[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124725-en":3,"doc-seo-124725-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},124725,8796095360427,"Lucas Martin","https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d",8,"Research & Report","Estimation of Bali Cattle Body Weight Based on Morphological Measurements by Machine Learning Algorithms - Comparative Regression Modeling","Body weight prediction for Bali cattle is modeled using machine learning regression driven by morphometric traits. The study constructs predictive models with body length, girth circumference, and height at wither as predictors for 439 cattle (228 males, 211 females) around 285 days. Linear regression is used as a baseline, while Random Forest, Support Vector, K-Neighbors, and Extra Trees are evaluated as alternative regressors. Model performance is assessed using determination coefficient, RMSE, MAE, and AAPE, showing machine learning yields more accurate estimates than the conventional approach.","Journal of Advanced Zoology  \nISSN: 0253-7214  \nVolume 44 Issue 03 Year 2023 Page 01:09  \nEstimation of Bali Cattle Body Weight Based on Morphological Measurements by Machine Learning Algorithms: Random Forest, Support Vector, K-Neighbors, and Extra Tree Regression  \nNi Putu Sarini1, Komang Dharmawan2  \n1Dept. of Animal Husbandry Universitas Udayana, Bali, Indonesia [Email:](Email: putusarini@unud.ac.id)[ ](Email: putusarini@unud.ac.id)[putusarini@unud.ac.id](Email: putusarini@unud.ac.id)  \n[ORCIDID: 0000-0003-2420-7850](ORCIDID: 0000-0003-2420-7850)  \n2Dept. of Mathematics Universitas Udayana, Bali, Indonesia  \n[Email:](Email: k.dharmawan@unud.ac.id)[ ](Email: k.dharmawan@unud.ac.id)[k.dharmawan@unud.ac.id](Email: k.dharmawan@unud.ac.id)  \n[ORCIDID: 0000-0002-7021-1386](ORCIDID: 0000-0002-7021-1386)  \n1Corresponding author’[s E-mail:](s E-mail: putusarini@unud.ac.id)[ putusarini@unud.ac.id](s E-mail: putusarini@unud.ac.id)  \n\n| Article History\u003Cbr>Received: 06 June 2023\u003Cbr>Revised: 05 August 2023\u003Cbr>Accepted:21 August 2023\u003Cbr>CC License\u003Cbr>CC-BY-NC-SA 4.0 | Abstract\u003Cbr>To forecast and model the weight of cattle, several techniques are used. Nonetheless, no machine algorithm has been utilized to estimate the weight of Bali cattle. This article examines the use of machine learning regression to create models for Bali cattle's body weight prediction. The response variables consist of body weight as the dependent variable and body length, girth circumference, and height at wither of 228 male and 211 female cattle of similar ages (285 days). The descriptive statistics of female Bali cattle in our investigation revealed that the morphological measurements were similar to those documented by other researchers. To predict body weight based on different characteristics, machine learning models such as Random Forest, Support Vector, K-Neighbors, and Extra Tree regressions have been used. Additionally, linear regression was utilized to estimate the body weight for comparison with the traditional approach. The assessment standards used included the determination coefficient, the root mean square error, the average absolute error, and the average absolute percentage error as measures of evaluation efficiency. We found that Linear Regression performs the best among all the regressors for female cattle. Similarly for males, it is about the same as extra tree regression. The machine learning algorithm (MLA) was discovered to furnish a more precise estimate of the weight of the body of cattle, surpassing the conventional algorithm.\u003Cbr>Keywords: Bali Cattle, Machine Learning Algorithm Random Forest, Support Vector, K-Neighbors, and Extra Tree Regression. |\n| --- | --- |\n\n1. Introduction  \nThe Bali cattle, also known as Balinese cattle, are a domesticated species of cattle that originated from the Banteng (Bos javanicus). Bali cattles are one of many Indonesians local cattle that play an important role in beef production. Breeding better beef has become more crucial, with a focus on enhancing growth attributes such as weaning and yearling cattle weight. The feasible growth characteristics are impacted by other supervisors, ecological circumstances, and commercial nourishment situations. As evidenced by Agung et al. (2018); Gunawan & Jakaria (2010) inquiries have been conducted regarding this issue, and they have revealed that the findings are subject to the influence of other managers, ecological circumstances, and corporate nourishment. Investigations have been undertaken on this subject., see for example Agung et al. (2018), Gunawan & Jakaria (2010), Hafid (2020), Astiti et al.(2021) .  \nThe evaluation of livestock appearance and performance heavily relies on the measurement of their body dimensions. Various dimensions, which are indicative of the animal's size, are critical factors in livestock selection and breeding. Additionally, body measurements can be applied to estimate the weight of the animal. The height at withers and hip width are o","cbCaiaoYZ8jvFxWo","https://ap.wps.com/l/cbCaiaoYZ8jvFxWo","pdf",423465,1,9,"English","en",105,"# Introduction\n## Morphometric measurements for livestock selection\n## Machine learning vs. linear regression\n# Materials and Methods\n## Predictors and response variable\n## Selected regression algorithms\n## Model evaluation metrics","[{\"question\":\"Which measurements are used to predict Bali cattle body weight?\",\"answer\":\"Body length, girth circumference, and height at wither are used as predictors to estimate body weight as the dependent variable.\"},{\"question\":\"What machine learning regression models are evaluated?\",\"answer\":\"Random Forest regression, Support Vector regression, K-Neighbors regression, and Extra Trees regression are evaluated, with linear regression used as a comparison baseline.\"},{\"question\":\"How is model performance assessed in the study?\",\"answer\":\"Evaluation uses determination coefficient plus error-based metrics including root mean square error, average absolute error, and average absolute percentage error.\"}]","Estimation of Bali Cattle Body Weight Based on Morphological Measurements by Machine Learning Algorithms - Comparative Regression Modeling | PDF",1785894133,23,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"estimation-of-bali-cattle-body-weight-based-on-morphological-measurements-by-machine-learning-algorithms-comparative-regression-modeling","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/estimation-of-bali-cattle-body-weight-based-on-morphological-measurements-by-machine-learning-algorithms-comparative-regression-modeling/124725/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Which measurements are used to predict Bali cattle body weight?","Question",{"text":75,"@type":76},"Body length, girth circumference, and height at wither are used as predictors to estimate body weight as the dependent variable.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What machine learning regression models are evaluated?",{"text":80,"@type":76},"Random Forest regression, Support Vector regression, K-Neighbors regression, and Extra Trees regression are evaluated, with linear regression used as a comparison baseline.",{"name":82,"@type":73,"acceptedAnswer":83},"How is model performance assessed in the study?",{"text":84,"@type":76},"Evaluation uses determination coefficient plus error-based metrics including root mean square error, average absolute error, and average absolute percentage error.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]