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This article examines the legal consequences of a delayed notification of a share acquisition under Indonesian competition law, focusing on the case of PT X's takeover of PT Y. The central issue is PT X's failure to report the acquisition to the Commission for the Supervision of Business Competition (KPPU) within the mandated 30-day period, as stipulated by Law Number 5 of 1999 and its implementing regulation, Government Regulation Number 57 of 2010. The notification was submitted with a significant delay of 2,023 days, a clear violation of the statutory requirements. As a result of this non-compliance, the KPPU, through its Decision No. 31/KPPU-M/2020, imposed an administrative fine on PT X amounting to   IDR 1,050,000,000.00 (one billion fifty million rupiah). Beyond the direct financial penalty, the violation led to severe indirect repercussions, including significant    reputational damage, which threatened to erode investor confidence and disrupt existing business relationships. The KPPU's firm and consistent enforcement in this case highlights the critical function of the post-merger notification system in Indonesia as a preventative mechanism to assess transactions that could lead to excessive market concentration. The decision underscores the legal principles of     transparency, fairness, and accountability that underpin Indonesian competition law. This case serves as a powerful deterrent, signaling to all business actors that non-compliance will not be tolerated. Ultimately, such rigorous enforcement is crucial for fostering a culture of legal adherence, maintaining market integrity, and building a more transparent and competitive business ecosystem that supports sustainable economic growth in Indonesia.

The purpose of this education is to increase public awareness, especially among teenagers, of the impacts of early marriage through educational seminars and Service-Learning-based outreach in Naga Kesiangan Village. Early marriage remains a critical issue in Indonesia, often associated with health risks, psychological stress, and limited educational and social opportunities for young people. The Service-Learning approach was chosen because it not only provides knowledge transfer but also actively engages participants in reflection and discussion, ensuring that the learning process is more contextual and sustainable. The method used was Service-Learning, involving 30 teenagers aged 15–19 years, 15 parents, and 5 community leaders who were purposively selected for their direct relevance to the issue. Activities included seminars, small group discussions, interactive question-and-answer sessions, and collective reflection. The results of the activity showed a significant increase in participants’ understanding, from 42% (pre-test) to 81% (post-test). Participants gained a deeper understanding of the health, psychological, social, and educational risks of early marriage and were encouraged to delay marriage by choosing positive alternatives through education and skill development. This program also strengthened the role of families and community leaders as preventive agents by fostering collective awareness and support. Thus, educational seminars integrated with Service-Learning prove to be effective and replicable strategies to prevent early marriage practices, while also empowering communities to build healthier, more resilient generations.

Public policies in the fields of health, environment, and safety are increasingly subject to disputes through the Investor-State Dispute Settlement (ISDS) mechanism. However, state efforts to protect the public often face claims from investors who consider themselves harmed. This situation carries serious consequences, as states not only bear high litigation costs but may also be required to pay significantly larger compensation if they lose the dispute. This gives rise to regulatory chill, a condition in which governments delay, weaken, or revoke regulations due to concerns over potential investment disputes. Even when some cases result in a state victory, the potential for regulatory chill remains significant, as investors do not need to win disputes to create regulatory uncertainty and pressure policymakers. This phenomenon can manifest in three forms precedential chill, anticipatory chill, and specific response chill, each affecting the policy-making process differently. Regulatory chill narrows the regulatory space, limits state capacity to protect public interests, and creates a deterrent effect on the implementation of new regulations. Using a normative juridical approach enriched with comparative case studies, this paper examines three primary sources of regulatory chill: the economic burden of arbitration and potential compensation, long-term commitments, and institutional limitations in meeting the standard of fair and equitable treatment.

Diabetes Mellitus (DM) is a non-communicable disease that is currently a major public health problem in Indonesia. The prevalence of DM continues to increase from year to year, not only in urban areas but also increasingly found in rural areas. One factor contributing to the high number of DM cases is a lack of public awareness of the importance of a healthy lifestyle, as well as the continued presence of many undiagnosed cases, resulting in delayed treatment. Therefore, early detection efforts and health education that can reach the community at the community level are needed. This community service program was designed to conduct random blood sugar screenings while increasing the knowledge of residents of RW 15 Kalibaru regarding the prevention and control of DM. The activity was carried out on August 24, 2025, involving 21 participants, most of whom were from adults to the elderly. The activity method consisted of two main stages: checking blood sugar levels using a glucometer and a health education session on a healthy lifestyle, a balanced diet, and the importance of regular physical activity. The results of the activity showed that the indicators of success were well achieved. This was indicated by the orderly implementation of the examinations, a high level of participation from residents, and increased awareness of the dangers of DM among participants. From the examination results, most participants had normal blood sugar levels, but several people were found with blood sugar levels above the normal limit who required medical follow-up.

This study aims to examine the effect of Return on Assets (ROA), Debt to Assets Ratio (DAR), and Total Assets on Audit Delay in food and beverage sub-sector companies listed on the Indonesia Stock Exchange (IDX) during the 2020–2024 period. Audit Delay is defined as the time interval between the end of the fiscal year and the issuance date of audited financial statements by independent auditors. The timeliness of financial reporting is a crucial element for stakeholders in evaluating company performance, enhancing transparency, and supporting decision-making processes. Therefore, understanding the factors that influence audit delay is important in the context of both regulatory compliance and corporate governance. This research adopts a quantitative methodology using multiple linear regression analysis. The data used are secondary data obtained from annual financial reports published and accessible through the official IDX website. The study sample consists of 33 companies, resulting in 165 observations. After conducting outlier analysis, the final dataset comprised 83 observations. Data analysis was carried out using the Statistical Package for the Social Sciences (SPSS) Version 22. The results show that Return on Assets and Total Assets do not have a significant effect on Audit Delay. This indicates that profitability and company size are not the main determinants of audit timeliness in this sector. However, the Debt to Assets Ratio was found to have a relatively positive effect on Audit Delay. This finding suggests that companies with higher leverage tend to be audited more quickly, possibly because auditors and stakeholders pay greater attention to firms with higher financial risk. Thus, a company’s capital structure plays an important role in influencing the timeliness of audit completion.

Child developmental delay is a public health issue that needs to be identified early to prevent long-term impacts on children’s quality of life. In Rantau Prapat Sub-district, cases are still found among toddlers with undernutrition, incomplete immunizations, and suboptimal developmental stimulation, which may pose risks of growth and developmental delays. This study aims to apply the Naive Bayes method in identifying child developmental delays based on health data collected through medical records and questionnaires. The research method includes data collection, pre-processing (cleaning, transformation, and normalization), classification using the Naive Bayes algorithm, and model validation with the k-fold cross-validation technique. The results showed that out of 150 toddler data samples, 30.7% experienced developmental delays, with the dominant influencing factors being nutritional status and immunization completeness. The Naive Bayes algorithm achieved an accuracy rate of 87.3% with a precision of 84.1%, recall of 85.7%, and F1-score of 84.9%. These findings demonstrate that Naive Bayes can be used as a decision support system in the early identification process of child developmental delays. Therefore, the results of this study are expected to assist healthcare workers, particularly midwives, in improving the quality of early detection and delivering more targeted interventions for children in the Rantau Prapat area.

This research aimed to determine how the Village Revenue and Expenditure Budget was managed in handling emergency caused by the vilcanic eruption in Boru Village, Wulanggitang Sub-district, East Flores Regency. The Lewotobi volcano eruption disaster that occurred at the end of December 2023 required the vullage government to make quick and appropriate budget adjustments. This research used a qualitative approach with the Miles and Huberman analysis method, which included data reduction, data presentation, and conclusion drawing. Data collection techniques were carried out through interviews, documentation, and observation. The results of the research showed that the Village Revenue and Expenditure Budget planning was carried out adaptively through a Spesial Village Meeting. The implementation of emergency funds was effective despite communication constraints, and administration and reporting were still carried out despite delays. The village government had formally accounted for its actions to the regional government and strove to build transparency with the community. This research supported the stewadship theory, in which village governments acted as trustees of the community in managing public finances. This research was also in line with several previous studies that emphasize the importance of accountability and participation in village fund management, especially in crisis situations.

In the automotive manufacturing industry, efficiency in quality control is a crucial factor to ensure consistent product quality. Conventional Quality Assurance (QA) processes using manual record-keeping often face challenges such as delayed reporting, human errors, and difficulty in tracking historical data. This study aims to design and implement a QA performance dashboard based on digital forms at PT Dharma Polimetal, Tbk, to enhance efficiency in production quality control. The research methodology includes direct field observation, collection of production and QA data, mapping of QA process flows, interactive dashboard interface design, and system trial implementation. The designed dashboard focuses on four main aspects: QA Incoming, QC Line, QC Gate, and Customer Handling, each containing measurable performance indicators and quality parameters. Initial implementation results indicate significant improvements in QA process monitoring, faster reporting of inspection results, and easier real-time data access for both production teams and management. The system enables early detection of potential quality issues, supports rapid decision-making, and facilitates internal and external audits. Moreover, the use of digital forms within the dashboard enhances data accuracy, minimizes human error, and creates structured historical records for long-term analysis. This study provides a tangible contribution to the digitalization of QA systems, strengthening sustainable quality control practices in the automotive industry, thereby ensuring consistent productivity and product quality.

Postoperative consciousness recovery in patients who have received general anesthesia sometimes experiences delays, which can lead to postponing the transfer of patients to the recovery room. One approach that nurses can use to accelerate consciousness recovery after general anesthesia is by adjusting the patient’s sleeping position. This study aims to determine the effect of the semi-Fowler position on the length of consciousness recovery in postoperative patients with general anesthesia. The research method is quasi-experimental with a posttest-only control group design. The sample consisted of 42 postoperative patients with general anesthesia at RSUD dr. H. Soewondo Kendal, divided into two groups: the intervention group and the control group, selected using consecutive sampling technique. Data analysis was performed using the independent sample t-test. The results showed that most patients were aged 36-45 years, male, with the most commonly used anesthetic being Laryngeal Mask Airway (LMA) and the duration of surgery was less than 1 hour. The average consciousness recovery time for patients in the semi-Fowler position was 11.19 minutes, categorized as quick recovery. Meanwhile, the average consciousness recovery time for patients in the supine position was 15.0 minutes, also categorized as quick recovery. The analysis showed a significant effect of the semi-Fowler position on the consciousness recovery time (p-value = 0.048). In conclusion, the semi-Fowler position can accelerate consciousness recovery time by 3.81 minutes compared to the supine position in postoperative patients with general anesthesia.

Patients admitted to the Intensive Care Unit (ICU) often experience physiological disturbances caused by both medical conditions and intensive treatment procedures. One of the most common problems encountered is sleep disturbance. Several factors contribute to poor sleep quality in ICU patients, including repeated medical procedures, environmental noise from medical equipment and staff activities, discomfort due to body positioning, frequent interactions with health workers, continuous exposure to lighting, pain, and the underlying disease process. Persistent sleep disturbances can delay the healing process, increase blood pressure, and even elevate the risk of stroke. This study aimed to analyze the relationship between anxiety levels and sleep quality in compos mentis patients in the ICU of Sultan Agung Islamic Hospital Semarang. The research design employed a correlational approach with a cross-sectional method. A total of 30 respondents were selected according to the inclusion criteria. Data were collected using the Pittsburgh Sleep Quality Index (PSQI) to measure sleep quality and the Hamilton Anxiety Rating Scale (HARS) to assess anxiety levels. The Chi-Square test was used for statistical analysis. The results showed an equal distribution of male and female respondents (15 each). Ten respondents had a post-laparotomy medical diagnosis, and the majority belonged to the late elderly age group (10 respondents). Most respondents experienced moderate anxiety (18 respondents), while poor sleep quality was reported by 17 respondents. The Chi-Square test revealed a p-value of 0.001, indicating a significant relationship between anxiety levels and sleep quality. In conclusion, higher anxiety levels were associated with poorer sleep quality among compos mentis patients in the ICU. These findings highlight the importance of nursing interventions that address both the physical and psychological aspects of patients to improve sleep quality and support recovery.

This study examines the influence of ship maintenance and spare-part availability on the operational continuity of the AHTS Transko Andalas, operated by Pertamina Marine Solutions. Using a qualitative-descriptive approach with supportive quantitative indicators, data were collected through semi-structured interviews, questionnaires, onboard observations, and document analysis. The Spare-Parts Readiness Index (SPRI) and Planned Maintenance Compliance (PMC) were applied to measure vessel preparedness. Results revealed that both maintenance and spare-part availability positively and significantly impact operational continuity, though challenges remain in procurement delays, critical maintenance compliance, and workforce competence in predictive diagnostics. Thematic analysis highlighted procurement bottlenecks, maintenance execution gaps, and human resource limitations as recurring barriers. Findings contribute to maritime operations management, shipping sustainability, and vocational education by demonstrating the interdependence of technical and human factors in sustaining offshore vessel reliability. The study emphasizes the urgency of integrated procurement reforms, condition-based maintenance, and workforce training to achieve sustainable maritime operations.

Dental and oral health is still a significant problem in Indonesia. Riskesdas 2018 data shows that 57.6% of the population has dental and oral problems, while only 2.8% brush their teeth properly. This condition is a serious concern because untreated dental caries can develop into pulp necrosis and subsequently radical gangrene. Both conditions have the potential to cause infections that can interfere with people's quality of life if not treated immediately. This study aims to compare the prevalence of visits to pulp necrosis and radical gangrene based on gender and age at the UPTD Baturiti II Tabanan Health Center during January-March 2025. The research uses a quantitative descriptive method with a purposive sampling technique based on secondary data from the E-Puskesmas system. The results showed that the prevalence of gangrene radicals (7.2%) was higher than that of pulp necrosis (5.9%). Female patient visits were more dominant in both cases, namely 52.7% in pulp necrosis and 56.5% in radical gangrene. The age distribution showed that the age group of 20–44 years dominated in cases of pulp necrosis (42.1%), while gangrene radicals occurred more in the age group of 45–59 years (34.8%). These results indicate a delay in dental care that contributes to the progression of the disease. The high number of these incidents cannot be separated from behavioral factors and the low level of public knowledge in maintaining dental and oral health. Therefore, increasing communication, information, and education efforts at the level of primary health care facilities is essential to encourage public awareness. Early detection and timely treatment are key in preventing serious complications such as pulp necrosis and radical gangrene.

This study aims to design and develop an expert system to assist in diagnosing diseases in dairy cattle at Cibugary Farm using the Forward Chaining method. The background of this research lies in the limited knowledge of farmers in identifying early symptoms of diseases, which often leads to delays in medical treatment and negatively affects dairy cattle productivity. To address this issue, an expert system was designed to replicate the reasoning process of a human expert through a knowledge base containing diagnostic rules derived from observable symptoms. The Forward Chaining method was chosen because of its capability to trace facts from known symptoms toward a conclusion regarding the type of disease affecting the cattle. The system was developed by incorporating common disease symptoms, inference rules, and a decision-making mechanism that simulates expert analysis. Testing was carried out on several diagnostic scenarios to evaluate the accuracy and efficiency of the system. The results of the study indicate that the expert system can provide an initial diagnosis quickly and accurately, producing outputs consistent with expert assessments. This functionality assists farmers in making timely decisions regarding appropriate medical interventions, thereby reducing treatment delays and minimizing the risk of disease transmission within the herd. Consequently, the Forward Chaining-based expert system is expected to serve as an innovative solution to improve dairy cattle health management and support sustainable livestock productivity at Cibugary Farm.

Typhoid fever is a significant health issue caused by the Salmonella Typhi bacteria, leading to symptoms such as fever, abdominal pain, diarrhea, muscle pain, and serious complications if not treated promptly. A common challenge faced by society is limited access to medical professionals, especially in remote areas, and delays in recognizing symptoms. To address this problem, this study designs and implements a web-based expert system using the Certainty Factor (CF) method, which helps diagnose typhoid fever quickly and accurately. The Certainty Factor method is used to calculate the certainty level of the symptoms experienced by the patient, providing a diagnosis result in the form of early-stage typhoid, mild typhoid, or severe typhoid. The system was developed using PHP programming language and MySQL database, and tested at RSUD Djoelham Binjai City. The research data was obtained from patients at RSUD Djoelham Binjai with a case study on patient number 22. The processing of symptoms through Certainty Factor calculation showed that the patient is most likely to have severe typhoid with a certainty value of 0.9443 or 94.43%. This result proves that the Certainty Factor method can be used to assist in providing an accurate early diagnosis of typhoid fever with a high degree of accuracy.

The increase in traffic volume in urban areas often triggers various problems, especially at Road intersection points that have a high level of interaction between vehicles. One of the locations that experience these problems is the intersection with the island of traffic without signal on Jl. Tebu-Jl. Tabrani Ahmad, City Of Pontianak. This study aims to analyze the performance of the intersection in the existing condition and project its performance in the next five years (2030), as well as formulate alternative treatment that can improve the smoothness of traffic. The analysis method refers to Indonesian road capacity guidelines (PKJI) 2023 and modeling using software PTV VISSIM. The data collected include intersection geometry, traffic volume, and vehicle speed. Traffic volumes were obtained through CCTV recordings for three consecutive days, then processed and presented in the form of tables and graphs for easy interpretation. The results of the existing condition analysis showed that the degree of saturation (DS) reached 0.407 with an average delay of 9.539 seconds (Level of Service/LOS B) based on PKJI, while VISSIM simulation resulted in a delay of 12.54 seconds (LOS B). The five-year projection (2030) shows an increase in DS to 0.878 with a delay of 15.177 seconds (LOS C) from PKJI, and 23.35 seconds (LOS C) from VISSIM, which indicates a decrease in Junction performance as traffic grows. Two handling alternatives were analyzed, namely the construction of roundabouts and the implementation of traffic flow management. VISSIM simulation shows that the roundabout can reduce the delay to 14.31 seconds with a queue length of 20.34 m (LOS B), while the flow management produces a delay of 11.81 seconds with a queue of 13.14 m (LOS B). This result confirms that both alternatives are able to improve the performance of the intersection compared to the projected condition without handling, so that it can be a technical recommendation for urban traffic planning in Pontianak.

Distribution is an important aspect that affects the operational efficiency of a company, especially in terms of goods delivery. This study aims to develop an optimization model for LPG gas distribution routes using Excel Solver based on geographic coordinate conversion. In this study, the method used includes converting geographic coordinates from decimal to Degree-Minute-Second (DMS) format, followed by conversion to kilometers to form a more accurate distance matrix. The optimization model was built using the Capacitated Vehicle Routing Problem (CVRP) approach, which takes into account vehicle capacity constraints (a maximum of 560 cylinders per truck) and the limited number of available fleets, which is only one truck. The results show that coordinate conversion produces high accuracy in calculating distances between distribution locations. By using Excel Solver, the optimization solution successfully minimizes the total distance traveled compared to the conventional route, where distribution is carried out more evenly to 57 scattered LPG base locations. The addition of Solver Parameters Evolutionary and All Different constraints proved effective in avoiding duplication of visits and producing optimal distribution routes. This solution not only improves distribution time and cost efficiency, but also improves service to customers by reducing delivery delays. The success of this optimization model is expected to be implemented by other distribution companies to improve their operational performance. This study also highlights the importance of selecting the right software to aid the distribution optimization process. Excel Solver, despite its simplicity, proved highly effective in solving complex distribution routing problems, especially when combined with coordinate conversion techniques that yield more accurate distances. Furthermore, the application of the CVRP method enabled more efficient decision-making in determining distribution routes, taking into account vehicle capacity and fleet limitations.

The spice industry faces significant challenges in maintaining product weight consistency as part of quality assurance and compliance with production standards. A case at PT X revealed that a newly installed filling machine produced deviations from the target weight of 50 grams, with hypothesis testing showing that out of 30 samples, 17 samples fell outside the  confidence interval. To mitigate this issue, this study proposes the development of a real-time data-driven Decision Support sistem (DSS) combined with statistical approaches. The methodology includes two-tailed hypothesis testing to detect weight deviations and Failure Mode and Effects Analysis (FMEA) to identify dominant failure causes based on high Risk Priority Numbers (RPN), such as delayed machine calibration, operator error, and worn-out machine components. These findings serve as the foundation for designing the DSS architecture, which consists of sensor input modules, statistical data processing, risk mapping, and an automated corrective recommendation engine. The sistem is designed to enable early detection of deviations, accelerate response time to quality issues, and support data-driven decision-making on the production floor. The study concludes that a structured implementation of DSS can be an effective strategy to improve product weight consistency and enhance operational efficiency in spice manufacturing.  

This study aims to determine the level of problematic smartphone use (PSU) and revenge sleep procrastination (RBP) among MTs/SMP students in District X, while also examining the relationship between the two variables. The problem of excessive smartphone use among adolescents is increasingly important to study because it can impact sleep quality, learning concentration, and mental health. This research approach uses a quantitative correlational method with data collection through a bold questionnaire (Google Form). The research sample consisted of 103 MTs/SMP students in District X who were selected using an incidental sampling technique. The RBP variable measurement scale was developed by the researcher with reference to aspects proposed by Kroese et al. (2014). Meanwhile, the PSU Scale was developed based on dimensions formulated by Foerster et al. (2015), including withdrawal, desire, loss of control, dependence on peers, and negative life consequences. The results of the correlation analysis showed that PSU had a very strong positive relationship with RBP (r = 0.833) and was statistically significant (p < 0.000). This means that the higher a person's tendency to experience problematic smartphone use, the greater the likelihood of revenge bedtime delay. Among the dimensions of PSU, withdrawal showed the highest correlation with RBP (r = 0.831). This was followed by negative life consequences (r = 0.778), craving (r = 0.577), loss of control (r = 0.489), and dependence on peers (r = 0.333). Overall, this study concludes that PSU plays a significant role in increasing RBP trends among students. These findings highlight the urgent need for awareness and intervention programs to reduce excessive smartphone use among adolescents. Therefore, the results of this study are expected to serve as a reference for schools and parents in designing strategies to prevent the negative impacts of smartphone use on adolescents.

This study aims to determine the relationship between emotional intelligence and academic procrastination in completing final assignments among Psychology students at Medan Area University. Academic procrastination is a procrastination behavior often carried out by students when facing important tasks, including their thesis, which can impact graduation delays and decrease learning motivation. Psychological factors, such as emotional intelligence, are thought to influence this procrastination tendency. Emotional intelligence encompasses an individual's ability to recognize, understand, manage, and express emotions healthily, as well as establish positive interpersonal relationships. Students with high emotional intelligence tend to be better able to cope with pressure, manage academic stress, and maintain focus on their academic goals. This study used a quantitative approach with a correlational method to examine the relationship between the two variables. The subjects in this study were 80 final-year students who were in the process of preparing their final assignments. The sampling technique used was purposive sampling, with the criteria being active students who were writing their thesis. The instruments used consisted of an emotional intelligence scale and an academic procrastination scale compiled based on relevant theoretical indicators. Data analysis was performed using the Pearson correlation test. The analysis results show a significant negative relationship between emotional intelligence and academic procrastination. This means that the higher a student's emotional intelligence, the lower their level of academic procrastination. This finding suggests that emotional intelligence plays a crucial role in supporting students in completing their final assignments on time. Therefore, developing emotional intelligence through psychological training or guidance could be a strategy to reduce procrastination among students.

Prolonged road damage disrupts community mobility, logistics activities, and reduces road user safety. The road maintenance project on Jl. Ir. Soekarno in Blitar City, which was planned to be completed in 120 days with a budget of Rp1.16 billion, experienced a delay of 8 days due to time management constraints. This study aims to evaluate the use of the Time Cost Trade Off (TCTO) method to accelerate project completion without reducing the quality of work. The TCTO method is used to analyze the relationship between time and cost. This research proposes additional overtime working hours of 2 hours per day with the assumption of resources according to the Cost Budget Plan (RAB). The results show that with this method, the project can be completed in 117 days at a total cost of Rp1,342,177,724. Although it requires additional costs, this acceleration allows the project to be completed faster than the previous condition