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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.

This study analyzes the implementation of the Central Papua One-Stop Service Information System (Sipersateng) at the Central Papua Provincial Secretariat as a model for administrative innovation in the New Autonomous Region (DOB). The main focus of the study is to explore how a region with extreme infrastructure limitations can leapfrog or institutionalize towards an agile and transparent digital bureaucracy. Using a qualitative descriptive-analytical method with a case study approach, this research involved in-depth interviews, participant observation, and documentation studies to capture the dynamics of the transition from manual to digital systems. The results show that Sipersateng successfully reduced administrative process time by up to 60%. This success was driven by three main dimensions: institutional legitimacy through strong leadership commitment, technical resilience through offline-syncing features to address internet signal fluctuations, and significant changes in work culture. Adaptation strategies such as peer-mentoring methods for senior officials and mandatory policies through gubernatorial instructions proved effective in breaking down organizational cultural resistance. This study concludes that Sipersateng is not merely a technical tool, but rather a manifestation of Frontier Digital Bureaucracy that is able to mitigate the risk of maladministration and build public accountability in the newly formed province. This innovation demonstrates that geographic limitations are not a major barrier to achieving clean governance if supported by inclusive and adaptive system design. These findings provide a theoretical contribution to the public management literature on digitalization in regions with high structural challenges.

This study investigates the performance of Internet of Things (IoT)-based monitoring systems using a mobile hotspot and IoT sensors for temperature and humidity data transmission. The research is based on the IoT concept, which enables electronic devices to communicate and exchange data through internet networks without direct human intervention. System performance was evaluated using standard Quality of Service (QoS) parameters, including throughput, packet loss, delay, and jitter. The experimental setup utilized a NodeMCU ESP32 microcontroller and a DHT22 sensor, with measurements conducted at various transmission distances through wireless communication media. The objective was to determine the reliability of hotspot connectivity and sensor communication in supporting IoT applications. The results indicate that the optimal performance was achieved at a distance of 20 meters using a 40-lambda variation. Furthermore, the communication signal between the ESP32 device and the mobile hotspot remained detectable up to a maximum distance of 32 meters. These findings demonstrate the effectiveness of the proposed IoT system for environmental monitoring applications within specific transmission ranges.

The growth of e-commerce has made online marketplaces a major channel for purchasing fashion products, yet it has also increased consumer concerns about counterfeit goods, especially in shoes and sneakers. This study examines the role of Shopee Mall Signal Perception in increasing Purchase Intention for original shoes among Gen Z consumers by considering the mediating roles of Perceived Shopping Security and Decision Convenience. A quantitative explanatory approach was used, involving 239 Gen Z Shopee users in Indonesia selected through purposive sampling. Data were collected through an online questionnaire and analyzed using Partial Least Squares Structural Equation Modeling with SmartPLS. The findings show that Shopee Mall Signal Perception positively affects Perceived Shopping Security (β = 0.430), Perceived Shopping Security improves Decision Convenience (β = 0.399), and Decision Convenience increases Purchase Intention (β = 0.359). Shopee Mall Signal Perception also has a direct effect on Purchase Intention (β = 0.182), while the serial mediation effect through Perceived Shopping Security and Decision Convenience is significant (β = 0.062). These findings imply that marketplace labels can function as authenticity signals that reduce uncertainty, simplify consumer decisions, and strengthen confidence in purchasing original products online.

Financial reiporting timeilineiss is a cruicial eileimeint that seirveis as a signal of information quiality for inveistors in making inveistmeint deicisions, eispeicially in strateigic seictors suich as thei food and beiveiragei induistry, which has high volatility. This stuidy aims to eixaminei and analyzei thei eiffeict of Profitability on Auidit Reiport Lag with thei Auidit Committeiei as a modeirating variablei in companieis in thei Food and Beiveiragei suib-seictor listeid on thei Indoneisia Stock Eixchangei (IDX) for thei peiriod 2020–2024. This stuidy uiseis a quiantitativei cauisality approach with seicondary data from annuial financial reiports and indeipeindeint auiditor reiports. Thei sampling teichniquiei uiseid puirposivei sampling, which produiceid a samplei of 48 companieis with a total of 240 obseirvations oveir fivei yeiars of obseirvation. Data analysis was peirformeid uising Paneil Data Reigreission with thei seileicteid Random Eiffeict Modeil (REiM) and Modeirateid Reigreission Analysis (MRA) uising EiVieiws 12 softwarei. Thei reisuilts show that profitability has a neigativei and significant eiffeict on auidit reiport lag, meianing that thei higheir a company's profitability, thei shorteir thei duiration of its auidit compleition beicauisei manageimeint is eincouirageid to conveiy “good neiws” to thei puiblic. Conveirseily, thei auidit committeiei, proxieid by thei nuimbeir of meimbeirs, has no significant eiffeict on auidit reiport lag. Fuirtheirmorei, thei MRA teist reisuilts provei that thei Auidit Committeiei is uinablei to modeiratei thei reilationship beitweiein Profitability and Auidit Reiport Lag. This finding has important implications that thei eiffeictiveineiss of suipeirvision in acceileirating thei auidit proceiss is not soleily deiteirmineid by thei quiantity or nuimbeir of Auidit Committeiei meimbeirs, buit is morei influieinceid by quialitativei aspeicts suich as compeiteincei, accouinting eixpeirtisei, and thei indeipeindeincei of meimbeirs in carrying ouit theiir suipeirvisory fuinctions

The banking sector faces dual challenges from economic turbulence and the implementation of expected credit loss accounting standards. An empirical anomaly has emerged where large-scale banks remain aggressive in distributing dividends despite soaring provisioning burdens, while medium-scale banks tend to retain earnings. This research aims to analyze the effect of capital buffer and firm size on dividend distribution decisions, while examining the ability of allowance for impairment losses to moderate these interactions. Utilizing a causal explanatory panel data design, this study observed 15 banking entities on the Indonesia Stock Exchange from 2020 to 2024. Data analysis was conducted using the Tobit regression model to accommodate dividend data characteristics left-censored at zero. Results prove that the capital buffer has no significant effect on dividend decisions, confirming the conservative posture of banks in prioritizing capital retention as a risk cushion. Conversely, firm size significantly determines profit distribution policy positively. In the moderation test, allowance for impairment losses does not moderate the capital buffer-dividend relationship but significantly moderates and amplifies the positive effect of firm size on dividend decisions. These findings imply a strategic resilience signaling maneuver, where large banks respond to high provisioning by expanding cash distribution to prove fundamental robustness to the market. Practically, this study recommends investors prioritize large-scale banks for stable returns and provides insights for regulators regarding the urgency of more adaptive regulatory adjustments.

Radio Gagak Rimang is a Local Public Broadcasting Institution (LPPL) owned by the Blora Regency Government that serves the function of disseminating public information, preserving local culture, and providing entertainment for the community. Objectively and systematically measuring listener satisfaction is a fundamental necessity to maintain sustainability and improve broadcast quality. This study applies the Decision Tree algorithm with the Gini Index criterion to classify listener satisfaction levels based on three main attributes: signal quality, content quality, and presenter quality. Data were collected through a survey of 200 respondents in Blora Regency using a Likert scale questionnaire (1-5). The satisfaction target variable was classified into three classes: Fairly Satisfied, Satisfied, and Very Satisfied. The data were divided with an 80:20 ratio for model training and testing. The evaluation results show that the Decision Tree model achieved an accuracy of 90.00% on the test data and an average accuracy of 88.00% on 10-fold cross validation. The presenter quality attribute had the highest contribution to the classification process at 47.13%, followed by signal quality at 32.60%, and content quality at 17.97%. These findings demonstrate that the Decision Tree algorithm is effective as a decision-support tool for evaluating local radio listener satisfaction.

Artificial intelligence has the potential to support radiology workflows by assisting in the identification of cases that may require additional clinical attention. However, alert-oriented medical AI systems should provide not only classification outputs but also interpretable evidence that can be reviewed and audited by clinicians. This study develops and evaluates an explainable multimodal framework for binary chest X-ray alert classification using paired radiology reports and chest X-ray images. The text branch employs TF-IDF n-gram features with a class-balanced Logistic Regression classifier, while the image branch fine-tunes a pretrained ResNet18 model. The two branches are integrated through probability-level late fusion using a validation-selected fusion weight. Explainability is implemented in a modality-specific manner: global coefficient analysis is used to identify influential textual cues, while Grad-CAM heatmaps are used to visualize salient image regions. Experiments were conducted on paired samples from the Open-i/IU X-Ray dataset using text-only, image-only, and fusion-based evaluation settings. Additional analyses include case-level complementarity analysis, bootstrap confidence intervals for ROC-AUC, shortcut-feature inspection, and qualitative Grad-CAM auditing. The results indicate that the text modality provides the dominant predictive signal under the current proxy-label setting. Late fusion produced a small descriptive improvement on the test set, increasing accuracy from 0.8533 to 0.8667, F1-score from 0.8817 to 0.8936, and ROC-AUC from 0.8936 to 0.9025 compared with the text-only baseline. However, the observed ROC-AUC improvement was not statistically conclusive based on bootstrap analysis. These findings suggest that the proposed framework is useful as a reproducible and auditable multimodal prototype, while also highlighting important limitations, including proxy-label ambiguity, potential label leakage from radiology reports, limited image-branch contribution, lack of external validation, and the need for stronger explanation and calibration assessment.

The development of transportation technology encourages companies to improve vehicle monitoring systems to be more effective and measurable, particularly in addressing speeding violations that can increase accident risks and reduce operational efficiency. This study aims to analyze the implementation and effectiveness of using a buzzer integrated with the Teltonika FMB910 GPS module as a vehicle speed warning indicator at PT. Lacak Cipta Aktual. This research employs a qualitative descriptive method with a case study approach, where data were collected through observation, interviews, and documentation during a one-month industrial internship and analyzed using the Miles and Huberman model, including data reduction, data presentation, and conclusion drawing. The results show that the system is capable of detecting overspeed conditions and automatically activating the buzzer when the vehicle speed exceeds the predefined threshold of 80 km/h. Based on logbook data, the system achieved a success rate of 93.9% in responding to overspeed conditions. The use of a buzzer is proven effective in providing immediate warnings to drivers, thereby improving driver awareness and speed control. However, the system still has limitations, particularly its dependence on GPS signal stability and vehicle electrical conditions. Overall, this study demonstrates that the integration of GPS and a buzzer provides a simple, effective, and cost-efficient solution to enhance driving safety and fleet management efficiency.

Corporate Income Tax payable is an important component of state revenue which is influenced by the company's financial performance and capital structure. The debt-equity ratio has direct implications for taxable profits through the recognition of interest expense as a fiscal deduction. An analysis of financial ratios that reflect the capital structure is necessary to assess its effect on the amount of tax payable. This study examines the Debt to Asset Ratio (DAR), Debt to Equity Ratio (DER), Long Term Debt to Asset Ratio (LDAR), and Long Term Debt to Equity Ratio (LDER) using secondary data from financial statements of consumer goods industry companies on the IDX for the 2020–2024 period. The quantitative approach was applied through multiple linear regression with the help of SPSS and purposive sampling techniques. The results of the partial test show that DAR and LDER have no effect on the Income Tax of the Payable Entity. On the other hand, DER and LDAR have been proven to have a significant effect on the Income Tax of the debtable Entity. Simultaneous testing showed that all variables together had a significant effect on taxes payable. These findings provide practical implications for management in optimizing capital structure policies to improve tax efficiency measurably. Theoretically, the results of this study strengthen the agency theory through the role of debt as a managerial discipline mechanism and support the signal theory that the capital structure is an indicator of information for external parties regarding the company's financial condition.

Travertine is a non-marine carbonate rock precipitated from calcium- and bicarbonate-rich waters, commonly associated with hot springs, streams, and lakes in tectonically active regions. This study presents a systematic literature review of travertine deposit characteristics, encompassing mineralogical composition, geochemical signatures, petrographic textures, morphological types, isotopic properties, biotic–abiotic controls on formation, early diagenesis, and petrophysical implications. The synthesis indicates that travertine is predominantly composed of calcite, with aragonite forming under conditions of elevated temperature, high Mg/Ca ratios, and rapid CO₂ degassing. Travertines display exceptional textural diversity, ranging from abiotic crystalline crusts to microbially mediated fabrics such as shrub, peloidal, and stromatolitic structures. Major morphologies include fissure ridges, mounds, terraces, cascades, and slopes, strongly governed by tectonic setting, topography, hydrology, and substrate geology. Stable isotopes (δ¹³C and δ¹⁸O), strontium isotopes, trace elements, and REE patterns effectively constrain fluid provenance and distinguish thermogene from meteogene travertines. Microbial activity plays a crucial role in biomineralization, influencing precipitation rates, crystal morphology, and lamination patterns. Early diagenetic processes occurring during active deposition may significantly modify primary fabrics and geochemical signals. Travertine petrophysical properties exhibit distinctive porosity–velocity relationships, making them valuable analogues for subsurface carbonate reservoirs. This review highlights that travertines record complex interactions among physical, chemical, biological, and geological processes and hold significant value for paleoenvironmental reconstruction and carbonate reservoir studies.

Cervical cancer is one of the most common cancers worldwide and is largely caused by Human Papillomavirus (HPV) infection, particularly types 16 and 18. The development of this cancer is influenced by the E6 and E7 oncoproteins, which disrupt the function of p53 and Rb proteins, as well as the involvement of cellular signaling pathways such as PI3K/AKT/mTOR and EGFR. Limitations of conventional therapies, such as resistance and side effects, drive the need for more targeted and selective therapeutic agents. This study aims to analyze the main molecular targets of cervical cancer and the medicinal chemistry approaches used in its therapeutic development. The method involved a review of 12 open access articles using molecular docking, molecular dynamics, QSAR, and network pharmacology approaches. The findings identified two main target groups: viral targets comprising the HPV E6 and E7 oncoproteins, and cellular targets including the PI3K/AKT/mTOR pathway, EGFR, PARP1, CDK1, and VEGFR. Various medicinal chemistry strategies, from structure-based and ligand-based drug design to multi-target network pharmacology approaches, proved effective in identifying potential inhibitor candidates. Bioactive compounds such as quercetin, gossypol, bixin, and rutin demonstrated stable interactions with these targets. However, further experimental validation is needed to support the development of clinically effective and safe therapies.

This study aims to investigate the influence of audit committee characteristics—including the proportion of independent audit committee members, audit committee size, and the frequency of audit committee meetings—on the risk of financial statement fraud in companies in the real estate and infrastructure sectors listed on the Indonesia Stock Exchange from 2020 to 2024. This study is grounded in agency theory and signaling theory. The sample was selected using purposive sampling, involving 62 companies or 310 observations. Data analysis was conducted using multiple linear regression via SPSS version 27. The findings of the study indicate that, collectively, the three audit committee characteristic variables, along with the control variables, have a significant impact on financial statement fraud risk. However, when examined individually, the proportion of independent audit committee members, the size of the audit committee, and the frequency of audit committee meetings do not show an influence. Meanwhile, the profitability control variable (ROA) showed an influence on financial statement fraud risk. This study concludes that the extent to which an audit committee can prevent fraud depends not only on quantitative factors such as the number of members or meeting frequency, but is also more influenced by the quality of the audit committee members’ capabilities and commitment in carrying out their oversight duties.

This study examines how environmental, social, and governance issues shape the impact of financial success on firm value. To understand the link between the variables, the legitimacy theory and signal theory are employed. The population used includes non-financial enterprises from 2019–2023 that are listed on the Indonesia Stock Exchange (IDX) and are part of the Refinitiv database. Secondary data was gathered from the Indonesia Stock Exchange, official corporate websites, and the Refinitiv database in the form of sustainability reports, annual reports, and ESG scores. The sample size is 176 company data points over 5 years, selected using the purposive sampling method. Firm value is positively and significantly impacted by financial success, according to the research findings. ESG also improves the link between firm value and financial performance, according to the study. Lastly, the study's results also show that ESG increases business value, while not significantly. These findings suggest that the study's ESG variable is a pure moderator variable. Furthermore, the implications of the research both theoretically and practically have been discussed.

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.

Sentiment analysis for Indonesian regional languages faces two persistent challenges: labeled training data is extremely limited for most regional varieties, and transformer models pre-trained on Bahasa Indonesia do not generalize reliably to languages with substantially different morphological structures. Prior work on the NusaX benchmark has primarily relied on direct fine-tuning, treating each regional language independently and without exploiting linguistic proximity between related languages as a transfer signal. This paper proposes Language-Similarity-Guided Transfer (LSGT), a sequential fine-tuning strategy that first adapts a pre-trained model to a pivot language selected using character trigram similarity, followed by fine-tuning on the target language. Four transformer models are evaluated across all 12 NusaX languages using the official train/validation/test splits: IndoBERT, NusaBERT, mBERT, and XLM-R. Performance is evaluated using four metrics: accuracy, macro F1, macro precision, and macro recall. Experimental results show that LSGT improves macro F1 in 44 of 48 model-language combinations, demonstrating that the fine-tuning strategy itself is a major factor in low-resource cross-lingual sentiment classification. XLM-R benefits most strongly from LSGT, achieving an average improvement of +0.137 macro F1 and a peak gain of +0.298 on Madurese. SHAP-based token attribution analysis further reveals that predictions rely heavily on named entities and domain-specific nouns rather than sentiment-bearing vocabulary, indicating a dataset-level bias inherited from the original SmSA corpus and propagated through the NusaX translation pipeline.

This research explores hedonistic lifestyle patterns as a social reality that grows within peer interactions, both in adolescence and adulthood. The investigation applies a qualitative descriptive literature review by examining national scholarly publications issued from 2016 to 2026. The findings indicate that hedonistic tendencies should not be interpreted merely as individual choices to seek enjoyment. Instead, they emerge from social processes shaped by interaction, peer influence, and shared norms that develop within a group. In this context, peer circles function as influential socialization agents, encouraging conformity so individuals can be accepted and avoid social exclusion. The study also identifies differences in underlying motivations across life stages. Among adolescents, hedonistic behavior is closely linked to identity exploration and self-definition. For adults, however, it is more associated with maintaining self-image, signaling social standing, and displaying markers of achievement. Overall, environmental dynamics, the expansion of consumer-oriented culture, and intensive exposure to social media play significant roles in strengthening this phenomenon in Indonesia.

Intellectual property rights (IPR) are an important legal tool for trademark ownership, protecting business quality, and protecting a company's economic interests. Consumers build trust in trademarks because they signal distinct product quality and reflect a positive and consistent corporate image. Trademark protection is regulated by national law under Trademark Law No. 20 of 2016, which provides legal certainty for trademark owners. This law stipulates that a trademark is only valid if it has distinctive elements, is not imitative, and has been officially registered with an authorized institution. The "first come, first served" principle in Indonesian trademark law can be interpreted as a mechanism that grants rights to the first party to file a valid application. However, the application of this principle in practice often raises complex legal issues, particularly when a trademark has already gained widespread public recognition prior to its formal registration. This study focuses on evaluating this legal protection through a normative legal research method by examining applicable laws, regulations, and court decisions related to trademark disputes in Indonesia. The Geprek Bensu dispute has attracted public attention because it highlights the conflict between legal provisions regarding trademark ownership and public perception. This case demonstrates that the existing legal framework still requires further refinement to balance the interests of trademark registrants with those of parties who have built public reputation through prior commercial use. Therefore, legal reform and consistent law enforcement are essential to ensure fair and comprehensive trademark protection in Indonesia.

This study was conducted to evaluate the impact of financial performance, capital structure, and good corporate governance on entities. The approach used is quantitative with a causal associative method. The research observations utilize secondary data sourced from the financial statements of entities listed on the stock exchange during the 2020–2023 period. The research sample was determined using a purposive sampling technique based on predefined criteria, totaling 160 observations. The analytical method employed is multiple linear regression, preceded by classical assumption tests. The results reveal that financial performance and good corporate governance have a positive and significant effect on the quality of financial statements, while capital structure has a significant negative effect. Simultaneously, the three independent variables are proven to significantly affect the quality of financial statements, with a coefficient of determination of 68%. These findings support agency theory and signaling theory in explaining the financial reporting behavior of entities. The implications of this study indicate that improving financial performance and implementing good corporate governance can enhance the quality of financial statements. Furthermore, optimal management of capital structure is also necessary to reduce the risk of financial statement manipulation.

This study discusses the design and simulation of an automatic lighting system based on a photodiode sensor using an Arduino Uno microcontroller as the main controller. The system is designed to detect changes in ambient light intensity and automatically control the lamp without human intervention. The photodiode sensor is used as a light detector that converts light energy into an analog electrical signal, which is then processed by the Arduino to determine bright or dark conditions. The output from the Arduino subsequently controls a relay module that functions as an electronic switch to connect or disconnect the current to the light bulb. The research method employed is an experimental approach, which includes system planning, hardware design, software programming, simulation using Proteus, and system performance testing. The simulation results indicate that the system operates as expected, where the lamp automatically turns on when the light intensity decreases and turns off when the ambient brightness increases. This system is expected to improve electrical energy efficiency and provide ease of operation for lighting control, particularly in public facilitiesand workplace environments.