{"title":"Logistic Regression Analysis with Bootstrap on Determining Factors Affecting Patient Satisfaction Level on Health Services","authors":"M. Ridho, D. Devianto, H. Yozza, F. Yanuar, I. Hg","doi":"10.1109/ICAITI.2018.8686744","DOIUrl":"https://doi.org/10.1109/ICAITI.2018.8686744","url":null,"abstract":"This study aims to determine the factors that affect patient satisfaction level to the service of a private hospital outpatient unit in Padang, Indonesia. In this case, the level of patient satisfaction is the response variable with an ordinal scale consisting of four categories, they are dissatisfied, quite satisfied, satisfied, or very satisfied. On the other hand, the predictor variables consist of 3 socio-demographic factor variables, namely gender, education level, and type of insurance that use, and also 5 service quality (SERVQUAL) variables. To determine the predictor variables that are considered affecting response variables, an ordinal logistic regression with a bootstrap estimate of standard error is performed. The result of this research shows two predictor variables that affect the response variable signs, namely responsiveness and assurance with hit ratio 78.520/0. Thus, it can be concluded that the model formed is feasible to determine patient satisfaction level of the hospital's services outpatient unit.","PeriodicalId":233598,"journal":{"name":"2018 International Conference on Applied Information Technology and Innovation (ICAITI)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114474995","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}
D. Devianto, Maiyastri, Uqwatul Alma Wisza, M. Wara, Putri Permathasari, Rika Okda Marlina Zen
{"title":"Time Series of Rainfall Model with Markov Switching Autoregressive","authors":"D. Devianto, Maiyastri, Uqwatul Alma Wisza, M. Wara, Putri Permathasari, Rika Okda Marlina Zen","doi":"10.1109/ICAITI.2018.8686745","DOIUrl":"https://doi.org/10.1109/ICAITI.2018.8686745","url":null,"abstract":"The intensity of rainfall can sometimes change due to seasonal changes, extreme weather changes or weather effects in other areas around a particular location. The changes of rainfall can be categorized as a change in structure or condition that often occur in time series data, it be influenced by an unobserved random variable, that is called as a state. Then structural change of rainfall can be modeled by using Markov Switching Autoregressive (MSAR) as the result from merging the Markov chain and the classic Autoregressive model in the data mining analysis. Therefore, this study will determine the best model for rainfall at the specific hilly location but close to the shore of the Indian Ocean, that is Limau Manis sub-district of Padang city, this is to obtain the probability of displacement and survival of a state, and the amount of suspected duration of each state. The rainfall data are defined in two states of rainfall condition, high rainfall and low rainfall. The best model MSAR is obtained as MS(2)-AR(2) with the probability of transition from state high rainfall to high rainfall has 0.84379, state high rainfall to state low rainfall has 0.15621, state low rainfall to state low rainfall has 0.37516 and state low rainfall to state high rainfall has 0.62485. While the expected duration of high rainfall is 6.40161 months and the expected duration of low rainfall is 1.60039 months. This result confirms that the high rainfall duration is longer than the low rainfall duration which is very specific intensity of rainfall at the selected location.","PeriodicalId":233598,"journal":{"name":"2018 International Conference on Applied Information Technology and Innovation (ICAITI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115765524","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}
{"title":"Solving Decent Home Distribution Problem Using ELECTRE Method with Triangular Fuzzy Number","authors":"I. Irvanizam, N. Nazaruddin, I. Syahrini","doi":"10.1109/ICAITI.2018.8686768","DOIUrl":"https://doi.org/10.1109/ICAITI.2018.8686768","url":null,"abstract":"A habitable housing program that aims to provide some decent homes has been widely implemented by the provincial government in Aceh. Due to the subjectivity of the decision maker's preferences for distributing the decent homes, some people and other social communities have highlighted the realization of the program as it is considered inaccurate. In order to overcome this problem, a multi-criteria decision making (MCDM) model using ELECTRE with fuzzy sets in terms of triangular fuzzy numbers (TFNs) was proposed. This model utilized the TFNs to express the fuzziness information on criteria weight and the collected data, and used the concept of Centre of Gravity (CoG) to perform ranking order for the fuzzy sets. Based on the concordance and discordance indices determined by the ELECTRE through a numerical example, the result in terms of ranking order for alternatives was obtained.","PeriodicalId":233598,"journal":{"name":"2018 International Conference on Applied Information Technology and Innovation (ICAITI)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132456321","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}