Analyzing the impact of Jakarta’s reclamation on the distribution of TSS using remote sensing technology

Jakarta Bay is a bay supporting the economy of thousands of nearby fishermen. Therefore, the reclamation in Jakarta Bay raises many environmental, economic, and social problems. During this reclamation, dredging and stockpiling activities increase the turbidity of the waters. This research aims to determine the changes in the distribution of total suspended solids (TSS) after reclamation using Sentinel 2A satellite imagery from 2016 to 2022. This research implemented the previous algorithm to produce the distribution of TSS in Jakarta Bay for attaining TSS values from Sentinel 2A satellite imagery processed by Google Earth Engine with overlay analysis method in a geographic information system. Spatial data were obtained by extracting TSS values using the previous estimation algorithm, namely the Budhiman algorithm, with a correlation coefficient of -0.745 and NMAE of 0.167. Based on the data processing results, it was found that the distribution of TSS from 2016 to 2022 was at a moderate level, which had a relatively significant influence on fisheries, requiring the fishermen to go to the open sea farther from the coast. This shows that reclamation carries no impact on the life of marine biota in Jakarta Bay

The EFL Students’ Perspectives on Library Modalities: Attitude and Correlation to Academic Achievement

The present study aimed to scrutinize the EFL students\u27 perspectives on library in various modalities to mediate EFL learning and to know the correlation of the EFL students\u27 attitudes to the EFL students\u27 academic achievement. Hence, quantitative research with descriptive and correlational research designs were applied. 112 EFL students in an English Education Department (EED) at a public university in West Nusa Tenggara, Indonesia contributed their responses by filling out an online questionnaire containing questions to answer the research goals and sharing their GPA files. To analyze the data, descriptive and correlational statistical calculations through SPSS 24 version were done. The results showed that EFL students had positive perspectives toward library modalities which were reflected by their attitude to frequently visiting the library in various modalities. Moreover, the EFL students’ positive belief about the correlation of their attitude with academic achievement was supported by statistical calculations and previous studies. However, further studies to confirm these research findings will be suggestible due to the limitations of this research. Hence, it is suggested to enhance the significance of the library in various modalities for academic purposes by increasing the visits

Microclimate-based mortality analysis of the Cibodas Botanic Gardens plant collection

Despite the routinely conducted treatment and maintenance of garden plant collection, the monthly mortality figures of the Cibodas Botanic Gardens (CBG) plant collections remain significant. It is presumed that the microclimate has a crucial influence on plant survivorship in the field. This study aimed to analyze the effect of microclimate conditions on the mortality rate of the CBG plant collection. The study was conducted by correlating the number of mortal plants with CBG monthly microclimatic conditions from 2017 to 2018. The analyzed microclimate parameters were temperature, relative humidity, precipitation, wind velocity, and solar radiation. The multiple regression modeling, t-test, and Pearson correlation test (r) were utilized to measure the level of significance of the correlation (α = 0.05). The findings were shown that the maximum wind velocity was the primary unit correlated to the number of mortality. The correlation was strong positive (r = 68.8%), and significant (p-value α). We suggested anticipating the disadvantages influences of strong wind supported by other extreme microclimate units, such as heavy rain. These events frequently caused high damage to the tree and other plant collections. These are expected to be taken into a consideration by the CBG operator and management in order to forecast and mitigate the risks of future plant collection losses

Hybrid ANFIS-Taguchi Method Based on PCA for Blood Bank Demand Forecasting

Kan; hastalıklar, ameliyatlar veya yaralanmalar nedeniyle her gün binlerce insan tarafından ihtiyaç duyulan hayati bir üründür. Bu nedenle hastanelerin kan ihtiyacını karşılayan kan bankalarının stoklarında yeterli miktarda kan bulundurması gereklidir. Gereğinden az miktarda kan elde bulundurulması ihtiyacın karşılanamaması ve can kaybı gibi önemli sorunlar oluştururken, fazla miktarda kanın stoklanması ise kanın bozulmasına ve kan ihtiyacı olan farklı hastanelerin stoksuz kalmasına neden olmaktadır. Bu çalışmada öncelikle kan bileşenlerinden biri olan eritrosit süspansiyonu talebine etki eden kriterler belirlenerek; bu kriterlere göre makine öğrenme algoritmalarından uyarlamalı ağ tabanlı bulanık çıkarım sistemi (ANFIS) yöntemi ile talebin tahmin edilmesi amaçlanmaktadır. Ancak talebe etki eden çok sayıda kriter olduğu için gruplandırarak azaltmak ve kriterler arasındaki bağımlılıkları ortadan kaldırmak amacıyla temel bileşen analizi (PCA) yönteminden yararlanılmıştır. Ayrıca ANFIS’in performansı; modelin yapısı ve öğrenmesini etkileyen parametre değerlerinin doğru belirlenmesi ile ilişkili olduğundan en yüksek doğrulukla tahmini sağlayacak değerler Taguchi deney tasarımı yöntemiyle belirlenmiştir. Geliştirilen PCA esaslı hibrit ANFIS-Taguchi yöntemi bir bölge kan merkezinde uygulanmıştır. Korelasyon katsayısı (??) performans ölçütü ile yöntemin tahmin yeteneği değerlendirilmiştir. Uygulama sonunda tahmin edilen eritrosit süspansiyon talep miktarının %88.1 oranla gerçekleşen talep miktarı ile benzer sonuç verdiği görülmüştür.Blood is a vital product that is needed by thousands of people every day due to diseases, surgeries or injuries. For this reason, it is necessary that the blood banks have enough blood quantity to meet the blood needs of hospitals . The provision of small amounts of blood in hospitals creates significant problems such as loss of life and can’t meet the demand. On the other hand, the stocking of large amounts of blood leads to the wastage of blood and the stockless of blood different hospitals. The aim of this study is to determine the criteria affecting blood demand and to forecast the blood demand by the machine learning algorithm Adaptive Network Based Fuzzy Inference System (ANFIS) method. However, since the number of impact criteria is high, principal component analysis (PCA) method has been used in order to decrease criteria and eliminate the dependencies between the criteria. In addition, the performance of ANFIS depend on determining ANFIS parameters that affect its structure and learning. So to provide the highest learning ANFIS parameters were determined by the Taguchi experimental design method. The developed hybrid method was applied in a regional blood center and evaluated with correlation coefficient (??). At the end of the application, it is seen that the estimated red blood cells demand is similar to the demand amount realized at the rate of 88.1%

ELEMENTARY SCHOOL BUILDINGS CONDITION ASSESSMENT: CASE OF PRIMORJE-GORSKI KOTAR COUNTY (CROATIA)

This study deals with the condition examination of elementary school buildings in Primorje-Gorski Kotar County, Croatia. For schools to be functional and of high quality, adequate maintenance is mandatory. Therefore, school maintenance programs need information on the building\u27s condition based on systematic and comprehensive assessments as a primary input. This study aims to establish a framework for assessing the condition of school buildings, based on which information can be obtained quickly and practically regarding the condition of all critical facility elements. To this end, a database on schools and their conditions was created. The conditions of school buildings in terms of damage and defects and their causes were determined. Descriptive and inferential statistical operations were performed on the collected data. A condition assessment of the buildings was performed using a questionnaire survey among the principals, based on the school buildings division model developed in this study; the model presents building elements and a systematic visual condition rating scale. According to the available data, this is Croatia\u27s first condition assessment on elementary school buildings. The main results show that on average, the examined schools are in good condition. Moreover, according to the results, the school building condition is most affected by dilapidation and lack of financial resources

Análise e gestão de dados em futebol: social network analysis

Em competições de futebol de alto rendimento desportivo é crucial a análise relativa aos desempenhos coletivos de cariz tático e individual. Assim se identificam as principais características e padrões táticos e se fornece informação relevante passível de auxiliar o treinador na compreensão das particularidades da sua equipa, e das dos adversários, na tomada de decisão em contexto de jogo e no aperfeiçoamento do treino. No jogo de futebol o movimento contínuo e constante dos jogadores é pautado por eventos e momentos críticos e disruptivos, que em muitos casos asseguram vantagens ofensivas favoráveis para a vitória competitiva. É neste contexto que o presente projeto pretende preencher uma lacuna existente na literatura. Na essência, no plano da gestão de dados e economia do tratamento de informação, pretende-se saber se a análise parcial do jogo, considerando instantes indexados a eventos críticos, reflete o mesmo fenómeno que a sua análise integral do jogo. Recorrendo à ferramenta de análise uPATO e a modelos matemáticos associados à Social Network Analysis (SNA), analisámos um jogo da época 2019/2020 da UEFA Champions League - Sport Lisboa e Benfica vs Olympique Lyonnais. Os resultados obtidos mostram limitações relativas à representatividade dos fenómenos coletivos da equipa e do comportamento individual dos jogadores, quando se analisam apenas alguns eventos críticos face à análise global do jogo. Contudo, a exclusiva análise dos momentos críticos do jogo é relevante no estudo das estratégias ofensivas e na identificação dos jogadores mais relevantes nestes eventos. A sua associação com o conhecimento resultante da SNA da totalidade do jogo, poderá potenciar a gestão do comportamento dos jogadores mais eficazes ao longo de todo o jogo e, dos mais relevantes nos eventos críticos. Esta informação é fundamental para análise complementar dos eventos críticos na compreensão do comportamento dos jogadores e das equipas

Analisis Faktor Yang Mempengaruhi Kasus Demam Berdarah di Kabupaten Malng dengan Metode Social Network Analysis

Kesehatan adalah hal yang diharapkan oleh setiap orang, karena dengan kesehatan aktivitas dapat berjalan sesuai dengan keinginan. Demam Berdarah merupakan penyakit tropis dan sub tropis yang umum ditemukan di daerah perkotaan dan sub-perkotaan. Data dari seluruh dunia menyatakan bahwa Asia berada di urutan pertama dalam jumlah penderita demam berdarah di setiap tahunnya, sedangkan World Health Organization (WHO) mencatat Indonesia merupakan negara dengan kasus demam berdarah tertinggi kasus demam berdarah di Asia Tenggara. Kabupaten Malang merupakan salah satu kabupaten endemik demam berdarah, dimana Badan Pusat Statistik Jawa Timur menyatakan kasus demam berdarah di Kabupaten Malang merupakan yang tertinggi. Demam berdarah salah satu kasus penyakit yang merupakan siklus musiman yang dapat diperkirakan sebelumnya. Dari banyaknya faktor-faktor yang mempengaruhi terjadinya demam berdarah perlu dilakukan analisis untuk mengetahui faktor yang paling berpengaruh terhadap terjadinya kasus demam berdarah. Faktor yang mempengaruhi terjadinya kasus demam berdarah terbagi menjadi dua yaitu faktor secara langsung dan tidak langsung. Faktor langsung diakibatkan oleh jumlah jentik dan iklim sedangkan faktor tidak langsung diakibatkan oleh perpindahan populasi/migrasi, kondisi ekonomi, kondisi geografis dan lingkungan. Perlunya analisis untuk mengetahui bagaimana pengaruh faktor penyebab demam berdarah terhadap kasus demam berdarah sehingga dengan mengetahui faktor yang paling berpengaruh dapat dilakukan rekomendasi terhadap Dinas Kesehatan Kabupaten Malang dalam melakukan pencegahan atau mitigasi untuk menekan penyebaran kasus demam berdarah di Kabupaten Malang. Analisis untuk mencari faktor yang berpengaruh dilakukan dengan menggunakan metode Social Network Analysis. Social Network Analysis adalah metode yang dikembangkan untuk memetakan dan mengukur hubungan dan aliran antar entitas informasi yang terhubung. Luaran dari penelitian ini adalah hasil entitas pengaruh faktor penyebab terjadinya demam berdarah. Pada dataran rendah dengan membandingkan variabel yang sama menghasilkan variabel kecepatan angin yang paling berpengaruh, sedangkan pada dataran tinggi dengan variabel yang sama menghasilkan variabel curah hujan yang paling berpengaruh. Dengan membandingkan variabel, puskesmas yang sama dan masa inkubasi nyamuk pada dataran rendah dan tinggi menghasilkan kelembapan udara memiliki pengaruh dalam penyebaran demam berdarah pada Kabupaten Malang. ================================================================================================================================= Health is something that is expected by everyone, because with health the activity can run as you wish. Dengue Fever is a tropical and sub-tropical disease that is commonly found in urban and sub-urban areas. Data graphoptom around the world states that Asia ranks first in the number of dengue fever sufferers each year, while the World Health Organization (WHO) notes Indonesia is the country with the highest dengue fever cases in dengue cases in Southeast Asia. Malang Regency is one of the dengue endemic districts, where the East Java Central Statistics Agency stated that dengue fever cases in Malang Regency were the highest. Dengue fever is one case of a disease which is a seasonal cycle that can be predicted in advance. Of the many factors that influence the occurrence of dengue fever analysis needs to be done to find out the factors that most influence the occurrence of dengue fever cases. Factors that influence the occurrence of dengue fever cases are divided into two factors, namely factors directly and indirectly. Direct factors are caused by the number of larvae and climate while indirect factors are caused by population movements / migration, economic conditions, geographical and environmental conditions. The need for analysis to find out how the influence of dengue fever factors on dengue fever cases so that by knowing the most influential factors can be made recommendations to Malang District Health Office in conducting prevention or mitigation to reduce the spread of dengue cases in Malang Regency. Analysis to look for influential factors is done by using the Social Network Analysis method. Social Network Analysis is a method developed to map and measure the relationships and flows between connected information entities.The output of this study is the result of an entity influencing factors causing dengue fever. In the lowlands comparing the same variable produces the most influential wind speed variable, whereas in the highlands the same variable produces the most influential rainfall variable. By comparing variables, the same public health center (puskesmas) and mosquito incubation period in the lowlands and highlands produce air humidity which has an influence in the spread of dengue fever in Malang Regency