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This study analyzes how digital interface design (UI/UX) and system architecture are manipulated to unethically extract user consent, resulting in personal data commercialization and massive online loan (pinjol) spam marketing. Employing a mixed-methods approach, this research combines descriptive quantitative analysis of digital user perception surveys with qualitative observations involving UI teardowns, privacy policy evaluations, and extensive literature reviews. Initial findings indicate a profound crisis of genuine informed consent, exacerbated by the deployment of dark patterns such as pre-ticked checkboxes, disguised opt-out architectures, and information overload engineered into legal documents. This systematic manipulation facilitates unauthorized personal data distribution to third parties under the guise of legitimate agreement, directly triggering privacy intrusions and psychological distress, including severe anxiety among data subjects. Philosophically and morally, these practices constitute a severe breach of Information Technology Professional Ethics (EPTI). Consequently, this study highlights the urgent need for developer accountability and advocates for the implementation of proactive, transparent ethical design frameworks compliant with Human-Computer Interaction (HCI) standards to reclaim digital autonomy.

Various viruses due to unhygienic surfaces of eating and drinking utensils, especially those that are frequently used and repeated, if they do not meet health standards have the potential to cause disease in subsequent users as a problem faced. The purpose of fabrication is to obtain eating and drinking utensils (talam-ompreng) measuring 400x300x0.4 mm made of SS304 which are hygienic, practical, heat resistant, not easily broken, not easily worn, easy to wash and easy to carry. The fabrication method includes: design of a 40 cm long, 30 cm wide eating tray, 7 serial basins (rice container 12 x 12 cm 2 basins, side dish container 8 x 8 cm 3 basins, vegetable container 6 x 6 cm 1 basin, fruit container 6 x 6 cm 1 basin) with a depth of 30 mm, a thickness of 0.4 mm; selection of SS304 plates; design of pressing molds; checking the thickness of SS304 plates; cutting material 55 x 45 cm; pressing until flat (not bulging or thinning/torn); bending the edges around; finishing cleaning metal thorns; stamping according to order; and quality inspection of the ompreng tray according to nutritional standards. The fabrication results in a 40 cm long, 30 cm wide, 0.4 mm thick tray made of SS304 material with a total production cost of IDR 75,000/unit, and a process duration of 2 minutes/unit which implies that the eating and drinking utensils can be used repeatedly after being washed clean from viruses.

The advancement of technology and information, which coincides with digitalization alongside the development of Artificial Intelligence (AI), has colored human social life around the world. Currently, cadets of the Naval Academy often use gadgets/digital tools to access information or other media. With this, there are emerging threats that are very dangerous for individuals and the state. An currently prevalent case is Cyber Crime Identity Theft. Cyber crime identity theft refers to the crime of stealing someone's personal information online for the purpose of fraud or financial gain by stealing personal data such as names, identity numbers, and financial information, to carry out illegal transactions or obtain illegal benefits, which can lead to financial loss and damage the victim's reputation. Indonesia still has a very high number of cases of cyber crime identity theft, but it should be preventable by fostering. the cyber security awareness of cadets at the Naval Academy of the Indonesian National Armed Forces. The conclusion of this research is that by strengthening modern technological infrastructure, both equipment and administrative services, developing modern software and hardware with strong security systems, and tightening regulations regarding access to users' personal data in cyber services, supported by strengthening cyber security institutions, it can enhance the cyber security awareness of cadets at the Naval Academy of the Indonesian National Armed Forces.

The frequent breakage of saw blades and the use of blades that are not suitable for beginner saw operators present a significant problem in metal sawing activities. This study aims to produce a double-sided sharp steel saw blade with dimensions of 310×30×0.8 mm. The production process consists of several stages, namely designing the double-sided sharp saw blade, cutting high-carbon steel material to size, drilling 4 mm diameter holes at both ends with a 310 mm distance between holes, forming sharp edges on both sides of the blade, hardening only the two cutting edges, followed by labeling, packaging, and quality and dimensional standard inspection. The production output is a double-sided sharp steel saw blade measuring 310×30×0.8 mm made from medium carbon steel. The manufacturing cost is Rp. 3,500 per unit with a processing time of 3 minutes per unit. These results indicate that the saw blade can be mounted on a general saw handle and has improved resistance to breakage, making it more suitable for beginner users whose sawing motion is not consistently aligned on a single flat plane.

Indonesia, as the largest archipelagic state in the world, lies on international trade and transportation routes and possesses abundant natural resources. This strategic position creates both opportunities and challenges, particularly in the maritime domain, which requires the Indonesian Navy’s significant contribution in force deployment planning to counter future threats and disruptions. The evolving strategic environment necessitates specific policies and strategies for the Navy to enhance its strength in safeguarding sovereignty, territorial integrity, and national security. This development is pursued through the establishment of the Minimum Essential Force (MEF), a fundamental standard that defines the minimum level of naval capability required to effectively execute missions and functions. This study employs a qualitative descriptive method, using primary data from expert and user interviews as well as secondary data from observation and documentation, to analyze the selection of helicopter escorts utilized by the Indonesian Navy.

Road improvement projects require consistency between technical planning documents and field implementation to ensure that service quality, structural performance, construction time, and user safety are achieved. This article evaluates the conformity between planning and realization in the Pangkalan-Batas Jambi road improvement project in Rawas Ulu District, North Musi Rawas Regency. The study used a descriptive-quantitative evaluative approach based on field monitoring, project technical documents, comparative quantity analysis between contract and Contract Change Order (CCO), and identification of implementation constraints. The results showed that several work items changed during construction because initial planning data did not fully capture actual field conditions. Quantities increased for drainage excavation (+18.87%), roadbed preparation (+8.99%), aggregate class A base course (+12.51%), and AC-Base (+11.98%). Conversely, reinforced pipe culverts decreased (-58.33%), unsealed aggregate base/sirtu decreased (-43.50%), and tack/prime coat volume slightly decreased (-0.47%). The time schedule showed a minor delay of -0.13% in the first week but recovered in the second week, indicating effective field coordination. Main constraints included traffic interference, limited worker visibility, and equipment visibility. The study recommends more detailed site surveys during planning, stronger traffic management, stricter occupational safety implementation, systematic progress control, and routine post-construction maintenance to maintain road service life.

The development of the internet and social media has encouraged e-commerce companies to utilize digital platforms as a marketing tool, one of which is Shopee through TikTok social media. The high frequency of digital advertising is thought to influence consumer attitudes, especially among Generation Z as active TikTok users. To determine the impact of Shopee's digital advertising frequency on consumer attitudes using promotions as a mediating variable on Generation Z TikTok social media users in Tasikmalaya, this study employed quantitative, descriptive, and verification techniques. A total of 100 respondents were sampled using purposive sampling techniques. An online questionnaire with a Likert scale of 1 to 5 was used to collect research data. Data were analyzed using Structural Equation Modeling-Partial Least Square (SEM-PLS) with the help of SmartPLS 4. The results showed that advertising frequency significantly and positively influenced consumer attitudes and promotions. In addition, promotions can mediate the effect of advertising frequency on consumer attitudes and have a beneficial and significant impact. These results indicate that consumer opinions towards Shopee will be more positive if advertisements are displayed more frequently and supported by appropriate promotions. This study serves as an academic reference and information source for businesses seeking to optimize social media-based digital marketing strategies.

Online transportation has become an essential component of modern urban mobility, significantly transforming the way people travel while creating new challenges related to service quality, safety, customer satisfaction, sustainability, and its impact on conventional public transportation. This study aims to examine the development of research on online transportation through a bibliometric analysis combined with a Systematic Literature Review (SLR). Data were collected from the Scopus database using the keyword "Online Transportation" and filtered using the PRISMA framework, resulting in 90 eligible articles for analysis. The bibliometric analysis was conducted using VOSviewer to identify publication trends, leading contributing countries, author affiliations, journal sources, and the most frequently occurring keywords. The findings reveal that research on online transportation remains relatively limited despite showing a gradual increase in recent years. Indonesia emerged as the country with the highest number of publications, followed by the United States, China, Japan, Malaysia, and the United Kingdom. Frequently occurring keywords indicate that online transportation research is commonly associated with traffic management, drivers, passenger safety, customer satisfaction, service quality, employment, and user loyalty. These findings suggest substantial opportunities for future studies, particularly in the areas of regulatory frameworks, sustainable transportation, traffic safety, digital technology integration, and the development of intelligent transportation systems to support more efficient, inclusive, and sustainable urban mobility.

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

Modern food supply chains, particularly those involving essential commodities like rice, often suffer from major challenges such as product fraud, inefficient record-keeping, and a lack of consumer trust. Traditional centralized systems are prone to data tampering, limited transparency, and poor traceability, making it difficult to verify the authenticity and origin of goods. To address these issues, our research introduces TraceRoot, a blockchain-based traceability framework designed to enhance transparency, accountability, and trust in agricultural supply chains.TraceRoot leverages the immutability and decentralization of blockchain technology to maintain a secure, distributed ledger that records every transaction and movement of goods across the supply chain. Each stakeholder including farmers, distributors, retailers, and consumers has role-based access to authenticated data through a user-friendly interface. The framework integrates smart contracts to automate transactions and digital signatures to verify the integrity of the data being uploaded, minimizing the risk of human error or manipulation

This study examines the implementation of a Figma-based UI/UX training program aimed at improving digital design literacy among students at Qotrun Nada Islamic Boarding School, Jakarta. The program was developed to address the limited digital competencies and practical design skills commonly found among santri in traditional Islamic educational environments. Using a project-based learning and mentoring approach, participants were introduced to fundamental concepts of User Interface (UI), User Experience (UX), and collaborative digital design using Figma. The activities included workshops, practical design exercises, mentoring sessions, and prototype development projects. The findings demonstrated significant improvements in students’ digital literacy, communication skills, teamwork, creativity, and confidence in using technology. Students successfully produced simple website prototypes that reflected basic usability and visual design principles. Furthermore, the integration of digital literacy training within the pesantren environment showed that technological skill development can be harmonized with Islamic educational values and community empowerment initiatives

The rapid advancement of information and communication technology has increased the need for data security and confidentiality in digital information exchange. Various threats, such as eavesdropping, data theft, and information manipulation, require effective security methods capable of protecting message content without attracting unauthorized attention. One of the techniques used to address this issue is steganography, which conceals secret information within digital media so that the existence of the message remains undetectable. This study aims to implement the Least Significant Bit (LSB) method on digital facial images as a medium for embedding secret messages and to evaluate the quality of the resulting stego images. The system was developed using the Python programming language with a Tkinter-based graphical user interface to facilitate the processes of message embedding and extraction. Prior to embedding, the secret message was secured using an XOR encryption operation with a specific key. The embedding process was performed by modifying the least significant bits of image pixels, resulting in minimal visual distortion. Experimental results indicate that the LSB method successfully conceals secret messages while maintaining the visual quality of the cover image. The evaluation produced low Mean Squared Error (MSE) values and Peak Signal-to-Noise Ratio (PSNR) values exceeding 85 dB, indicating a very high similarity between the original and stego images. Furthermore, the hidden message could be accurately extracted using the correct key, provided that the image had not undergone compression or manipulation. Therefore, the LSB-based steganography approach on digital facial images is proven to be an effective method for enhancing information security and confidentiality.

The rapid expansion of social media has intensified the phenomenon of Fear of Missing Out (FOMO), a form of anxiety arising from the perception that others are experiencing more rewarding lives. With more than 5.17 billion active social media users worldwide in 2024, including Indonesians who spend over three hours daily on social media, FOMO has become an increasingly prevalent psychological and social issue. This study employs a qualitative approach using a systematic literature review to examine the relationship between social media use, FOMO, and psychological well-being, while exploring its spiritual dimensions from an Islamic perspective. The analysis draws on Social Comparison Theory, Self-Determination Theory, and Islamic psychospiritual concepts, particularly qana'ah (contentment) as articulated by Ibn Qayyim al-Jawziyyah. The findings indicate that FOMO is strongly influenced by social comparison, declining self-esteem, and compulsive engagement with digital platforms, all of which contradict Islamic values such as qana'ah, tawakkul (reliance on God), shukr (gratitude), and zuhd (detachment from excessive worldly attachment). The study argues that FOMO should be understood not only as a psychological problem but also as a spiritual challenge resulting from the erosion of inner contentment. To address this issue, the study proposes integrating evidence-based digital well-being strategies with Islamic spiritual practices, including mindful dhikr, structured digital detox, and gratitude cultivation. This research contributes to the growing field of Islamic digital psychology by offering an integrative framework for promoting psychological resilience and spiritual well-being in Muslim communities.

Vandalism is a social problem affecting public space quality, urban aesthetics, and the effectiveness of public facilities utilization. Karawang Regency, as a developing industrial area, faces challenges related to increasing acts of vandalism targeting public facilities, open spaces, and government and private assets. This study aims to analyze preventive efforts carried out by the Civil Service Police Unit (Satpol PP) of Karawang Regency using J. Salusu’s public sector strategic management perspective. This research employed a qualitative approach with a descriptive case study method. Data were collected through observation, interviews, and documentation involving Satpol PP officers and public facility users. Data analysis consisted of data reduction, data display, and conclusion drawing with source, technique, and time triangulation. The findings indicate that preventive strategies have been implemented through four strategic management phases. In the identification phase, Satpol PP recognized vandalism patterns but lacked systematic mapping of vulnerable locations. In the development phase, institutional strengths existed alongside limitations in resources and innovation. In the resolution phase, strategies focused on socialization, routine patrols, and cross-sector collaboration. In implementation and evaluation, preventive programs operated adaptively but still encountered limitations in personnel capacity and public participation. Strengthening technology utilization, human resources, and collaborative governance is necessary to improve long-term preventive effectiveness.

The rapid growth of e-commerce has significantly transformed consumer purchasing behavior, particularly in how information is accessed and evaluated. This study aims to analyze the impact of online reviews on consumer purchasing decisions, with a specific focus on the mediating role of consumer trust. A quantitative research approach was employed using data collected from 150 e-commerce users through an online questionnaire. The data were analyzed using regression analysis and Structural Equation Modeling (SEM) to examine the relationships between variables.The results indicate that online reviews have a significant and positive effect on purchasing decisions. Additionally, online reviews significantly influence consumer trust, which in turn positively affects purchasing decisions. The findings also reveal that consumer trust partially mediates the relationship between online reviews and purchasing decisions. This suggests that credible, high-quality, and consistent reviews not only directly influence consumer decisions but also indirectly affect them by building trust.This study contributes to the existing literature on electronic word-of-mouth (e-WOM) and consumer behavior by confirming the importance of online reviews in shaping purchasing decisions in digital environments. From a practical perspective, the findings highlight the need for e-commerce businesses to effectively manage online reviews, encourage authentic customer feedback, and maintain transparency to enhance consumer trust and improve sales performance.

The development of digital services by BPJS Ketenagakerjaan through the JMO (Jamsostek Mobile) application has triggered a surge in large-scale and unstructured user reviews on the Google Play Store, thereby complicating manual analysis and conventional sentiment analysis in accurately identifying specific issues. This research aims to implement the Aspect-Based Sentiment Analysis (ABSA) method to granularly evaluate JMO application reviews based on specific aspects, while simultaneously addressing class imbalance and computational efficiency issues. The proposed method combines the pretrained IndoBERT model as a contextual feature extractor, the SMOTE technique to balance the training data, and an artificial neural network (Neural Network) as the classification layer without performing full fine-tuning. The dataset used consists of 90,268 unique reviews categorized into five main aspects through keyword matching, namely General Satisfaction/Complaints, Performance & Stability, Service & Support, Feature Quality, and UI/UX, with initial lexicon-based labeling using the InSet Lexicon. The research results indicate that the proposed model successfully achieves highly optimal performance with an accuracy rate of 91.81% and a weighted F1-score of 92%. Furthermore, the implementation of SMOTE proved effective in enhancing model reliability on the minority class (negative sentiment), achieving an F1-score of 89%. The implications of this research contribute an accurate and efficient aspect-based sentiment analysis framework for developers, and serve as a strategic evaluation tool for BPJS Ketenagakerjaan in mapping specific user complaints to accelerate continuous improvements in the performance, stability, and service quality of the JMO application.

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.

The study aims to analyze the influence of consumption behavior, projected through cultural, social, personal, and psychological factors, through Generation Z's decision to use the Quick Response Code Indonesian Standard (QRIS). The focus subjects were taken from undergraduate students of Economics at Surabaya State University from 2021 to 2024 who are active users of QRIS. Using an associative quantitative approach using primary data to be collected using an online questionnaire distribution. The data analysis technique applied Structural Equation Modeling–Partial Least Square (SEM-PLS) using SmartPLS 4 software. The results of the study showed that four factors of consumption behavior, namely cultural factors, social factors, personal factors, and psychological factors, have a positive and significant impact on students' decisions to use QRIS. Evaluation of the F-square value F2 shows that psychological factors (internal motivation, perceived ease, security, and trust) are the most dominant predictors with the largest effect value of 0.434 in influencing the decision to adopt this digital payment system technology. These findings indicate that a combination of students' internal motivation, the digital culture inherent in the campus environment, and the demands of practicality in Generation Z's lifestyle strengthen the decision to use QRIS in daily economic activities.  

This study aims to evaluate user satisfaction with the Customer Service Management System (CSMS) at PT Jaya Abadi Kontrindo using the End User Computing Satisfaction (EUCS) method. The CSMS is utilized to support various operational activities, such as purchase requests, payment requests, accounts receivable management, sales order rescheduling, and digital report generation. However, the system still faces several issues, including suboptimal response time, lack of user guidance, and the absence of a specific evaluation of user satisfaction. This study employs a qualitative approach by distributing questionnaires to 50 CSMS users using purposive sampling. The instrument was developed based on the five EUCS dimensions, namely content, accuracy, format, ease of use, and timeliness. The collected data were analyzed using validity testing, reliability testing, mean-based descriptive analysis, and Spearman correlation analysis. The results show that all questionnaire items are valid and reliable. In addition, all EUCS dimensions fall into the satisfied category, with the highest score in ease of use and the lowest in content. The Spearman correlation results also indicate that all EUCS dimensions have a significant relationship with user satisfaction.

Online maps applications have become an essential tool for modern society in finding the fastest and most efficient routes. However, these applications often fail to detect current road conditions such as flooding, demonstrations, accidents, or public events, causing users to get stuck in problematic routes. This study aims to develop a prototype of a community-based road condition reporting system, visualized through a web-based digital map. The system allows users to directly report road conditions by providing photo evidence, descriptions, and event categories. It is also equipped with features for designing event routes such as carnivals and suggesting alternative paths based on community reports. The development process was carried out using a simulation-based approach with scenario testing that reflects real field conditions, without involving direct user data. The implementation results show that all core features work properly. The technologies used include Leaflet.js, OpenStreetMap, and the Nominatim geolocation API. This research produces an adaptive community-based GIS model that can be further developed as an intelligent navigation solution at the city scale