Publication Search

Plastic waste detection in indoor environments is an essential challenge in the development of intelligent cleaning systems and robotic automation. Small and medium-sized plastic debris is often difficult to identify using conventional methods due to variations in color, shape, and reflectance. This study proposes an image-processing-based approach that combines thresholding and contour detection techniques to improve the accuracy of detecting plastic objects on floor surfaces. The initial stage involves converting the image into a color space that is more stable under varying illumination, such as HSV or grayscale, to reduce the influence of lighting intensity. Subsequently, adaptive thresholding is applied to separate plastic objects from the background by using dynamic threshold values tailored to the image’s conditions. The segmentation results are refined through morphological operations such as opening and closing, enabling the removal of small noise and enhancing the clarity of object boundaries. The core stage of the system employs contour detection to extract object shapes and areas, allowing the identification of plastic waste based on size, perimeter, and specific geometric characteristics. Experiments were conducted under different lighting conditions and various floor types, and the results demonstrate that the proposed approach successfully detects plastic debris with satisfactory accuracy and relatively fast processing time. Therefore, this method is suitable for implementation in robotic cleaning systems, indoor cleanliness monitoring devices, and other computer vision applications requiring real-time and efficient object detection.

Noise is a physical hazard in the work environment that caan reduce hearing loss, especially in the rubber processing industry. The research aims to describe the noise level and control efforts in the production area of PT. Karet XYZ Palembang City in 2025. This study uses a descriptive design with a cross-sectional approach.  Data were collected through direct noise level measurements using sound level meters at wet and dry production areas by taking 8 measurements and questionnaires on 75 selected purposive sampling workers.  Data analysis was carried out univariately. It shows that most of the measurement points have a noise level above the threshold value of 85 dBA in accordance with the Regulation of the Minister of Health of the Republic of Indonesia Number 70 of 2016. The highest values were recorded in the Hummer Mill engine (89,76 dBA) and the Cooling Tunnel (89,70 dBA). All respondents were exposed to noise for ≥8 hours/day. Noise control has been carried out with administrative techniques and the use of personal protective equipment (PPE) but has not been fully effective from the complaints of 7 workers regarding suboptimal protection. The noise level at PT. Karet XYZ and duration of exposure exceeding threshold values that increase the risk to workers health. It is necessary to increase the effectiveness of noise control with a technical, administrative approach and monitoring the optimal use of personal protective equipment (PPE).

The purpose of this study was to analyze the relationship between noise levels and work stress among employees at Karunia Kasih Hospital. This study used a cross-sectional design with a population consisting of all employees in the Front Office, Polyclinic Nurses, and Specialist Doctors. The study sample consisted of 80 respondents selected using total sampling technique. Noise levels were measured using a Sound Level Meter, while work-related stress was assessed using a questionnaire. Data analysis was conducted using the chi-square test with a significance level of α = 0.05. The measurement results indicated that 80% of the work areas had noise levels exceeding the NAB 65 dBA threshold. The Outpatient Corridor area had the highest noise level (83 dBA). A total of 65% of workers experienced moderate to severe work-related stress. There was a significant relationship between noise levels and work-related stress (p-value = 0.001). Age (p-value = 0.024) and length of service (p-value = 0.037) also showed a significant relationship with work-related stress. There is a significant relationship between noise levels and work-related stress among workers at Karunia Kasih Hospital. Efforts to control noise levels and comprehensive stress management programs are needed to protect worker health.

Noise in educational environments can affect the effectiveness of teaching and learning processes. This study aims to analyze the impact of traffic noise on teaching and learning activities in Building V of Semarang University, located along the Soekarno-Hatta arterial road. The research method uses a qualitative descriptive approach by measuring noise levels using a Sound Level Meter on six floors of the building. Measurements were taken during active lecture hours with time intervals of 3 x 30 minutes. The results showed that noise levels on floors 1 to 3 were above the educational environment quality standard of 55 dB according to KepMenLH No. 48 of 1996. Meanwhile, on the 6th floor, the noise level averaged around 55 dB. Excessive noise makes it difficult for students to hear lecturers' explanations, reduces their ability to capture information, and decreases learning material retention. To address these issues, sound insulation installation, spatial planning improvements by designing room layouts farther from noise sources, vegetation planting, and lecture rescheduling to avoid peak traffic times are necessary.

Construction work is one of the jobs that has various high risks for workers and people who are around it. These risks come from various sources, one of which is noise from various equipment and ongoing activities. One of the jobs that cause high noise in construction work is MEP (Mechanical Electrical Plumbing) work. Based on Permenaker Number 13 Year 2011, the Threshold Value (NAB) for noise that can be accepted by workers is 85 dBA for 8 hours a day. Based on the measurement of the construction of the flats, the MEP work in the form of Beam Separator Elevator Installation, Pipe Fabrication, Electrical Wiring Lighting Installation, as well as Welding and Grinding of Iron Pipe causes noise above the NAB. The highest noise comes from pipe fabrication in the form of iron pipe cutting activities using large grinding tools and bevel machines that produce noise of 107 dBA. From the Daily Noise Dose (DND) calculation, the noise generated from MEP work has a dangerous risk level for workers' hearing. Risk control efforts that can be done are preventive actions based on the K3 hierarchy in the form of administrative controls such as changing working hours or shifts and conducting safety talks before work is carried out. In addition, another preventive measure is the use of PPE such as ear plugs. Based on the calculation of the noise reduction level, the use of ear plugs has not reduced the noise level to reach the NAB, so it is recommended that workers in pipe fabrication work use ear muffs to reduce noise exposure.