Maintaining stable cage temperature is a crucial factor in the success of broiler chicken farming, especially in close house systems that rely on optimal microclimate control. Temperature instability can lead to thermal stress, reduced growth rates, and increased mortality in broilers, particularly during the early stages of life (0 to 30 days old). This study aims to design and implement an automatic temperature control system based on the Arduino Uno microcontroller integrated with a DHT11 temperature and humidity sensor in the broiler chicken cages of PT. Barokah Restu Utama. The system is designed to read temperature and humidity in real-time and automatically activate or deactivate cooling devices such as fans or heating devices like incandescent lamps, depending on the temperature range required for each growth phase. The ideal temperature range used as a reference in this system includes 30–32°C for chickens aged 0–7 days, 29°C for ages 8–14 days, 28°C for ages 15–21 days, and 26–27°C for chickens aged 22–30 days. Testing results show that the system is capable of maintaining stable temperatures according to the specified standards for each growth phase. With this automatic control system in place, broiler chicken maintenance becomes more efficient and effective. The risk of mortality due to heat stress is significantly reduced, and chicken growth becomes more optimal. This technology offers a practical and economical solution, especially for small- to medium-scale broiler chicken farmers who use close house systems. The system is easy to operate and relatively affordable to install, making it an accessible innovation that supports better livestock management through automation and smart farming practices.

The life insurance industry plays a strategic role in the national financial system, not only as a provider of protection against life risks such as premature death or critical illness, but also as an instrument of long-term fund accumulation. Increased public awareness of the importance of risk protection has driven significant growth in the number of active policies. This condition has a direct impact on the risk exposure of claims that must be carefully managed by insurance companies. One of the main challenges in risk management is to accurately estimate the number of claims in a certain period, to support premium setting, technical reserve planning, and maintain the company's financial stability. This study aims to examine the use of Poisson regression model in estimating the frequency of life insurance claims based on the number of active policies in life insurance company. The data used is simulative and represents an exponential relationship between the number of policies and claims. The model is analyzed using the Maximum Likelihood Estimation (MLE) approach and evaluated through goodness-of-fit indicators such as deviance, Pearson chi-square, log-likelihood, and Mean Squared Error (MSE). The results of the analysis show that the Poisson regression model can capture the significant relationship pattern between the number of active policies and claims, and provide accurate prediction results. Thus, Poisson regression is proven to be a relevant and applicable statistical method in supporting strategic decision-making in insurance companies, especially in the context of data-driven risk management.

Flying fish (Hirundichthys oxycephlus) roe filaments, which are often considered as by-products, have high protein content and various essential nutrients, thus potentially increasing the nutritional value of food products. With innovation and in-depth research, this waste can be transformed into products with economic value while supporting the implementation of sustainability principles in the fisheries industry, in this case sauce as a flavoring that has become an important part of the food industry. This study aims to determine the quality of the texture and taste of chili sauce fortified with fly fish (Hirundichthys oxycephlus) roe filament extract and to determine the protein content and water content of chili sauce enriched with fly fish (Hirundichthys oxycephlus) roe filament extract. The methodology used in this study was Complete Random Design (CRD) with variations in filament powder concentration (0%, 0.5%, 1%, and 1.5%) on the sensory characteristics of chili sauce, which include aroma, color, taste, and texture. The results of organoleptic tests showed that the addition of fly fish (Hirundichthys oxycephlus) egg filament extract had a significant positive impact on all sensory parameters tested. The average aroma score increased from 2.88 in the non-enriched treatment to 3.90 at the highest filament powder concentration (1.5%). In addition, the taste score also showed the most striking increase, from 2.80 to 4.33. Analysis of the water content of the chili sauce product was recorded at 79.93% according to (SNI 01-2976-2006), while the protein content reached 10.53%, indicating the potential of this product as an additional source of protein in daily consumption patterns.

This research is motivated by the problems in class VIII of Al-Irsyad TI Bulaan Kamba Islamic Boarding School that the learning process is still centered on the teacher, lack of student response to mathematics learning, lack of student courage to ask the teacher, students still think mathematics is difficult and scary, lack of interest in learning mathematics, and students are less enthusiastic when participating in mathematics learning. One alternative learning that can be done to overcome these problems is to apply the Problem Based Learning learning model. This study aims to determine the effect of the Problem Based Learning learning model on the interest in learning mathematics of class VIII students of Al Irsyad TI Bulaan Kamba Islamic Boarding School. The hypothesis in this study is "there is a significant effect of the Problem Based Learning learning model on the interest in learning mathematics of class VIII students of Al Irsyad TI Bulaan Kamba Islamic Boarding School". This type of research is a pre-experiment with a one group pretest-posttest research design, the population in this study were all students of class VIII of Al Irsyad TI Bulaan Kamba Islamic Boarding School, the sampling used was Random Sampling, first a normality test, homogeneity test, and average similarity test were carried out on the population data. The sample in this study was class VIII A as the sample class. The instrument in this study was a questionnaire on students' interest in learning mathematics. The data analysis technique used in this study was the paired sample t test. The results obtained from the paired sample t test were t count = 2.81 and t table = 2.05 and sig = 0.0045 at a real level of α = 0.05. From these results it can be concluded that H0 is rejected and H1 is accepted. So it can be concluded that there is a significant influence of the Problem Based Learning learning model on the interest in learning mathematics of class VIII students of Al Irsyad TI Bulaan Kamba Islamic Boarding School.
 
 

This study is a descriptive and correlational study to investigate students’ mastery of essential mathematics concept and find the connection to their critical and creative thinking. The subjects of the study consisted of 234 junior high school students from various schools in high, average, and low qualities. The results of the study indicated that 1) Students’ mastery of essential mathematics concept are at average level; 2) The difficulties that encountered by the students come from internal factor (themselves), and external factors (teachers, the characteristics of mathematics, schoolmates and the facilities; 3) There is a significant relationship between students’ mastery of essential mathematics concept and their critical thinking; 4) The correlation between the ability to be skilled  in essential math concept and their creative thinking is at high level.

This study aims to examine and compare the expenditure and income patterns between traditional market traders in Sukaramai Market and MMTC with street vendors operating around the State University of Medan (UNIMED). This study is based on the main differences between the two groups, especially related to business legality, sales location, and operational costs, which have the potential to affect business effectiveness and the economic welfare of the actors. The comparative quantitative method was used to collect data through questionnaires and Simple Random Sampling sampling techniques on 45 respondents, consisting of 30 market traders and 15 street vendors. The collected data were then analyzed using statistical inference techniques to obtain accurate and reliable parameter estimates. The results of the study show that market traders have an average income of IDR 9.37 million with expenses of IDR 6.7 million per month, so that the net profit obtained reaches IDR 2.67 million. Meanwhile, street vendors have an average income of IDR 7.2 million and expenses of IDR 5.53 million, so that their net profit is around IDR 1.67 million. Although market traders' expenses are higher, they still get a greater net profit. This study confirms that business location, legality, and management system factors significantly affect the efficiency and economic success of traders. This finding is very relevant as a basis for formulating fair and sustainable policies for empowering the informal sector, especially for small and micro traders in urban areas, in order to optimally improve their economic welfare.

This study aims to compare two main theories in modern cosmology, namely the Big Bang Theory and the Steady State Theory, using a descriptive cosmographic approach. This study is motivated by the lack of deep understanding as well as the limited Indonesian literature discussing the fundamental differences between the two theories. By employing a qualitative method through literature review, this research examines the characteristics, advantages, and limitations of each theory based on the latest scientific evidence and cosmographic perspectives. The analysis results show that the Big Bang Theory has strong support from observational evidence, such as cosmic microwave background radiation (CMB), galaxy redshift, and the distribution of light elements, which reinforces the narrative of the expansion and evolution of the universe. In contrast, the Steady State Theory is considered less relevant due to the absence of observational evidence for the creation of new matter and its inability to explain structure and the dynamics of the universe that are currently observed.

Rainfall potential analysis plays a critical role in the management of air resources, mitigation of hydrometeorological disasters, and agricultural activity planning. Accurate estimation of rainfall patterns is essential to ensure effective decision-making in irrigation systems, water resource management, and disaster risk reduction strategies. This study aims to model the probability of rainfall occurrence using a statistical approach based on historical data obtained from the Bureau of Meteorology. The data spans a multi-year period and captures seasonal and regional variability in rainfall events. To characterize rainfall patterns, various probability distributions are tested, including the exponential distribution and the Weibull distribution, which are commonly applied in hydrological studies. Furthermore, the Markov chain method is employed to assess the likelihood of rainfall occurrence on a given day based on the conditions of the preceding day, thereby capturing temporal dependencies. Parameter estimation is conducted using Maximum Likelihood Estimation (MLE), a robust statistical method that enhances the precision of the model. The suitability of each probability distribution in representing the observed rainfall data is evaluated through goodness-of-fit tests such as the Kolmogorov-Smirnov test. The findings reveal that certain distributions align more closely with the local rainfall characteristics, demonstrating the importance of regional analysis in climate modeling. The combination of probabilistic modeling, Markov analysis, and rigorous statistical testing provides a reliable framework for forecasting rainfall. These results are expected to serve as a scientific basis for stakeholders in agriculture, environmental planning, and disaster preparedness, offering insights that support sustainable water resource utilization and risk management.

Bedda Lotong is a traditional scrub from the Bugis tribe of South Sulawesi, Indonesia. The name ‘Bedda Lotong’ literally means ‘black powder’ in Bugis language, referring to the distinctive black colour of this scrub which comes from its main ingredient, white glutinous rice that is roasted until burnt. The purpose of this study was to determine the number of colonies of moulds (thread moulds) and yeasts (one-celled fungi) in Bedda Lotong with the addition of Eucheuma cottoni seaweed. In addition, this study also aimed to determine the level of panellists' liking through organoleptic tests. The research design used was a factorial Completely Randomised Design (CRD) with 3 levels of treatment with 3 replications. The treatment of adding Eucheuma cottoni seaweed as a microbial growth inhibitor. Data processing was done with analysis of variance (ANOVA) test and continued with Duncan test using SPSS V.23 software. Based on the results of the study, it was obtained that the effect of the addition of Eucheuma cottoni seaweed did not significantly affect the ALT/TPC test (>0.05) (0.087) and had a significant effect (<0.05) (0.003) on the Bedda Lotong pH test and in the treatment of A1 (5%) and B1 (10%) seaweed concentrations gave organoleptic test scores from panellists, namely a score of 4 (like).

This study aims to analyze the level of understanding of PSPK 23 B students at Medan State University on atomic theory questions. With a quantitative descriptive approach, data were collected through multiple-choice tests filled out by 30 students. The results showed an average understanding of 75.33%, which is quite good. However, there was significant variation where some students mastered basic concepts (eg Dalton and Thomson's atomic models), while others had difficulty with abstract topics (eg Bohr's model and quantum mechanics). This finding is in line with previous studies on misconceptions in atomic structure. This study emphasizes the importance of innovative learning strategies, such as visual media and conceptual approaches, to improve student understanding. Periodic evaluation is needed to detect learning gaps and adjust teaching methods. The results of this study can be a basis for developing more effective chemistry education practices.