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All Journal Jurnal Teknodik Jurnal Statistika dan Aplikasinya
Rohimah, Siti Rohmah
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Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences Other

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PERFORMANCE EVALUATION OF WORD EMBEDDING TECHNIQUES IN TWITTER SENTIMENT ANALYSIS USING LSTM Ladayya, Faroh; Rahayu, Widyanti; Rohimah, Siti Rohmah; Saputra, Ferdiansyah Rizki; Maulana, Thoriq Akbar; Madinah, Najwa Nur
Jurnal Statistika dan Aplikasinya Vol. 9 No. 2 (2025): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.09206

Abstract

Opinions expressed on social media can be used as feedback on a product, both goods and services. The sentiment analysis was utilized for analyzing opinions given by the public via social media. The sentiment contained in an opinion can be positive, negative, or neutral. This study aims to compare the performance of three word embedding techniques—Word2Vec, GloVe, and FastText—when combined with a Long Short-Term Memory (LSTM) model for sentiment classification of Indonesian Twitter data. LSTM was selected due to its ability to model sequential text data and capture long-term contextual dependencies that are often present in natural language. To enable sentiment classification using LSTM, textual data from social media were transformed into numerical vectors. Thus, the word embedding technique is used to convert text into a vector. The vector that had been obtained will be used as input for LSTM. All embeddings were evaluated under the same preprocessing pipeline and LSTM architecture to ensure a fair comparison. Model performance was assessed using accuracy, precision, recall, F1-score, and ROC/AUC metrics. The results indicate that the LSTM model effectively captures sentiment patterns in Indonesian tweets, with Word2Vec achieving the best overall performance, followed by GloVe and FastText. These findings suggest that domain-adapted word embeddings remain highly effective for sentiment analysis in Indonesian social media contexts.
FAKTOR-FAKTOR YANG MEMPENGARUHI KEMAMPUAN MICROTEACHING MAHASISWA Rohimah, Siti Rohmah; Ismah, Ismah
Jurnal TEKNODIK Jurnal Teknodik
Publisher : Pusat Data dan Teknologi Informasi Kementerian Pendidikan Kebudayaan, Riset dan Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (88.118 KB) | DOI: 10.32550/teknodik.v19i3.165

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Abstrak:Tujuan penelitian ini adalah untuk mengetahui faktor-faktor yang mempengaruhi kemampuan microteaching mahasiswa. Penelitian ini merupakan penelitian kuantitatif yang menggunakan analisis regresi linear berganda. Populasi penelitian ini adalah seluruh mahasiswa Program Studi Pendidikan Matematika semester 6 yang sedang mengambil mata kuliah Pembinaan Kompetensi Mengajar (Microteaching) tahun ajaran 2012/2013 pada Fakultas Ilmu Pendidikan Universitas Muhammadiyah Jakarta yang berlokasi di Cirendeu. Data dikumpulkan dari nilai hasil akhir setiap mata kuliah Media dan Teknologi Pembelajaran, Strategi Pembelajaran Matematika, dan Perencanaan Pembelajaran Matematika. Nilai kemampuan mengajar dikumpulkan menggunakan Microteaching Test Performance setiap mahasiswa yang terintegrasi dalam nilai akhir dari mata kuliah Pembinaan Kompetensi Mengajar. Kemudian dilakukan uji asumsi yang harus dipenuhi dalam regresi linear berganda yaitu uji multikolinearitas, uji autokorelasi, uji heteroskedastisitas, dan uji linearitas. Hasil penelitian menunjukkan bahwa variabel nilai mata kuliah Media dan Teknologi Pembelajaran (X1), Strategi Pembelajaran Matematika (X2), dan Perencanaan Pembelajaran Matematika (X3) secara bersamaan mempengaruhi nilai mata kuliah Pembinaan Kompetensi Mengajar (Y) secara signifikan. Koefisien determinasi dari model regresi sebesar 0.37. Hal ini berarti bahwa varian nilai mata kuliah Pembinaan Kompetensi Mengajar (Y) mampu dijelaskan sebesar 37% oleh variabel nilai mata kuliah X1, X2, dan X3. Sedangkan 63% sisanya oleh faktor lainnya. Semoga hasil penelitian ini bisa menjadi bahan literatur untuk penelitian berikutnya dengan menentukan lebih banyak lagi faktor yang mempengaruhi kemampuan microteaching mahasiswa.Kata Kunci: kemampuan microteaching, regresi linear berganda, koefisien determinasiAbstract:The aim of this research is to determine the factors affecting the students’ microteaching ability. This research is a quantitative research which applies multiple linear regression analysis. The population is all 6th semester students of Mathematic Education Program at Education Faculty of Universitas Muhammadiyah Jakarta who are taking microteaching subject in 2012/2013 academic year. Data are from their final scores of three subjects: Media and Instructional Technology, Math Learning Strategy, and Math Learning Plan. Microteaching capacity scores are based on their Microteaching Test Performance integrated in their final Microteaching subject score. Then, assumption test that must be met in multiple linear regression is carried out which are multicolinearity test, autocorrelation test, heteroscedacticity test, and linearity test. The result shows that the score variables of Media and Instructional Technology (X1), Math Learning Strategy (X2), and Math Learning Plan (X3) collectively effect the score of Microteaching (Y) significantly. Determination coefficient of regression model is 0.37, meaning that the variable of Microteaching (Y) subject score can be explained by variables X1, X2, and X3 of 37%. The rest of 63% is explained by other variables. Hopefully, this researchcan be reference for continuous research on students’ microteaching capacity with more affecting factors.Keywords: microteaching capacity, multiple linear regression, determination coefficient
Co-Authors Ismah, Ismah Ladayya, Faroh Madinah, Najwa Nur Maulana, Thoriq Akbar Saputra, Ferdiansyah Rizki Widyanti Rahayu