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All Journal Format : Jurnal Imiah Teknik Informatika RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Technomedia Journal PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Jurnal IKA PGSD : Ikatan Alumni PGSD UNARS JSR : Jaringan Sistem Informasi Robotik Jurnal Pendidikan dan Kewirausahaan JURNAL PENDIDIKAN, SAINS DAN TEKNOLOGI Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Journal of Community Empowerment and Innovation Journal of Education Technology Information Social Sciences and Health Indonesian Journal of Multidisciplinary on Social and Technology Jurnal Informatika: Jurnal Pengembangan IT Jurnal Pendidikan Teknologi Informasi (JUKANTI) JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Journal of Information Technology Jurnal Informatika Dan Tekonologi Komputer Teknik: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Neuroscience Nursing Public Health Social Sciences Other

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Analisis Sentimen Ulasan Aplikasi Lazada dengan Metode Naive Bayes dan Random Forest Mohammad Rizal; Nur Azizah; Firman Jaya
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 6 No. 2 (2026): Juli : Jurnal Informatika dan Tekonologi Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v6i2.11418

Abstract

The rapid growth of e-commerce applications has increased the number of user reviews that reflect public opinion on service quality and user experience. However, many previous studies rely only on rating-based sentiment analysis and do not utilize positive and negative sentiment lexicons, resulting in limited insight into public opinion. This study aims to analyze public opinion toward the Lazada application using a data mining–based sentiment analysis approach by combining user ratings and sentiment lexicons in the labeling process. The data set consists of Lazada user reviews collected from digital platforms. The research process includes data collection, data cleaning, and text preprocessing, such as text normalization, removal of emojis and symbols, and stopword elimination. Feature extraction is performed using the Term Frequency–Inverse Document Frequency (TF-IDF) method. Sentiment labeling is conducted by integrating rating scores and lexicon analysis, where reviews with ratings of 4–5 or dominant positive words are classified as positive, while reviews with ratings of 1–2 or dominant negative words are classified as negative; neutral reviews are excluded. Sentiment classification is carried out using Naive Bayes and Random Forest algorithms. Model performance is evaluated using accuracy, precision, recall, and F1-score. The results show that both models perform well, with Random Forest achieving better performance than Naive Bayes. This study provides useful insights for improving e-commerce service quality based on user feedback.
Pengaruh Penggunaan Media Pembelajaran Interaktif Berbasis CodeCombat terhadap Motivasi Belajar Siswa SMK Negeri 1 Panji pada Mata Pelajaran Informatika Ahmad Ihsan; Arico Ayani Suparto; Firman Jaya
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 6 No. 2 (2026): Juli : Jurnal Informatika dan Tekonologi Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v6i2.11542

Abstract

This study aims to examine the effect of CodeCombat-based interactive learning media on students’ learning motivation in Informatics subjects at SMK Negeri 1 Panji. This research employed a quantitative approach using a quasi-experimental method with a pretest-posttest control group design. The sample consisted of 72 students, divided into an experimental class of 36 students and a control class of 36 students. The experimental class was taught using CodeCombat, while the control class received conventional instruction. Data were collected using a 20-item Likert-scale learning motivation questionnaire that had been tested for validity and reliability. Data analysis was conducted using IBM SPSS through normality tests, homogeneity tests, paired sample t-tests, independent sample t-tests, and N-Gain analysis. The results showed that the pretest scores of the experimental and control classes were not significantly different, with a significance value of 0.53 > 0.05. However, the posttest results showed a significant difference between the two classes, with p<0.001. The experimental class obtained a higher posttest mean score of 87.86 compared to the control class, which obtained 73.69. The N-Gain score of the experimental class was 0.6316, categorized as moderate or fairly effective, while the control class obtained 0.1867, categorized as low. These findings indicate that CodeCombat-based interactive learning media has a significant positive effect on improving students’ learning motivation in Informatics subjects.
Co-Authors Ahmad Ihsan Anis Febriyanti ansori ansori Arico Ayani Suparto As’ad As’ad Azka Maliya cahaya wijayanti Dyan Yuliana Erfandi Agusti Kiki Wahyono Fathor Rosit Irma Noervadila Kholidy Kholidy Kholiqin Kholiqin Kholisotul Muawanah Latifatus Fitri Lova Aulia Savina Refonita Luluk Handayani M. Anton Mahfud Hadi Miftahus Surur Moch. Rizal Maulana Mohammad Rizal Muhammad Hafied Hermawan Nisfa Daud Supu Nur Azizah Nurhosen Puryantoro P Rahmat Shofan R Rahmat Shofan Razaki Rahmat Shofan Razaqi Rahmat Sofan Razaqi Rizky Maghfirah Sandi Rohmatullah Alifa Sasmita Sari Siti Nur Azizah Siti Seituni TRI MERI WULANDARI Triastuti Desy Artika Yesi Puspitasari Zainul Munawwir Zainur Rahman