bluuebunny/crossref_metadata_2025_split huggingface dataset:
Determination of Propagation Times of Finite Ultrasonic Signals in the UFM Measuring Path
Authors: Gerasimov S I , Glushnev V D , Zhelbakov I N 
Published: November 2021

Abstract
This article provides a brief analysis of the error in calculating the discrete crosscorrelation function of the transit-time ultrasonic flowmeter signals. Special attention is paid to the study of the influence of the obtained discrete correlation function inaccuracy on the ultrasonic flowmeter’s propagation times determining error. It is known that for real time-limited acoustic signals, the discrete correlation function values are calculated with a significant error. The consequence of this is the appearance of the measurement error of the time delay between signals. The reason for this phenomenon is incorrect truncation of finite length digital sequences of the received acoustic signals. The report presents and describes an improved cross-correlation method for determining the time difference. The new algorithm takes into account the existing discretizing parameters of the received UPS – sampling frequency, sequence size and the truncated signal’s shape. Theoretical analytical expressions for the signals discrete cross-correlation function estimating are obtained as an approximation of a continuous function (the method of trapezoids and Simpson is used as an integral replacement). The numerical simulation by MatLab explains the error formation essence in the signal times difference calculating.
Exact Nearest Neighbour Search within Constrained Neighbourhood Using the Forest of Vp-Tree-Like Structures
Authors: Myasnikov E 
Published: November 2021

Abstract
In this paper, we address the problem of fast nearest neighbour search. Unfortunately, well-known indexing data structures, such as vp-trees perform poorly on some datasets and do not provide significant acceleration compared to the brute force approach. In the paper, we consider an alternative solution, which can be applied if we are not interested in some fraction of distant nearest neighbours. This solution is based on building the forest of vp-tree-like structures and guarantees the exact nearest neighbour search in the epsilon-neighbourhood of the query point.
Analysis conception of secondary student’s using four tier test on heat and temperature
Authors: Devialita A , Suhandi A , Samsudi A , Hendriyani D , Purwanto M G , Riani V R , Nurzakiyah E , Gitnita S 
Published: November 2021

AbstractThe main purpose in this research is to analyse student conception about heat and temperature used four tier test question, the test consists of three question including material about temperature, temperature and heat, as well specific heat. The research has been implemented by using purposive sampling technique. The participants consisted of 67 secondary students including (23 male students and 44 female students) of senior high school in Bungo city. After the analysis obtained the largest percentage of student conception id in the category of misconception such as: (1) Objects that feel colder to the touch must be lower in temperature than objects that feel warmer to the touch; (2) Objects that have a higher temperature must have more calorific content than objects with lower temperatures; (3) Objects that are easier to increase in temperature when heated, it will be more difficult to decrease the temperature when cooled. One way to reduce student misconceptions of concept in temperature and heat material is to facilitate student learning using conceptual change model, conceptual change text or Refutation text.
Undergraduate student’s misconception about projectile motion after learning physics during the Covid-19 pandemic era
Authors: Defianti A , Rohmi P 
Published: November 2021

Abstract
This research aimed to describe undergraduate students’ misconception about projectile motion after learning physics during the Covid-19 pandemic era. This research was qualitative research with a descriptive method. The subjects were 52 first-year undergraduate students who took physics courses. Data collecting methods used in this research were a test, questionnaires, and interviews. The test was taken from Physics by Giancoli with an additional question about certainty of response index (CRI). Data from the test were analyzed by categorizing it into lack of knowledge, knowledge of correct concepts, and misconception while open-ended questionnaires and interviews were used to help to clarify the condition. The test results indicated that 5.13% of students in lack knowledge, 28.85% the knowledge of correct concepts, and 66.02% in misconception. The questionnaire responses showed that students learned physics via online meeting with direct instruction model and ask-answer method, exercised with only applied problem (C3), and virtual practicum. The interviews showed that only a few of the students learned physics and responded to the lecturer during the online meeting. The results are that the majority of first-year undergraduate students are in misconception after learning physics during the Covid-19 pandemic era and need remedial learning about projectile motion.
What do students need during Covid-19? A need analysis of augmented reality with STEAM worksheet (AR-STEAM) in electromagnetic induction
Authors: Amin A M , Sulsilah H , Laurently F , Samsudin A , Suhandi A 
Published: November 2021

Abstract
This study aims to collect initial information in designing Augmented Reality-based Physics worksheet with a Science, Technology, Engineering, Art, and Mathematical (AR-STEAM) approach. The research method used descriptive qualitative by collecting some field research information was carried out by sharing the viewpoints of 26 students (male N=3 and female N=23) who had studied the material of Electromagnetic Induction. Based on field studies using questionnaires, it is known that 69.2% of respondents enjoy learning by using visual media, 66.3% consider the concept of type induction to be very abstract and difficult to apply in real life, 80.8% of respondents say they are happy if physics learning is explained in the form of three-dimensional animation. Therefore, it can be said that the STEAM-AR worksheet is needed in learning physics on the topic of Electromagnetic Induction.
Comparison between the maximum likelihood and the bayesian estimation methods for logistic regression model (case study: risk of low birth weight in Indonesia)
Authors: Sihombing P R , Rohimah S R , Kurnia A 
Published: November 2021

Abstract
This study aims to compare the efficacy of logistic regression model for identifying the risk factors of low-birth-weight babies in Indonesia using the maximum likelihood estimation (MLE)and the Bayesian estimation methods. The data used in this study is secondary data derived from the 2017 Indonesian Demographic Health Survey with a total sample of 16,344 newborn babies. Selection of the best logistic regression model was based on the smaller Bayesian Schwartz Information Criterion (BIC) value. The logistic regression model with the Bayesian estimation method has a smaller BIC value than the MLE method. Twin births, baby girl, maternal age at risk, birth spacing that is too close, iron deficiency, low education, low economy, inadequate drinking water sources have provided a higher risk of low-birth-weight incidence.
Rainfall prediction climatological station of Banjarbaru using arima kalman filter
Authors: Mehta W A , Sukmawaty Y , Khairullah  
Published: November 2021

AbstractTime series analysis is a method built in a particular time sequence for prediction. One of the models in time series analysis used for prediction is the ARIMA model introduced by Box and Jenkins. As time goes by, the ARIMA model was developed by applying algorithms, one of which was the Kalman Filter algorithm. This study aims to estimate the parameters of the ARIMA model used as the Kalman Filter’s initial value to forecast rainfall using ARIMA and ARIMA Kalman Filter. Determination of the ARIMA model is done by dividing the data into training and testing. The results obtained from the three training data have the same model, namely ARIMA (0,0,0) × (0,1,1)12models but with different parameter values than those used as initial values for the Kalman Filter. The results obtained using the ARIMA model with Kalman Filter significantly affect the initial data of 90% training data model parameters with an RMSE value of 155,13. Then predictions are made, the results obtained by ARIMA Kalman Filter can follow the actual data, but from June to October, the prediction results cannot approach the actual data. According to events in the field, June to October is the dry season, where rainfall is deficient
Structural equation modeling on the post-flood regional public welfare in South Kalimantan
Authors: Sur W A A , Machfiroh I S , Nurmalina R 
Published: November 2021

Abstract
This research was conducted to know the structural equation model on public welfare in the post-flood region of South Kalimantan in early 2021. The method and analysis in this study used Structural Equation Model (SEM) with compared the Maximum Likelihood (ML) and Generalized Least Square (GLS) approach to test and estimate the suitability of the post-flood public welfare model in South Kalimantan. The data collection technique in this study used a questionnaire to the people in areas victims of floods in South Kalimantan. The result is GLS approach gave more fit data than MLE based on AGFI and GFI values. The validated models gave the structural equation model with the final interpretation is Economy condition gives the significant relationship to the post-flood public welfare in South Kalimantan.
Prediction of students’ academic performance using ANN with mini-batch gradient descent and Levenberg-Marquardt optimization algorithms
Authors: Simanungkalit F R J , Hanifah H , Ardaneswari G , Hariadi N , Handari B D 
Published: November 2021

Abstract
Online learning indirectly increases stress, thereby reducing social interaction among students and leading to physical and mental fatigue, which in turn reduced students’ academic performance. Therefore, the prediction of academic performance is required sooner to identify at-risk students with declining performance. In this paper, we use artificial neural networks (ANN) to predict this performance. ANNs with two optimization algorithms, mini-batch gradient descent and Levenberg-Marquardt, are implemented on students’ learning activity data in course X, which is recorded on LMS UI. Data contains 232 students and consists of two periods: the first month and second month of study. Before ANNs are implemented, both normalization and usage of ADASYN are conducted. The results of ANN implementation using two optimization algorithms within 10 trials each are compared based on the average accuracy, sensitivity, and specificity values. We then determine the best period to predict unsuccessful students correctly. The results show that both algorithms give better predictions over two months instead of one. ANN with mini-batch gradient descent has an average sensitivity of 78%; the corresponding values for ANN with Levenberg-Marquardt are 75%. Therefore, ANN with mini-batch gradient descent as its optimization algorithm is more suitable for predicting students that have potential to fail.
Stability analysis of a smoking behavior model
Authors: Lestari S M , Yulida Y , Lestia A S , Karim M A 
Published: November 2021

Abstract
This research discussed the mathematical model of smoking behavior. The model will be analogous to an epidemic model which will be divided into several compartments/groups. This research aimed to explain the formation of a mathematical model of smoking behavior, to investigate the equilibrium point, the value of the basic reproduction number, to analyze the stability of the model, then to determine and interpret the numerical solutions using the fourth-order Runge-Kutta method. By the results of this research, a mathematical model of smoking behavior which consists of three compartments, namely the population of non-smokers, smokers and ex-smokers, was obtained. Based on the model formed the smoke-free equilibrium point and the smoker equilibrium point, then the basic reproduction number was also obtained using the next generation matrix. Furthermore, the result of the stability analysis of the smoker-free population was asymptotically stable provided that the basic reproduction number is less than one, while the population was asymptotically stable provided that the basic reproduction number is greater than one. The simulation of the model was presented to support the explanation of the stability analysis of the model using the fourth-order Runge-Kutta method based on the parameters that met the requirements of the stability analysis.
Application of the K-Means algorithm to determine poverty status in Hulu Sungai Tengah
Authors: Istiqamah N , Soesanto O , Anggraini D 
Published: November 2021

Abstract
Poverty is a condition of living in an inability to meet the minimum needs of life or basic needs. In Indonesia, poverty is one of the main problems that still need an optimal solution. Several government programs to address the problem of poverty have been carried out, but not infrequently the implementation is not right on target. The importance of this assistance is expected to improve the welfare of the community so it is very unfortunate if the assistance has not been right on target. This study aims to determine the status of poverty in Hulu Sungai Tengah Regency. By observing a problem above, it can be necessary to use a grouping method in determining poverty status. so that in this study using the cluster method, namely K-Means in clustering population data. Based on the results of data analysis using 353 head of family in the population data of HST Regency, it can be concluded that there are three poverty status clusters, namely low-level poverty (cluster 3) with a total of 130 head of family, medium-level poverty (cluster 2) with a total of 130 head of family. 111 head of family, and high poverty level (cluster 1) with a total of 112 head of family.
Subtraction of soft matrices
Authors: Abdurrahman S , Thresye  , Lula R R , Rachman R A , Evina Y 
Published: November 2021

AbstractIn this paper, we introduce subtraction operation notation on the soft matrix of size m×n with its entry on the set {0, 1}. In addition, we studied the characteristics of subtraction operations over intersection and union operations on soft matrices. The result shows the distributive law of subtraction operations over intersection and union operations on the soft matrix. Finally, we discuss the characteristics of De Morgan’s law analogous to set theory.
Impact of North America snow cover on tropical cyclogenesis over the western North Pacific
Authors: Cao Xi , Wu Renguang , Sun Ying , Wang Zhibiao , Dai Yifeng , Song Lei , Lan Xiaoqing , Zhang Xiping 
Published: November 2021

Abstract
This study reveals a connection of summer–fall (JJASO) tropical cyclone (TC) genesis over the western North Pacific (WNP) to preceding boreal spring (MAM) North America snow cover (NASC). Sea surface temperature (SST) anomalies in the tropical central Pacific and subtropical eastern Pacific play a crucial role in relaying influence of the MAM NASC on the following JJASO WNP TC genesis frequency. The increased NASC leads to a decrease in upward sensible heat flux and the atmospheric cooling over the North America. The atmospheric cooling enhances the meridional thermal contrast and geopotential height gradient, which is favorable for the occurrence of lower-level westerly wind anomalies and positive precipitation anomalies over the tropical eastern Pacific. The lower-level northeasterly wind anomalies over the subtropical northeastern Pacific as a Gill-type atmospheric response to positive precipitation anomalies induce ocean surface cooling via the enhanced wind speed. A positive feedback between the northeasterly wind anomalies and negative SST anomalies leads to a westward extension of the easterly flows to the western Pacific. The easterly wind anomalies along with the negative specific humidity anomalies and negative lower-level vorticity anomalies, and enhanced vertical wind shear suppress the TC genesis over the WNP during JJASO.
Adoption of integration systems of rice and cattle in Serdang Bedagai, North Sumatra
Authors: Mulyono J , Suryana A T , Hermawan H , Suryana E A 
Published: November 2021

Abstract
The integrated rice and cattle system (SITT) is an innovative technology package to increase agricultural production and encourage zero waste fulfillment. The technology components introduced include new HYV, fertilization, young seedlings, organic fertilizers, Jajar Legowo, IPM, bio urine, and compost. Although it has been implemented at the farmer level, there are insufficient details of its adoption performance; therefore, it is necessary to measure the adoption to evaluate the technology dissemination. This research objective was to analyze the farmers’ adoption level, adoption period, and technology application frequency. The research was conducted in Serdang Bedagai, North Sumatra, in 2018. The respondents were 40 farmers (cooperator and noncooperator), and the respondents’ selection was made purposively. The data obtained were analyzed using qualitative and quantitative descriptive approaches. The results showed that the adoption of technology by cooperator farmers was higher than noncooperator farmers, both from the perspective of each technology component and the level of adoption. The average duration of technology adoption by farmers was 44,0% require more than one planting season, 28,4% require one planting season, and 27,6% require less than one planting season. The frequency of technology application showed that farmers who apply SITT technology more than two planting seasons were 66,0%, exactly two planting seasons were 24,5%, and one planting season was 9,5%. Thus, to increase farmers’ adoption of technology, the technology should be suited to farmers’ preferences and needs, increase profits and ensure that the technology is available in the field. Moreover, providing continuous assistance during the introduction of technology.
Smallholder farmers’ perceptions and future aspirations toward dairy farming development in Bandung District, West Java
Authors: Anugrah I S , Ariningsih E , Erwidodo  , Saliem H P , Purwantini T B , Suryani E , Irawan A R , Hetherington J B 
Published: November 2021

Abstract
Dairy farming has an essential role in meeting the ever-increasing demand for milk. However, efforts to develop dairy farming in Indonesia are still facing various obstacles. This paper aims to analyze farmers’ perceptions and expectations toward developing dairy farming and its sustainability, along with its constraints. The data used in this paper are part of the IndoDairy Smallholder Household Survey database conducted between July and September 2017, consisting of 300 smallholder dairy farm households randomly selected from KPBS Pangalengan members. The data were analyzed using descriptive statistics and clustering analysis. The results show that the majority of dairy farmers (>50%) rated as ‘good’ the availability of extension services, availability of veterinary services, availability of veterinary medicines, availability of credit, and availability of concentrates; rated as ‘fair’ prices paid by buyers for milk, the number of milk buyers, and quality of the grass and forages; and rated as ‘bad’ the price of concentrates and the availability of land to purchase. In contrast, most farmers perceived the availability of land to purchase and the price of concentrates as ‘bad.’ As much as 90.3% of farmers expected to increase their dairy farm operations. The majority of dairy farmers (94%) showed their willingness to participate in training in the village, especially in animal husbandry (31.2%). This study strongly suggests that the government facilitates an increased supply of quality concentrate feed at affordable prices and land availability for dairy farming development.
The impact of agricultural extension on productivity of smallholder sugarcane farmers in East Java
Authors: Kosim M , Aji J M M , Hapsari T D 
Published: November 2021

Abstract
Agricultural extension is one of the most important factors to increase smallholder sugarcane farmer capacity and encourage the acceleration of technology adoption which positively correlates with farm productivity. This study aims to evaluate the impact of agricultural extension on the productivity of smallholder sugarcane farmers in East Java. While few previous studies showing the relationships, very limited involving a relatively large number of samples. This study used data from Indonesian Plantation Farm Household Survey 2014 by the Indonesian Statistical Agency (BPS). The number of samples was 2,893 farmers consisting of 2,463 farmers who did not participate (control group) and 430 farmers who participated in agricultural extension (treatment group). Propensity score matching (PSM) was used to evaluate the impact of agricultural extension on the productivity of sugarcane farming. Typically, the treatment group is better than the control group. The treatment group has an average education of 7.89 years, land area of 2.74 hectares and sugarcane productivity of 72 tons/ha. Meanwhile, the control group has an average education of 5.96 years, land area of 0.88 hectares and sugarcane productivity of 61 tons/ha. Our results show that farmers who participated in agricultural extension have a 9.05 tons higher productivity compared to those who did not participate. Therefore, farmers’ participation in agricultural extension should be encouraged by improving the frequency as well as the quality of agricultural extension. While the number of extension workers for plantation crops is limited, recruitment of more extension workers can be an optional policy for the government.
Adaptation of cayenne pepper farmers (Capsicum frutescens L.) on climate change in Jelbuk Subdistrict Jember
Authors: Rahman A , Subekti S , Rokhani  
Published: November 2021

Abstract
Climate change becomes more difficult to predict. Thus, makes farmers no longer able to accurately predict planting season. The impacts are decreasing productivity and production of cayenne pepper which can cause farmers to suffer losses. Efforts to minimize these losses are carried out with appropriate adaptation actions according to the conditions of the cultivated land. This study aims to determine the adaptation made by cayenne pepper farmers in Jelbuk Subdistrict, Jember District because of climate change. The used analysed method is qualitative through structured interviews, observation, and documentation. The used sampling method is purposive. The results showed that in the last 10 years, cayenne pepper farmers have experienced climate change. These changes such as seasonal shifts, extreme rains, droughts, and changes in air temperature which have an impact on increasing attacks of plant-disturbing organisms. The adaptations carried out by cayenne pepper farmers are adjusting the planting season, adjusting plant types (using tolerant varieties and crop rotation), using mulch and adding organic fertilizer, adjusting the shape of the beds/mounds, adjusting spacing settings, improving irrigation channels (adjusting the depth of the canal), applying water-saving technology, applying integrated pest and disease management techniques, implementing an intercropping system, accessing information technology, and actively participating in agricultural extention and field schools.