Purpose: This research aims to develop a system for detecting the credibility of information on social media X by classifying tweets as credible or non-credible. Additionally, it seeks to improve the accuracy of classification and prediction of information credibility using feature extraction methods, semantic features, feature expansion, and optimization.
Methods: The system is built using a deep learning approach with Long Short-Term Memory (LSTM), Term Frequency-Inverse Document Frequency (TF-IDF), Robustly optimized BERT Approach (RoBERTa), Global Vector (GloVe), and Particle Swarm Optimization (PSO). The dataset consists of 54,766 Indonesian tweets from social media X, focusing on the 2024 General Election and using several keywords such as ‘Pemilu 2024’, ‘Pilpres 2024’, ‘anies baswedan’, ‘Prabowo’, ‘#GanjarPranowo’, and ‘#debatCapres’.
Result: The results of this study show that the highest accuracy achieved is 89.09% using LSTM with an 80:20 data split, baseline unigram, RoBERTa, Top1 corpus IndoNews, and PSO of the LSTM model’s hyperparameters, resulting in a highly significant statistical improvement of 0.96% over the baseline model.
Novelty: This research contributes to information credibility classification research using RoBERTa to add semantic features and GloVe to expand features by utilizing a built corpus and finding similar words to connect with these expanded features. Additionally, PSO is applied to find the optimal hyperparameters, thereby improving the performance and accuracy of the LSTM classification model.

Campur kode berarti menggunakan dua bahasa atau lebih dalam waktu yang bersamaan. Kode mengacu pada bahasa berdasarkan ragam daerah, dialek sosial (siolek), ragam dan gaya, serta ragam pemakaian dan pencatatan. Tujuan dari penelitian ini adalah untuk menjelaskan fenomena campur kode dalam komunikasi pada masyarakat desa Kedungbokor. Penelitian dilakukan dengan menggunakan metode penelitian deskriptif kualitatif. Sumber bahan penelitian adalah para pedagang pasar tradisional desa Kedungbokor yang melakukan transaksi jual beli dan komunikasi masyarakat dalam kehidupan sehari-hari. Pedagang pasar tradisional yang digunakan sebagai sumber data diidentifikasi terlebih dahulu. Pedagang pasar diobservasi dan diwawancarai oleh peneliti dengan menggunakan kuesioner.

Micro, Small and Medium Enterprises (MSMEs) are productive business entities owned by individuals who have a role and contribution to the Indonesian economy. The presence of MSMEs greatly supports the national economy. Internally, the MSME sector needs to empower employees and build a better management system to maintain its business image. On the other hand, problems related to branding also often occur among MSMEs, these two problems faced by MSMEs can be solved by implementing an image management strategy. One of the motivations for implementing this strategy is how they want to influence and benefit others [13].
Baktik's research [5] proves the influence of impression management on employee productivity at Chocolicious Indonesia Stores. On the other hand, according to dramaturgical theory, the use of digital branding and marketing techniques in MSMEs is part of the front stage. This concept is supported by Prabhawati's findings [10] that brand image has a higher influence on purchasing decisions for MSME products assisted by Jogja Sukurmi
Key words: impression management, dramaturgi theory, MSMEs