bluuebunny/crossref_metadata_2025 huggingface dataset:
Long-Term Consequences of Puumala Hantavirus Infection
Authors: Mustonen Jukka , Vaheri Antti , Pörsti Ilkka , Mäkelä Satu
Published: March 2022

Several viral infections are associated with acute and long-term complications. During the past two years, there have been many reports on post-infectious symptoms of the patients suffering from COVID-19 disease. Serious complications occasionally occur during the acute phase of Puumala orthohantavirus caused nephropathia epidemica. Severe long-term consequences are rare. Fatigue for several weeks is quite common. Hormonal insufficiencies should be excluded if the patient does not recover normally.
Seed Transmission of Three Viruses in Two Pear Rootstock Species Pyrus betulifolia and P. calleryana
Authors: Li Liu , Wen Lihong , Wang Guoping , LYU Yuzhuo , Yang Zuokun , Yang Xiaoping , Li Qingyu , Hong Ni
Published: March 2022

Viral seed transmission causes the spread of many plant viral diseases. Pyrusbetulifolia and P. calleryana are important rootstock germplasms for pear production in China. This study revealed the widespread infection of apple stem grooving virus (ASGV), apple chlorotic leaf spot virus (ACLSV), and apple stem pitting virus (ASPV) in maternal trees of P. betulifolia and P. calleryana by nested multiplex reverse transcription-polymerase chain reaction (nmRT-PCR) assays. Seeds from eight P. betulifolia and two P. calleryana trees had positive rates of 15.9–73.9%, 0–21.2%, and 40.4% for ASGV, ASPV, and ACLSV, respectively. At the cotyledon and 6–8 true leaf stages, seedlings grown from seeds of infected trees gave positive rates of 5.4% and 9.3% for ASGV, 6.7% and 15.6% for ACLSV, and 0% and 2.7% for ASPV, respectively. Incidence in nursery P. betulifolia seedlings of 10.1%, 5.3%, and 3.5% were determined for ASGV, ACLSV, and ASPV, respectively. The nucleotide sequences of coat protein (CP) and movement protein coding genes of both ASGV and ASPV, and CP gene of ACLSV from maternal trees, seeds, and seedlings were analyzed. Sequence identities and phylogenetic comparison with corresponding sequences from GenBank demonstrated that molecular variation occurred within ASGV, ACLSV, and ASPV isolates, with most sequences determined here had close relationships with reported isolates infecting pear or formed independent clades. This is the first report on the seed transmission and the molecular characteristics of these viruses infecting two rootstock species. These findings provided important evidence in management effort for pear viral diseases.
A Novel H-2d Epitope for Influenza A Polymerase Acidic Protein
Authors: Uddbäck Ida , Kohlmeier Jacob E. , Thomsen Allan R. , Christensen Jan P.
Published: March 2022

Understanding the complexity of the T-cell epitope hierarchy in humans through mouse models can be difficult. In particular, using only one murine strain, the C57BL/6 mouse, to investigate the immune response to influenza virus infection limits our understanding. In the present study, by immunizing C57BL/6 mice with an adenoviral vector encoding the polymerase acidic (AdIiPA) protein of influenza A virus, we were able to induce a high number of PA-specific T cells. However, upon challenge, these cells were only partly protective. When instead immunizing BALB/c mice with AdIiPA, we found that the immunized mice were fully protected against challenge. We found that this protection was dependent on CD8 T cells, and we identified a novel H-2Dd-restricted epitope, PA33. These findings provide a new tool for researchers to study PA-specific immunity in mice with an H-2d haplotype. Additionally, our findings underscore the importance of critically evaluating important limitations of using a single inbred mouse strain in vaccine studies.
Hallmarks of Metabolic Reprogramming and Their Role in Viral Pathogenesis
Authors: Allen Charles N. S. , Arjona Sterling P. , Santerre Maryline , Sawaya Bassel E.
Published: March 2022

Metabolic reprogramming is a hallmark of cancer and has proven to be critical in viral infections. Metabolic reprogramming provides the cell with energy and biomass for large-scale biosynthesis. Based on studies of the cellular changes that contribute to metabolic reprogramming, seven main hallmarks can be identified: (1) increased glycolysis and lactic acid, (2) increased glutaminolysis, (3) increased pentose phosphate pathway, (4) mitochondrial changes, (5) increased lipid metabolism, (6) changes in amino acid metabolism, and (7) changes in other biosynthetic and bioenergetic pathways. Viruses depend on metabolic reprogramming to increase biomass to fuel viral genome replication and production of new virions. Viruses take advantage of the non-metabolic effects of metabolic reprogramming, creating an anti-apoptotic environment and evading the immune system. Other non-metabolic effects can negatively affect cellular function. Understanding the role metabolic reprogramming plays in viral pathogenesis may provide better therapeutic targets for antivirals.
Investigation of a Cluster of Immunization Stress-Related Reactions after Coronavirus Disease 2019 (COVID-19) Vaccination, Thailand, 2021
Authors: Mahasing Chayanit , Yasopa Oiythip , Sansilapin Chalo , Rattanathumsakul Thanit , Thammawijaya Panithee , Suphanchaimat Rapeepong , Doung-ngern Pawinee
Published: March 2022

On 28 April 2021, the investigation team of the Department of Disease Control, Ministry of Public Health, was notified of a cluster of people developing neurological symptoms following COVID-19 vaccination in a province in eastern Thailand. We conducted an investigation from 29 April to 20 May 2021 to confirm the outbreak, describe the epidemiological characteristics and identify possible risk factors. A matched case-control study was conducted. Matching factors were gender and vaccination site. A confirmed case was a person receiving COVID-19 vaccination in the province and developed at least one neurological symptom between 21 April and 20 May 2021. The rapid assessment of the vaccination cold chain system was carried out. We found a total of 36 cases out of 3920 vaccinees (attack rate = 0.92%), all cases were recovered and classified as an immunization stress-related reaction (ISRR) by the National AEFI Expert Committee. An analytic study found that menstruation was significantly associated with ISRR (AOR = 6.84 [95%CI = 1.09–42.91]). The environmental survey suggested that the cold chain system was properly managed. Further studies on other precipitating causes of ISRR should be performed. In terms of recommendation, health providers should pay greater attention to women menstruating during and after COVID-19 immunization.
Effectiveness of Monovalent Rotavirus Vaccine in Mozambique, a Country with a High Burden of Chronic Malnutrition
Authors: Chissaque Assucênio , Burke Rachel M. , Guimarães Esperança L. , Manjate Filomena , Nhacolo Arsénio , Chilaúle Jorfélia , Munlela Benilde , Chirinda Percina , Langa Jerónimo S. , Cossa-Moiane Idalécia , Anapakala Elda , Bauhofer Adilson Fernando Loforte , Garrine Marcelino , João Eva D. , Sambo Júlia , Gonçalves Luzia , Weldegebriel Goitom , Shaba Keith , Bello Isah Mohammed , Mwenda Jason M. , Parashar Umesh D. , Tate Jacqueline E. , Mandomando Inácio , de Deus Nilsa
Published: March 2022

Mozambique introduced monovalent rotavirus vaccine (Rotarix®) in September 2015. We evaluated the effectiveness of Rotarix® under conditions of routine use in Mozambican children hospitalized with acute gastroenteritis (AGE). A test negative case-control analysis was performed on data collected during 2017–2019 from children <5 years old, admitted with AGE in seven sentinel hospital sites in Mozambique. Adjusted VE was calculated for ≥1 dose of vaccine vs. zero doses using unconditional logistic regression, where VE = (1 − aOR) × 100%. VE estimates were stratified by age group, AGE severity, malnutrition, and genotype. Among 689 children eligible for analysis, 23.7% were rotavirus positive (cases) and 76.3% were negative (controls). The adjusted VE of ≥1 dose in children aged 6–11 months was 52.0% (95% CI, −11, 79), and −24.0% (95% CI, −459, 62) among children aged 12–23 months. Estimated VE was lower in stunted than non-stunted children (14% (95% CI, −138, 66) vs. 59% (95% CI, −125, 91)). Rotavirus vaccination appeared moderately effective against rotavirus gastroenteritis hospitalization in young Mozambican children. VE point estimates were lower in older and stunted children, although confidence intervals were wide and overlapped across strata. These findings provide additional evidence for other high-mortality countries considering rotavirus vaccine introduction.
Correction: Pereira et al. Effect of the Progressive Increase of Organic Loading Rate in an Anaerobic Sequencing Batch Reactor for Biodiesel Wastewater Treatment. Water 2022, 14, 223
Authors: Pereira Erlon Lopes , Borges Alisson Carraro , da Silva Greicelene Jesus
Published: March 2022

In the original article [1], there were the following mistakes:-In Table 4, where it reads “kap” it should read “kap” [...]
Effects of functional poly(ethylene terephthalate) nanofibers modified with sericin-capped silver nanoparticles on histopathological changes in parenchymal organs and oxidative stress in a rat burn wound model
Authors: ŞAHİN Yaşar , GÜN GÖK Zehra , ALÇIĞIR Mehmet Eray , ÇINAR Miyase
Published: March 2022

In this study, it was aimed to investigate the effect of a poly(ethylene terephthalate)-g-poly(hydroxyethyl methacrylate) (PET-g-HEMA) nanofiber wound dressing modified with sericin-coated silver nanoparticles (S-AgNPs) on internal organs, oxidative stress, and biochemical parameters. To establish a burn model, the backs of anesthetized rats were shaved and then third-degree burns were created with a round-bottomed stainless steel rod 2 cm in diameter kept in 100 °C water for 20 seconds. The wounds of the negative control group (G1) were covered with standard bandages; the wounds of the positive control group (G2) were covered with silvercel, used as burn wound material; and the wounds of the experimental group (G3) were covered with PET-based dressing material. Histopathological changes in organs (liver, kidneys, heart, pancreas, lungs), total oxidant status (TOS), total antioxidant status (TAS), nitric oxide (NO), and biochemical parameters (serum aspartate aminotransferase [AST], alanine aminotransferase [ALT], gamma glutamyl transpeptidase [GGT], creatine kinase, lactate dehydrogenase [LDH], total protein, albumin, globulin, urea) were examined. Compared with the G1 group, plasma AST, ALT, and GGT levels were found to be significantly decreased in G2 and G3 (P<0.001). Plasma TAS was found to be significantly increased in G2 and G3 compared to G1 (P<0.05). Compared to the G1 group, degenerative and necrotic changes in the liver, kidneys, and pancreas were found to be significantly reduced in G2 and G3 (P<0.05). In conclusion, this work demonstrates that the synthesized PET-based wound dressing material has the capacity to be used commercially.
Short-Term Forecasting of Air Travellers Outflows from Bali Using Web Search Data
Authors: Oktama Parma Dwi Widy
Published: March 2022

Air travelers have become one of the strategic indicators in the transportation sector. The official data-released by Statistics Indonesia (BPS) for thirty days-lag, makes the condition of this indicator can’t be known in real-time. By the utilization of web search data that has been briskly evolving in recent years, this study aims to explore the possibility of using web search data in performing short-term forecasting to know the general outlook of the indicator earlier. Based on this study, web search data and official statistics figures show a strong correlation and having similar movement patterns over time. The application of web search data as a predictor in time series modeling, especially on time series regression and autoregressive model (SARIMA and SARIMAX), turn out a predicted value that well-approach the actual value of the response variable. In addition, it is proven that the use of web search data can increase model accuracy. The analysis results using SARIMAX model shows that the number of air traveller’s outflows from Bali in September and October 2021 will generally be higher than the number in August 2021. The increasing number of air travelers is thought due to a decrease in Covid-19 cases which has triggered the public's confidence in travelling about to rise again.
Revisiting Local Walking Based on Social Network Trust (LWSNT): Friends Recommendation Algorithm in Facebook Social Networks
Authors: Nurkarim Wahidya , Wijayanto Arie Wahyu
Published: March 2022

In the last decades, the internet penetration rate and online social network users have grown very fast. Online social network, such as Facebook, is a platform where one can find friends without having to meet face to face. A social network is represented by a large graph because it involves many participants. Hence, it is hard to find potential friends who have the same thoughts and interests. The Local Walking Based on Social Network Trust (LWSNT) algorithm is one of the popular algorithms for social friend recommendation. This study re-examines whether the correlation between attributes gives un-match ranks in different cases (cases with and without correlation). We assess the performance of LWSNT in Facebook networks under the supervised manner by comparing its F-score against similar methods. By using Kendall’s tau correlation, the results show that the correlation of attributes has no significant effect on the order of friend recommendations. In addition, the LWSNT performance is quite inferior against the Common Neighbors algorithm and Jaccard index.
Spatial Panel Data Approach on Environmental Quality in Indonesia
Authors: Saputri Debita Tejo , Pratama Anugrah Alief
Published: March 2022

Indonesia adopted a strategic long-term development plan (2005-2025) targeting to achieve a green and everlasting Indonesia through implementing various environmental policies. One of the mandatory matters for governments is to continue environmental control by constructing Environmental Quality Indexes (EQI). This study focuses on the relationship between regional output or real Regional GDP, level of population density, and the government expenditure on environment quality on EQI in 34 provinces in Indonesia by the time period 2015 to 2019 using a spatial panel data approach. Within the context of spatial modeling, the interaction between provinces depends on their geographical location and condition. Using the geographic information system (GIS) and stata attributes, the coordinates and distances can be mapped and then defined for observation units in space via the spatial weight matrix used. From the perspective of spatial geography, this paper verifies the spatial dependence of Indonesia’s Environmental Quality Index (EQI). Pesaran's CD test indicates the spatial effect on the model and SAR with random effect can be considered a better-fitting spatial panel regression model. The results of the econometric spatial panel using SAR panel with random effect analysis show that Indonesia’s EQI in the provinces was dependent on the spatial. It was also found that regional GDP has a significant and negative effect on EQI and population density has a negative and significant effect on EQI. While fiscal policy on the environmental area on improving environmental quality did not pass a significance test. Thus, it is recommended to look for ways to promote green growth in the country.
Working Age Population and CO2 Emissions in Indonesia:
Authors: Wulandari Mirta Dwi
Published: March 2022

An increase in the working age population causes an increase in consumption which in turn will have an impact on increasing CO? emissions. The household is an element that must be responsible for increasing emissions of greenhouse gases because of their fossil fuels consumption. This study aims to observe the relationship of the working age population and the CO? emissions in households. This study use data from National Socio-Economic Survey (Susenas) 2019 with households consuming gasoline / diesel / kerosene for transportation, and LPG / kerosene for cooking as a unit of analysis. Apart from working age population as the main independent variable, socioeconomic characteristics (household size, income, residential area, poverty, age, sex, education, employment status, and access to modern fuels) are also used as control variables. Multiple regression analysis was used in this study. The results show that the working age population variable is positively correlated to total CO? emissions, transportation-related emissions, and cooking fuels emissions. Respectively, households dominated by members of working age (15-64 years) emitted 8.7%, 12.7%, 3.2% higher than households dominated by non working age (0-14 years and/or 65+ years). Providing sustainable transport system can be the best solution to reduce CO? emissions.
Analysis of Government Policy in Handling Covid-19 in Indonesia
Authors: Ilafi Atika Kautsar , Fadhilah Annisa Nur , Jowanti Lita
Published: March 2022

The Covid-19 pandemic has affected the economy in many countries, including Indonesia. Until July 2021, the Government has implemented social activity policies for the community, starting from Large-Scale Social Restrictions in the first semester of last year to PPKM Level 4 to stop the spread of Covid-19. Responding to the Covid-19 pandemic, Google released data from people who access google applications using mobile devices. The Google Mobility report shows changes in population activity and mobility in several locations. This study aims to examine the effect of the PSBB and PPKM policies in Indonesia on the decline in COVID-19 cases in Indonesia using the Google Mobility Index and their impact on the economy in Indonesia. The analysis uses graphs and Pearson Correlation and Long Short-Term Memory (LSTM) method to predict Covid-19 cases and mobility data. The result shows that the mobility of people to five places has a significant effect on the number of daily cases of Covid-19, while there is a significant effect on three places of community mobility on Indonesian economic. As the results, controlling the spread of Covid-19 is better prioritized than economic condition.
Estimating Customer Lifetime Value in the E-Commerce Industry Using Multivariate Analysis
Authors: Laksono Bagaskoro Cahyo , Wulansari Ika Yuni
Published: March 2022

Companies can develop their business using big data to support decision-making. Big data in the e-commerce industry that includes size and speed of high transactions can be used to analyze customer behaviour and predict customer value. Nowadays, companies are starting to develop customer-oriented rather than product-oriented business interests. One way that can be used to determine customer value is by calculating Customer Lifetime Value (CLV). By knowing CLV at the individual level, it will be useful to help decision-makers to develop customer segmentation and resource allocation. It is important to do segmentation or customer grouping that describes customer loyalty groups. Therefore, this research aims to calculate CLV and customer segmentation using the RFM analysis method. The dimensions of forming CLV include the values of Recency, Frequency, and Monetary. In this study, concept of multivariate statistical analysis will be applied, namely K-Means Clustering and factor analysis. Segmentation is done to determine the level of customers. The higher the CLV value, more valuable customer is to maintain. In the end, the customer segmentation method built by author can be used to optimize company's strategy to get maximum profit. This method can be applied to various cases and other companies.
The Impact of Domestic Investment, Foreign Investments, HDI, Export, and Import on the Economic Growth in Indonesia
Authors: Septiningrum Lutfia , Dewanti Paramita , Hikmawati Fauzah
Published: March 2022

The aims of this study were to examine the causal relationship between domestic investment, foreign, Export, Import, HDI and their impact on Indonesia's economic growth measure with GDP. The data used was panel data from 18 provinces in 2016-2020 which was taken based on stratified random sampling. The model used to complete the purpose of this research was panel data regression. The results of the analysis show economic growth based on the value of GDP in each province tends to decline. Modelling of economic growth in Indonesia was used Panel Data Regression. In this research, Hausman Test is used to obtain the best model of panel data regression because the model contain of Random Effect Model. Based on Simultaneous test results obtained at least one significant variable to the model and based on partial test the GDP was significantly influenced by the variables of FDI, DDI, HDI and Import sectoral value. Variable Export has an effect on GDP but is not significant where R2 shows the results of 98.9%
Multilevel Analysis: Household and Regional Factors Influence Agricultural Household Poverty in Indonesia, 2019
Authors: Romadhon Ariful , Sari Diyana Indah , Wicaksono Bayu Rhamadani
Published: March 2022

The agriculture sector is not only a source of food but also a support for the economic activities of most people in Indonesia, especially in rural areas. Unfortunately, most of their life are still below the Poverty Line/Garis Kemiskinan (GK). The uniqueness of this study is that this study uses household and regional variables to see their effect on agricultural household poverty. Thus, the policies will be taken are not only from the micro-economic of the household but also from the macro-economic perspective. Using multilevel binary logistic regression analysis, this study aims to examine the household and regional factors that affect the household poverty in agriculture sector in 2019 as the potential sector to alleviate poverty. Household and regional factors that affect agricultural household poverty are education, household size, resident area, ownership of pension social security, ownership of social assistance, credit assistance for businesses, and Gross Regional Domestic Product (GRDP) agricultural per capita. The variation of agriculture household poverty due to differences in characteristics between 514 districts in Indonesia is 35.19 percent.
Application of Resampling and Boosting Methods Using the C5.0 Algorithm
Authors: Kuswanto Hedi , Sunusi Nurtiti , Siswanto Siswanto , Nirwan Nirwan
Published: March 2022

Hypertension is a non-communicable disease that is characterized by an increase in systolic and diastolic blood pressure of more than 140 mmHg and or 90 mmHg. Hypertension needs to get more attention the condition is because hypertension will cause complications in the target organs and this disease does not appear to show significant symptoms at the beginning of the disease because it is called "silent disease". The study discusses the integration method of resampling and boosting in predicting hypertension status using the C5.0 algorithm. Classification of the C5.0 Algorithm by applying to resample increases performance specificity and AUC. Random oversampling (ROS) increased the specificity by 95.67% and AUC increased by 91.11%. Random over-under sampling (ROUS) increased specificity by 88.84% and AUC increased by 87.13%. In addition, applying boosting to the C5.0 algorithm that has been reapplied increases the accuracy performance. Random oversampling (ROS) increased accuracy by 93.86% and random over-under sampling (ROUS) increased accuracy by 89.98%. The response variables that contributed the most were high cholesterol and heart problems. The application of resampling and boosting to the contribution of high cholesterol and heart problems always topped the list.
Measuring Child Poverty in Jakarta Metropolitan Area Using a Multidimensional Perspective
Authors: Tantan Nigel Roy , Astuti Erni Tri
Published: March 2022

This study aims to quantitatively uncover multidimensional child poverty in Jakarta Metropolitan Area, where Indonesia’s capital and its surrounding regions are located. It comprises 15 indicators in six dimensions of child wellbeing: housing, education, facility, food and nutrition, child protection, and health. It is a very alarming condition in the region that nearly one-fourth of children are deprived in at least three dimensions. These children experience, on average, 0.57 of all possible deprivations, or 3.4 deprivations, which indicates a massive high deprivation intensity. The overall deprived children are also almost two times larger than the poor children that suggest the lower monetary child poverty rate doesn’t guarantee to lower the multidimensional child poverty.
Welfare Index of Person with Disabilities in Indonesia, 2018
Authors: Manikka Sari Ni Putu Ayu Chyntia , Siagian Tiodora Hadumaon
Published: March 2022

Most people with disabilities in Indonesia still live in vulnerable, backward, or poor conditions due to restrictions, obstacles, difficulties, and reduction or elimination of the rights of persons with disabilities. In realizing prosperity for all Indonesian people, it should be fair and not contain discriminatory elements, including persons with disabilities. For this reason, a measure of the achievement of the welfare of persons with disabilities is needed as evaluation support material in making plans and policies. This study aims to obtain the welfare factors of persons with disabilities and compile them into the Welfare Index of Persons with Disabilities (WIPD). The construction of the WIPD was carried out using the exploratory factor analysis method. Based on the results, 20 indicators formed five factors, namely accessibility, housing and access to information, physical and spiritual well-being, social relations and sanitation, and economic well-being. From the WIPD scores, it is known that there is a gap in WIPD achievement between the Western and the Eastern Region of Indonesia. For this reason, the government needs to prioritize inclusive development in provinces with very low and low WIPD achievements.
Construction of Smart City Development Index in Indonesia
Authors: Irfandha Nabil Miftah
Published: March 2022

Development in urban areas requires city management to solve problems that occur because of high population growth. The complexity of the issues in urban areas varies widely, including a decrease in the quality of public services, reduced availability of residential land, congestion on the highway, excessive energy consumption, waste accumulation, increased crime rates, and other social problems. City assessment tools can be used as support for decision-making in urban development as they provide assessment methodologies for cities to show progress towards defined targets. In the 21st century, there has been a shift from sustainability assessment to developing smart cities. The construction of the Smart City Development Index (SCDI) is considered capable of providing a basis for formulating effective and efficient solutions in reducing existing city problems. The purpose of this study is to find out the general description and get the factors that form SCDI; get the results of SCDI measurements; examine the uncertainty analysis and sensitivity analysis of SCDI, and see the relationship between SCDI and HDI (Human Development Index). Based on the results of factor analysis, there are six factors formed where the highest SCDI with a population of fewer than 200,000 people in Madiun City (East Java Province), the highest SCDI with a population between 200,000 to 1,000,000 people in Yogyakarta City (DI Yogyakarta Province) and the highest SCDI with a total population of over than 1,000,000 people in Tangerang City (Banten Province). The results of uncertainty analysis and sensitivity analysis show that the formed SCDI is robust and reliable. In general, SCDI has a positive relationship to Human Development Index (HDI). The construction of this index aims to facilitate local and central governments in reviewing policies regarding the distribution of funds so that the smart city's development is by existing conditions.
Detection of Public Sentiment Analysis Model on the Implementation of PPKM in Indonesia
Authors: Henessa Renata Putri , Fisabilillah Muhammad Al-Fath , Azizah Windy Rahmatul
Published: March 2022

Covid-19 pandemic which has been being serious problem in Indonesia indirectly force Indonesian government to issue policies in order to decrease the number of Covid-19 spread. One of the policies is the Implementation of Restrictions on Community Activities (PPKM) in Java-Bali region from January 11-25, 2021. Due to its continued implementation, this policy raises pros and cons in the community. This research’s goal is to determine the best classification model and determine the effect of adding feature engineering in analyzing public sentiment on PPKM with scrapping data from Twitter so that with the best model, it is possible to classify public responses to PPKM automatically. The twitter scrapping dataset is preprocessed first, which includes case folding, tokenizing, filtering, stemming, and term weighting to clean the data. After preprocessing and through the analysis steps, it concludes that using feature engineering can increase the accuracy of the best selected four models. The logistic regression method with feature engineering with accuracy rate of 87.50% become the best method. In conclusion, the best suggested model to analyze public sentiment using Twitter scrappimg towards PPKM is by using the logistic regression.
Analysis of Input-Output Table: Identifying Leading Sectors in Indonesia (Case Study in 2010, 2016 and 2020)
Authors: Nugroho Yoga Dwi
Published: March 2022

According to Neoclassical theory every country has to maximize their own resources include labor, natural resources also physical resources for developing their economy. Sector-based economic development must be carried out using comprehensive economic indicators, not only looking at the economic structure but also being able to identify and analyze inter-industry relationships. One of the right indicators is through the analysis of the Input-Output Table. The I-O table used is this research are I-O Table 2010, 2016, and 2020 estimated. In this comprehensive analysis, the Forward and Backward Linkage Indexes were calculated so that the sectors that are included in the Leading sector can be identified. In addition, a good multiplier analysis is carried out include output, income, labor, and value-added multiplier to see the amount of output, income, labor, and value-added changes caused by the changes of final demand. The results of the research show that sector that is included as a lever sector is the manufacturing sector (sector 3) and the procurement of electricity and gas (sector 4). Sector 3 is the most potential sector as leading sector due to some reasons this sector has a large output, added value and input structure, and has a high multiplier for four types of multipliers and analysis of Forward linkages and Backward Linkage Indexes shows this sector has high value. Manufacturing industry is a strong leading sector, from this the recommendation is the government can increase output of the manufacturing industry by give subsidy or decrease the tax or government can decrease the price of another sector that be the intermediate sector for manufacturing industry by giving subsidy.
The Best K-Exponential Moving Average with Missing Values: Gold Prices in Indonesia, Saudi Arabia, and Turkey during COVID-19
Authors: Mubarak Fadhlul , Aslanargun Atilla , Siklar Ilyas
Published: March 2022

There have been missing values in the gold price data for Indonesia, Saudi Arabia, and Turkey at the weekend so that imputation techniques have been carried out to solve this problem. The imputation method of replacing NAs with the latest non-NA values also known as last observation carried forward (LOCF) made it a solution to overcome the missing values. This study selected the best -exponential moving average based on the smallest mean absolute percentage error (MAPE) from simulations. The 2-exponential moving average analysis was the best analysis for the price of gold which has missing values in Indonesia, Saudi Arabia, and Turkey during COVID-19, while the largest MAPE values are different for each country.
Topic Modelling in Knowledge Management Documents BPS Statistics Indonesia
Authors: Hendrawan Muhammad Yunus , Projo Nucke Widowati Kusumo
Published: March 2022

Knowledge management is an important activity in improving the performance an organization. BPS Statistics Indonesia has recently implemented such a system to improve the quality and efficiency of business processes. The purposes of this research are: 1) implementing topic modelling on BPS Knowledge Management System to identify groups of document topics; 2) providing recommendations on which the best topic modelling; 3) building a web service function of topic modelling for BPS that includes data preprocessing function and topic group recommendation function. This study applies the Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) topic modelling methods to determine the best grouping techniques for knowledge management systems in BPS Statistics Indonesia. The results show that the LDA model using Mallet is the best model with 25 topic groups and a coherence score of 0.4803. The performance result suggest that the best modelling method is the LDA. The LDA model is then successfully implemented in RESTful web service to provide services in the preprocessing function and topic recommendations on documents entered into the Knowledge Management System BPS.
Micro and Macro Determinants of Precarious Employment in Indonesia: An Empirical Study of Paid Workers using Multilevel Binary Logistic Regression
Authors: Pontoh Mohammad Rifky , Projo Nucke Widowati Kusumo
Published: March 2022

Decent work for all is one of the goals stated in the Sustainable Development Goals (SDGs). One indicator that can represent proper work conditions is the precarious employment rate (PER). In recent periods, the precarious employment rate in Indonesia has shown an increasing trend. It indicates a decent work deficit in Indonesia. In addition, the PER among provinces has a different figure. This study aims to analyze the micro and macro factors that influence the status of precarious employees in Indonesia. The analytical method used in this study is multilevel binary logistic regression. The results show that micro factors; namely the worker's characteristics, including age, education level, employment sector, previous work status, and urban-rural area; have a significant effect on the precarious status of employees. In terms of macro factors, it is found that an increase in the output of the industrial and construction sectors can reduce the tendency of a worker to become a precarious employee. Meanwhile, an increase in labour supply increases the likelihood of workers becoming precarious employees. Various parties, including society and government, have to put extra efforts to reduce the precarious employment rate by improving the quality of human capital and domestic products demand.
R Package Development for Difference Benchmarking in Small Area Estimation Fay-Herriot Model
Authors: Perwira Zaza Yuda , Ubaidillah Azka
Published: March 2022

In recent decades, the use of small area estimation (SAE) for producing official statistics has been widely recognized by many National Statistics Offices including BPS-Statistics Indonesia. For official statistics usage, the aggregation of small area estimates is expected to be numerically consistent and more efficient than the aggregation of the unbiased direct estimates that cannot be guaranteed by Fay-Herriot model. Simulation experiments are performed to assess the behaviour of the difference benchmarking method Fay-Herriot model and to compare the mean squared error (MSE). The result shows that the difference benchmarking method can produce a consistent aggregation towards the direct estimation. Furthermore, an R package was built to implement the method that is easier to be used and is already available in the CRAN website. The package has been evaluated using validity (simulation), performance, case studies, and usability tests. These evaluations show that the package is suitable for use. Implementation of the methodology is also be applied to estimate average household consumption per capita expenditure in districts in D.I. Yogyakarta province, Indonesia 2019
Application of The Sequential Hot-deck Imputation Method for Identification of Indonesian Standard Classification of Business Fields (KBLI)
Authors: Fadillah Iman Jihad , Puspita Chaterina Dwi
Published: March 2022

The Covid-19 pandemic requires the adjustment of new habits in daily life, including in a series of data collection processes. One of the new adjustments is to use alternative types of data collection other than face-to-face, such as the telephone and the web. Information collected through telephone interviews is less accurate than the same information collected through face-to-face interviews, such as the level of non-response, consistency between entries, and outliers in the data or often identified as missing values. Missing value will be very influential on data quality when it appears on important variables. One of these variables is the Standard Classification of Business Fields (KBLI). Imputation is one method that can be used to deal with this problem. One method that is quite popular is Sequential Hot-deck Imputation. Therefore, this study aims to facilitate the identification of 5-digit KBLI by utilizing the Sequential Hot-deck Imputation method. The results of this study indicate that the use of the Sequential Hot-deck Imputation method in the KBLI identification process gives very high accuracy results. In addition, the use of this method is very efficient in the identification process, because the time required is very short, even in large datasets.
Study of Search Algorithm Optimization from Multi-Version Data Warehouse using NoSQL Non-relational Database
Authors: Maghfiroh Lutfi Rahmatuti , Yusuf Ramadhan Azizulhakim
Published: March 2022

Statistics Indonesia, which produces large-scale data, requires effective and optimal storage. Research related to Multi-Version Data Warehouse (MVDW), which utilizes document-based NoSQL itself, has attempted to be developed for the sake of BPS data storage and proposed an algorithm to store and search data. This paper is made to examine algorithm optimization methods to reduce the time used in the process of storing and searching data when needed. The algorithm proposed in this paper focuses on the data storage process by suggesting a storage model that generalizes the coding of variables in the data warehouse used so that later data searches can be carried out more easily and optimally. Other optimization methods are also carried out by applying query optimization methods to support and improve the optimization of the proposed algorithm. The results of the two optimization methods carried out can be said to be successful because the time used in the data search process by utilizing the algorithm after the application of the optimization method has been reduced when compared to the data search process using algorithms that have been developed by previous research.
Compliance of Patients with Alcohol Dependence and Aggressive Behavior in a State of Intoxication
Authors: Сайков А.Д. , Скугаревский О.А.
Published: March 2022

В статье анализируются результаты собственных исследований авторов связи типов комплаенса с агрессивным поведением пациентов с синдромом алкогольной зависимости в состоянии интоксикации. Для этого сравниваются группы пациентов с алкогольной зависимостью с объективно доказанными случаями агрессивного поведения разной степени выраженности на фоне алкогольной интоксикации и пациенты, не имеющие в анамнезе объективных данных об открыто проявляемом агрессивном поведении. Авторы приходят к выводу, что у пациентов, имевших многократную судимость, связанную с гетероагрессивным поведением в состоянии интоксикации алкоголем, были выявлены формы комплаенса, не имеющие места у неагрессивных пациентов и пациентов, имевших однократную судимость.

The article analyzes the results of the authors‘ own research on the relationship of compliance types with aggressive behavior of patients with alcohol dependence syndrome in a state of intoxication. To do this, we compare groups of patients with alcohol dependence with objectively proven cases of aggressive behavior of varying degrees of severity against the background of alcohol intoxication and patients who do not have a history of objective data on openly manifested aggressive behavior. The authors conclude that in patients who had multiple criminal records associated with heteroaggressive behavior in a state of alcohol intoxication, forms of compliance that do not occur in non- aggressive patients and patients who had a single criminal record were identified.
Review of road pavement heating methods
Authors: Pasztetnik Agata
Published: March 2022

Abstract: The main aspect of winter maintenance is removing winter slipperiness. The article presents an overview of pavement heating methods that are an alternative to standard methods of dealing with snow and ice. Hydraulic, electric, microwave and induction heating was analyzed. The research and implementation of individual methods were presented. Keywords: Heated pavements; Winter maintenance
Identity, Repression, and the Collapse of Apartheid
Authors: Anisin Alexei
Published: March 2022

Scholars emphasize that an influx of resources during the 1980s lowered the costs of collective action and nourished a mass nonviolent anti-apartheid movement that eventually brought down the incumbent regime. Utilising a discourse theoretic approach, this study demonstrates that the 1976 Soweto massacre along with its antecedent organisational campaign waged by the Black Consciousness movement (BCM) were pivotal, yet overlooked historical factors that contributed to the apartheid collapse. While the Soweto massacre led to the detainment of BCM leadership and the death of leader Steve Biko, the event of white police killing black unarmed students in June of 1976 backfired and revealed central antagonisms and contradictions underpinning the apartheid project. Only once political identities were dislocated did the possibility arise for a unified mass opposition movement to form. Alongside weighing economic costs under threat of state repression, this study demonstrates that historical waves of revolutionary mobilisation are also influenced by identity and meanings that get attribute to repressive events by publics.
Análisis de riesgo en aprovechamientos de recursos hídricos superficiales para riego de arroz
Authors: San Miguel Silvina , Alvez Carlos , Losco Federico , Zamanillo Eduardo
Published: March 2022

Se presenta una síntesis del desarrollo e implementación de los modelos de simulación SIMHUNER y ARHIUNER. SIMHUNER tiene como objetivos simular matemáticamente la respuesta hidrológica de cuencas de aporte y extender series de caudal a partir de series de precipitación y evaporación diarias. Se basa en un esquema conceptual que representa los almacenamientos en la cuenca mediante reservorios. Las transferencias de masa y la generación de los distintos escurrimientos están reguladas por funciones y algoritmos cuyos parámetros se determinan mediante el algoritmo de optimización bloqueada de Rosenbrock. ARHIUNER permite simular la operación de embalses en base a series de aporte observadas o sintéticas y posibilita relacionar la capacidad del embalse con la demanda y la probabilidad de falla en la atención de la demanda de riego. Los modelos se complementan para una planificación racional y sustentable del uso de recursos hídricos en áreas irrigadas. La aplicación de los modelos a la cuenca superior del Río Gualeguaychú permitió su validación y evidenció la importancia de la disponibilidad de registros de aporte extensos para una adecuada evaluación de los riesgos hídricos en áreas agrícolas irrigadas a partir de fuentes superficiales.
Uso del suelo y grado de cobertura vegetal en una cuenca del centro de la provincia de Buenos Aires
Authors: Ares María Guadalupe , Varni Marcelo , Entraigas Ilda , Marzoratti Martín
Published: March 2022

El uso del suelo y el grado de cobertura vegetal son parámetros importantes para estimar la potencialidad deescurrimiento superficial y erosión en una cuenca, y además para evaluar el desarrollo de cultivos,producción, etc. En este trabajo se evalúa la variación del uso del suelo y de la cobertura vegetal porcentual alo largo de un año (abril de 2005 hasta marzo de 2006) en una cuenca agrícola ganadera del centro de laprovincia de Buenos Aires, Argentina. Este ciclo anual, mientras no se produzcan modificaciones deestructura productiva de la zona, puede ser válido para muchos años más. Para lograr el objetivo buscado, serecurre a técnicas de procesamiento digital de imágenes satelitales y de sistemas de información geográfica.Así se determina el uso del suelo por medio de clasificación no supervisada de las imágenes. A cada usoluego se le asigna su cobertura porcentual estimada de manera conjunta según mediciones a campo y deacuerdo al estado fenológico, si se trata de cultivos. Se obtuvieron 12 categorías de uso a lo largo del año, alas que se agregan lagunas, afloramientos rocosos y montes. Los resultados muestran menores grados decobertura en invierno, y presentan un mínimo del 66 % en septiembre, para luego crecer hasta alcanzar unmáximo del 92 % en febrero y marzo, en el apogeo de los cultivos de soja y maíz.
Simulación agregada y distribuida de un área de llanura:
Authors: Cazenave Georgina , Vives Luis , Villanueva Adolfo
Published: March 2022

Se modeló matemáticamente el escurrimiento superficial de una cuenca mixta (nacientes en el borde oriental de las sierras de Azul y el resto de su superficie en la llanura pampeana) con distintos programas: uno agregado y otro distribuido. En este trabajo se presenta el estudio del funcionamiento hidrológico de la misma y la comparación de los resultados obtenidos para la simulación de eventos. En la modelación se empleó el programa agregado HEC-HMS del U.S. Army Corps of Engineers, y el modelo distribuido Sistema de Simulación SSHH-I de la Universidad Nacional de Rosario. Se empleó para este último un modelo digital del terreno (MDT) de detalle, construido mediante técnicas de interferometría a partir de imágenes radar. La comparación entre los modelos se hizo considerando dos aspectos: i) caudales y volúmenes a la salida de la cuenca, a la manera tradicional; y ii) tomando en cuenta la capacidad de representar la distribución espacial del agua en la superficie de la cuenca, que es un factor crítico de la inundaciones en áreas de llanura. El empleo de un MDT de detalle permitió representar mejor el movimiento superficial del agua y las áreas de almacenamiento en este tipo de relieve que es de morfología básicamente llana.
Comparación de índices de calidad de aguas aplicados en el arroyo del Azul, provincia de Buenos Aires
Authors: Rodríguez Lorena , Peluso Fabio , González Castelain José
Published: March 2022

p>La evaluación de la calidad del agua en los países desarrollados se ha convertido en una decisión crítica en los últimos años. Los índices de calidad de agua son herramientas de gestión aplicadas frecuentemente para ese fin. En el presente trabajo se comparan cuatro índices de calidad del agua aplicados con el fin de estudiar su comportamiento en base a información de 9 campañas de muestreo estacionales realizadas en el Arroyo del Azul, para su adopción como herramienta de gestión y el establecimiento de un sistema de monitoreo continuo de la calidad de sus aguas que contemple diversos usos. Los cuatro índices se muestran sensibles a cierta variación de la calidad del agua en diversos tramos del arroyo del Azul, presentando la misma tendencia general, siempre en un rango de calidad entre buena y media. Cobra importancia considerar, al elegir entre ellos, el número y la cantidad de variables incluidas como factor clave para que el mismo refleje las características del cuerpo de agua en estudio. El índice de la Nacional Science Foundation es un evaluador aceptable de la calidad del agua del arroyo del Azul debido a su sensibilidad y grado de exigencia a un costo operativo razonable.