakan metode Research and Development (R&D) dengan pengumpulan data melalui observasi dan wawancara bersama guru BK untuk menyusun basis pengetahuan berupa gejala dan aturan inferensi. Sistem dirancang menggunakan bahasa pemrograman PHP dan basis data MySQL, serta diuji melalui white box dan black box testing untuk memastikan keakuratan logika dan fungsionalitas sistem. Hasil pengujian menunjukkan bahwa sistem mampu mengklasifikasikan lima tingkatan stres secara tepat berdasarkan input gejala siswa, serta memberikan saran penanganan sesuai tingkat stres yang terdeteksi. Sistem ini terbukti efisien dan relevan digunakan sebagai alat bantu guru BK dalam proses identifikasi awal stres belajar siswa. Penelitian ini berkontribusi pada pemanfaatan sistem pakar dalam bidang pendidikan, khususnya dalam pengambilan keputusan berbasis gejala psikologis siswa. Di masa mendatang, sistem ini dapat dikembangkan lebih lanjut melalui integrasi teknologi mobile dan kecerdasan buatan berbasis data historis
Co-Authors Abdul Ma’arief Al Imran Kamase, Hamka Witri Kitta, Syafruddin Maro, Muhammad Ihsan Maryadi Maryadi Mursyid Ardiansyah Nur Insani Salma P. Nua Sulistiawati Rahayu Ahmad