International Journal of Quantitative Research and Modeling最新文献_第9页

Robust Optimization for Food Supply Chain Management Problems: A Critical Review and its Novelty 食品供应链管理问题的鲁棒优化:综述及其新颖性

International Journal of Quantitative Research and Modeling Pub Date : 2021-09-08 DOI: 10.46336/ijqrm.v2i3.155

Athaya Zahrani Irmansyah, S. Subiyanto

引用次数: 0

Principal Component Regression in Statistical Downscaling with Missing Value for Daily Rainfall Forecasting 日雨量预报统计降尺度的缺失值主成分回归

International Journal of Quantitative Research and Modeling Pub Date : 2021-09-08 DOI: 10.46336/ijqrm.v2i3.151

M. Saputra, A. F. Hadi, Abduh Riski, D. Anggraeni

{"title":"Principal Component Regression in Statistical Downscaling with Missing Value for Daily Rainfall Forecasting","authors":"M. Saputra, A. F. Hadi, Abduh Riski, D. Anggraeni","doi":"10.46336/ijqrm.v2i3.151","DOIUrl":"https://doi.org/10.46336/ijqrm.v2i3.151","url":null,"abstract":"Drought is a serious problem that often arises during the dry season. Hydrometeorologically, drought is caused by reduced rainfall in a certain period. Therefore, it is necessary to take the latest actions that can overcome this problem. This research aims to predict the potential for a drought to occur again in the Kupang City, Indonesia by developing a rainfall forecasting model. Incomplete daily local climate data for Kupang City is an obstacle in this analysis of rainfall forecasting. Data correction was then carried out through imputed missing values using the Kalman Filter method with Arima State-Space model. The Kalman Filter and Arima State-Space model (2,1,1) produces the best missing data imputation with a Root Mean Square Error (RMSE) of 0.930. The rainfall forecasting process is carried out using Statistical Downscaling with the Principal Component Regression (PCR) model that considers global atmospheric circulation from the Global Circular Model (GCM). The results showed that the PCR model obtained was quite good with a Mean Absolute Percent Error (MAPE) value of 2.81%. This model is used to predict the daily rainfall of Kupang City by utilizing GCM data.","PeriodicalId":14309,"journal":{"name":"International Journal of Quantitative Research and Modeling","volume":"113 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79410244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Production Technology for Adding GDL (Glucono Delta Lactone) to Soy-Based Foods 大豆基食品中添加葡萄糖- δ内酯的生产技术

International Journal of Quantitative Research and Modeling Pub Date : 2021-06-07 DOI: 10.46336/ijqrm.v2i2.150

Athila Safira Rahma

引用次数: 0

Bifurcation Analysis and Electronic Circuit for Sprott Jerk System 运动抽动系统的分岔分析及电子电路

International Journal of Quantitative Research and Modeling Pub Date : 2021-06-06 DOI: 10.46336/ijqrm.v2i2.145

R. A. Miptahudin

引用次数: 0

Procrustes Analysis of Indonesian Mortality Table Iv and Indonesia's Death Rate During Covid-19 Pandemic Covid-19大流行期间印度尼西亚死亡率表四和印度尼西亚死亡率的Procrustes分析

International Journal of Quantitative Research and Modeling Pub Date : 2021-06-06 DOI: 10.46336/ijqrm.v2i2.148

Fanny Novika, Revi Meliyani

{"title":"Procrustes Analysis of Indonesian Mortality Table Iv and Indonesia's Death Rate During Covid-19 Pandemic","authors":"Fanny Novika, Revi Meliyani","doi":"10.46336/ijqrm.v2i2.148","DOIUrl":"https://doi.org/10.46336/ijqrm.v2i2.148","url":null,"abstract":"The level of accuracy to calculate the premium is one of the main points for an actuary to determine the criteria of product which is offered by an insurance company to customers. The main reference in this accuracy is the mortality table. The last mortality table made by AAJI (Asosiasi Asuransi Jiwa Indonesia) was Mortality Table Indonesia (MTI) IV which was published in 2019. However, unexpectedly, the Covid-19 pandemic occurred in early 2020 which caused the death rate to be higher than normal situation. This study aims to compare MTI IV which was made with assumptions before the Covid-19 pandemic according to the death rate in Indonesia during the Covid-19 pandemic. This study uses secondary data, by finding the probability of death in Indonesia by calculating the death rate in Indonesia based on population data according to age group classifications obtained from BPS (Badan Pusat Statistik) Indonesia. Furthermore, both data were compared using Procrustes analysis to calculated the level of conformity. The results showed that 75.97% of the data matched MTI IV with the death rate during the pandemic. If the insurance company wants more accurate results, they can be adjusted to the Indonesian Mortality Table using data during the pandemic. If it is quite satisfied with the accuracy of 75.97%, the company can continue to use MTI IV.","PeriodicalId":14309,"journal":{"name":"International Journal of Quantitative Research and Modeling","volume":"34 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76194308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Application of Artificial Intelligence in Modern Ecology for Detecting Plant Pests and Animal Diseases 人工智能在现代生态学动植物病虫害检测中的应用

International Journal of Quantitative Research and Modeling Pub Date : 2021-06-06 DOI: 10.46336/ijqrm.v2i2.149

D. Sara, Mdd Maharani, Hafiza Farwa Amin, Y. S. Triana

{"title":"Application of Artificial Intelligence in Modern Ecology for Detecting Plant Pests and Animal Diseases","authors":"D. Sara, Mdd Maharani, Hafiza Farwa Amin, Y. S. Triana","doi":"10.46336/ijqrm.v2i2.149","DOIUrl":"https://doi.org/10.46336/ijqrm.v2i2.149","url":null,"abstract":"Climate change could lead to an increase in diseases in plants and animals. Plant pathogens have caused devastating production losses, such as in tropical countries. The development of algorithms that match the accuracy of plant and animal disease detection in predicting the toxicity of substances has continued through a massive database. Data and information from 10,000 substances from more than 800,000 animal tests have been carried out to generate the algorithms. Plant and animal disease detection using artificial intelligent in the modern ecological era is important and needed. Diseases in animals are still found in several Ruminant-Slaughterhouses. The purpose of the study is to identify the leverage attributes for using of Artificial Intelligent (AI) in detecting plant pests and animal diseases. The use of Multidimensional Scaling (MDS) produces a leverage attribute for the use of AI in detecting plant pests and animal diseases. The results showed that leverage attributes found were: Prediction of the presence of proteins structures produced by pathogens with a Root Mean Square (RMS) value of 4.5123; and Plant and Animal Disease Data will be opened with an RMS value of 4.2555. The findings of this study in the real world are to produce the development of smart agricultural applications in detecting plant pests and animal diseases as an early warning system. In addition, the application is also useful for eco-tourism managers who have a natural close relationship with plants and animals, so that ecological security in the modern ecological era, can be better maintained.","PeriodicalId":14309,"journal":{"name":"International Journal of Quantitative Research and Modeling","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79168655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Wireless Chaos-Based Communication System: Literature Review 基于无线混沌的通信系统:文献综述

International Journal of Quantitative Research and Modeling Pub Date : 2021-01-01 DOI: 10.46336/ijqrm.v2i1.128

S. H. Yuningsih, S. Supian, S. Sukono, S. Subiyanto

引用次数: 0

Application of the Leslie Matrix to Predict the Number and Growth Rate of Women in West Java 2021 应用莱斯利矩阵预测西爪哇女性数量和增长率2021

International Journal of Quantitative Research and Modeling Pub Date : 2021-01-01 DOI: 10.46336/ijqrm.v2i1.78

Atik Maryati, Sudrajat Supian, S. Subiyanto

{"title":"Application of the Leslie Matrix to Predict the Number and Growth Rate of Women in West Java 2021","authors":"Atik Maryati, Sudrajat Supian, S. Subiyanto","doi":"10.46336/ijqrm.v2i1.78","DOIUrl":"https://doi.org/10.46336/ijqrm.v2i1.78","url":null,"abstract":"Data from the Central Statistics Agency 2019 collected that the total population of women in Indonesia is less than male, which is 131.48 million people if compared to the total male population, which is 132.68 million population. This matter is directly relation to the total female population in West Java which is also less than the male population around 24031252.0 female and 24652609.0 male population(Badan Pusat Statistika, 2019).This should be the focus of the government to balance the population growth of women and men in West Java because of the role of women being central in the population growth of the people of West Java. The targets of the development plan contained in the RPJM 2005-2025 is to improve the quality of human resources, including the role of women in development. The growth of the female population is an important thing that must be observed, considering the role of women is determining the development of the human population in the future, because without the role of women the population will not be able to develop. This encourages researchers to predict the number and rate of female population growth in West Java in 2021. The Leslie matrix is a matrix used to predict the number and growth rate of a population. By applying the Leslie matrix to predict the number and growth rate of women in West Java in 2021, it can be concluded that the number of female populations in West Java is around tends to increase.","PeriodicalId":14309,"journal":{"name":"International Journal of Quantitative Research and Modeling","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80839197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Integrating Technologies in the New Normal: A Study of Blended Learning 新常态下的技术整合:混合式学习研究

International Journal of Quantitative Research and Modeling Pub Date : 2020-12-02 DOI: 10.46336/ijqrm.v1i4.90

Rahma Sakina, Eva Meidi Kulsum, A. S. Uyun

{"title":"Integrating Technologies in the New Normal: A Study of Blended Learning","authors":"Rahma Sakina, Eva Meidi Kulsum, A. S. Uyun","doi":"10.46336/ijqrm.v1i4.90","DOIUrl":"https://doi.org/10.46336/ijqrm.v1i4.90","url":null,"abstract":"The objective of this research is to describe how the teacher integrates technologies in blended learning and to analyze students’ perception and challenges in blended learning. The research was conducted in a private senior high school in Bandung and used a qualitative descriptive method. The data were collected through interview and questionnaire. The findings show that the teacher had already integrated technologies to run the process of teaching and learning in the new normal era as a replacement of a face to face learning due to Covid-19 pandemic. In the blended learning, the teacher integrated the variety of technologies in teaching-learning activities, namely zoom meeting and WhatsApp group chatting for the synchronous learning and she utilized google classroom, screencast o matic screen recorder, viva video editor, YouTube, and Quizizz the synchronous learning. The students perceived blended learning positively and determined that it is it is one of the effective ways of teaching. The biggest challenge overcome by the teacher is more time needed to learn and adapt to this new situation where they must employ technology in our educational culture. For the students, the stability of internet connection also becomes major obstacle in blended learning. Apart from that, blended learning can be an option applied in the learning process in the current pandemic era.","PeriodicalId":14309,"journal":{"name":"International Journal of Quantitative Research and Modeling","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74129001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

Probability distributions of COVID-19 tweet posted trends use a nonhomogeneous Poisson process COVID-19推文趋势的概率分布使用非均匀泊松过程

International Journal of Quantitative Research and Modeling Pub Date : 2020-12-02 DOI: 10.46336/ijqrm.v1i4.94

D. Munandar, S. Supian, S. Subiyanto

{"title":"Probability distributions of COVID-19 tweet posted trends use a nonhomogeneous Poisson process","authors":"D. Munandar, S. Supian, S. Subiyanto","doi":"10.46336/ijqrm.v1i4.94","DOIUrl":"https://doi.org/10.46336/ijqrm.v1i4.94","url":null,"abstract":"The influence of social media in disseminating information, especially during the COVID-19 pandemic, can be observed with time interval, so that the probability of number of tweets discussed by netizens on social media can be observed. The nonhomogeneous Poisson process (NHPP) is a Poisson process dependent on time parameters and the exponential distribution having unequal parameter values and, independently of each other. The probability of no occurrence an event in the initial state is one and the probability of an event in initial state is zero. Using of non-homogeneous Poisson in this paper aims to predict and count the number of tweet posts with the keyword coronavirus, COVID-19 with set time intervals every day. Posting of tweets from one time each day to the next do not affect each other and the number of tweets is not the same. The dataset used in this study is crawling of COVID-19 tweets three times a day with duration of 20 minutes each crawled for 13 days or 39 time intervals. The result of this study obtained predictions and calculated for the probability of the number of tweets for the tendency of netizens to post on the situation of the COVID-19 pandemic.","PeriodicalId":14309,"journal":{"name":"International Journal of Quantitative Research and Modeling","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75712406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1