Pub Date : 2023-01-26DOI: 10.21776/ub.jeest.2022.009.01.4
Ani Purwanti
The Seyegan tofu industry has increased the output of tofu wastewater, which has not yet been put to good use. Biogas can be created by mixing wastewater from the tofu business with waste from the cow feces industry. In this study, we measure the time of fermentation, the composition variation, and the rate of increase in gas pressure from the biogas generation process. Three versions with three repetitions each were used in this investigation. Three different variations were tested: one with a ratio of 20% cow excrement and 80% wastewater tofu industry, one with a ratio of 35% cow feces and 65% wastewater tofu industry, and one with a ratio of 50% cow feces and 50% wastewater tofu industry. Using a biogas reactor consisting of 120 L plastic drums, the experiment was conducted. Gas pressure (mm) was monitored with a water column and fermentation duration using a digital timer (hours). To ascertain the viscosity variance of each variation composition, a level test was conducted. By using the gravimetric approach, water. According to the study's findings, a 2.5 mm water column containing a mixture of 50% cow feces and 50% wastewater from the tofu business had the maximum gas pressure. The ideal ratio of mixed materials within 7 days has a significant impact on optimal biogas production.
{"title":"OPTIMIZATION OF BIOGAS PRODUCTION FROM TOFU WASTEWATER","authors":"Ani Purwanti","doi":"10.21776/ub.jeest.2022.009.01.4","DOIUrl":"https://doi.org/10.21776/ub.jeest.2022.009.01.4","url":null,"abstract":"The Seyegan tofu industry has increased the output of tofu wastewater, which has not yet been put to good use. Biogas can be created by mixing wastewater from the tofu business with waste from the cow feces industry. In this study, we measure the time of fermentation, the composition variation, and the rate of increase in gas pressure from the biogas generation process. Three versions with three repetitions each were used in this investigation. Three different variations were tested: one with a ratio of 20% cow excrement and 80% wastewater tofu industry, one with a ratio of 35% cow feces and 65% wastewater tofu industry, and one with a ratio of 50% cow feces and 50% wastewater tofu industry. Using a biogas reactor consisting of 120 L plastic drums, the experiment was conducted. Gas pressure (mm) was monitored with a water column and fermentation duration using a digital timer (hours). To ascertain the viscosity variance of each variation composition, a level test was conducted. By using the gravimetric approach, water. According to the study's findings, a 2.5 mm water column containing a mixture of 50% cow feces and 50% wastewater from the tofu business had the maximum gas pressure. The ideal ratio of mixed materials within 7 days has a significant impact on optimal biogas production.","PeriodicalId":498652,"journal":{"name":"Journal of Environmental Engineering and Sustainable Technology","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135997916","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 : 2023-01-26DOI: 10.21776/ub.jeest.2022.009.01.2
Iva Yenis Septiariva, Sapta Suhardono, Mega Mutiara Sari, I Wayan Koko Suryawan
Leachate is one of the results of the waste degradation process that can pollute the environment. Leachate is usually treated by biological processes, including aerobic processes that require sufficient oxygen. Oxygen transfer by aeration process is one way to consider gas transfer coefficient (KLa). This study aims to determine the gas KLa kinetics in leachate. This study used a chemical oxygen demand (COD) concentration limit of 100 mg/L. The oxygen flow rates used in this study were 1 L/minute and 1.5 L/minute. The main parameter measured in this study is dissolved oxygen (DO) which is measured by a DO meter every minute. The final DO in this study can be as high as 4 to 6 mg/L. The KLa values in this study show values at the flow of 1 and 1.5 L/min, respectively 0.0095/min and 0.017/min. These results also show that the detention time required for 1 and 1.5 L/min flow rates is 1.75 hours and 0.96 hours. This indicates that the greater the flow rate is given to the oxygen transfer process, the greater the flow rate the KLa value will increase. This will also affect the volume required for the oxygen transfer process. In addition, further research is needed with more diverse variations to further determine the appropriate detention time in leachate processing.
{"title":"PRELIMINARY STUDY ON OXYGEN TRANSFER FOR LEACHATE WASTEWATER TREATMENT","authors":"Iva Yenis Septiariva, Sapta Suhardono, Mega Mutiara Sari, I Wayan Koko Suryawan","doi":"10.21776/ub.jeest.2022.009.01.2","DOIUrl":"https://doi.org/10.21776/ub.jeest.2022.009.01.2","url":null,"abstract":"Leachate is one of the results of the waste degradation process that can pollute the environment. Leachate is usually treated by biological processes, including aerobic processes that require sufficient oxygen. Oxygen transfer by aeration process is one way to consider gas transfer coefficient (KLa). This study aims to determine the gas KLa kinetics in leachate. This study used a chemical oxygen demand (COD) concentration limit of 100 mg/L. The oxygen flow rates used in this study were 1 L/minute and 1.5 L/minute. The main parameter measured in this study is dissolved oxygen (DO) which is measured by a DO meter every minute. The final DO in this study can be as high as 4 to 6 mg/L. The KLa values in this study show values at the flow of 1 and 1.5 L/min, respectively 0.0095/min and 0.017/min. These results also show that the detention time required for 1 and 1.5 L/min flow rates is 1.75 hours and 0.96 hours. This indicates that the greater the flow rate is given to the oxygen transfer process, the greater the flow rate the KLa value will increase. This will also affect the volume required for the oxygen transfer process. In addition, further research is needed with more diverse variations to further determine the appropriate detention time in leachate processing.","PeriodicalId":498652,"journal":{"name":"Journal of Environmental Engineering and Sustainable Technology","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135997913","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 : 2023-01-26DOI: 10.21776/ub.jeest.2022.009.01.3
Jely Nova
Parasites, viruses, and bacteria contribute to the transmission of infectious diseases. Catfish Enteric Septicemia (ESM) is caused by the bacterium Edwardsiella ictaluri . Antibiotics are used to treat this disease. However, the continuous use of antibiotics will lead to antibiotic resistance in fish and the contamination of the environment. Therefore, it is vital to have an alternative containing natural antibacterial components, such as Sintrong Leaf (Crassocephalum crepidioides). The composition of sintrong leaves consists of flavonoids, alkaloids, saponins, and tannins. This study employed an experimental method with a completely randomized design (CRD), which included five treatments and three replications. Treatment dosages of 25 ppm, 50 ppm, 75 ppm, 100 ppm, and 125 ppm were utilized along with the positive control (doxycycline) and negative control (without treatment). The investigation revealed that a crude extract of sintrong leaf exhibited an inhibitory effect that was effective against E. ictaluri bacteria. The equation pattern indicated y = -0.0004x 2 + 0.0716x + 6.933 with an R 2 coefficient of 0.71 showing a quadratic graph as the outcome. The graph results show that the best dose of crude extract from sintrong leaves against E. ictaluri bacteria is 89.5 ppm.
{"title":"IN-VITRO INHIBITION TEST OF SINTRONG LEAVES (CRASSOCEPHALUM CREPIDIOIDES) CRUDE EXTRACT ON EDWARDSIELLA ICTALURI BACTERIA","authors":"Jely Nova","doi":"10.21776/ub.jeest.2022.009.01.3","DOIUrl":"https://doi.org/10.21776/ub.jeest.2022.009.01.3","url":null,"abstract":"Parasites, viruses, and bacteria contribute to the transmission of infectious diseases. Catfish Enteric Septicemia (ESM) is caused by the bacterium Edwardsiella ictaluri . Antibiotics are used to treat this disease. However, the continuous use of antibiotics will lead to antibiotic resistance in fish and the contamination of the environment. Therefore, it is vital to have an alternative containing natural antibacterial components, such as Sintrong Leaf (Crassocephalum crepidioides). The composition of sintrong leaves consists of flavonoids, alkaloids, saponins, and tannins. This study employed an experimental method with a completely randomized design (CRD), which included five treatments and three replications. Treatment dosages of 25 ppm, 50 ppm, 75 ppm, 100 ppm, and 125 ppm were utilized along with the positive control (doxycycline) and negative control (without treatment). The investigation revealed that a crude extract of sintrong leaf exhibited an inhibitory effect that was effective against E. ictaluri bacteria. The equation pattern indicated y = -0.0004x 2 + 0.0716x + 6.933 with an R 2 coefficient of 0.71 showing a quadratic graph as the outcome. The graph results show that the best dose of crude extract from sintrong leaves against E. ictaluri bacteria is 89.5 ppm.","PeriodicalId":498652,"journal":{"name":"Journal of Environmental Engineering and Sustainable Technology","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135997915","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 : 2023-01-26DOI: 10.21776/ub.jeest.2022.009.01.1
Syawaldin Ridha, Meta Syafitri, Sukir Maryanto, Agustya Adi Martha
A share wave velocity model to a depth of 30 meter (vs30) can be used to find the type of the ground as a preventive action against earthquake disaster mitigation. Vs30 is obtained from the inversion of ellipticity curve using HVTFA method. HVTFA method is a method that can minimize the love curve in the ellipticity curve. Therefore, a more reliable share wave velocity can be obtained. It is necessary to find reliability of a model in a further research. The objectives of this research were to find the reliability of HVTFA and HVSR methods and determine the reliability of vs30 model from the result of inversion of Rayleigh-wave ellipticity curve using HVTFA method with duration of microtremor measurement of 0.5 hour, 1 hour, 2 hours, 3 hours, 4 hours, 5 hours and 6 hours. Data used in this research were microtremor data. The microtremor data were processed using HVTFA and HVSR method in Geopsy software to find the ellicpticity curve. Next, the inversion of ellipticity was carried out in dinver software to obtain the share wave velocity model. After that, the error value from the model was calculated using vs%Miss, Boun%Miss, Ev, and Eb. The error value of HVTFA method still met the requirement of reliable model, but not the error value of HVSR method. The high error value in HVSR method was found in Bound%Miss and Eb. It meant that the share wave velocity of HVSR method had a high error value in the estimation of surface depth and thickness. Therefore, HVTFA method produced a more reliable vs30 model than HVSR method. In addition, the velocity model of HVTFA method from microtremor data with duration of 0.5 hour, 1 hour, 2 hours, 3 hours, 4 hours, 5 hours and 6 hours also had reliable model. Keywords: vs30 model, microtremor, HVTFA, HVSR, ellipticity curve
{"title":"SHARE WAVE VELOCITY MODEL TO A DEPTH OF 30 METER (Vs30) USING HORIZONTAL VERTICAL TIME FREQUENCY ANALYSIS (HVTFA) METHOD","authors":"Syawaldin Ridha, Meta Syafitri, Sukir Maryanto, Agustya Adi Martha","doi":"10.21776/ub.jeest.2022.009.01.1","DOIUrl":"https://doi.org/10.21776/ub.jeest.2022.009.01.1","url":null,"abstract":"A share wave velocity model to a depth of 30 meter (vs30) can be used to find the type of the ground as a preventive action against earthquake disaster mitigation. Vs30 is obtained from the inversion of ellipticity curve using HVTFA method. HVTFA method is a method that can minimize the love curve in the ellipticity curve. Therefore, a more reliable share wave velocity can be obtained. It is necessary to find reliability of a model in a further research. The objectives of this research were to find the reliability of HVTFA and HVSR methods and determine the reliability of vs30 model from the result of inversion of Rayleigh-wave ellipticity curve using HVTFA method with duration of microtremor measurement of 0.5 hour, 1 hour, 2 hours, 3 hours, 4 hours, 5 hours and 6 hours. Data used in this research were microtremor data. The microtremor data were processed using HVTFA and HVSR method in Geopsy software to find the ellicpticity curve. Next, the inversion of ellipticity was carried out in dinver software to obtain the share wave velocity model. After that, the error value from the model was calculated using vs%Miss, Boun%Miss, Ev, and Eb. The error value of HVTFA method still met the requirement of reliable model, but not the error value of HVSR method. The high error value in HVSR method was found in Bound%Miss and Eb. It meant that the share wave velocity of HVSR method had a high error value in the estimation of surface depth and thickness. Therefore, HVTFA method produced a more reliable vs30 model than HVSR method. In addition, the velocity model of HVTFA method from microtremor data with duration of 0.5 hour, 1 hour, 2 hours, 3 hours, 4 hours, 5 hours and 6 hours also had reliable model. Keywords: vs30 model, microtremor, HVTFA, HVSR, ellipticity curve","PeriodicalId":498652,"journal":{"name":"Journal of Environmental Engineering and Sustainable Technology","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135997917","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}
In pandemic conditions, awareness of keeping a healthy balance is necessary. One is considering food consumption and understanding its nutrition content to avert food waste. We have been developing a prototype to estimate the nutrition of leftover food, and the main problem lies in image segmentation. Therefore, we propose the Improved Food Image Segmentation (IFIS) and Contour Based Calculation (CBC) to measure the area of the segmented image instead of pixel-wise. First, the tray box image is acquired and broken down into compartments using an automated cropping algorithm. The first step of this proposed method is tray box image acquisition and dividing the compartment using an automatic cropping algorithm. Then each compartment is treated using IFIS, calculates the result of IFIS by CBC, measures the estimated leftover by Automatic Food Leftover Estimation (AFLE), and then predicts the nutritional content. The evaluation is applied by comparing the actual measurement from the Comstock method and leftover estimation by the proposed algorithm. The result shows that Root Square Means Error (RMSE) reaches 0.48 compared to the actual weighing scale and 96.67% accuracy compared to the Comstock method. Based on the results, the proposed algorithm is sufficient to be applied.
{"title":"NUTRITION ESTIMATION OF LEFTOVER USING IMPROVED FOOD IMAGE SEGMENTATION AND CONTOUR BASED CALCULATION ALGORITHM","authors":"Sigit Adinugroho, Yuita Arum Sari, Jaya Mahar Maligan, Kartika Sari, Yusuf Gladiensyah Bihanda, Nabila Nuraini, Danial Fatchurrahman","doi":"10.21776/ub.jeest.2022.009.01.5","DOIUrl":"https://doi.org/10.21776/ub.jeest.2022.009.01.5","url":null,"abstract":"In pandemic conditions, awareness of keeping a healthy balance is necessary. One is considering food consumption and understanding its nutrition content to avert food waste. We have been developing a prototype to estimate the nutrition of leftover food, and the main problem lies in image segmentation. Therefore, we propose the Improved Food Image Segmentation (IFIS) and Contour Based Calculation (CBC) to measure the area of the segmented image instead of pixel-wise. First, the tray box image is acquired and broken down into compartments using an automated cropping algorithm. The first step of this proposed method is tray box image acquisition and dividing the compartment using an automatic cropping algorithm. Then each compartment is treated using IFIS, calculates the result of IFIS by CBC, measures the estimated leftover by Automatic Food Leftover Estimation (AFLE), and then predicts the nutritional content. The evaluation is applied by comparing the actual measurement from the Comstock method and leftover estimation by the proposed algorithm. The result shows that Root Square Means Error (RMSE) reaches 0.48 compared to the actual weighing scale and 96.67% accuracy compared to the Comstock method. Based on the results, the proposed algorithm is sufficient to be applied.","PeriodicalId":498652,"journal":{"name":"Journal of Environmental Engineering and Sustainable Technology","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135997914","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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