Pub Date : 2023-05-31DOI: 10.24843/mtk.2023.v12.i02.p407
Ulyatil Aeni, Wayan Sumarjaya, Gusti Ayu, Made Srinadi
Forecasting is a way to predict future events. One of the methods for forecasting is to use fuzzy time series Chen method. Fuzzy time series Chen is a development of fuzzy time series Song and Chissom method with more simplified arithmetic operations. In this study, the forecasting for the NTP especially in food crops sub-sector of Bali was done by using first-order and high-order fuzzy time series methods to predict next period. The results show that the most appropriate forecasting method is the second-order fuzzy time series Chen with the result for June 2022 are 90.95, July 2022 are 91.95, and August 2022 are 92.45 with MSE value of 0.4563 and MAPE value of 0.2824%
{"title":"PERAMALAN NILAI TUKAR PETANI SUBSEKTOR TANAMAN PANGAN PROVINSI BALI MENGGUNAKAN METODE FUZZY TIME SERIES CHEN","authors":"Ulyatil Aeni, Wayan Sumarjaya, Gusti Ayu, Made Srinadi","doi":"10.24843/mtk.2023.v12.i02.p407","DOIUrl":"https://doi.org/10.24843/mtk.2023.v12.i02.p407","url":null,"abstract":"Forecasting is a way to predict future events. One of the methods for forecasting is to use fuzzy time series Chen method. Fuzzy time series Chen is a development of fuzzy time series Song and Chissom method with more simplified arithmetic operations. In this study, the forecasting for the NTP especially in food crops sub-sector of Bali was done by using first-order and high-order fuzzy time series methods to predict next period. The results show that the most appropriate forecasting method is the second-order fuzzy time series Chen with the result for June 2022 are 90.95, July 2022 are 91.95, and August 2022 are 92.45 with MSE value of 0.4563 and MAPE value of 0.2824%","PeriodicalId":11600,"journal":{"name":"E-Jurnal Matematika","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48433973","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}
Pub Date : 2023-05-31DOI: 10.24843/mtk.2023.v12.i02.p408
Ida Bagus Angga Darmayuda, K. Dharmawan, Kartika Sari
Portfolio optimization using downside deviation is an optimal portfolio by defining the standard deviation of returns below the target (benchmark) as a level of risk measure. Every optimal portfolio certainly has risks. Therefore, it’s necessary to estimate the risk as an illustration of the worst investment condition. Expected shortfall is a measure of risk because it fulfills the coherent risk measures, and its estimated value exceeds VaR. This study aims to obtain optimal portfolio results using the downside deviation method and estimate portfolio risk using the expected shortfall model. The data used in this study are five stocks with the highest average trading volume that are incorporated into IDXHEALTH, namely SAME.JK, KLBF.JK, MIKA.JK, SIDO.JK, and IRRA.JK during the study period from 1 January 2020 to 23 September 2022. As a result obtained from this study, the combined weight of each stock in the optimal portfolio formed is, 2,8% in SAME.JK, 55,63% in KLBF.JK, 26,56% in MIKA.JK, 0,21% in SIDO.JK, and 14.8 % on IRRA.JK with a portfolio return of 0.0249%. The expected shortfall estimation value obtained accurately at a 99% confidence interval of 0.0399, whose value exceeds VaR (0.0343).
{"title":"ESTIMASI EXPECTED SHORTFALL DALAM OPTIMALISASI PORTOFOLIO DENGAN METODE DOWNSIDE DEVIATION PADA SAHAM IDXHEALTH","authors":"Ida Bagus Angga Darmayuda, K. Dharmawan, Kartika Sari","doi":"10.24843/mtk.2023.v12.i02.p408","DOIUrl":"https://doi.org/10.24843/mtk.2023.v12.i02.p408","url":null,"abstract":"Portfolio optimization using downside deviation is an optimal portfolio by defining the standard deviation of returns below the target (benchmark) as a level of risk measure. Every optimal portfolio certainly has risks. Therefore, it’s necessary to estimate the risk as an illustration of the worst investment condition. Expected shortfall is a measure of risk because it fulfills the coherent risk measures, and its estimated value exceeds VaR. This study aims to obtain optimal portfolio results using the downside deviation method and estimate portfolio risk using the expected shortfall model. The data used in this study are five stocks with the highest average trading volume that are incorporated into IDXHEALTH, namely SAME.JK, KLBF.JK, MIKA.JK, SIDO.JK, and IRRA.JK during the study period from 1 January 2020 to 23 September 2022. As a result obtained from this study, the combined weight of each stock in the optimal portfolio formed is, 2,8% in SAME.JK, 55,63% in KLBF.JK, 26,56% in MIKA.JK, 0,21% in SIDO.JK, and 14.8 % on IRRA.JK with a portfolio return of 0.0249%. The expected shortfall estimation value obtained accurately at a 99% confidence interval of 0.0399, whose value exceeds VaR (0.0343).","PeriodicalId":11600,"journal":{"name":"E-Jurnal Matematika","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49175719","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}
Pub Date : 2023-05-31DOI: 10.24843/mtk.2023.v12.i02.p415
Haflatul Intihaniah, I. N. Widana, Ketut Jayanegara
Last survivor insurance is life insurance for two or more participants with premiums paid up to the death of the last participant. This study discusses term last survivor insurance for two participants, namely husband and wife. Compensation money is paid after the second person dies. The purpose of this study is to determine the value of annual premiums and benefit reserves in last survivor term insurance with non-constant premiums using a retrospective calculation method. The conclusion obtained for the annual premium model is not constant, the 10-year term last survivor insurance with an annual premium change of 10% of the fixed premium( 𝛼) is that during the first 5 years, premiums with α negative are always greater than premiums with α positive . But the opposite is true for the next 5 years. then, the value of reserves in the same year with α negative is greater than α positive, reserves with α positive and α negative also have the same pattern, namely increasing in the first year to the 6th year then decreasing in the 7th year until the contract expires.
{"title":"PERHITUNGAN PREMI TAHUNAN TIDAK KONSTAN DAN CADANGAN BENEFIT ASURANSI LAST SURVIVOR BERJANGKA","authors":"Haflatul Intihaniah, I. N. Widana, Ketut Jayanegara","doi":"10.24843/mtk.2023.v12.i02.p415","DOIUrl":"https://doi.org/10.24843/mtk.2023.v12.i02.p415","url":null,"abstract":"Last survivor insurance is life insurance for two or more participants with premiums paid up to the death of the last participant. This study discusses term last survivor insurance for two participants, namely husband and wife. Compensation money is paid after the second person dies. The purpose of this study is to determine the value of annual premiums and benefit reserves in last survivor term insurance with non-constant premiums using a retrospective calculation method. The conclusion obtained for the annual premium model is not constant, the 10-year term last survivor insurance with an annual premium change of 10% of the fixed premium( 𝛼) is that during the first 5 years, premiums with α negative are always greater than premiums with α positive . But the opposite is true for the next 5 years. then, the value of reserves in the same year with α negative is greater than α positive, reserves with α positive and α negative also have the same pattern, namely increasing in the first year to the 6th year then decreasing in the 7th year until the contract expires.","PeriodicalId":11600,"journal":{"name":"E-Jurnal Matematika","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41988303","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}
Pub Date : 2023-05-31DOI: 10.24843/mtk.2023.v12.i02.p409
Gusti Ngurah, Sentana Putra, I. Putu, Winada Gautama
This research was conducted to determine the variables that have a significant impact on the stages of a well-off family in Sidemen Sub-district based on indicators obtained from the BKKBN and to classify the stages of a well-off family. This study used secondary data obtained from the stage of well-being data, Sidemen Sub-district, Karangasem Regency from BKKBN, totaling 1796 families. The method used is ordinal logistic regression and bagging ordinal logistic regression. Based on the logit regression model of ordinal logistic regression and ordinal logistic regression bagging, there are fourteen variables that have a significant effect on the dependent variable, namely marital status, type of insurance, age of head of household, occupation of head of household, having a source of income, eating a variety of food, having savings, accessing information from online media, families have ever recreated together, families have ever participated in social/community activities, the largest type of floor, main source of drinking water, ownership of a house/building, and children are still in school. The classification accuracy level in testing data using the ordinal logistic regression method was 79.4%, while the classification accuracy level using the bagging ordinal logistic regression method with 50,000 replications was 82.78%, so bagging showed an increase in classification by 3.38%..
{"title":"KLASIFIKASI TINGKAT KESEJAHTERAAN KELUARGA DI KECAMATAN SIDEMEN MENGGUNAKAN BOOTSTRAP AGGREGATING (BAGGING) REGRESI LOGISTIK ORDINAL","authors":"Gusti Ngurah, Sentana Putra, I. Putu, Winada Gautama","doi":"10.24843/mtk.2023.v12.i02.p409","DOIUrl":"https://doi.org/10.24843/mtk.2023.v12.i02.p409","url":null,"abstract":"This research was conducted to determine the variables that have a significant impact on the stages of a well-off family in Sidemen Sub-district based on indicators obtained from the BKKBN and to classify the stages of a well-off family. This study used secondary data obtained from the stage of well-being data, Sidemen Sub-district, Karangasem Regency from BKKBN, totaling 1796 families. The method used is ordinal logistic regression and bagging ordinal logistic regression. Based on the logit regression model of ordinal logistic regression and ordinal logistic regression bagging, there are fourteen variables that have a significant effect on the dependent variable, namely marital status, type of insurance, age of head of household, occupation of head of household, having a source of income, eating a variety of food, having savings, accessing information from online media, families have ever recreated together, families have ever participated in social/community activities, the largest type of floor, main source of drinking water, ownership of a house/building, and children are still in school. The classification accuracy level in testing data using the ordinal logistic regression method was 79.4%, while the classification accuracy level using the bagging ordinal logistic regression method with 50,000 replications was 82.78%, so bagging showed an increase in classification by 3.38%..","PeriodicalId":11600,"journal":{"name":"E-Jurnal Matematika","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44263955","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}
Pub Date : 2023-05-31DOI: 10.24843/mtk.2023.v12.i02.p411
Annisa Agustin Mahardika, Eka N. Kencana, Komang Gde Sukarsa, Ketut Jayanegara, Ign Lanang Wijayakusuma, Wayan Sumarjaya
Since the Covid-19 pandemic, Indonesian tourism has experienced a drastic decline. This decline can be seen in the number of foreign tourists visiting Indonesia. The number of foreign tourist arrivals in 2020 and 2021 is far less compared to 2019 before Covid-19 entered. As a result, the Indonesian economy also suffered. Regarding the recovery of Indonesian tourism after the pandemic has been slow down, this study aims to cluster foreign tourists visiting Indonesia based on the amount of their expenditures and length of stays using the K-means algorithm. Secondary data from National Statistics Bureau classified the origin of tourists were 86 countries. Applying k-means algorithm methods to cluster country of origin, result showed they were three clusters formed based on the attributes of visiting, i.e. length of stay in Indonesia and total amount of their expenditures. Each cluster consists of 14, 54 and 18 countries. The first cluster is characterized by countries that have high tourism spending; the second cluster is formed by countries with moderate tourism spending; and the third cluster is characterized by countries with low tourism spending. The accuracy of the three clusters in explaining the variance of tourist spending is 68.8 percent.
{"title":"KLASTERISASI KARAKTERISTIK WISATAWAN MANCANEGARA MENGGUNAKAN METODE K-MEANS CLUSTERING","authors":"Annisa Agustin Mahardika, Eka N. Kencana, Komang Gde Sukarsa, Ketut Jayanegara, Ign Lanang Wijayakusuma, Wayan Sumarjaya","doi":"10.24843/mtk.2023.v12.i02.p411","DOIUrl":"https://doi.org/10.24843/mtk.2023.v12.i02.p411","url":null,"abstract":"Since the Covid-19 pandemic, Indonesian tourism has experienced a drastic decline. This decline can be seen in the number of foreign tourists visiting Indonesia. The number of foreign tourist arrivals in 2020 and 2021 is far less compared to 2019 before Covid-19 entered. As a result, the Indonesian economy also suffered. Regarding the recovery of Indonesian tourism after the pandemic has been slow down, this study aims to cluster foreign tourists visiting Indonesia based on the amount of their expenditures and length of stays using the K-means algorithm. Secondary data from National Statistics Bureau classified the origin of tourists were 86 countries. Applying k-means algorithm methods to cluster country of origin, result showed they were three clusters formed based on the attributes of visiting, i.e. length of stay in Indonesia and total amount of their expenditures. Each cluster consists of 14, 54 and 18 countries. The first cluster is characterized by countries that have high tourism spending; the second cluster is formed by countries with moderate tourism spending; and the third cluster is characterized by countries with low tourism spending. The accuracy of the three clusters in explaining the variance of tourist spending is 68.8 percent.","PeriodicalId":11600,"journal":{"name":"E-Jurnal Matematika","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45898914","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}
Pub Date : 2023-01-31DOI: 10.24843/mtk.2023.v12.i01.p393
NI Luh Putu Suciptawati, Ni Made Yuni Sugiantari, M. Susilawati
{"title":"PENERAPAN METODE GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) PADA KASUS PENYAKIT COVID-19 DI PROVINSI BALI","authors":"NI Luh Putu Suciptawati, Ni Made Yuni Sugiantari, M. Susilawati","doi":"10.24843/mtk.2023.v12.i01.p393","DOIUrl":"https://doi.org/10.24843/mtk.2023.v12.i01.p393","url":null,"abstract":"","PeriodicalId":11600,"journal":{"name":"E-Jurnal Matematika","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44929738","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}
Pub Date : 2023-01-31DOI: 10.24843/mtk.2023.v12.i01.p395
Diana Diana, M. Susilawati, I. K. G. Sukarsa, I. P. E. N. Kencana
{"title":"PENGKLASIFIKASIAN STATUS GIZI BALITA MENGGUNAKAN ANALISIS DISKRIMINAN","authors":"Diana Diana, M. Susilawati, I. K. G. Sukarsa, I. P. E. N. Kencana","doi":"10.24843/mtk.2023.v12.i01.p395","DOIUrl":"https://doi.org/10.24843/mtk.2023.v12.i01.p395","url":null,"abstract":"","PeriodicalId":11600,"journal":{"name":"E-Jurnal Matematika","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46342067","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}
Pub Date : 2023-01-31DOI: 10.24843/mtk.2023.v12.i01.p402
Sundanis Agung Pertiwi, I. N. Widana, Kartika Sari
{"title":"ESTIMASI CADANGAN KLAIM PADA ASURANSI UMUM DENGAN METODE CHAIN LADDER","authors":"Sundanis Agung Pertiwi, I. N. Widana, Kartika Sari","doi":"10.24843/mtk.2023.v12.i01.p402","DOIUrl":"https://doi.org/10.24843/mtk.2023.v12.i01.p402","url":null,"abstract":"","PeriodicalId":11600,"journal":{"name":"E-Jurnal Matematika","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46663765","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}
Pub Date : 2023-01-31DOI: 10.24843/mtk.2023.v12.i01.p398
Farrel Willieardan, I. N. Widana, I. P. W. Gautama
Pension plan is an investment plan offered by employee company or life insurance companies to help create retirement funds. This research attempts to estimate the normal cost that participants must pay as well as the actuarial liability that must be paid by the insurance company to the participants using Projected Unit Credit method. Projected Unit Credit method uses the present value of the pension benefit and divided it by participant’s years of service. stochastic interest such as the Vasicek model and the CIR model will be used as a comparison. The result of this research is that the estimation of the normal cost and actuarial liability with the CIR model is smaller than the Vasicek model in the initial year, but the CIR model experience a greater increase than the Vasicek model which causes the normal cost and actuarial liability with the CIR model more expensive than the Vasicek model at the end of the contract. Both premiums and the actuarial liabilities increase as participants age.
{"title":"PENGGUNAAN METODE PROJECTED UNIT CREDIT PADA ASURANSI PENSIUN GABUNGAN MODEL VASICEK DAN CIR","authors":"Farrel Willieardan, I. N. Widana, I. P. W. Gautama","doi":"10.24843/mtk.2023.v12.i01.p398","DOIUrl":"https://doi.org/10.24843/mtk.2023.v12.i01.p398","url":null,"abstract":"Pension plan is an investment plan offered by employee company or life insurance companies to help create retirement funds. This research attempts to estimate the normal cost that participants must pay as well as the actuarial liability that must be paid by the insurance company to the participants using Projected Unit Credit method. Projected Unit Credit method uses the present value of the pension benefit and divided it by participant’s years of service. stochastic interest such as the Vasicek model and the CIR model will be used as a comparison. The result of this research is that the estimation of the normal cost and actuarial liability with the CIR model is smaller than the Vasicek model in the initial year, but the CIR model experience a greater increase than the Vasicek model which causes the normal cost and actuarial liability with the CIR model more expensive than the Vasicek model at the end of the contract. Both premiums and the actuarial liabilities increase as participants age. \u0000 ","PeriodicalId":11600,"journal":{"name":"E-Jurnal Matematika","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44253556","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}
Pub Date : 2023-01-31DOI: 10.24843/mtk.2023.v12.i01.p397
I. W. S. Yadnya, G. Gandhiadi, Kartika Sari
{"title":"MEDIASI KENYAMANAN BERWISATA PADA PENGARUH PENERAPAN PROGRAM CHSE TERHADAP KEPUASAN WISATAWAN","authors":"I. W. S. Yadnya, G. Gandhiadi, Kartika Sari","doi":"10.24843/mtk.2023.v12.i01.p397","DOIUrl":"https://doi.org/10.24843/mtk.2023.v12.i01.p397","url":null,"abstract":"","PeriodicalId":11600,"journal":{"name":"E-Jurnal Matematika","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43530706","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}
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