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This study examines the emergence of localized English expressions in Indonesian social media discourse, highlighting how English is adapted and reinterpreted in multilingual digital contexts. While previous studies on English in Indonesia have primarily focused on formal domains such as education and language policy, limited attention has been given to informal online communication where linguistic innovation is highly visible. This study aims to analyze how English lexical items are re-semanticized and creatively transformed by Indonesian users on social media platforms. The study employed a qualitative approach using data collected from Instagram posts and comments, focusing on selected examples of English-derived expressions such as boba, gas, voucher, server, and suamiable. The analysis compares the conventional meanings of these terms in Inner Circle English with their localized meanings in Indonesian usage. The findings reveal that English functions as a flexible linguistic resource, undergoing processes of semantic shift, metaphorical extension, and lexical blending. These localized forms reflect users’ creativity as well as their ability to adapt global linguistic resources to local cultural contexts. The study concludes that English in Indonesian social media is not merely borrowed but actively reconstructed, contributing to the dynamic development of English in the Expanding Circle.

Urban plant care is increasingly important for sustainable living, but many users face inconsistent watering, insufficient care knowledge, unsuitable plant selection and delayed disease recognition. This study presents Easy Grow Plants, an integrated web and Internet of Things (IoT) ecosystem that connects plant care guidance, soil-moisture monitoring, automated watering, plant recommendation, image-based plant health assistance, marketplace functions, community interaction and plant exchange. The prototype was implemented using a React frontend, Django REST backend, SQLite database and an Arduino UNO R4 WiFi smart pot with a soil moisture sensor, relay module and DC water pump. Functional, interface, API, IoT connectivity, sensor calibration, watering control and LAN deployment tests were conducted. The results show that the core modules operated together as an integrated academic prototype. The system demonstrates a practical foundation for smart urban gardening, although cloud deployment, multi-device testing and stronger AI validation remain future improvements

Document-level sentiment analysis assigns a single polarity label to an entire review, often obscuring opinion diversity within multi-sentence submissions. This limitation is particularly evident in reviews of multi-service platforms, where users frequently express heterogeneous opinions toward different aspects of the platform in the same review. To address this challenge, this study proposes a sentence-level sentiment analysis framework for Indonesian Gojek app reviews collected from the Google Play Store. The proposed framework introduces a two-stage segmentation strategy that combines punctuation-aware rules with conjunction-aware splitting based on coordinating and adversative conjunctions (e.g., tapi [but], padahal [even though]) to identify opinion boundaries and decompose mixed-sentiment reviews into independently classifiable sentence units. A total of 14,730 raw reviews collected between May and July 2025 were subjected to data cleaning and quality filtering, resulting in 7,187 valid reviews that were further segmented into 14,187 sentence-level instances. Each instance was manually annotated by three annotators using a four-class labeling scheme consisting of app-positive, app-negative, app-neutral, and service categories. Sentiment-level inter-annotator agreement, computed on the subset of instances unanimously categorized as app-related by all three annotators (n = 4,384), achieved substantial agreement (Fleiss'  = 0.636). Hyperparameter optimization was conducted using Optuna with the Tree-structured Parzen Estimator (TPE) sampler across four experimental scenarios. The best performance was achieved by IndoBERTweet under Stratified K-Fold evaluation, attaining an accuracy of 0.751 and a macro F1-score of 0.729, outperforming all IndoBERT configurations. The results demonstrate the effectiveness of domain-adaptive pre-training on informal Indonesian text and highlight the value of conjunction-aware segmentation for preserving fine-grained opinion structures in mixed-sentiment reviews. These findings suggest that domain-aligned language representations provide a practical and effective solution for sentence-level sentiment analysis of Indonesian app reviews.

Transportation plays an important role in supporting community mobility and enhancing socio-economic activities in urban areas. The increasing population growth and community activities in Sorong City have led to a higher demand for transportation modes. This study aims to identify the characteristics of transportation users in Kota Sorong and to analyze the probability of selecting different transportation modes using the Multinomial Logit (MNL) method. A quantitative approach was employed in this research. Questionnaires were distributed to 225 transportation users in Sorong City. The variables analyzed included gender, age, occupation, income, trip purpose, travel frequency, and reasons for choosing a transportation mode. The data were analyzed using multinomial logistic regression with SPSS software. The results indicate that transportation mode choice is influenced not only by socio-economic factors, but also by showed that income, trip purpose, travel frequency, and reasons for choosing the mode significantly influenced transportation mode choice, while gender, age, and occupation did not have significant effects. The probability analysis indicated that private vehicles had the highest probability of selection at 89.63%, followed by online transportation at 9.96%, and conventional motorcycle taxis at 0.41%. These findings imply that socio-economic and travel behavior factors strongly influence transportation mode preferences in Sorong City and may serve as a reference for future urban transportation planning and policy development.

This study aims to analyze the reconceptualization of national security in the digital era through the case of the 2021 Facebook data breach involving 533 million users across 106 countries. As digital technologies become increasingly integrated into governance, economic activities, and social interactions, cyber threats have emerged as a significant challenge to contemporary security frameworks. This research employs a qualitative descriptive approach using library research methods, drawing upon academic literature, official reports, and relevant policy documents. The findings indicate that national security has evolved from a traditional military-centered concept toward a broader and multidimensional framework that includes cyber threats as a form of non-traditional security challenge. The Facebook data breach demonstrates how cyber threats transcend geographical boundaries, involve complex attribution problems, and generate multidimensional impacts on individuals, societies, economies, and states. Through the lens of Securitization Theory developed by Buzan, Wæver, and de Wilde (1998), the incident illustrates how data security has become securitized as a matter of national and international concern. Furthermore, the Human Security framework proposed by UNDP (1994) highlights the vulnerability of individuals whose personal information becomes exposed in the digital environment. This study concludes that cybersecurity should be recognized as a fundamental pillar of national security in the digital age, requiring comprehensive strategies that integrate technological resilience, data protection regulations, human resource development, and international cooperation.

The increasing complexity of urban transportation systems demands intelligent and measurable navigation methods. Medan City, the capital of North Sumatra Province, has a dense road network with multiple route options that often confuse road users. Dijkstra's Algorithm, developed by Edsger Wybe Dijkstra in 1959, is a greedy-based computational approach proven effective for solving the shortest path problem on non-negative weighted graphs. This study applies Dijkstra's Algorithm to determine the shortest route from Medan Railway Station to Universitas Negeri Medan (UNIMED). The road network was modeled as an undirected weighted graph with 15 nodes and 16 edges, where edge weights represent actual road distances measured via Google Maps. The graph has a density of 0.152, confirming its sparse graph characteristic. Three alternative routes were identified and analyzed. The algorithm was implemented in Python 3 using the heapq module as a priority queue. Results show that the optimal route is A → B → C → E → F → M → N → O via Jl. M.T. Haryono, Jl. Aipda KS Tubun, Jl. Madong Lubis, and Jl. Prof. H.M. Yamin, with a total distance of 6.64 km. This achieves 99.1% accuracy compared to Google Maps, with a deviation of only 0.06 km. The optimal route is 6.25% more efficient than Alternative Route 1 (7.30 km) and 11.9% more efficient than Alternative Route 2 (7.54 km). The algorithm executes in under 1 millisecond with time complexity O((V+E) log V). These findings confirm Dijkstra's Algorithm as highly effective for medium-scale urban road network optimization.

 The rapid adoption of smartphones among Indonesian digital natives has increased reliance on biometric authentication systems. However, empirical evidence regarding the relationship between user satisfaction and security risk awareness remains limited, particularly in developing-country contexts. This study investigates the behavioral dynamics of biometric security perception among 266 respondents, consisting of 221 high school students and 45 university students in Indonesia. A Python-based computational pipeline incorporating Akaike Information Criterion (AIC) validation and 1,000-iteration stochastic bootstrapping was employed to evaluate nonlinear behavioral patterns using Polynomial Regression and Ordinary Least Squares (OLS) multivariate analysis. The results confirm the existence of a nonlinear Security Paradox. While the overall population demonstrates a positive quadratic trajectory, the university student group exhibits a concave-down parabolic relationship (a=−0.0460), indicating a decline in perceived utility beyond a specific security threshold. The identified behavioral breaking point occurs at X≈5.45 (95% CI: 2.99–20.77), suggesting that excessive security hardening may reduce perceived usability and increase cognitive friction. Furthermore, the ablation analysis reveals that security risk awareness (p<0.001) is the strongest predictor of user satisfaction, exceeding the influence of daily usage intensity. Segment-level analysis further demonstrates behavioral divergence between respondent groups. High school students exhibit relatively uniform satisfaction toward biometric systems, whereas university students display greater variability and more critical perceptions regarding authentication friction. These findings indicate that highly rigid security configurations may become less effective for users with higher digital literacy and risk awareness. This study contributes a computationally validated behavioral framework for understanding security–utility trade-offs and provides a conceptual foundation for developing adaptive, user-centric, and friction-aware biometric authentication systems.

The swift proliferation of short-video-centric social media, notably TikTok, has revolutionized the educational landscape by facilitating novel methods of knowledge production, dissemination, and interpretation. This phenomenon denotes a transition in media and signifies an epistemological transformation in educational practices within the digital age. This study seeks to analyze the representation and interpretation of knowledge in TikTok educational content using a qualitative methodology grounded in an interpretive case study framework. Data were gathered via digital participant observation, comprehensive interviews, and document analysis involving 12 participants, comprising educational content creators and active TikTok users in higher education settings. Thematic data analysis was performed utilizing a Multimodal Critical Discourse Analysis framework to elucidate the interplay among visual, verbal, and auditory components in the construction of meaning. The results show three main patterns: the conflict between quick understanding and deep knowledge, the importance of emotional multimodal experiences in learning, and the negotiation of knowledge authority in changing digital spaces. These results indicate that learning via TikTok encompasses not only cognitive aspects but also intricate emotional, aesthetic, and social dimensions. This study theoretically enhances multimodal discourse analysis by integrating users' subjective experiences, while practically informing the advancement of critical digital literacy and the design of social media-based learning. Moreover, this study facilitates additional investigation into algorithmic dynamics, digital identity, and the evolution of learning methodologies within platform-centric contexts.

Desa Motu is an area that experiences limited internet access due to the unavailability of conventional ISP services and weak cellular signal coverage. This study aims to develop a community-based RT/RW Net network system to provide internet access by utilizing Starlink as the main ISP and distributing connectivity through networking devices such as MikroTik routers, access points, switches, and fiber optic media. Network testing was conducted by measuring download and upload speeds using network testing ap-plications, evaluating connection stability through latency (ping) measurements, and assessing signal coverage at several user locations. The results show that the implemented RT/RW Net network is able to provide a stable internet connection with consistent speeds at different testing times, as well as optimal signal distribution across multiple measurement points. The authentication system using vouchers, PPPoE, hotspot login, and MAC Binding functions properly, and the free educational access feature also operates effectively. These findings indicate that the RT/RW Net–based community network model can serve as an affordable and sustainable solution for expanding internet access in rural areas.

Communication is an essential human right, yet a significant communication gap persists between individuals with sensory disabilities, specifically the deaf and speech-impaired, and the general public. While many technological solutions have been proposed to translate sign language, existing models primarily rely on heavy deep learning architectures such as Convolutional Neural Networks (CNN) or Recurrent Neural Networks (RNN/LSTM). These models often demand high computational power, leading to latency and limiting real-time application on standard devices. This study proposes a lightweight, fast, and highly responsive sign language translation system specifically designed to recognize static alphabets (A-Z) and single-character air writing. The system utilizes MediaPipe for hand tracking, where feature extraction is intelligently processed by calculating the relative spatial coordinates of fingertips to the wrist, reducing dependency on raw camera coordinates. Classification is performed using a Support Vector Machine (SVM) with a Radial Basis Function (RBF) kernel, prioritizing computational efficiency without sacrificing accuracy. To enhance user experience, the system introduces three key novelties: smart relative feature extraction, an anti-duplication hold system with a 1-second timer to prevent input spamming, and a non-blocking multithreaded audio execution (Daemon Thread) utilizing Google Text-to-Speech (gTTS), ensuring the webcam feed remains fluid during audio playback. Additionally, an alternative air-writing mode is integrated, utilizing geometric heuristics and PyTesseract OCR to read single drawn letters in the air. The results indicate that the proposed system operates swiftly and efficiently, bridging the communication barrier with a hardware-friendly approach.

This research investigates how celebrity endorsements, customer reviews, and pricing affect consumers’ intention to purchase Scarlett Whitening products. Amid intense competition in the skincare industry, firms are required to focus not only on product features but also on psychological and perceptual aspects that influence consumer behavior. Celebrity endorsers contribute to strengthening brand trust, customer reviews offer insight based on user experiences, while price reflects consumers’ perceived value of the product. This study adopts a quantitative explanatory design, with data obtained from 204 respondents through structured questionnaires using a five-point Likert scale. The collected data were analyzed using multiple linear regression with SPSS version 26. The findings indicate that celebrity endorsers, customer reviews, and price have both simultaneous and individual positive and significant impacts on purchase intention. An adjusted R-square value of 0.274 suggests that these variables account for 27.4% of the variation in consumers’ purchase intention. Overall, the results highlight that appropriate endorsements, trustworthy reviews, and competitive pricing collectively enhance consumers’ intention to purchase Scarlett Whitening products

This study is motivated by the growing public demand for reliable and high-quality public transportation services such as the Trans Solo Bus on corridor 4. The purpose of this research is to analyze the influence of Facilities, Innovation, and Service Quality on User Interest, both partially and simultaneously. This study employs a quantitative method with a sample of 100 respondents who are users of the Trans Solo Bus on corridor 4. Data were collected through questionnaires and analyzed using IBM SPSS Statistics through several tests, including validity, reliability, normality, multicollinearity, heteroscedasticity, multiple linear regression, t-test, F-test, and coefficient of determination (R²). The results revealed that Facilities, Innovation, and Service Quality significantly influence User Interest, either individually or simultaneously. These findings imply that improving facilities, implementing continuous innovation, and ensuring high service quality can increase public interest in using Trans Solo Bus services, thus supporting the development of sustainable urban transportation.

This study aimed to examine the influence of promotional strategies and user-friendliness on consumer purchasing decisions on the ShopeeFood platform in Batam City. The research used a descriptive quantitative approach, involving 100 actively transacting respondents, selected through purposive sampling based on Lemeshow's calculation guidelines to ensure sample representativeness. Data were collected through a structured questionnaire and analyzed using a series of validity and reliability tests, classical assumption checks, multiple linear regression, and hypothesis testing using t- and F-tests. The research findings indicated that promotions contributed 42.4% to purchasing decisions, while user-friendliness contributed 26.0%. The coefficient of determination (R²) of 78.9% confirmed that these two variables collectively explained most of the variation in purchasing behavior. The results of the t- and F-tests confirmed that promotions and user-friendliness had a significant influence, both partially and simultaneously, emphasizing the importance of integrating effective digital marketing strategies and an intuitive application interface to drive consumer decisions on ShopeeFood in Batam City.

This study was conducted to examine the extent to which product price and quality influence consumer interest in purchasing MMTC Tax. These two elements are believed to be the main considerations in the purchase decision-making process. This research applied a quantitative method using a survey technique, in which data was collected through the distribution of questionnaires to MMTC Tax service users. The data analysis technique used was multiple linear regression to measure the effect of each independent variable on the dependent variable. The findings show that both price and product quality have a positive and significant impact on purchasing interest. Together, these two factors were found to significantly influence consumers' willingness to make a purchase. Based on these results, it can be concluded that competitive pricing and superior product quality can drive an increase in the purchasing interest of MMTC Tax consumers.

This study aims to analyze the factors that influence consumer purchasing decisions on the Shopee e-commerce platform. The variables studied include promotion (X1), price (X2), product completeness (X3), and product quality (X4) on purchasing decisions (Y). This study uses a quantitative approach with a survey method, where data is collected through questionnaires distributed to active Shopee users. The research sample consisted of 100 respondents selected using a specific sampling technique (eg purposive sampling). Data analysis was carried out using multiple linear regression techniques to determine the effect of each independent variable on the dependent variable. The results of the study show that all independent variables, namely promotion, price, product completeness, and product quality, simultaneously have a significant effect on consumer purchasing decisions. Partially, the variables promotion (X1), price (X2), product completeness (X3), and product quality (X4) on purchasing decisions (Y) have the greatest influence on purchasing decisions. These findings emphasize the importance of a marketing strategy that focuses on attractive promotions, competitive pricing, completeness of products offered, and improving product quality to improve consumer purchasing decisions on Shopee e-commerce. This research is expected to contribute to the development of marketing strategies in e-commerce, especially for Shopee, as well as being a reference for further research in similar fields.

The development of information and communication technology has significantly transformed consumer behavior, particularly in the process of searching for information prior to making a purchase. One rapidly growing phenomenon is Electronic Word-of-Mouth (eWOM), which refers to informal communication among consumers through digital platforms such as social media, online forums, and product review websites. eWOM is considered more credible than traditional advertising because it originates from real user experiences. This study aims to analyze the impact of eWOM on consumer purchase intention with trust as a mediating variable. A quantitative approach with a cross-sectional survey design was employed, involving active users of digital platforms who accessed product reviews before purchasing. Data were collected via online questionnaires and analyzed using multiple regression and mediation testing (Baron and Kenny approach with Sobel test). The findings reveal that eWOM has a positive and significant effect on consumer trust (β = 0.72) and directly influences purchase intention (β = 0.31). Trust demonstrates a stronger effect on purchase intention (β = 0.56) and serves as a significant mediator in the relationship between eWOM and purchase intention (indirect effect = 0.40). These results highlight that the quality, credibility, and consistency of eWOM information are crucial in building consumer trust, which subsequently enhances purchase intention. Theoretically, this study enriches digital marketing literature, while practically it provides implications for companies to manage online reviews transparently and foster consumer trust to drive purchasing decisions.

This study was conducted with the aim of identifying and analyzing the influence of price, innovation, and service quality variables on consumer decisions in using the Maxim online transportation service. The background of this research is the increasing competition in the online transportation industry in Indonesia, which encourages companies to continuously improve their marketing strategies to attract and retain customers. As one of the rapidly growing online transportation service providers, Maxim needs to understand the factors that influence consumer decisions in order to compete effectively. The method used in this research is a quantitative approach, with data collected through questionnaires distributed to 134 respondents who are active users of Maxim's transportation services. The data collected were analyzed using multiple linear regression to examine the effect of each independent variable (price, innovation, and service quality) on the dependent variable (consumer decision). Validity and reliability tests were also conducted to ensure the research instrument was appropriate for use.The results of the study show that all three independent variables—price, innovation, and service quality—have a positive and significant effect on consumer decisions. This means that the more competitive the price offered, the higher the level of innovation provided, and the better the perceived service quality, the more likely consumers are to choose and continue using the Maxim online transportation service.These findings provide practical implications for Maxim’s management in designing more targeted marketing strategies and service improvements, as well as strengthening the company’s position in facing market competition.

TikTok Shop is a popular application that offers online shopping and interaction experiences for consumers. Marketers at TikTok Shop use various methods to encourage consumer decisions to make purchases. This study aims to determine the effect of celebrity endorsers, online customer reviews, and viral marketing on purchasing decisions for TikTok Shop e-commerce products. This study uses a quantitative method with a survey approach by providing questionnaires to respondents. The population studied was all people in Semarang City who have the TikTok Shop application and have purchased products through the application. A sample of 112 people was taken using the convenience sampling technique. Data were obtained through questionnaires and analyzed using multiple linear regression analysis, F test, R2 test, and t test. The results of the study indicate that celebrity endorsements have a positive and significant effect on consumer purchasing decisions for Tiktok Shop users in Semarang City. The increasing use of celebrity endorsements will encourage consumer decisions to buy. Online customer reviews have a positive and significant effect on consumer purchasing decisions for Tiktok Shop users in Semarang City. The more positive online customer reviews, the more it will encourage consumer decisions to buy. Viral marketing has a positive and significant effect on consumer purchasing decisions for Tiktok Shop users in Semarang City. The increasing use of viral marketing will encourage consumer decisions to buy.  

The rapid development of social media, particularly TikTok, has transformed digital marketing strategies by emphasizing influencer endorsement and content marketing to reach Generation Z consumers. This generation is characterized by high social media usage and strong responsiveness to visual content and influencer recommendations. This study aims to analyze the effect of influencer endorsement and content marketing on the purchase intention of Generation Z TikTok users toward Antarestar products in Makassar City, both partially and simultaneously. This study employed a quantitative approach with an associative research method. The population consisted of Antarestar consumers residing in Makassar City, and the sample was determined using purposive sampling. A total of 140 respondents who met the research criteria were involved in this study. Data were collected through a questionnaire using a five-point Likert scale and analyzed using multiple linear regression analysis with the assistance of IBM SPSS Statistics software. The results of this study indicate that (1) influencer endorsement has a positive and significant effect on the purchase intention of Generation Z TikTok users toward Antarestar products, (2) content marketing has a positive and significant effect on purchase intention, and (3) influencer endorsement and content marketing simultaneously have a positive and significant effect on the purchase intention of Generation Z TikTok users toward Antarestar products in Makassar City. The findings conclude that the effectiveness of Antarestar’s digital marketing on TikTok is strongly influenced by credible and attractive influencers as well as relevant, informative, and consistent marketing content. Therefore, optimizing influencer endorsement and content marketing strategies is essential to enhance purchase intention among Generation Z consumers.

This study aims to determine the influence of Product Quality, Price Perception, and Brand Image on Purchase Decisions in Shopee application users in South Jakarta. The population in this study is Shopee application users in South Jakarta who have made purchases in the last six months. The research sample was determined using the Non Probability Sampling method with the Lemeshow formula and obtained as many as 96 respondents who were considered to represent the characteristics of the population. Data was collected through a questionnaire with a Likert scale distributed through Google Form, then processed using Microsoft Excel 365 and SPSS software version 29 for descriptive analysis and hypothesis testing. The analysis techniques used included validity tests, reliability, classical assumption tests, multiple linear regression analysis, as well as t-tests and F-tests. The results showed that Product Quality, Price Perception, and Brand Image had a significant effect on Purchase Decisions in Shopee application users, both partially and simultaneously, which indicates the importance of marketing strategies based on product and brand values in improving consumer purchase decisions.