Pub Date : 2023-04-30DOI: 10.33394/j-ps.v11i2.7754
Theresia Grefyolin Simbolon, E. Frida, M. Sinambela, M. Situmorang, S. Humaidi, Yahya Darmawan
Climate change is a major threat to global prosperity. The industrial revolution has occurred since 1750 to 2010 where the increase in global air temperature has reached 0.7°C. Rising temperatures and fluctuating rainfall is the identification of climate change, one of the impacts of climate change is changing the distribution of some types of mosquitoes (Aedes Aegypti).Based on the results of the analysis of the main components, a good model uses an accuracy rate of about 85% and passes the test individually and as a whole. Indonesia has a tropical climate where warm temperatures and high rainfall variability are a comfortable habitat for Aedes Aegypti mosquitoes. The breeding and life cycle of the Aedes Aegypti mosquito is directly influenced by climatic conditions. The purpose of this study is to determine the normal rainfall map, an overview of climate projection patterns, identification of characteristics of climate change in the short term (2011 – 2040), medium term (2041 – 2070) and long term (2071-2100) based on rainfall and temperature projections in North Sumatra province. Statistical methods used to determine the effect of climate on health (dengue) include statistical downscaling, delta bias correction, Principal Component Analysis, and ordinal logistic regression. The results of the ordinal logistic regression analysis show that rainfall that is suitable for dengue fever ranges from 100 - 300 mm. For North Sumatra rainfall ranges from 50 - 600 mm. In March and November is the strongest threat because of the peak with high rainfall intensity where the danger of flooding and dengue. The air temperature ranges from 24.5 - 28.5 oC, this condition is still optimal for the development of the Aedes Aegypti mosquito. The climate change projection index for the short term (2011 - 2040), medium term (2041 - 2070) and long term (2071 - 2100) shows a consistent increase with a range of 0.40C, this value will affect the acceleration of the reproduction of the Aedes aegypti mosquito as the cause of DHF. The projection probability of dengue hemorrhagic fever shows that North Sumatra Province still has a high chance of being categorized as a high risk area for dengue fever with a probability value of 0.82 - 0.99.
{"title":"Projection of Climate Change on the Probability of Dengue Hemorrhagic Fever in North Sumatra Province","authors":"Theresia Grefyolin Simbolon, E. Frida, M. Sinambela, M. Situmorang, S. Humaidi, Yahya Darmawan","doi":"10.33394/j-ps.v11i2.7754","DOIUrl":"https://doi.org/10.33394/j-ps.v11i2.7754","url":null,"abstract":"Climate change is a major threat to global prosperity. The industrial revolution has occurred since 1750 to 2010 where the increase in global air temperature has reached 0.7°C. Rising temperatures and fluctuating rainfall is the identification of climate change, one of the impacts of climate change is changing the distribution of some types of mosquitoes (Aedes Aegypti).Based on the results of the analysis of the main components, a good model uses an accuracy rate of about 85% and passes the test individually and as a whole. Indonesia has a tropical climate where warm temperatures and high rainfall variability are a comfortable habitat for Aedes Aegypti mosquitoes. The breeding and life cycle of the Aedes Aegypti mosquito is directly influenced by climatic conditions. The purpose of this study is to determine the normal rainfall map, an overview of climate projection patterns, identification of characteristics of climate change in the short term (2011 – 2040), medium term (2041 – 2070) and long term (2071-2100) based on rainfall and temperature projections in North Sumatra province. Statistical methods used to determine the effect of climate on health (dengue) include statistical downscaling, delta bias correction, Principal Component Analysis, and ordinal logistic regression. The results of the ordinal logistic regression analysis show that rainfall that is suitable for dengue fever ranges from 100 - 300 mm. For North Sumatra rainfall ranges from 50 - 600 mm. In March and November is the strongest threat because of the peak with high rainfall intensity where the danger of flooding and dengue. The air temperature ranges from 24.5 - 28.5 oC, this condition is still optimal for the development of the Aedes Aegypti mosquito. The climate change projection index for the short term (2011 - 2040), medium term (2041 - 2070) and long term (2071 - 2100) shows a consistent increase with a range of 0.40C, this value will affect the acceleration of the reproduction of the Aedes aegypti mosquito as the cause of DHF. The projection probability of dengue hemorrhagic fever shows that North Sumatra Province still has a high chance of being categorized as a high risk area for dengue fever with a probability value of 0.82 - 0.99.","PeriodicalId":33562,"journal":{"name":"Prisma Sains Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47153921","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 : 2023-04-30DOI: 10.33394/j-ps.v11i2.7720
Yolanda Mutiara Tondang, M. Situmorang, Tulus Ikhsan, Yahya Darmawan
The weather radar is a remote sensing-based observation tool that identifies and records rainfall. Remote sensing is a technology that determines atmospheric conditions, measures rainfall, and performs other functions. However, the accuracy of weather radar products concerning rainfall estimation need to be evaluated. This research aims to investigate the accuracy of weather radar products for rainfall estimation in North Sumatra. We analyzed the raw weather radar data using RAINBOW software for data processing. We presented the accuracy evaluation between weather data and observation data using several statistical error parameters such as the Mean Absolute Error (MAE), Mean Error (ME), and Pearson Correlation (r). The results indicate that the CMAX radar product estimates rainfall better than the PPI and CAPPI products. The CMAX product has the lowest error value and higher correlation coefficient (r), indicating its superior rainfall estimation performance.
{"title":"Accuracy of Weather Radar Products for Rainfall Estimation in North Sumatra Region","authors":"Yolanda Mutiara Tondang, M. Situmorang, Tulus Ikhsan, Yahya Darmawan","doi":"10.33394/j-ps.v11i2.7720","DOIUrl":"https://doi.org/10.33394/j-ps.v11i2.7720","url":null,"abstract":"The weather radar is a remote sensing-based observation tool that identifies and records rainfall. Remote sensing is a technology that determines atmospheric conditions, measures rainfall, and performs other functions. However, the accuracy of weather radar products concerning rainfall estimation need to be evaluated. This research aims to investigate the accuracy of weather radar products for rainfall estimation in North Sumatra. We analyzed the raw weather radar data using RAINBOW software for data processing. We presented the accuracy evaluation between weather data and observation data using several statistical error parameters such as the Mean Absolute Error (MAE), Mean Error (ME), and Pearson Correlation (r). The results indicate that the CMAX radar product estimates rainfall better than the PPI and CAPPI products. The CMAX product has the lowest error value and higher correlation coefficient (r), indicating its superior rainfall estimation performance.","PeriodicalId":33562,"journal":{"name":"Prisma Sains Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44105266","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 : 2023-04-30DOI: 10.33394/j-ps.v11i2.7738
Deassy Eirene Diana Doloksaribu, Kerista Tarigan, R. M. Putra, Yahya Darmawan
Indonesia has diverse topographical conditions that result in Indonesia having a unique climate. One of the unique climate elements to be studied is rainfall, because rainfall has a different pattern in each region, this different rainfall pattern is caused by several climate phenomena factors that affect the rainfall pattern, including El-Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Madden Julian Oscillation (MJO). Medan City is the capital of North Sumatra province which is one of the areas in the flood-prone category in North Sumatra, where the factor of flooding is due to rainfall events in a long period of time, so the author wants to know which climatic phenomena factors can affect rainfall events in Medan city by using Machine Learning technology through the Matlab application, where in this study has a method by forming four combination models, namely the combination of the influence of IOD, SOI and MJO; second combination of IOD and SOI; third combination of SOI and MJO; and fourth combination of MJO and IOD, these four combinations will be the rainfall value of the four models. Furthermore, the rainfall value of the model is compared with the observed rainfall value and verification test using Mean Absolute Error (MAE) and correlation. Then the calculation of the comparison between the four rainfall models with the observed rainfall obtained the lowest MAE value during the SOI and MJO phenomenon of 15.0 mm and the highest correlation value during the IOD and SOI and SOI and MJO phenomena. So it is concluded that the combination of SOI and MJO has the best verification value. This shows that based on Machine Learning modeling, the model shown as the best predictor in Medan city is when the model combination consists of SOI and MJO.
{"title":"Identification of Rainfall events on Climate Phenomena in Medan based on Machine Learning","authors":"Deassy Eirene Diana Doloksaribu, Kerista Tarigan, R. M. Putra, Yahya Darmawan","doi":"10.33394/j-ps.v11i2.7738","DOIUrl":"https://doi.org/10.33394/j-ps.v11i2.7738","url":null,"abstract":"Indonesia has diverse topographical conditions that result in Indonesia having a unique climate. One of the unique climate elements to be studied is rainfall, because rainfall has a different pattern in each region, this different rainfall pattern is caused by several climate phenomena factors that affect the rainfall pattern, including El-Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Madden Julian Oscillation (MJO). Medan City is the capital of North Sumatra province which is one of the areas in the flood-prone category in North Sumatra, where the factor of flooding is due to rainfall events in a long period of time, so the author wants to know which climatic phenomena factors can affect rainfall events in Medan city by using Machine Learning technology through the Matlab application, where in this study has a method by forming four combination models, namely the combination of the influence of IOD, SOI and MJO; second combination of IOD and SOI; third combination of SOI and MJO; and fourth combination of MJO and IOD, these four combinations will be the rainfall value of the four models. Furthermore, the rainfall value of the model is compared with the observed rainfall value and verification test using Mean Absolute Error (MAE) and correlation. Then the calculation of the comparison between the four rainfall models with the observed rainfall obtained the lowest MAE value during the SOI and MJO phenomenon of 15.0 mm and the highest correlation value during the IOD and SOI and SOI and MJO phenomena. So it is concluded that the combination of SOI and MJO has the best verification value. This shows that based on Machine Learning modeling, the model shown as the best predictor in Medan city is when the model combination consists of SOI and MJO.","PeriodicalId":33562,"journal":{"name":"Prisma Sains Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41649056","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 : 2023-04-30DOI: 10.33394/j-ps.v11i2.7842
Waslina Rangkuti, Kerista Tarigan, S. Humaidi, M. Situmorang, E. Frida, Yahya Darmawan
Microbath Fluke Type 7102 is used for thermometer calibration. In the calibration process, Microbath uses liquid media as heat conductor. Liquid media in Microbath during the calibration process there is a value of uniformity and temperature stability. The value of temperature uniformity and stability is an influential component in determining the value of measurement uncertainty (U95). The smaller the U95 value, the better the calibration results. This is a factor in this study to analyse the uniformity and temperature stability of liquid types of Water, Methanol and Glycol. The uniformity test method is carried out using 5 (five) point measurements, where the reference point is in the middle. The stability test method uses the measurement of one reference point. Uniformity and stability values are connected to determine the uncertainty of measurement value using the GUM (Guide to the expression of Uncertainty in Measurement) method. The analysis showed that Methanol is more homogeneous than Glycol and Water, with values of 0.0855 ºC < 0.0942 ºC < 0.1030 ºC. Water is more stable than Methanol and Glycol, with values of 0.0021 ºC < 0.0027 ºC < 0.0028 ºC. The time to stabilise Methanol is better than Water and Glycol. Methanol can be stabilised with ± 35 - 40 minutes, Water needs ± 38 - 40 minutes and Glycol needs ± 48 - 50 minutes. The relationship between uniformity and temperature stability is that the smaller the uniformity and stability values, the smaller the U95 of a calibration result. The U95 value of Methanol 0.11 ºC, Glycol 0.12 ºC and Water is 0.13 ºC.
{"title":"The Effect of Different Liquid on Temperature Uniformity and Stability in Microbath 7102","authors":"Waslina Rangkuti, Kerista Tarigan, S. Humaidi, M. Situmorang, E. Frida, Yahya Darmawan","doi":"10.33394/j-ps.v11i2.7842","DOIUrl":"https://doi.org/10.33394/j-ps.v11i2.7842","url":null,"abstract":"Microbath Fluke Type 7102 is used for thermometer calibration. In the calibration process, Microbath uses liquid media as heat conductor. Liquid media in Microbath during the calibration process there is a value of uniformity and temperature stability. The value of temperature uniformity and stability is an influential component in determining the value of measurement uncertainty (U95). The smaller the U95 value, the better the calibration results. This is a factor in this study to analyse the uniformity and temperature stability of liquid types of Water, Methanol and Glycol. The uniformity test method is carried out using 5 (five) point measurements, where the reference point is in the middle. The stability test method uses the measurement of one reference point. Uniformity and stability values are connected to determine the uncertainty of measurement value using the GUM (Guide to the expression of Uncertainty in Measurement) method. The analysis showed that Methanol is more homogeneous than Glycol and Water, with values of 0.0855 ºC < 0.0942 ºC < 0.1030 ºC. Water is more stable than Methanol and Glycol, with values of 0.0021 ºC < 0.0027 ºC < 0.0028 ºC. The time to stabilise Methanol is better than Water and Glycol. Methanol can be stabilised with ± 35 - 40 minutes, Water needs ± 38 - 40 minutes and Glycol needs ± 48 - 50 minutes. The relationship between uniformity and temperature stability is that the smaller the uniformity and stability values, the smaller the U95 of a calibration result. The U95 value of Methanol 0.11 ºC, Glycol 0.12 ºC and Water is 0.13 ºC.","PeriodicalId":33562,"journal":{"name":"Prisma Sains Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43536736","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 : 2023-04-30DOI: 10.33394/j-ps.v11i2.7852
Endah Paramita, S. Humaidi, Yahya Darmawan
February is climatologically the first peak of the dry season in the North Sumatra region, but floods can still occur. This study analyzes the characteristics of rainfall patterns that occur during extreme rainfall that occurred in the Medan area on February 27, 2022 which resulted in flooding in several areas in Medan with Pearson correlation. The data used are rainfall data, satellite data, radar and other atmospheric dynamics analysis data. Based on dynamic analysis on February 27, 2022, the growth of CB clouds began at 14.00 WIB reaching its peak at 17.00 WIB where the peak temperature of the cloud reached 82.4 ° C and cloud growth lasted until 21.00 WIB, where the rain lasted long enough to cause hydrometeorological disasters (floods) to occur. The Pearson correlation coefficient method (r) used to analyze the relationship between rainfall and DMI, ENSO, SST Anomalies and SOI conditions can be seen that the dominant influence is SST Anomalies and SOI, where in February conditions that affect rainfall are ENSO with a correlation value of 0.36272 and SST Anomalies with a correlation value of 0.37548.
{"title":"Rainfall Characteristics In Medan City With Pearson Correlation Analysis (Case Study Of February 27, 2022)","authors":"Endah Paramita, S. Humaidi, Yahya Darmawan","doi":"10.33394/j-ps.v11i2.7852","DOIUrl":"https://doi.org/10.33394/j-ps.v11i2.7852","url":null,"abstract":"February is climatologically the first peak of the dry season in the North Sumatra region, but floods can still occur. This study analyzes the characteristics of rainfall patterns that occur during extreme rainfall that occurred in the Medan area on February 27, 2022 which resulted in flooding in several areas in Medan with Pearson correlation. The data used are rainfall data, satellite data, radar and other atmospheric dynamics analysis data. Based on dynamic analysis on February 27, 2022, the growth of CB clouds began at 14.00 WIB reaching its peak at 17.00 WIB where the peak temperature of the cloud reached 82.4 ° C and cloud growth lasted until 21.00 WIB, where the rain lasted long enough to cause hydrometeorological disasters (floods) to occur. The Pearson correlation coefficient method (r) used to analyze the relationship between rainfall and DMI, ENSO, SST Anomalies and SOI conditions can be seen that the dominant influence is SST Anomalies and SOI, where in February conditions that affect rainfall are ENSO with a correlation value of 0.36272 and SST Anomalies with a correlation value of 0.37548.","PeriodicalId":33562,"journal":{"name":"Prisma Sains Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47007859","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 : 2023-04-30DOI: 10.33394/j-ps.v11i2.7820
Romeo Kondouw, Kerista Tarigan, S. Humaidi, M. Situmorang, Mardiningsi Mardiningsi, Yahya Darmawan
Many factors trigger the uncertainty of rainfall measurement. Several factors can be related to the instruments, weather conditions, and acquisition methods. The degree of uncertainty could be obtained through the calibration process. In principle, rain gauges are calibrated based on the standard process ruled by ISO/IEC 17025 using the law of propagation of uncertainty (LPU). However, LPU requires complex and complicated mathematical calculations. An alternative approach is needed to evaluate measurement uncertainty besides the LPU method. This research used the Monte Carlo method to determine the uncertainty during the rainfall measurement. This method involves repeated random simulations by providing probability distribution on the input and output of rainfall measurement. The results showed that the Monte Carlo method can accurately determine the uncertainty of rainfall measurement. In addition, the uncertainty analysis also showed that instrument inaccuracy is the most significant factor that causes the uncertainty of rainfall measurement.
{"title":"Implementation of Monte Carlo Simulation in Evaluation of The Uncertainty of Rainfall Measurement","authors":"Romeo Kondouw, Kerista Tarigan, S. Humaidi, M. Situmorang, Mardiningsi Mardiningsi, Yahya Darmawan","doi":"10.33394/j-ps.v11i2.7820","DOIUrl":"https://doi.org/10.33394/j-ps.v11i2.7820","url":null,"abstract":"Many factors trigger the uncertainty of rainfall measurement. Several factors can be related to the instruments, weather conditions, and acquisition methods. The degree of uncertainty could be obtained through the calibration process. In principle, rain gauges are calibrated based on the standard process ruled by ISO/IEC 17025 using the law of propagation of uncertainty (LPU). However, LPU requires complex and complicated mathematical calculations. An alternative approach is needed to evaluate measurement uncertainty besides the LPU method. This research used the Monte Carlo method to determine the uncertainty during the rainfall measurement. This method involves repeated random simulations by providing probability distribution on the input and output of rainfall measurement. The results showed that the Monte Carlo method can accurately determine the uncertainty of rainfall measurement. In addition, the uncertainty analysis also showed that instrument inaccuracy is the most significant factor that causes the uncertainty of rainfall measurement.","PeriodicalId":33562,"journal":{"name":"Prisma Sains Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41492788","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 : 2023-04-30DOI: 10.33394/j-ps.v11i2.7774
Masherlina Masherlina, Kerista Tarigan, S. Humaidi
Indonesia is a country with a large area of oil palm plantations, so there are many factories for the production of cooking oil. Indonesian people use a lot of cooking oil because processed food in Indonesia is mostly fried which causes a lot of used cooking oil to be wasted. The purpose of this study was to determine the resistivity of used cooking oil on the quality of palm cooking oil which can be useful in the field of renewable energy and reduce environmental pollution due to excessive waste of palm cooking oil which can cause damage to aquatic ecosystems, pollute the soil, and cause health problems. Used cooking oil can be processed properly so it is not harmful to the environment and health. One of the steps in processing used cooking oil is to know its resistivity value as the beginning of the refining process. Used cooking oil has a resistivity value that contrasts with soil so it is easy to interpret. Thus it is expected to know the resistivity value of used palm cooking oil. The results of this test obtained the resistivity value of used cooking oil after frying five times, namely 13.320 Ohm meter.
{"title":"The Effect of Resistivity of Used Cooking Oil on The Quality of Palm Cooking Oil","authors":"Masherlina Masherlina, Kerista Tarigan, S. Humaidi","doi":"10.33394/j-ps.v11i2.7774","DOIUrl":"https://doi.org/10.33394/j-ps.v11i2.7774","url":null,"abstract":"Indonesia is a country with a large area of oil palm plantations, so there are many factories for the production of cooking oil. Indonesian people use a lot of cooking oil because processed food in Indonesia is mostly fried which causes a lot of used cooking oil to be wasted. The purpose of this study was to determine the resistivity of used cooking oil on the quality of palm cooking oil which can be useful in the field of renewable energy and reduce environmental pollution due to excessive waste of palm cooking oil which can cause damage to aquatic ecosystems, pollute the soil, and cause health problems. Used cooking oil can be processed properly so it is not harmful to the environment and health. One of the steps in processing used cooking oil is to know its resistivity value as the beginning of the refining process. Used cooking oil has a resistivity value that contrasts with soil so it is easy to interpret. Thus it is expected to know the resistivity value of used palm cooking oil. The results of this test obtained the resistivity value of used cooking oil after frying five times, namely 13.320 Ohm meter.","PeriodicalId":33562,"journal":{"name":"Prisma Sains Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45652215","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 : 2023-04-30DOI: 10.33394/j-ps.v11i2.7494
Vina Fauzia, U. Nisak, C. Cholifah
The accuracy of data diagnosis is important for clinical data management, reimbursement, and issues related to healthcare and services. Based on preliminary observations, it was found that the inaccuracy of the diagnosis code maker with the genitourinary disease standard at the Sidarjo District Hospital. The purpose of this study was to find out the comparison of coder clinical codes with genitourinary disease standards at the sidoarjo district hospital. The method used was quantitative with random sampling techniques presented in the form of frequency tables and cross tabulations and tested using the chi-square test. This study used medical records for inpatient genitourinary cases in 2022, with a total sample of 80 medical records. The results showed that completeness, timeliness, and accuracy had a significant influence on coding accuracy. Completness ( completeness of supporting information) obtained 58,8% complete medical record documents and 51.3% incomplete medical record documents (p=0.012). Accuracy (coding accuracy):52.5% of medical record documents were accurate and 47.5% of medical record documents were inaccurate (p=0,0001). This study suggests improving the quality of coding by conducting coding training and evaluating coding audits to support coding speed.
{"title":"Comparison of Clinical Codes with Standards of Genitourinary Disease in Public Hospital of Sidoarjo","authors":"Vina Fauzia, U. Nisak, C. Cholifah","doi":"10.33394/j-ps.v11i2.7494","DOIUrl":"https://doi.org/10.33394/j-ps.v11i2.7494","url":null,"abstract":"The accuracy of data diagnosis is important for clinical data management, reimbursement, and issues related to healthcare and services. Based on preliminary observations, it was found that the inaccuracy of the diagnosis code maker with the genitourinary disease standard at the Sidarjo District Hospital. The purpose of this study was to find out the comparison of coder clinical codes with genitourinary disease standards at the sidoarjo district hospital. The method used was quantitative with random sampling techniques presented in the form of frequency tables and cross tabulations and tested using the chi-square test. This study used medical records for inpatient genitourinary cases in 2022, with a total sample of 80 medical records. The results showed that completeness, timeliness, and accuracy had a significant influence on coding accuracy. Completness ( completeness of supporting information) obtained 58,8% complete medical record documents and 51.3% incomplete medical record documents (p=0.012). Accuracy (coding accuracy):52.5% of medical record documents were accurate and 47.5% of medical record documents were inaccurate (p=0,0001). This study suggests improving the quality of coding by conducting coding training and evaluating coding audits to support coding speed.","PeriodicalId":33562,"journal":{"name":"Prisma Sains Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45260931","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 : 2023-04-30DOI: 10.33394/j-ps.v11i2.7735
M. Sirait, S. Humaidi, M. Sinambela, M. Situmorang, E. Frida
Flood is a natural disaster that often occurs in Indonesia. Currently, flood events are relatively difficult to predict because floods generally occur suddenly in uncertain periods. Extreme rainfall is a major factor for the occurrence of floods. Considering that floods can be caused by heavy rainfall events within a few hours, it is necessary to produce daily flood forecasts for flood disaster mitigation. This study aims to test the accuracy of utilizing rainfall forecast data from the Weather Research and Forecasting (WRF) model to create daily flood forecast maps. The data used in this study include Global Forecast System (GFS) data, BMKG rainfall measurement data which spread across several points in North Sumatra Province, and flood incident reports from BNPB. Data processing is carried out by Geospatial Information System (GIS) using Quantum-GIS, which includes weighting and scoring the parameters of soil type, slope, land elevation, river density, and land cover to produce Flood Prone Maps, then integrated with rainfall data to produce Daily Flood Forecast Maps. The case studies of flood events in this study are August 28 and November 28, 2022. The results showed that the spatial forecast of flood potential (WRF) has a pattern in accordance with the flood event area. Therefore, the WRF model output rainfall prediction data can be used to create a daily flood forecast map in the North Sumatra region.
{"title":"Study of the Utilization of WRF Model Output Data to Produce Daily Flood Forecast Maps in the North Sumatra Region","authors":"M. Sirait, S. Humaidi, M. Sinambela, M. Situmorang, E. Frida","doi":"10.33394/j-ps.v11i2.7735","DOIUrl":"https://doi.org/10.33394/j-ps.v11i2.7735","url":null,"abstract":"Flood is a natural disaster that often occurs in Indonesia. Currently, flood events are relatively difficult to predict because floods generally occur suddenly in uncertain periods. Extreme rainfall is a major factor for the occurrence of floods. Considering that floods can be caused by heavy rainfall events within a few hours, it is necessary to produce daily flood forecasts for flood disaster mitigation. This study aims to test the accuracy of utilizing rainfall forecast data from the Weather Research and Forecasting (WRF) model to create daily flood forecast maps. The data used in this study include Global Forecast System (GFS) data, BMKG rainfall measurement data which spread across several points in North Sumatra Province, and flood incident reports from BNPB. Data processing is carried out by Geospatial Information System (GIS) using Quantum-GIS, which includes weighting and scoring the parameters of soil type, slope, land elevation, river density, and land cover to produce Flood Prone Maps, then integrated with rainfall data to produce Daily Flood Forecast Maps. The case studies of flood events in this study are August 28 and November 28, 2022. The results showed that the spatial forecast of flood potential (WRF) has a pattern in accordance with the flood event area. Therefore, the WRF model output rainfall prediction data can be used to create a daily flood forecast map in the North Sumatra region.","PeriodicalId":33562,"journal":{"name":"Prisma Sains Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45378232","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 : 2023-04-30DOI: 10.33394/j-ps.v11i2.7353
Wiwid Yuliastuti, S. Suharyoto, S. Suciati, Leny Indrawati, Aesthetica Islamy
The use of personal protective equipment masks is an important factor in protecting workers from potential hazards while working in marble processing. Many diseases are caused by exposure to dust, especially acute respiratory infections (ARI). The purpose of this study was to determine the relationship between the use of masks and the incidence of ARI in marble stone workers in Besole village, Besuki Tulungagung district. The design of this study is an analytic association using a cross-sectional design. The population is all marble stone workers in Besole village, Besuki Tulungagung district. The sample size is 44 respondents, the sampling technique uses purposive sampling. The independent variable of this study is the use of masks and the dependent variable is the incidence of ARI. Data collection using a questionnaire was given to marble workers in Besole Village, Besuki Tulungagung sub-district. Data analysis used the Spearman Rho statistical test with Confidence Interval (CI): of 95% or = 0.05. The results showed that most of the respondents, 28 respondents (64%), wore masks and half of the respondents, 22 respondents (50%), had mild ARI. The statistical test results showed p value = 0.015 < α = 0.05 which means H0 was rejected so it can be stated that there is a relationship between the use of masks and the incidence of ARI in marble stone workers. The conclusion from the results of this study is the use of masks when working properly and correctly as self-protection from dust so that marble workers do not experience pain, especially ARI.
{"title":"Relationship between Using Masks and Incidence of Acute Respiratory Infection in Marble Stone Workers","authors":"Wiwid Yuliastuti, S. Suharyoto, S. Suciati, Leny Indrawati, Aesthetica Islamy","doi":"10.33394/j-ps.v11i2.7353","DOIUrl":"https://doi.org/10.33394/j-ps.v11i2.7353","url":null,"abstract":"The use of personal protective equipment masks is an important factor in protecting workers from potential hazards while working in marble processing. Many diseases are caused by exposure to dust, especially acute respiratory infections (ARI). The purpose of this study was to determine the relationship between the use of masks and the incidence of ARI in marble stone workers in Besole village, Besuki Tulungagung district. The design of this study is an analytic association using a cross-sectional design. The population is all marble stone workers in Besole village, Besuki Tulungagung district. The sample size is 44 respondents, the sampling technique uses purposive sampling. The independent variable of this study is the use of masks and the dependent variable is the incidence of ARI. Data collection using a questionnaire was given to marble workers in Besole Village, Besuki Tulungagung sub-district. Data analysis used the Spearman Rho statistical test with Confidence Interval (CI): of 95% or = 0.05. The results showed that most of the respondents, 28 respondents (64%), wore masks and half of the respondents, 22 respondents (50%), had mild ARI. The statistical test results showed p value = 0.015 < α = 0.05 which means H0 was rejected so it can be stated that there is a relationship between the use of masks and the incidence of ARI in marble stone workers. The conclusion from the results of this study is the use of masks when working properly and correctly as self-protection from dust so that marble workers do not experience pain, especially ARI.","PeriodicalId":33562,"journal":{"name":"Prisma Sains Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41332694","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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