This study aims to describe elementary school teachers’ perceptions of the use of STEM-based instructional media as an effort to strengthen 21st-century skills. The research employed a descriptive qualitative approach with the subjects being elementary school teachers in the regions of Tasikmalaya City and Regency. The population included all elementary school teachers in both areas, with a purposive sample of 50 participants. The research instrument was a Likert-scale questionnaire developed based on three indicators of STEM literacy: (1) awareness of the role of STEM in modern society, (2) familiarity with basic STEM concepts, and (3) foundational fluency in STEM application. Data were collected using an online questionnaire via google forms, while the data analysis involved calculating the average score for each indicator. The results showed that for the first indicator, teachers in Tasikmalaya City had higher awareness (average score of 4.05) compared to those in the Regency (3.93). However, in the second and third indicators, teachers from the Regency scored higher, at 3.39 and 3.67 respectively, compared to city teachers who scored 3.30 and 3.59. These findings suggest that although urban teachers have stronger conceptual awareness, rural teachers demonstrate greater mastery in understanding and applying STEM practically in classroom learning. This difference is suspected to be influenced by contextual experience and more frequent implementation of hands-on learning approaches in the Regency.

This study investigates impoliteness strategies used in the YouTube comment section of Gibran Rakabuming's video entitled "Generasi Muda, Bonus Demografi, dan Masa Depan Indonesia." Using a qualitative approach and Culpeper's (2005) impoliteness framework, the researchers analyzed 50 purposively selected comments. The study identifies various strategies such as bald-on-record impoliteness, sarcasm/mock politeness, positive impoliteness, and negative impoliteness. The findings reveal that bald-on-record and sarcasm are the most frequent strategies used, often driven by political dissatisfaction and emotional expression. This study aims to determine the most dominant impoliteness strategy employed by netizens and contributes to understanding digital discourse in Indonesian political contexts, highlighting the role of anonymity and group identity in shaping online communication.

The detection of hazardous gases, such as carbon monoxide (CO), is crucial for ensuring human safety and health, especially in enclosed environments or areas with a high potential for exposure to toxic gases. Carbon monoxide is a colorless, odorless gas that is extremely dangerous when inhaled in large amounts. Therefore, a CO detection system that can provide early warnings is essential. This research aims to design a carbon monoxide (CO) detector using the MQ-7 sensor, which can detect CO concentrations in the air. The detection system is developed based on Internet of Things (IoT) technology, enabling real-time CO detection data to be transmitted to a cloud platform or user devices via an internet connection. This allows users to monitor CO levels in their environment anytime and anywhere. The system consists of the MQ-7 sensor to detect CO levels, a microcontroller as the controller, and a communication module to send data to the internet. The main advantage of this system is its ability to notify users if CO levels exceed a safe threshold. Thus, this detector can function as a preventive tool against CO exposure accidents. The use of IoT in this system also facilitates remote monitoring, improving the effectiveness and efficiency of managing a safe environment.

Compressive strength is one of the mechanical properties of rock behavior. This study focuses on the Balikpapan and Kampungbaru Formations located in the Kutai Kartanegara area, East Kalimantan. The Schmidt Hammer testing method was applied due to the lack of previous studies utilizing this tool to evaluate rock hardness in correlation with compressive strength. The research site is situated in the Kutai Kartanegara area, specifically in the districts of Muara Badak, Muara Jawa, and Sanga-Sanga. Field observations revealed the presence of claystone slopes at predetermined locations. Based on the test results, the uniaxial compressive strength (UCS) values for the Balikpapan Formation range from 3.453 MPa to 5.454 MPa, while the Kampungbaru Formation ranges from 3.317 MPa to 8.571 MPa. The Schmidt Hammer rebound number (RN) values for the Balikpapan Formation range from 17 to 19.6, and for the Kampungbaru Formation from 15 to 23.7. A negative correlation was found between the rebound number and UCS, where higher RN values tend to correspond with lower UCS values. This is supported by the linear regression analysis showing a negative coefficient (-0.450).
 

Rapid development has caused changes in land use patterns, where built space increasingly dominates and pressures natural spaces to change function (Pribadi et al., 2006) explaining that changes in land use patterns result in fluctuations in the carrying capacity of land resources, giving rise to land disasters. landslide (landslide). Buol et al. (1980) and Darmawijaya (1990) explained that landslides are essentially caused by the inability of the soil to support the load above it because the soil has experienced degradation of its soil properties. The method used in this research uses a weighted scoring method. The results of the analysis of 5 parameters of potential landslide-prone areas in Tanah Datar Regency obtained 3 classifications of levels of vulnerability, namely high-level landslide-prone areas covering an area of ??2032.6955 ha, moderate-level landslide-prone areas covering an area of ??16174.395 ha and low-level landslide-prone areas covering an area of ??6284 ha. ,6345 ha. The most extensive area prone to landslides with a high level is in North Lintau Buo District. The area prone to moderate landslides is most extensive in North Lintau Buo District. The most extensive low-level landslide-prone areas are in Sepuluh Koto District.

This research is motivated by the problems faced by fifth-grade students at SDN 1 Narimbang Mulia in understanding the material on forms and changes of energy in everyday life. One of the main obstacles identified is the lack of teaching aids and the unappealing nature of student worksheets, which hampers the learning process. The purpose of this study is to analyze the level of elementary students' understanding of the forms and changes of energy, as well as to identify the obstacles they face in learning the material. This research uses a qualitative approach with data collection techniques including student observations, teacher interviews, and the administration of a post-test at the end of the learning session. The research subjects are fifth-grade students of SDN 1 Narimbang Mulia. The results of the study show that most students have a fairly good understanding of the concepts of energy forms and changes. However, there are still obstacles in the learning process, including limited teaching aids and uninteresting student worksheets. This study is expected to serve as a basis for developing more effective learning strategies to improve students' understanding of the material on energy forms and changes in everyday life.

This research aims to design a Solar Power System (PLTS) for households that can meet an energy demand of 4.5 kWh per day. The system design takes into account the efficiency of solar panels and the average solar radiation potential in Semarang, which is around 5 hours per day. The method used in this research involves calculating the required solar panel capacity based on the daily energy needs of the household, panel efficiency, and solar radiation hours. The calculation results show that the required PLTS capacity is 1125 Wp, which is then designed using 4 solar panels with a capacity of 300 Wp each. This system is expected to allow households to meet their energy needs independently and sustainably. The implication of this research is to provide an alternative solution for households in reducing their dependence on conventional energy sources, while contributing to the effort to reduce greenhouse gas emissions.

System Development Life Cycle (SDLC) is a common methodology used to develop information systems. The purpose of this study is to determine system development between the Waterfall and Rapid Application Development (RAD) models The advantage of using the waterfall method is that the quality of the resulting system will be good because the implementation is carried out in stages. The disadvantage of using the waterfall method is that the system development process takes a long time. The advantage of using the RAD Model method is that the integration of sensors/other applications can be processed faster and more effectively. The disadvantage of using the RAD method is the limitations of payment gateways, and chat bots.

Vehicles in Indonesia are an important part of moving people or goods from one place to the destination, one of which is the transportation of boxed goods. However, the lack of security for boxed goods transport vehicles has always been the target of burglary of goods cargo in the area of Jalan Perniagaan Barat Roa Malaka Tambora, West Jakarta, perpetrators of goods theft from boxed goods cars that are traveling. Therefore, it is necessary to have a security system that can notify the driver when the back door of the vehicle is broken into, namely a Security Detection Tool on Iot-Based Goods Transport Vehicles Using Telegram this tool is able to detect the movement of the thief and evidence will be sent via Telegram. The research method used in this research is research adopting the ADDIE model R&D method, namely Analysis, Design, Development, Implementation, and Evaluation (assessment) of the reference model (ADDIE). In implementing the design of a Security Detection Tool on Iot-Based Goods Transport Vehicles Using Telegram Using the Esp32 Cam Microcontroller, MCU Node, and PIR sensors. Based on the Security Detection Tool, the transportation of box goods works well. Using the PIR Sensor, which is tested and applied directly to the vehicle. The tool is capable of sending telegrams in the form of messages, locations, and photos of the break-in.

This study aims to develop an accurate predictive model for identifying students at risk of academic dropout using Decision Tree and Random Forest algorithms. The research utilizes a publicly available dataset sourced from Kaggle, which includes academic and demographic features such as GPA, attendance, credit load, financial aid status, and exam scores. The methodology involves several stages: data collection, preprocessing (handling missing values, encoding categorical variables, and feature scaling), model training, and evaluation using performance metrics such as Accuracy, Precision, Recall, F1-Score, and Confusion Matrix. Results show that the Random Forest algorithm outperforms Decision Tree in terms of accuracy and robustness, with notable feature importance on math, reading, and writing scores. The findings highlight the potential of machine learning in early detection of dropout risks and provide actionable insights for academic institutions to design timely interventions. This research contributes to the growing field of educational data mining and supports data-driven decision-making processes in higher education management.