Evaluation of Indonesian Butterfly Pea (Clitoria ternatea L.) Using Stability Analysis and Sustainability Index

Yield and yield attributes are important components in genotypic evaluation. The butterfly pea is a native plant of Indonesia, and it is considered an underutilized crop. The goals of this study were to evaluate genotypes using environment (year) interactions (GEIs) with yield and yield attributes, and evaluate butterfly pea genotypes based on stability measurements and sustainability index (SI). The study was conducted at the Ciparanje Experimental Field, Faculty of Agriculture, Universitas Padjadjaran using 35 butterfly pea genotypes in a randomized complete block design with two replications. The field trial was conducted over three years (2018–2020). The results showed that the yield and yield attributes were influenced by GEIs. Additive main effects and multiplicative interaction (AMMI) selected 11 stable genotypes (31.43%);genotype plus genotype by environment interaction (GGE) biplot, AMMI stability value (ASV), and genotype stability index (GSI), each selected six genotypes (17.14%) that were stable and high-yielding, and SI selected 18 genotypes (51.43%) that were stable and high-yielding. There were three genotypes identified by all measurements, namely G2, G14, and G16. These three genotypes can be selected as the superior genotypes of the butterfly pea for flower production, and can be used as material for crosses in plant-breeding prog.

COVID-19 Preparedness and Response by Global South and Global North Countries: A Comparative Analysis

Comparing the countries' level of preparedness and response to the Covid-19 pandemic involves the assessment of human development, health, connectivity and death rate indicators. In this study, information published by the United Nations Development Program (UNDP) and the World Health ]Organization (WHO) was used to assess the performance of 148 countries classified as either of the Global South (Africa, Latin America and Asia-Oceania) or the Global North, describing how the unequal social and health conditions between regions are reflected in terms of contagion and death figures at year-end 2020. The HJ-Biplot multivariate technique was used to simultaneously represent both the countries and the indicators, providing a descriptive and exploratory analysis of how the countries' level of preparedness to face the pandemic in terms of health and human development did not determine their success in reducing Covid-19 contagion and death rates, because success also depends on efficient and quick government action and reaction strategies.

HJ-Biplot and Clustering to Analyze the COVID-19 Vaccination Process of American and European Countries

HJ-Biplot and Cluster Analysis are used in a data set that contains variables related to the impact of COVID-19 and vaccination in American and European countries. The variables considered are total cases per million, total tests per thousand, total deaths per million, total vaccinations per hundred, and people fully vaccinated per hundred. The purpose of this paper is to analyze the time evolution of the COVID-19 vaccination process in the aforementioned region during March, April, May, June, July, and August 2021. The results obtained provide a straightforward way of determining each country’s status with respect to the variables considered, which could be useful for policymakers to understand the evolution of their country throughout the pandemic. © 2022, Springer Nature Switzerland AG.

HJ-BIPLOT as a Basis for the Search of Clusters Based on Pension Indicators for Latin American Countries

In the 1980s, Chile’s Decree-Law No. 3500 introduced a new Pension System in Latin America based on individual savings by workers during their working life, thus discarding the distribution model. The system has been implemented in several countries in the region, such as Mexico, Uruguay, Peru, Colombia, Panama, Costa Rica, El Salvador, and the Dominican Republic, so that today in Latin America, two types of systems coexist, one with a public fund and the other with individual savings managed by private companies called Pension Fund Administrators (AFP). Since before the Pandemic, Latin America has had demographic, occupational, and other problems, which have deepened with COVID-19 and have had a negative impact on the economies of various countries in the region, and which have seen pension savings as a support option for overcoming the crisis. Different politicians and experts have analyzed the situation, if this withdrawal of savings from pension funds supports people to overcome one of the worst economic crises in recent years, risking the pension systems to get rid of assets in different markets, mainly where demand is weak and liquidity is low. This article seeks to explain the trend of the AFPs using the HJ-Biplot statistical method. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Reconstruction of Non-linear Path Analysis Accompanied by Measurement Models on Food Security Models in Indonesia Post-Covid19 Pandemic based on Big Data

This study aims to map and model the determinants of food security. Mapping is done by cluster and biplot analysis, while modeling is done by non-linear path analysis. This research is mix-method research that combines quantitative and qualitative research. In the qualitative method, this study applies a qualitative Discourse Network Analysis (DNA) approach. Sources of DNA data come from various information in cyberspace (mass media, journals, articles, etc.) that are in accordance with the research context. In DNA data processing, statements, actors, concepts/issues, sentiments, along with the origin of the organization will be generated. As for the quantitative method, this study uses descriptive statistical analysis, biplot, cluster, and non-linear path analysis (square and cubic). The coefficient of determination for both quadratic and cubic path analysis is 0.88, which means that the influence of the independent variable simultaneously on the Y variable is 0.88, which is very strong. Thus, the model formed is quite good because the predictor variable is able to explain food security by 88% while the rest is explained by other factors outside the model. The originality of this research is the reconstruction of non-linear path analysis which is more flexible (no need for assumptions of normality and homogeneity) and is equipped with a measurement model. © 2021 World Scientific and Engineering Academy and Society. All rights reserved.