Riki Purnama Putra, Seni Susanti, Indy Ramadhanti, R. D. Agustina
Renewable energy is an energy that can be used to turn on all the energy that is still widely used in the world, including in Indonesia. Solar energy is a renewable energy that uses solar energy as the main ingredient in the formation of electrical energy. Solar energy is one of the most likely energies in a country that is on the equator like Indonesia. One of the interesting problems is how to determine the most effective area for the installation of solar power plants to make the power received by the power plant more effective. This study aims to analyze the effective area for installing solar panels using a Geographic Information System (GIS) as well as mapping of Centralized Solar Power (CSP) and centralized solar photovoltaic (SPV) in the East Priangan area, West Java. The method used in this study is based on the use of remote sensing of the average annual horizontal irradiation (GHI) and Normal Direct Irradiation (DNI). Solar irradiation data (GHI and DNI) were obtained from data from the surface meteorological program and solar energy by NASA, while Land Use/Land Cover, and Digital Elevation Models were used with the use of GIS. The results show that high areas in East Priangan get more effective CSP and SPV results than low areas, but low areas show an average effectiveness value in denuded areas. Keywords: solar energy, east Priangan, satellite imagery, environmental, GIS
{"title":"Potential of Solar Energy Mapping in East Priangan Using Satellite Imagery and Environmental Based on GIS","authors":"Riki Purnama Putra, Seni Susanti, Indy Ramadhanti, R. D. Agustina","doi":"10.18502/kls.v8i1.15592","DOIUrl":"https://doi.org/10.18502/kls.v8i1.15592","url":null,"abstract":"Renewable energy is an energy that can be used to turn on all the energy that is still widely used in the world, including in Indonesia. Solar energy is a renewable energy that uses solar energy as the main ingredient in the formation of electrical energy. Solar energy is one of the most likely energies in a country that is on the equator like Indonesia. One of the interesting problems is how to determine the most effective area for the installation of solar power plants to make the power received by the power plant more effective. This study aims to analyze the effective area for installing solar panels using a Geographic Information System (GIS) as well as mapping of Centralized Solar Power (CSP) and centralized solar photovoltaic (SPV) in the East Priangan area, West Java. The method used in this study is based on the use of remote sensing of the average annual horizontal irradiation (GHI) and Normal Direct Irradiation (DNI). Solar irradiation data (GHI and DNI) were obtained from data from the surface meteorological program and solar energy by NASA, while Land Use/Land Cover, and Digital Elevation Models were used with the use of GIS. The results show that high areas in East Priangan get more effective CSP and SPV results than low areas, but low areas show an average effectiveness value in denuded areas. \u0000Keywords: solar energy, east Priangan, satellite imagery, environmental, GIS","PeriodicalId":17898,"journal":{"name":"KnE Life Sciences","volume":"22 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140375464","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}
Kurriawan Budi Pranata, Hari Lugis Purwanto, M. Ghufron, Istiroyah, Muhammad Priyono Tri Sulistyanto, Anggri Sartika Wiguna, Sulthoni Akbar, Fauzan Azhiman
Identification of the operating voltage of a lead acid battery with 30% sulfuric acid electrolyte flow has been carried out. The battery consists of six cells with Pb and PbO as electrodes. The battery is equipped with a 1200 ml reservoir system to collect electrolyte and supply electrolyte to each cell. Each cell has electrolyte inlets and outlets at the top and bottom that circulate through each cell using a peristaltic pump. The battery prototype built was tested for five charge-discharge cycles with a constant current of 2 A for the charging process and 0.5 A for the discharging process using Turnigy Accucell. During the charge-discharge cycle test, monitoring and recording of voltage data is carried out using a Laptop PC. Data processing uses WebplotDigitizer and Microsoft Excel for data graphing. The results are analyzed and used to identify the operating voltage of the battery by taking the average voltage over five charge-discharge cycles. The average voltage is 13.98 V for the charging process and 12.11 V for the discharging process. Six-cell battery with full capacity works at a voltage range of 12.11-13.98 V. In the process of charging with a constant current of 2 A, the battery takes an average of 7.49 hours. So, the charging capacity can be estimated at 14,980 mAh. Whereas the battery discharge process takes an average of 11 hours with a constant current of 0.5 A to a voltage drop of 10.81 V. The resulting capacity of the discharged battery is 5500 mAh. Keywords: flowing electrolyte, lead acid battery, operating voltage
{"title":"Identification of Flowing Electrolyte Lead Acid Battery Operating Voltage","authors":"Kurriawan Budi Pranata, Hari Lugis Purwanto, M. Ghufron, Istiroyah, Muhammad Priyono Tri Sulistyanto, Anggri Sartika Wiguna, Sulthoni Akbar, Fauzan Azhiman","doi":"10.18502/kls.v8i1.15589","DOIUrl":"https://doi.org/10.18502/kls.v8i1.15589","url":null,"abstract":"Identification of the operating voltage of a lead acid battery with 30% sulfuric acid electrolyte flow has been carried out. The battery consists of six cells with Pb and PbO as electrodes. The battery is equipped with a 1200 ml reservoir system to collect electrolyte and supply electrolyte to each cell. Each cell has electrolyte inlets and outlets at the top and bottom that circulate through each cell using a peristaltic pump. The battery prototype built was tested for five charge-discharge cycles with a constant current of 2 A for the charging process and 0.5 A for the discharging process using Turnigy Accucell. During the charge-discharge cycle test, monitoring and recording of voltage data is carried out using a Laptop PC. Data processing uses WebplotDigitizer and Microsoft Excel for data graphing. The results are analyzed and used to identify the operating voltage of the battery by taking the average voltage over five charge-discharge cycles. The average voltage is 13.98 V for the charging process and 12.11 V for the discharging process. Six-cell battery with full capacity works at a voltage range of 12.11-13.98 V. In the process of charging with a constant current of 2 A, the battery takes an average of 7.49 hours. So, the charging capacity can be estimated at 14,980 mAh. Whereas the battery discharge process takes an average of 11 hours with a constant current of 0.5 A to a voltage drop of 10.81 V. The resulting capacity of the discharged battery is 5500 mAh. \u0000Keywords: flowing electrolyte, lead acid battery, operating voltage","PeriodicalId":17898,"journal":{"name":"KnE Life Sciences","volume":"16 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140375753","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}
Indy Ramadhanti, Riki Purnama Putra, Shidiq Andhika, Roprop Latiefatul Millah, R. D. Agustina, M. Listiawati
Education in the 21st century is an era where learning is unconventional. Interactive learning in the 21st century can be done by conducting virtual or real laboratory activities, even by combining the two in one activity at once. Various innovations in virtual laboratories have spread to optical materials, especially refraction by using a virtual spectrometer. Conceptually, the refractive index is a measure of the bending ray of a light beam as it passes from one medium to another. The refractive index is given by measurement between the refractive index of air, the angle of the prism, and the angle of minimum deviation. The angle of the prism and the angle of minimum deviation can be measured with a spectrometer. The spectrometer is a scientific instrument used to separate and measure the spectral components of physical phenomena and can separate white light and measure individual narrow color bands. Other than an on-hand spectrometer, other tools that we can use to measure the angle of minimum deviation are by using a virtual spectrometer provided by several virtual labs. The study aimed to compare the result of refractive index between on on-hand spectrometer and a virtual lab. Here we report our study on spectrometer whether the virtual lab experiment yields the same results as the real lab. We compare both results of experimental data using data and graph analytics. The results of the study show that the difference in the index of refraction measured between the virtual lab and the real lab is about 0.2%. This shows that there is no significant difference between virtual lab and real lab. Keywords: amrita virtual lab, real spectrometer, refractive index, blended laboratory
{"title":"Comparison Test Between Amrita Virtual Lab and Real Spectrometer on Refractive Index Using Blended Laboratory","authors":"Indy Ramadhanti, Riki Purnama Putra, Shidiq Andhika, Roprop Latiefatul Millah, R. D. Agustina, M. Listiawati","doi":"10.18502/kls.v8i1.15621","DOIUrl":"https://doi.org/10.18502/kls.v8i1.15621","url":null,"abstract":"Education in the 21st century is an era where learning is unconventional. Interactive learning in the 21st century can be done by conducting virtual or real laboratory activities, even by combining the two in one activity at once. Various innovations in virtual laboratories have spread to optical materials, especially refraction by using a virtual spectrometer. Conceptually, the refractive index is a measure of the bending ray of a light beam as it passes from one medium to another. The refractive index is given by measurement between the refractive index of air, the angle of the prism, and the angle of minimum deviation. The angle of the prism and the angle of minimum deviation can be measured with a spectrometer. The spectrometer is a scientific instrument used to separate and measure the spectral components of physical phenomena and can separate white light and measure individual narrow color bands. Other than an on-hand spectrometer, other tools that we can use to measure the angle of minimum deviation are by using a virtual spectrometer provided by several virtual labs. The study aimed to compare the result of refractive index between on on-hand spectrometer and a virtual lab. Here we report our study on spectrometer whether the virtual lab experiment yields the same results as the real lab. We compare both results of experimental data using data and graph analytics. The results of the study show that the difference in the index of refraction measured between the virtual lab and the real lab is about 0.2%. This shows that there is no significant difference between virtual lab and real lab. \u0000Keywords: amrita virtual lab, real spectrometer, refractive index, blended laboratory","PeriodicalId":17898,"journal":{"name":"KnE Life Sciences","volume":"34 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140377032","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}
Yosi Dinar Nugerahani, F. H. Muhammad, R. Wiratama, Imamal Muttaqien, R. D. Agustina
The imaging of shallow subsurface structures, weathered rock thickness and velocity propagation distribution of the rocks can be identified by seismic refraction. This method is one of the geophysical exploration methods utilizing refracted wave once it reaches the boundary of subsurface layer. In this research we used the generalized reciprocal method (GRM) as one of the robust processing methods in analyzing subsurface data. This method was chosen due to its accuracy in interpreting shallow subsurface layer with highly undulating refractors by determining time velocity analysis, XY optimum distances, and time depth analysis, then, the expected depth values can be achieved. The acquisition of data for this research was conducted using 13 geophones with forward and reverse sources, the data were then picked to get travel time values and inverted to obtain real geological setting of the earth. The results were interpreted as 2 layers, the first layer had a velocity distribution of 499.289 m/s which was identified as a weathered layer with a thickness of about 4.74 meters, whereas the second layer was interpreted as clay rock with velocity distribution of 1270.433 m/s with the thickness reached up to 16 meters. Keywords: generalized reciprocal method, 2D seismic refraction
{"title":"Application of Generalized Reciprocal Method on 2D Seismic Refraction Data in Mt. Manglayang, West Java","authors":"Yosi Dinar Nugerahani, F. H. Muhammad, R. Wiratama, Imamal Muttaqien, R. D. Agustina","doi":"10.18502/kls.v8i1.15619","DOIUrl":"https://doi.org/10.18502/kls.v8i1.15619","url":null,"abstract":"The imaging of shallow subsurface structures, weathered rock thickness and velocity propagation distribution of the rocks can be identified by seismic refraction. This method is one of the geophysical exploration methods utilizing refracted wave once it reaches the boundary of subsurface layer. In this research we used the generalized reciprocal method (GRM) as one of the robust processing methods in analyzing subsurface data. This method was chosen due to its accuracy in interpreting shallow subsurface layer with highly undulating refractors by determining time velocity analysis, XY optimum distances, and time depth analysis, then, the expected depth values can be achieved. The acquisition of data for this research was conducted using 13 geophones with forward and reverse sources, the data were then picked to get travel time values and inverted to obtain real geological setting of the earth. The results were interpreted as 2 layers, the first layer had a velocity distribution of 499.289 m/s which was identified as a weathered layer with a thickness of about 4.74 meters, whereas the second layer was interpreted as clay rock with velocity distribution of 1270.433 m/s with the thickness reached up to 16 meters. \u0000Keywords: generalized reciprocal method, 2D seismic refraction","PeriodicalId":17898,"journal":{"name":"KnE Life Sciences","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140373743","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}
W. Sulandari, Y. Yudhanto, Sri Subanti, E. Zukhronah, Muhammad Zidni Subarkah
Theoretically, forecast error increases as the forecast horizon increases. This study aims to assess whether the statement is generally accepted or not. This study applies time series cross-validation to evaluate forecasting results up to seven steps ahead. As an illustration, we use Malaysia’s hourly electricity load data. Each hour is considered a series of each, so there are 24 daily series. Time series cross-validation with a 334 window was applied to 24 data series, and then each daily series was modeled with the Autoregressive Integrated Moving Average (ARIMA), Neural Network Autoregressive (NNAR), ExponenTial Smoothing (ETS), Singular Spectrum Analysis (SSA), and General Regression Neural Network (GRNN) models. In terms of mean absolute percentage error (MAPE) from one to seven steps ahead, we then evaluate the performance of all models. The experimental results show that the MAPEs obtained from the GRNN model tend to increase along with the theory. However, MAPEs obtained from ETS increase by up to three steps ahead and decrease after that. Among the five models, ARIMA, NNAR, and SSA produce a reasonably stable MAPE value for one to seven steps ahead. However, SSA has the most stable error value compared to ARIMA and NNAR. Keywords: time series, cross-validation, evaluate, forecasting model performance
{"title":"Implementing Time Series Cross Validation to Evaluate the Forecasting Model Performance","authors":"W. Sulandari, Y. Yudhanto, Sri Subanti, E. Zukhronah, Muhammad Zidni Subarkah","doi":"10.18502/kls.v8i1.15584","DOIUrl":"https://doi.org/10.18502/kls.v8i1.15584","url":null,"abstract":"Theoretically, forecast error increases as the forecast horizon increases. This study aims to assess whether the statement is generally accepted or not. This study applies time series cross-validation to evaluate forecasting results up to seven steps ahead. As an illustration, we use Malaysia’s hourly electricity load data. Each hour is considered a series of each, so there are 24 daily series. Time series cross-validation with a 334 window was applied to 24 data series, and then each daily series was modeled with the Autoregressive Integrated Moving Average (ARIMA), Neural Network Autoregressive (NNAR), ExponenTial Smoothing (ETS), Singular Spectrum Analysis (SSA), and General Regression Neural Network (GRNN) models. In terms of mean absolute percentage error (MAPE) from one to seven steps ahead, we then evaluate the performance of all models. The experimental results show that the MAPEs obtained from the GRNN model tend to increase along with the theory. However, MAPEs obtained from ETS increase by up to three steps ahead and decrease after that. Among the five models, ARIMA, NNAR, and SSA produce a reasonably stable MAPE value for one to seven steps ahead. However, SSA has the most stable error value compared to ARIMA and NNAR. \u0000Keywords: time series, cross-validation, evaluate, forecasting model performance","PeriodicalId":17898,"journal":{"name":"KnE Life Sciences","volume":"40 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140373870","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}
Export is one of the factors that increase the economic growth of a country. One measure of export activity that can describe economic growth in Indonesia is The Export Unit Value Index, which is an index that measures changes in the price of export commodities sold by residents of one country to residents of other countries. The purpose of this study is to predict the unit value index of exports in Indonesia using a single input transfer function model and to see the influence of the value of oil and gas and non-oil and gas exports on the unit value index of exports in Indonesia. The single input transfer function model is a model that describes the future forecast of a series (output series) obtained based on the past values of the output series and other time series (input series) that affect the output series. The results of this study obtained a transfer function model with the order (0,0,1) with a noise series following ARIMA (1,0,1). Based on this model, the export unit value index at time t is influenced by the unit value export index in the previous month and is influenced by the oil and gas and non-oil and gas export value in the same month. As indicated by its MAPE value of 4.89%, the forecast value does not diverge much from the actual value, which suggests that the transfer function model can be used to predict the export unit value index in Indonesia. Keywords: forecasting, export unit value index, single input, transfer function
出口是促进国家经济增长的因素之一。出口单位价值指数（The Export Unit Value Index）是衡量一国居民向其他国家居民出售出口商品的价格变化的指数，它是衡量出口活动的一个指标，可以说明印尼的经济增长情况。本研究的目的是利用单一输入转移函数模型预测印尼的出口单位价值指数，并了解石油天然气和非石油天然气出口价值对印尼出口单位价值指数的影响。单一输入转移函数模型是根据输出序列和影响输出序列的其他时间序列（输入序列）的过去值，对某一序列（输出序列）的未来预测进行描述的模型。本研究的结果得到了一个阶数为（0,0,1）的转移函数模型，其噪声序列遵循 ARIMA（1,0,1）。根据该模型，t 时刻的出口单位价值指数受上月出口单位价值指数的影响，并受当月石油天然气和非石油天然气出口价值的影响。从 4.89% 的 MAPE 值来看，预测值与实际值的偏差不大，这表明转移函数模型可用于预测印度尼西亚的出口单位价值指数。关键词：预测；出口单位价值指数；单一输入；传递函数
{"title":"Forecasting the Export Unit Value Index in Indonesia Using the Single Input Transfer Function","authors":"Ika Fitria Millenia, E. Zukhronah, W. Sulandari","doi":"10.18502/kls.v8i1.15581","DOIUrl":"https://doi.org/10.18502/kls.v8i1.15581","url":null,"abstract":"Export is one of the factors that increase the economic growth of a country. One measure of export activity that can describe economic growth in Indonesia is The Export Unit Value Index, which is an index that measures changes in the price of export commodities sold by residents of one country to residents of other countries. The purpose of this study is to predict the unit value index of exports in Indonesia using a single input transfer function model and to see the influence of the value of oil and gas and non-oil and gas exports on the unit value index of exports in Indonesia. The single input transfer function model is a model that describes the future forecast of a series (output series) obtained based on the past values of the output series and other time series (input series) that affect the output series. The results of this study obtained a transfer function model with the order (0,0,1) with a noise series following ARIMA (1,0,1). Based on this model, the export unit value index at time t is influenced by the unit value export index in the previous month and is influenced by the oil and gas and non-oil and gas export value in the same month. As indicated by its MAPE value of 4.89%, the forecast value does not diverge much from the actual value, which suggests that the transfer function model can be used to predict the export unit value index in Indonesia. \u0000Keywords: forecasting, export unit value index, single input, transfer function","PeriodicalId":17898,"journal":{"name":"KnE Life Sciences","volume":"16 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140374683","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}
I. Utami, Dadi Rusdiana, Nahadi, Irma Rahma Suwarma
The study aims to develop and test the characteristics of briquettes made from durian skin with a mixture of various compositions conducted that obtained briquettes from ingredients such as 100% durian peel, 100% husk rice, 100% shell coconut, 50% durian peel and 50 % shell coconut, 70% durian peel and 30% shell coconut, 50% durian peel and 50% husk, 70% durian peel and 30% husk, and 30% durian peel and 70% husk. Have been tested for variable endurance after dropping from a height of 180 cm as influenced by variation mixture that results in the test obtained the missing mass by consecutive 0.1 gr, 10 gr, 15.8 gr, 3.6 gr, 0.3 gr, 0.4 gr, 0.4 gr, 0.4 gr, 0.3 gr, and 0.4 gr. Test time burning by consecutive are 174 minutes, 120 minutes, 502 minutes, 410 minutes, 376 minutes, 406 minutes, 380 minutes, 367 minutes, and 280 minutes. The resulting calorific value consecutive are 105.8 kcal /kg, 124.9 kcal /kg, 135.3 kcal /kg, 38.2 kcal /kg, 121.5 kcal /kg, 59 kcal /kg, 95 kcal /kg, 128.4 kcal /kg, and 128.4 kcal /kg. Keywords: briquettes, durian peel, husk rice, shell coconut
{"title":"Making Briquettes Variation Ingredient Durian Peel, Husk Rice, and Shell Coconut -- Impact on Strength, Burnability, Temperature, and Calorific Value","authors":"I. Utami, Dadi Rusdiana, Nahadi, Irma Rahma Suwarma","doi":"10.18502/kls.v8i1.15594","DOIUrl":"https://doi.org/10.18502/kls.v8i1.15594","url":null,"abstract":"The study aims to develop and test the characteristics of briquettes made from durian skin with a mixture of various compositions conducted that obtained briquettes from ingredients such as 100% durian peel, 100% husk rice, 100% shell coconut, 50% durian peel and 50 % shell coconut, 70% durian peel and 30% shell coconut, 50% durian peel and 50% husk, 70% durian peel and 30% husk, and 30% durian peel and 70% husk. Have been tested for variable endurance after dropping from a height of 180 cm as influenced by variation mixture that results in the test obtained the missing mass by consecutive 0.1 gr, 10 gr, 15.8 gr, 3.6 gr, 0.3 gr, 0.4 gr, 0.4 gr, 0.4 gr, 0.3 gr, and 0.4 gr. Test time burning by consecutive are 174 minutes, 120 minutes, 502 minutes, 410 minutes, 376 minutes, 406 minutes, 380 minutes, 367 minutes, and 280 minutes. The resulting calorific value consecutive are 105.8 kcal /kg, 124.9 kcal /kg, 135.3 kcal /kg, 38.2 kcal /kg, 121.5 kcal /kg, 59 kcal /kg, 95 kcal /kg, 128.4 kcal /kg, and 128.4 kcal /kg. \u0000Keywords: briquettes, durian peel, husk rice, shell coconut","PeriodicalId":17898,"journal":{"name":"KnE Life Sciences","volume":"38 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140375249","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}
Dalia Sukmawati, Alza Kirana Thaharah, Esti Komariah, Herawati Herawati, Vicky Theodora, A. Supiyani, Shabrina Nida Al Husna, N. Ratnaningtyas, H. E. El Enshasy, D. Dailin
Dark Septate Endophytes (DSE) are a group of ascomycetes that live in intracellular and extracellular root tissue to facilitate plant growth and stress tolerance in extreme environments. However, little is known about the DSE fungi isolated from certain plant roots such as Pteris vittata, especially under drought condition. Pteris vittata is known for its ability to live in various types of substrates and ecosystems. In this study, we obtained DSE fungi from the fern roots Pteris vittata collected from the area of Universitas Negeri Jakarta. DSE isolation was carried out by inoculating the Pteris vittata fern roots with a size of 0.5 cm on the surface of sterilized PDA media for 5-7 days at 27∘C. Observations were made every 24 hours using a stereo microscope to see the first hyphae appeared from the plant roots. The results exhibited 13 samples of roots with hyphae colonization and were suspected to be DSE fungi. Of the 13 root isolates, only 3 isolate (PP2, PP4A, and PPB) showed the DSE growth (23%) with melanin pigment. The morphological characteristics of endophytic DSE fungi collected from Pteris vittata roots represented septate hyphae, brownish to black colony color, a growing zone, and a velvety texture. For the isolate PP2, it showed sclerotia while for the isolate PP4, it exhibited light brown colonies. Keywords: isolation, DSE, ferns, pteris vittata, roots
{"title":"Isolation of Dark Septate Endophyte (DSE) from Ferns (Pteris Vittata) Roots","authors":"Dalia Sukmawati, Alza Kirana Thaharah, Esti Komariah, Herawati Herawati, Vicky Theodora, A. Supiyani, Shabrina Nida Al Husna, N. Ratnaningtyas, H. E. El Enshasy, D. Dailin","doi":"10.18502/kls.v8i1.15403","DOIUrl":"https://doi.org/10.18502/kls.v8i1.15403","url":null,"abstract":"Dark Septate Endophytes (DSE) are a group of ascomycetes that live in intracellular and extracellular root tissue to facilitate plant growth and stress tolerance in extreme environments. However, little is known about the DSE fungi isolated from certain plant roots such as Pteris vittata, especially under drought condition. Pteris vittata is known for its ability to live in various types of substrates and ecosystems. In this study, we obtained DSE fungi from the fern roots Pteris vittata collected from the area of Universitas Negeri Jakarta. DSE isolation was carried out by inoculating the Pteris vittata fern roots with a size of 0.5 cm on the surface of sterilized PDA media for 5-7 days at 27∘C. Observations were made every 24 hours using a stereo microscope to see the first hyphae appeared from the plant roots. The results exhibited 13 samples of roots with hyphae colonization and were suspected to be DSE fungi. Of the 13 root isolates, only 3 isolate (PP2, PP4A, and PPB) showed the DSE growth (23%) with melanin pigment. The morphological characteristics of endophytic DSE fungi collected from Pteris vittata roots represented septate hyphae, brownish to black colony color, a growing zone, and a velvety texture. For the isolate PP2, it showed sclerotia while for the isolate PP4, it exhibited light brown colonies. \u0000Keywords: isolation, DSE, ferns, pteris vittata, roots","PeriodicalId":17898,"journal":{"name":"KnE Life Sciences","volume":"14 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140375614","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}
This study aims to introduce a bivariate Log-Normal regression model and to develop a technique for parameter estimation and hypothesis testing. We term the model Bivariate Log-Normal Regression (BLNR). The estimation procedure is conducted by the standard Maximum Likelihood Estimation (MLE) employing the Newton-Raphson method. To perform hypothesis testing, we adapt the Maximum Likelihood Ratio Test (MLRT) for simultaneous testing with test statistics which, for large n, follows Chi-Square distribution with degrees of freedom p. In addition, the partial testing is derived from a central limit theorem which results in a Z-test statistic. Keywords: parameter estimation, hypothesis testing, bivariate log, normal regression
本研究旨在介绍一种双变量对数正态回归模型，并开发一种参数估计和假设检验技术。我们将该模型称为双变量对数正态回归模型（BLNR）。估计过程采用标准的最大似然估计法（MLE）和牛顿-拉斐逊法（Newton-Raphson method）。为了进行假设检验，我们采用最大似然比检验（MLRT）进行同步检验，检验统计量在大 n 时遵循自由度为 p 的 Chi-Square 分布。关键词：参数估计、假设检验、二元对数、正态回归
{"title":"Parameter Estimation and Hypothesis Testing on Bivariate Log-Normal Regression Models","authors":"Kadek Budinirmala, Purhadi, Achmad Choiruddin","doi":"10.18502/kls.v8i1.15546","DOIUrl":"https://doi.org/10.18502/kls.v8i1.15546","url":null,"abstract":"This study aims to introduce a bivariate Log-Normal regression model and to develop a technique for parameter estimation and hypothesis testing. We term the model Bivariate Log-Normal Regression (BLNR). The estimation procedure is conducted by the standard Maximum Likelihood Estimation (MLE) employing the Newton-Raphson method. To perform hypothesis testing, we adapt the Maximum Likelihood Ratio Test (MLRT) for simultaneous testing with test statistics which, for large n, follows Chi-Square distribution with degrees of freedom p. In addition, the partial testing is derived from a central limit theorem which results in a Z-test statistic. \u0000Keywords: parameter estimation, hypothesis testing, bivariate log, normal regression","PeriodicalId":17898,"journal":{"name":"KnE Life Sciences","volume":"83 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140375919","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}
Rendi Zulni Ekaputri, H. Surtikanti, Topik Hidayat, Wahyu Surakusumah
Conservation is one of the actions taken to maintain biodiversity and improve ecosystems. This study aimed to analyze the community’s view of conserving watersheds. The research method used is descriptive quantitative, involving the community as respondents to identify and analyze the proposed research instrument. Data were collected through a questionnaire, and community interaction data were collected through field observations and secondary data. The empirical data obtained was then analyzed and interpreted according to the research findings. The results of the research found that the community did not know much about conservation of biodiversity. Based on the community’s perception of conservation, it is necessary to emphasize to the community the importance of biodiversity as the basis for conservation to achieve disaster preparedness. Keywords: conservation, biodiversity, ecosystem
{"title":"Community Perceptions on Conserving Watershed Areas","authors":"Rendi Zulni Ekaputri, H. Surtikanti, Topik Hidayat, Wahyu Surakusumah","doi":"10.18502/kls.v8i1.15611","DOIUrl":"https://doi.org/10.18502/kls.v8i1.15611","url":null,"abstract":"Conservation is one of the actions taken to maintain biodiversity and improve ecosystems. This study aimed to analyze the community’s view of conserving watersheds. The research method used is descriptive quantitative, involving the community as respondents to identify and analyze the proposed research instrument. Data were collected through a questionnaire, and community interaction data were collected through field observations and secondary data. The empirical data obtained was then analyzed and interpreted according to the research findings. The results of the research found that the community did not know much about conservation of biodiversity. Based on the community’s perception of conservation, it is necessary to emphasize to the community the importance of biodiversity as the basis for conservation to achieve disaster preparedness. \u0000Keywords: conservation, biodiversity, ecosystem","PeriodicalId":17898,"journal":{"name":"KnE Life Sciences","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140377115","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：