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Coal hauling activities are an important part of mining operation because they affect production continuity, cycle time efficiency, and operational safety. This study aims to analyze the requirements of road support equipment on the coal hauling road from Sector 4 to the new Coal Processing Plant (CPP) at PT. Asmin Bara Bronang, Central Kalimantan. Based on road geometry, traffic density, California Bearing Ratio (CBR), and Unsurfaced Road Condition Index (URCI). The research method used was applied research with a quantitative approach. Primary data ware collected through field measurements consisting of road geometri observations, traffic density observations, Dynamic Cone Penetrometer (DCP) testing to obtain CBR values, and road surface condition assessment using the URCI method. Secondary data were obtained from the company records. The results showed that the hauling road has a total length of 9.1 km with an average width of 16 m, and grade values ranging from -7.68% to 10.52%, which are still below the maximum standard of 12%. Traffic density reached 184 dump trucks/day, for coal hauling and 62 units/day for construction material transportation, indicating high traffic intensity. CBR values ranged from 7% to 100%, showing variations in subgrade bearing capacity. The URCI value ranged from 72,50 to 91.00, indicating fair to good road conditions. Based on the analysis of road conditions and maintenance area requirements, the recommended support equipment for maintaining the hauling road consists of 1 motor grader unit, 1 compactor unit, 1 bulldozer unit, and 1 water truck unit.

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.

Land rights disputes arising from overlapping land certificates remain a complex agrarian law issue frequently encountered in Indonesia. This phenomenon reflects weaknesses in the land administration system, particularly in data collection, land measurement, and certificate issuance. Such disputes create conflicts, legal uncertainty, and reduced public trust in the land registration system. In practice, these disputes are generally resolved through civil litigation procedures in the District Court. This study aims to comprehensively analyze civil procedural law in resolving land rights disputes involving overlapping certificates and to examine the evidentiary strength of land certificates in judicial proceedings. This research employs a normative legal method using statutory and conceptual approaches, supported by primary and secondary legal materials. The findings indicate that dispute resolution begins with the filing of a lawsuit, followed by mediation, court examination, and the evidentiary process as the most crucial stage in determining lawful ownership. Land certificates serve as strong evidence; however, they are not absolute, as they may be challenged if administrative or substantive legal defects are identified. Judges play a central role in assessing certificate validity by considering land history, physical possession, good faith, and compliance with legal procedures. Nevertheless, the effectiveness of dispute resolution still requires improvement through better land administration, enhanced data accuracy, and stronger institutional integration.

This study aims to analyze a comparison of coal stockpile volumes using the DJI Mavic 3 Pro Unmanned Aerial Vehicle (UAV) method versus the truck count method at PT. Mitra Barito. Data collection was conducted through aerial photography using a UAV at altitudes of 60 meters and 70 meters, as well as Ground Control Point (GCP) measurements using GPS. The aerial imagery data was processed using photogrammetry software to generate orthophotos and a Digital Elevation Model (DEM), followed by a geometric accuracy test based on the Geospatial Information Agency Regulation No. 6 of 2018, using the Circular Error 90% (CE90) and Linear Error 90% (LE90) parameters. The research results show that high-quality processing at an altitude of 60 meters yields a CE90 value of 2.1619 meters and an LE90 value of 4.3656 meters, thereby meeting the accuracy standards for RBI maps at a scale of 1:5,000, Class 3 for horizontal accuracy, and a scale of 1:10,000, Class 3 for vertical accuracy. Volume calculations of the stockpile using UAVs yielded a result of 22,750.900 m³, while the truck count method produced a volume of 23,503.300 m³. The volume difference between the two methods was 753.400 m³, with a deviation percentage of 3.2%. Based on the research results, the UAV method is considered capable of providing relatively accurate calculations of coal stockpile volume.

Gesture  recognition  technology  is  used  to  detect  movements  through  image processing,   enabling  computers  or digital devices to understand and interpret human  body  movements  as  input  or  commands.   This  technology  has  great potential  to bridge communication between the deaf community and individuals without   hearing   impairments,    enhancing  interaction  and  enriching  mutual understanding between the two.  However,  the accuracy ofgesture recognition is often  affected  by variations in the distance between hand landmarks.  Based on this problem,  this research proposes a methodfor stabilizing the measurement of distances between landmark points  in gesture recognition through a polynomial regression  approach.   Specifically,   the  distance  between  hand  landmarks  is calculated and stabilized using polynomial  regression to improve the accuracy of gesture recognition.  This method is implemented using the MediaPipeframework to detect and track hands in real-time,  and the OpenCV library to manage video. The  research  results  show  that  this  approach  can  significantly  improve  the stability  and accuracy  of gesture detection.   The developed system successfully detects gestures for  letters A  through F with a high accuracy  rate,  averaging above 98,3%.  The use ofpolynomial regression helps enhance detection accuracy by reducing noise in the landmark data.

One of the goals of a building is to create a comfortable environment that does not affect the health and operations of its occupants, therefore a system needs to be created to ensure comfort in classrooms. To fulfill a comfortable situation, there is a standard that regulates comfort, especially thermal and visual comfort. Thermal comfort is regulated in SNI 03-6572-2001 and visual comfort is regulated in SNI 03-6575-2001. The aim of this research is to design a tool to automatically monitor temperature and lighting, determine greater accuracy, determine temperature and lighting comfort distances, and test Smart Comfort measurement results in accordance with the SNI-03-6571-2001 and SNI-03-6575-2001 conformity standards. This design uses ESP32 with IoT-based LDR and DHT11 sensors which can be seen on the web and application, determines the accuracy and range of Smart Comfort values for monitoring temperature and lighting and determines the suitability of measurement quantities in the SDN PINANG 3 classroom.

Adolescents are considered a vulnerable group to nutritional problems because they experience rapid physical growth accompanied by lifestyle changes and unhealthy eating habits. The increasing prevalence of overweight and obesity among teenagers has become a major public health concern that requires serious attention. This study was conducted to examine the relationship between peer influence, the frequency of eating out, and fast-food consumption habits with the incidence of overweight among students at SMAN 1 Surabaya. The research applied a quantitative approach using an analytical observational design with a cross-sectional method. A total of 81 students participated in the study and were selected through proportional random sampling. Data were collected using questionnaires, SQ-FFQ forms, and anthropometric measurements, then analyzed using the Chi-Square statistical test. The findings revealed significant associations between peer influence, eating out frequency, and fast-food consumption habits with the occurrence of overweight among adolescents. Students who more frequently consumed meals outside the home and regularly ate fast food showed a greater tendency to experience overweight and obesity. These results indicate that social environments and modern dietary patterns contribute to the increasing prevalence of overweight among adolescents. Therefore, nutrition education and healthy lifestyle promotion should be strengthened through the involvement of schools, families, and peer groups.

Blast hole drilling is an initial stage that plays a critical role in determining the success of blasting activities in mining and construction operations. Drilling quality directly affects rock fragmentation, drilling equipment efficiency, drilling equipment productivity, as well as blasting safety and costs. This study aims to analyze the influence of drilling parameters on blast hole quality, including hole diameter, drilling depth, hole inclination, and the suitability of drilling patterns with respect to the planned blasting design. The research methodology involves field observations, actual measurements of drill holes, and analysis of data obtained from drilling and blasting productivity. The results show that deviations in hole depth and direction can lead to irregular distribution of blasting energy, resulting in suboptimal rock fragmentation and an increased potential for flyrock and overbreak. In addition, the selection of appropriate drilling methods and equipment based on rock mass characteristics has been proven to improve productivity and blast hole quality. Therefore, controlling drilling parameters and implementing proper operational procedures are essential to enhance the overall effectiveness and productivity of blasting activities. This study is expected to serve as a reference for the planning and evaluation of blast hole drilling activities to achieve more efficient, safe, and economical operations.

This study aims to analyze the integration of tax policy with the Environmental, Social, and Governance (ESG) framework in supporting the achievement of sustainable development. Current sustainability challenges require public policies that are not only focused on state revenue collection but also capable of encouraging more environmentally friendly, inclusive, and accountable economic behavior. As a fiscal instrument, taxation has strategic potential to promote business activities aligned with ESG principles through incentives, disincentives, and strengthened policy governance. This study uses a qualitative approach with a literature review method to examine the relationship between tax policy, ESG, and sustainable development. The findings indicate that integrating tax policy with ESG can serve as an important instrument in supporting the transition toward a green economy, strengthening social responsibility, and improving transparency and accountability in fiscal policy. However, its implementation still faces challenges such as suboptimal policy harmonization, limited measurement indicators, and weak cross-sector integration. Therefore, a more comprehensive tax policy design is needed to make a tangible contribution to sustainable development.

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.

The evaluation of haul road geometry at PT Trubaindo Coal Mining was conducted to ensure that the haul road from the stockroom to the jetty meets applicable technical standards, thereby supporting the smoothness, safety, and efficiency of coal transportation activities. This study aims to analyze the conformity of haul road geometric parameters, including straight road width, curve width, curve radius, cross slope, longitudinal grade, and superelevation, based on the standards of AASHTO 7th Edition and Kepmen 1827 of 2018. The research method employed field measurements using a Terrestrial Laser Scanner (TLS), followed by data processing using Maptek and Surpac software. The obtained data were then compared with the applicable standards to determine the level of conformity of the haul road geometry. Based on field measurements, the average values obtained were 14.99 m for straight road width, 18.45 m for curve width, 0.22 m for cross slope, 6.97% for grade, 223.51 m for curve radius, and 1.40 m for superelevation. Furthermore, based on calculations and analysis referring to AASHTO 7th Edition and Kepmen 1827 of 2018, and considering the largest haulage equipment used (Volvo FMX 480), the ideal haul road geometry values were determined as follows: 13 m for straight road width, 17 m for curve width, 124 m for curve radius, 0.26 m for cross slope, 1 m for superelevation, and 6% for grade based on PT Trubaindo Coal Mining standards.

Iron deficiency anemia remains a major public health problem among pregnant women in Indonesia, with a national prevalence of 37.1% and higher rates in regions such as Brebes Regency. Adequate nutritional knowledge and sufficient iron intake are expected to prevent decreases in hemoglobin (Hb) levels during the third trimester. This study aimed to analyze the relationship between nutritional knowledge, iron intake adequacy, and Hb levels among third-trimester pregnant women at Puskesmas Brebes. An analytic observational study with a cross-sectional design was conducted on 62 respondents using total sampling. Data were collected through a nutritional knowledge questionnaire, a Semi-Quantitative Food Frequency Questionnaire (SQ-FFQ) to assess iron intake based on the Recommended Dietary Allowance of 27 mg/day, and Hb measurement using a digital device. The prevalence of anemia was 32.3%, with a mean Hb level of 11.25 ± 1.74 g/dL. Most respondents had high nutritional knowledge (72.6%), but 79.0% had inadequate iron intake. Chi-Square analysis showed no significant relationship between nutritional knowledge and Hb levels (p=0.109) or between iron intake adequacy and Hb levels (p=0.426). Other factors, including iron absorption inhibitors, compliance with iron supplementation, nutritional status, and limited sample size, may have influenced the results.

This study aims to analyze the role of assessment in decision-making within guidance and counseling services. Assessment plays a crucial role in providing accurate, objective, and comprehensive data regarding students’ characteristics, needs, and problems. This research employs a qualitative approach using a literature review method by analyzing 25 relevant scholarly sources related to assessment, measurement, and counseling services. The findings indicate that measurement serves as the fundamental basis of assessment, which involves systematic processes to obtain quantitative data. The quality of assessment results is highly influenced by the reliability and validity of the instruments used. Reliable instruments ensure consistency, while valid instruments ensure accuracy in measuring intended variables. Furthermore, assessment functions as a basis for diagnosis, planning, implementation, and evaluation of guidance and counseling services. The study also reveals that the application of assessment in schools is not yet optimal due to several factors, including limited counselor competence and lack of effective use of instruments. In addition, the integration of technology and the use of both test and non-test instruments have been shown to improve the accuracy and effectiveness of assessment. In conclusion, systematic and well-implemented assessment significantly enhances the quality of decision-making in guidance and counseling services. Therefore, improving counselors’ competencies and optimizing the use of assessment instruments are essential to support more effective counseling practices

The transition from paper-based to Computer-Based Test (CBT) in the Academic Potential Test (TPA) for state university entrance selections has significantly transformed the educational assessment landscape. This conceptual study aims to evaluate the instruments of CBT-based TPA, focusing on validity, reliability, fairness, and technological infrastructure constraints. Employing a systematic literature review approach, this research synthesizes various foundational theories of educational measurement, specifically Item Response Theory (IRT) and Computerized Adaptive Testing (CAT), alongside contemporary empirical findings from the last five years. The findings indicate that while CBT offers enhanced administrative efficiency and rapid grading, the validity of the instruments is frequently challenged by item exposure and the diverse digital literacy levels of test-takers. Furthermore, infrastructural disparities among regions pose a significant threat to testing fairness. The implication of this study suggests the urgent need for a dynamic item bank generation system and the implementation of adaptive testing to mitigate cheating and ensure equitable assessment. Future educational policies must bridge the digital divide before uniformly mandating CBT. Ultimately, this review provides a comprehensive framework for test developers to refine CBT TPA instruments, ensuring they genuinely measure academic potential rather than technological proficiency.

Type 2 diabetes mellitus has now become a widespread health issue with serious implications for public health. In an effort to support non-pharmacological management, the use of aloe vera (Aloe vera) decoction is one option being considered, given that this plant contains bioactive components such as aloin, emodin, and polysaccharides that have the potential to help lower blood glucose levels. This study aims to examine the effect of consuming aloe vera (Aloe vera) decoction on lowering blood sugar levels in patients with type 2 diabetes mellitus in Lampaseh Lhok Village, Montasik Subdistrict, Aceh Besar. The research was conducted from June 19 to 28, 2025, in that area. The study design employed a quantitative research approach using a quasi-experimental design with a one-group pretest-posttest model. The study population consisted of 38 patients with type 2 diabetes mellitus, while the sample comprised 15 respondents. Sampling was conducted using purposive sampling. The measurement tools included a glucometer and an observation sheet. Based on the data analysis results, a decrease in blood glucose levels was observed after the respondents consumed the aloe vera decoction. The Wilcoxon signed-rank test yielded a p-value of 0.001 (< 0.05), leading to the conclusion that the administration of the aloe vera (Aloe vera) decoction has a significant effect on reducing blood glucose levels in the respondents. Therefore, respondents are advised to drink aloe vera tea at least once a day as an alternative measure to help control blood glucose levels.

This research aims to analyze the influence of thermal conditions; specifically the temperature difference between the test object and the environment; on the characteristics of air flow and heat transfer around it. The object of this study is a test piece subjected to free air flow under various temperature conditions; focusing on the convection heat transfer phenomenon. The main problem addressed is how temperature variations affect the convection heat transfer coefficient; heat transfer rate; and heat flux; as well as changes in air velocity and pressure profiles. Therefore; the objective of this research is to quantitatively compare and assess these thermal and fluid parameters through an experimental study approach and Computational Fluid Dynamics (CFD) simulation. The methodology involves direct measurement of temperature and pressure parameters under low and high-temperature conditions; which are then processed to determine the convection coefficient (); heat transfer rate (); and heat flux (). The main findings indicate that at low-temperature conditions; the heat transfer coefficient () was found to be 53.26 ; the heat transfer rate () was 24.99 W; and the heat flux () was 537.87 ; with a pressure drop of 0.86 Pa. In conclusion; thermal conditions play a crucial role in determining the dynamics of air flow and the efficiency of heat transfer; the greater the temperature difference (); the higher the potential heat transfer rate; establishing a strong correlation between thermal conditions and the convection phenomenon.

The coal mining industry requires accurate stockpile volume measurements for inventory and production reporting. Conventional methods have limitations in accuracy, efficiency, and safety. This study compares the accuracy and efficiency of coal stockpile volume measurements using a Terrestrial Laser Scanner (TLS) Leica MS60 and an Unmanned Aerial Vehicle (UAV) DJI Matrice 4E, validated by the ASTM D6172-98 standard. Conducted on five Run of Mine (ROM) coal stockpiles covering 13,500 m² at PT XYZ, Lahat, South Sumatra, the TLS method used 43 scan positions, while the UAV employed 430 aerial images with specific flight parameters. Data were processed using Leica Infinity, Surpac, and Agisoft Metashape. The results showed volumes of 94,076 m³ (TLS) and 94,965 m³ (UAV), with a difference of 889 m³ (0.95%). Volume deviations ranged from 0.48% to 1.89%, with an average of 1.42%, all within the ASTM tolerance (<2%). Time efficiency analysis revealed that the UAV method required 200 minutes (3.33 hours), saving 63.3% (approximately 6.17 hours) compared to the TLS method (570 minutes). The largest efficiency gain occurred during field data acquisition, with an 85% reduction in time. This study confirms UAV photogrammetry as a valid, accurate, and efficient alternative for coal stockpile volume measurement in mining.

This research aims to design and develop a prototype wave power plant that utilizes the vertical motion of a buoy as a source of mechanical energy, which is then converted into electrical energy using a recoil starter mechanism. The system is designed to be installed at the stern of a prototype ship. The vertical movement of the buoy caused by ocean waves is transmitted to the recoil starter through a drive rope, producing a stable one-way rotational motion. This rotation is further transmitted to a gearbox to increase rotational speed before driving a DC generator. The electrical energy generated is stored in a 12 VDC battery, supported by a buck–booster converter to stabilize the output voltage. This study employs an experimental engineering approach to evaluate system performance based on empirical test data. The main components of the system include a buoy as a wave energy collector, a recoil starter as the initial rotating mechanism, a DC generator as the electrical energy producer, a buck–booster converter as a voltage regulator, a 12 VDC battery as an energy storage unit, and a monitoring system based on an ESP32 microcontroller integrated with a PZEM-017 sensor. Experimental results show that the recoil starter operates effectively in driving the generator under both no- load and buoy-loaded conditions. Increases in generator rotational speed are directly proportional to increases in output voltage and current. The PZEM-017 sensor demonstrates a high level of measurement accuracy, approaching 100% when compared with a multimeter. Overall, the proposed wave power generation system functions reliably and shows potential for further development as a small-scale alternative renewable energy source.

Background: Automatic segmentation of the thyroid gland in ultrasonography (USG) images using deep learning requires a user-friendly interface to support diagnostic and educational processes. Purpose: This study aims to develop and implement a Graphical User Interface (GUI) that integrates a deep learning U-Net model for interactive and efficient segmentation and visualization of thyroid USG images. Method: The development method employed the Rapid Application Development (RAD) approach using MATLAB programming language. The GUI is designed to load transverse and sagittal USG images, display automatic segmentation results, and calculate thyroid gland volume based on dimensions measured automatically from the segmentation output. Testing was conducted using USG image data from 15 volunteers, and GUI functionality was evaluated using black box testing. Result: The GUI successfully displayed USG images and segmentation results with a responsive 4-panel interface; zoom, pan, and image navigation features functioned well. Automatic segmentation occurred in real-time after image input, and volume measurement results appeared automatically. Black box testing evaluation showed all GUI features operated as expected. The average Dice Similarity Coefficient (DSC) of 0.91 indicates high performance of the U-Net model in thyroid segmentation, consistent with previous findings. Statistical testing confirmed no significant difference between volume measurements using the application and manual methods (p = 0.953). Conclusion: This GUI implementation facilitates users in performing deep learning-based segmentation and visualization of thyroid USG images, improving efficiency and accuracy in thyroid volume measurement. The GUI has potential applications in clinical practice and radiology education.

Preeclampsia remains a major contributor to maternal morbidity and mortality, particularly in developing countries such as Indonesia. Early detection and integrated management at the primary healthcare level are essential to prevent disease progression and improve maternal outcomes.  Modifiable risk factors such as maternal obesity, inadequate calcium intake, and poor clinical management contribute significantly to disease progression (WHO, 2021; Zhang et al., 2020). This study aimed to evaluate the effectiveness of an Integrated Maternal Health Model (IMHM) combining risk assessment, nutritional intervention, and clinical management for early prevention and control of preeclampsia in primary healthcare settings. A quasi-experimental cohort study was conducted among 104 pregnant women, consisting of 52 preeclamptic and 52 normotensive participants in community health centers in Medan, Indonesia. Data were collected across four antenatal visits, including blood pressure measurements, proteinuria (dipstick), calcium intake, supplementation adherence, and antihypertensive therapy. Statistical analyses included bivariate and longitudinal tests. The results showed that maternal obesity, history of preeclampsia, and hypertension were significant risk factors. Adequate calcium intake demonstrated a protective effect against preeclampsia (p < 0.05), consistent with recent evidence indicating that calcium supplementation can reduce the risk of preeclampsia by up to 49%. However, calcium supplementation did not significantly influence blood pressure among normotensive pregnant women. Antihypertensive therapy, particularly intensive nifedipine regimens, showed significant differences in blood pressure patterns across visits (p < 0.05). In addition, proteinuria levels significantly decreased over time (p < 0.001), indicating improvement in renal function. In conclusion, the IMHM is effective in improving maternal outcomes through a multi-component approach integrating clinical, nutritional, and monitoring strategies. This model provides a practical and scalable framework for early prevention and management of preeclampsia in primary healthcare settings.