International Journal Papier Advance and Scientific Review <p><strong>International Journal Papier Advance and Scientific Review </strong>ISSN <strong>2709-0248 </strong>covers research areas in Medical Science, Chemistry, Biology, Engineering, Technology, Information Sciences, Health Science, Applied Sciences, Cognitive Sciences, Artificial Intelligence, Life Sciences, Agricultural, Fisheries, Earth, Environmental Science, Botany, Zoology, Microbiology, Ecology, Ethnobiology, Genetics, Dental Health, Biochemistry, Bioinformatics, Biophysics, Biostatistics, Health Care Delivery, Health Care Research, Epidemiology, Midwifery, Health Psychology, Social Health, Biodiversity and Conservation Biology, Physical health, Quaternary Care, Secondary Care, Veterinary Nursing, Pharmaceutical Sciences, Hospital and Clinical Pharmacy, Architecture, Pathology, Physiotherapy &amp; Rehabilitation, Ergonomics, Food and Nutrition, Veterinary Medicines.</p> en-US Mon, 04 Jul 2022 00:00:00 +0700 OJS 60 A review of machine learning for big data analysis <p>Big data is the key to the success of many large technology companies right now. As more and more companies use it to store, analyze, and get value from their huge amounts of data, it gets harder for them to use the data they get in the best way. Most systems have come up with ways to use machine learning. In a real-time web system, data must be processed in a smart way at each node based on data that is spread out. As data privacy becomes a more important social issue, standardized learning has become a popular area of research to make it possible for different organizations to train machine learning models together while keeping privacy in mind. Researchers are becoming more interested in supporting more machine learning models that keep privacy in different ways. There is a need to build systems and infrastructure that make it easier for different standardized learning algorithms to be created. In this research, we look at and talk about the unified and distributed machine learning technology that is used to process large amounts of data. FedML is a Python program that let machine learning be used at any scale. It is a unified, distributed machine learning package.</p> Nadia Mahmood Hussien, Samira Abdul-Kader Hussain, Khlood Ibraheem Abbas, Yasmin Makki Mohialden Copyright (c) 2022 International Journal Papier Advance and Scientific Review Mon, 04 Jul 2022 00:00:00 +0700 Structure of Agrophytocenoses of Eastern Goat <p>The goals and purposes of the study included conducting all phases of field research on the creation of a novel method for weed management in goat's rue herbage that is based on the use of NRS. An arable community is referred to by the biological term "agrophytocenosis." The components of an agrophytocenosis include sowed cultivated plants and satellites, which are species of segetal weeds. These components are linked to the soil by seed banks and banks of vegetative rudiments. When determining an agrophytocenosis, not a particular sowing but rather the complete rotation of crops in a crop rotation within a homogenous region is taken into consideration; if the crop rotation is altered in any way, the agrophytocenosis will also be altered</p> Adilkhen Aiaru Copyright (c) 2022 International Journal Papier Advance and Scientific Review Thu, 08 Sep 2022 00:00:00 +0700 Efforts to Develop Bicycle Transportation in Supporting the Internal Transportation System <div><span lang="EN-GB">The Unhas Tamalanrea Campus has green open space which is one of the best urban forest areas in Makassar. This is supported by the implementation of Non-Motorized-Transport by re-developing bicycle transportation management. Campus Green Open Space is an attraction for the community to cycle, for this reason, attention to bicycle transportation facilities and connectivity with other transportation is needed so that vehicle access continues to run safely and comfortably, at the Unhas Tamalanrea Campus. This study aims to find out how the services of bicycle transportation facilities, the suitability of bicycle lanes, and development concepts can be applied at the Unhas Tamalanrea Campus. The analysis methods used are Importance Performance Analysis (IPA), Scoring Analysis, and Map interpretation. Data collection was carried out through observation, interviews, and questionnaires. The respondents taken were cyclists at the Unhas Tamalanrea Campus using accidental sampling techniques. The results showed that the condition of bicycle transportation facilities at the Unhas Tamalanrea Campus was quite good but still needed to be improved by the guidelines and concept of campus bicycle transportation.</span></div> Syarifah Nuzul Ahmad, Muhammad Yamin Jinca, Yashinta Kumala D. S. Copyright (c) 2022 International Journal Papier Advance and Scientific Review Mon, 19 Sep 2022 00:00:00 +0700