Pub Date : 2022-07-31DOI: 10.25077/jnte.v11n2.968.2022
A. Rajab, Dzaki Ahmad Fertoni, Riko Novendra, Husnul Fajri
This paper deals with the gas production by monoester oil intended to be used as insulating oil under an electrical discharge of low energy. The monoester contains only saturated fatty acids in its hydrocarbon chain. The electrical fault was realized by implementing an AC high voltage to hemispherical shaped electrode pairs with the gap of 2.5 mm immersed in the oil sample. The voltage application was paused when the breakdown occurred in oil and re-applied repeatedly up to 50 and 75 times to allow a high concentration of gasses produced by the oil sample. The resulting gasses were extracted from the oil sample using the headspace method and then analyzed using gas chromatography (GC). Fault identification methods, like DGA status, Key Gas, Duval Triangle, and IEC Ratio, were performed to predict the fault causing the production of such gasses. The results are compared with those of the monoester of unsaturated type. It is found that the Key Gas method is applicable for both oils under electrical discharge. The Duval Triangle and the IEC Ratio methods diagnose the electrical discharge in both monoesters but overestimate them as high energy discharge.
{"title":"Gas Production by Monoester of Saturated Fatty Acids under Electrical Fault","authors":"A. Rajab, Dzaki Ahmad Fertoni, Riko Novendra, Husnul Fajri","doi":"10.25077/jnte.v11n2.968.2022","DOIUrl":"https://doi.org/10.25077/jnte.v11n2.968.2022","url":null,"abstract":"This paper deals with the gas production by monoester oil intended to be used as insulating oil under an electrical discharge of low energy. The monoester contains only saturated fatty acids in its hydrocarbon chain. The electrical fault was realized by implementing an AC high voltage to hemispherical shaped electrode pairs with the gap of 2.5 mm immersed in the oil sample. The voltage application was paused when the breakdown occurred in oil and re-applied repeatedly up to 50 and 75 times to allow a high concentration of gasses produced by the oil sample. The resulting gasses were extracted from the oil sample using the headspace method and then analyzed using gas chromatography (GC). Fault identification methods, like DGA status, Key Gas, Duval Triangle, and IEC Ratio, were performed to predict the fault causing the production of such gasses. The results are compared with those of the monoester of unsaturated type. It is found that the Key Gas method is applicable for both oils under electrical discharge. The Duval Triangle and the IEC Ratio methods diagnose the electrical discharge in both monoesters but overestimate them as high energy discharge.","PeriodicalId":30660,"journal":{"name":"Jurnal Nasional Teknik Elektro","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41396419","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 : 2022-07-31DOI: 10.25077/jnte.v11n2.977.2022
Laud Christian Ainoo, E. Normanyo
The safe movement of Light Vehicles (LVs) is jeopardised on underground mine ramps due to the single lane nature of ramp and the use of ramp by Heavy Vehicles (HVs). Two-way traffic flow dynamics in single-lane underground mine haulage ramps do affect productivity of ramp in times of ore transportation from underground to the surface for processing. In this research, we made use of traffic signal lights, Radio Frequency (RF) Transmitters (Tx) and Receivers (Rx) and a traffic signal lights module to safeguard LV motion on underground ramp. Simulation outcomes confirm safe movement of LV in the midst of HV and other LV on the haulage ramp. This development assures of safety of LV and stands to minimise the incidents occurrences rate in mine ramp haulage systems.
{"title":"Signal Lights-Based Light Vehicle Safe Movement on Underground Mine Ramps","authors":"Laud Christian Ainoo, E. Normanyo","doi":"10.25077/jnte.v11n2.977.2022","DOIUrl":"https://doi.org/10.25077/jnte.v11n2.977.2022","url":null,"abstract":"The safe movement of Light Vehicles (LVs) is jeopardised on underground mine ramps due to the single lane nature of ramp and the use of ramp by Heavy Vehicles (HVs). Two-way traffic flow dynamics in single-lane underground mine haulage ramps do affect productivity of ramp in times of ore transportation from underground to the surface for processing. In this research, we made use of traffic signal lights, Radio Frequency (RF) Transmitters (Tx) and Receivers (Rx) and a traffic signal lights module to safeguard LV motion on underground ramp. Simulation outcomes confirm safe movement of LV in the midst of HV and other LV on the haulage ramp. This development assures of safety of LV and stands to minimise the incidents occurrences rate in mine ramp haulage systems.","PeriodicalId":30660,"journal":{"name":"Jurnal Nasional Teknik Elektro","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45448651","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 : 2022-03-29DOI: 10.25077/jnte.v11n1.999.2022
K. Amiroh, Bernadus Anggo Seno Aji, Farah Zakiyah Rahmanti
Surabaya is a city with an area of 326.81 km2 and is the center of land transportation in the eastern part of Java Island. The construction of digital infrastructure in the Surabaya area will make it easier for the City Government to make efficient services. Traffic accidents that occurred in Surabaya until 2017 recorded 1,365 incidents. EVAN (Emergency Vehicle Automatic Notification) is a research topic that focuses on the field of transportation, especially in real-time traffic accidents which can be integrated with city information centers and hospitals for primary assistance in accidents. The purpose of this research is to make it easier for the Surabaya city government to provide first aid in the event of an accident. The design of the device on the user side is made using the Arduino, the accelerometer sensor and the gyroscope in the form of the MPU6050 sensor and the u-blox gps module. Crash detection on the system using the k-Nearest neighbors algorithm (KNN). On the operator side, the design is done on a web basis by utilizing the ReactJs framework which is integrated with the Google Maps APIs. The results of the accuracy of the accident detection system reached 97% and the detection of accident locations and the nearest hospital from the location reached 100%. Thus, real-time accident detection can be implemented in Surabaya city to support the smart city.
{"title":"Real-Time Accident Detection Using KNN Algorithm to Support IoT-based Smart City","authors":"K. Amiroh, Bernadus Anggo Seno Aji, Farah Zakiyah Rahmanti","doi":"10.25077/jnte.v11n1.999.2022","DOIUrl":"https://doi.org/10.25077/jnte.v11n1.999.2022","url":null,"abstract":"Surabaya is a city with an area of 326.81 km2 and is the center of land transportation in the eastern part of Java Island. The construction of digital infrastructure in the Surabaya area will make it easier for the City Government to make efficient services. Traffic accidents that occurred in Surabaya until 2017 recorded 1,365 incidents. EVAN (Emergency Vehicle Automatic Notification) is a research topic that focuses on the field of transportation, especially in real-time traffic accidents which can be integrated with city information centers and hospitals for primary assistance in accidents. The purpose of this research is to make it easier for the Surabaya city government to provide first aid in the event of an accident. The design of the device on the user side is made using the Arduino, the accelerometer sensor and the gyroscope in the form of the MPU6050 sensor and the u-blox gps module. Crash detection on the system using the k-Nearest neighbors algorithm (KNN). On the operator side, the design is done on a web basis by utilizing the ReactJs framework which is integrated with the Google Maps APIs. The results of the accuracy of the accident detection system reached 97% and the detection of accident locations and the nearest hospital from the location reached 100%. Thus, real-time accident detection can be implemented in Surabaya city to support the smart city.","PeriodicalId":30660,"journal":{"name":"Jurnal Nasional Teknik Elektro","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43280846","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 : 2022-03-29DOI: 10.25077/jnte.v11n1.1007.2022
Infall Syafalni, T. Adiono
Soft errors from radiations can change the data in electronic devices especially memory cells such as in TCAMs. The soft errors cause bit-flip errors that makes the data are corrupted in the network. This paper presents a novel machine learning for a multiple-bit-flip-tolerant TCAM that address soft errors problem using partial don't-care keys (X-keys). The general methodology is classified into two steps, i.e., statistical training and X-keys matching. First, we train the machine by collecting match probability of a filter by using X-keys that match the same locations as the search key. This method uses statistical training to determine the most efficient of number of don't cares. Moreover, in the statistical training, we also explore the maximum number of don't cares that produce best performance in covering the soft errors. Finally, the X-keys are implemented in the TCAM to correct bit-flip errors. The suitable number of don't cares in X-key is determined from the distribution of match probability of the X-keys so that the best degree of tolerance of the TCAM against soft errors is found. Match probabilities for various filters are shown. Experimental results demonstrate that the soft-error tolerance using statistical data has better soft-error tolerance than other methods. The proposed method is useful for soft-error tolerant TCAMs in routers and firewalls for robust networks.
{"title":"Optimized Multiple-Bit-Flip Soft-Errors-Tolerant TCAM using Machine Learning","authors":"Infall Syafalni, T. Adiono","doi":"10.25077/jnte.v11n1.1007.2022","DOIUrl":"https://doi.org/10.25077/jnte.v11n1.1007.2022","url":null,"abstract":"Soft errors from radiations can change the data in electronic devices especially memory cells such as in TCAMs. The soft errors cause bit-flip errors that makes the data are corrupted in the network. This paper presents a novel machine learning for a multiple-bit-flip-tolerant TCAM that address soft errors problem using partial don't-care keys (X-keys). The general methodology is classified into two steps, i.e., statistical training and X-keys matching. First, we train the machine by collecting match probability of a filter by using X-keys that match the same locations as the search key. This method uses statistical training to determine the most efficient of number of don't cares. Moreover, in the statistical training, we also explore the maximum number of don't cares that produce best performance in covering the soft errors. Finally, the X-keys are implemented in the TCAM to correct bit-flip errors. The suitable number of don't cares in X-key is determined from the distribution of match probability of the X-keys so that the best degree of tolerance of the TCAM against soft errors is found. Match probabilities for various filters are shown. Experimental results demonstrate that the soft-error tolerance using statistical data has better soft-error tolerance than other methods. The proposed method is useful for soft-error tolerant TCAMs in routers and firewalls for robust networks.","PeriodicalId":30660,"journal":{"name":"Jurnal Nasional Teknik Elektro","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44011361","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 : 2022-03-29DOI: 10.25077/jnte.v11n1.989.2022
Munaf Ismail, Sri Arttini Dwi Prasetyowati
Ethanol, isopropyl and methanol belong to the same alcohol group. The latter is commonly used as an industrial solvent, not for personal consumption. Many traditional alcoholic drink sellers often mix alcoholic beverages, which are commonly called as oplosan, this mixed drink is very dangerous for human if it contains methanol. Based on this problem, it is necessary to make a measuring device for the alcohol content in the liquid to classify the alcohol type. The design of this gas sensor-based alcohol classification system and method consists of a series of hardware and software applications. The block diagram of the alcohol classification system measures the ethanol and methanol substances in each alcoholic drink using the MQ3 gas sensor and WeMos as a data acquisition device and microcontroller. The computer was used to process the acquisition data from the gas sensor being used then calculates the K-Nearest Neighbor (K-NN) to obtain the prediction results. The K-NN system testing consists of testing the effect of the K value and testing its accuracy. The result of testing the effect of the K value produces 100% optimum accuracy at the values namely K=1, K=3, K=5, K=10 and 55% on K=20.
{"title":"Classification Of Alcohol Type Using Gas Sensor And K-Nearest Neighbor","authors":"Munaf Ismail, Sri Arttini Dwi Prasetyowati","doi":"10.25077/jnte.v11n1.989.2022","DOIUrl":"https://doi.org/10.25077/jnte.v11n1.989.2022","url":null,"abstract":"Ethanol, isopropyl and methanol belong to the same alcohol group. The latter is commonly used as an industrial solvent, not for personal consumption. Many traditional alcoholic drink sellers often mix alcoholic beverages, which are commonly called as oplosan, this mixed drink is very dangerous for human if it contains methanol. Based on this problem, it is necessary to make a measuring device for the alcohol content in the liquid to classify the alcohol type. The design of this gas sensor-based alcohol classification system and method consists of a series of hardware and software applications. The block diagram of the alcohol classification system measures the ethanol and methanol substances in each alcoholic drink using the MQ3 gas sensor and WeMos as a data acquisition device and microcontroller. The computer was used to process the acquisition data from the gas sensor being used then calculates the K-Nearest Neighbor (K-NN) to obtain the prediction results. The K-NN system testing consists of testing the effect of the K value and testing its accuracy. The result of testing the effect of the K value produces 100% optimum accuracy at the values namely K=1, K=3, K=5, K=10 and 55% on K=20.","PeriodicalId":30660,"journal":{"name":"Jurnal Nasional Teknik Elektro","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43770487","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 : 2022-03-29DOI: 10.25077/jnte.v11n1.994.2022
A. F. Isnawati
The need for an efficient transmit power is affected by the condition of user and power control methods used. User conditions that categorized in cognitive femtocell networks included in the category as distributed user, so it required a distributed power control (DPC). To be implemented in cognitive radio network (CRN) communication, the system must be feasible. The problem raised in this research regarding the feasibility of implementing the DPC system on the CR network To meet the feasible requirements, it is necessary to test the system's feasibility through testing the eigenvalues of the link gain matrix obtained and testing the non-negative power vector conditions. In this study, experiments were carried out on 2 schemes of the number of users, namely the scheme of 5 users and 10 users, to determine the power requirements of each user according to the channel distribution. The results obtained for both schemes show that the total eigenvalue of the link gain matrix for all channels is less than 1 and all users meet the non-negative power vector requirements. So it can be concluded that those two schemes are feasible to implement a distributed power control system. Furthermore, as more users use the channel and the closer the distance between users, the more power is consumed due to high interference, necessitating high power compensation in order to maintain the target of signal to interference and noise ratio (SINR).
{"title":"Feasibility Analysis of Distributed Power Control System for Cognitive Radio Networks","authors":"A. F. Isnawati","doi":"10.25077/jnte.v11n1.994.2022","DOIUrl":"https://doi.org/10.25077/jnte.v11n1.994.2022","url":null,"abstract":"The need for an efficient transmit power is affected by the condition of user and power control methods used. User conditions that categorized in cognitive femtocell networks included in the category as distributed user, so it required a distributed power control (DPC). To be implemented in cognitive radio network (CRN) communication, the system must be feasible. The problem raised in this research regarding the feasibility of implementing the DPC system on the CR network To meet the feasible requirements, it is necessary to test the system's feasibility through testing the eigenvalues of the link gain matrix obtained and testing the non-negative power vector conditions. In this study, experiments were carried out on 2 schemes of the number of users, namely the scheme of 5 users and 10 users, to determine the power requirements of each user according to the channel distribution. The results obtained for both schemes show that the total eigenvalue of the link gain matrix for all channels is less than 1 and all users meet the non-negative power vector requirements. So it can be concluded that those two schemes are feasible to implement a distributed power control system. Furthermore, as more users use the channel and the closer the distance between users, the more power is consumed due to high interference, necessitating high power compensation in order to maintain the target of signal to interference and noise ratio (SINR).","PeriodicalId":30660,"journal":{"name":"Jurnal Nasional Teknik Elektro","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45756614","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 : 2022-03-29DOI: 10.25077/jnte.v11n1.984.2022
Maulana Akbar Dwijaya, Umar Ali Ahmad, Rudi Purwo Wijayanto, Ratna Astuti Nugrahaeni
COVID-19 has become a pandemic and is a big problem that needs to be checked out immediately. CT scan images can explain the lung conditions of COVID-19 patients and have the potential to be a clinical diagnostic tool. In this research, we classify COVID-19 by recognizing images on a computer tomography scan (CT scan) of the lungs using digital image processing and GLCM feature extraction techniques to obtain grayscale level values in CT images, followed by the creation of an artificial neural network model. So that the model can classify CT scan images, the results in this research obtained the most optimal model for COVID-19 classification performance with 90% accuracy, 88% precision, 91% recall, and 90% F1 score. This research can be a useful tool for clinical practitioners and radiologists to assist them in the diagnosis, quantification, and follow-up of COVID-19 cases.
{"title":"Model Design of The Image Recognition of Lung CT Scan for COVID-19 Detection Using Artificial Neural Network","authors":"Maulana Akbar Dwijaya, Umar Ali Ahmad, Rudi Purwo Wijayanto, Ratna Astuti Nugrahaeni","doi":"10.25077/jnte.v11n1.984.2022","DOIUrl":"https://doi.org/10.25077/jnte.v11n1.984.2022","url":null,"abstract":"COVID-19 has become a pandemic and is a big problem that needs to be checked out immediately. CT scan images can explain the lung conditions of COVID-19 patients and have the potential to be a clinical diagnostic tool. In this research, we classify COVID-19 by recognizing images on a computer tomography scan (CT scan) of the lungs using digital image processing and GLCM feature extraction techniques to obtain grayscale level values in CT images, followed by the creation of an artificial neural network model. So that the model can classify CT scan images, the results in this research obtained the most optimal model for COVID-19 classification performance with 90% accuracy, 88% precision, 91% recall, and 90% F1 score. This research can be a useful tool for clinical practitioners and radiologists to assist them in the diagnosis, quantification, and follow-up of COVID-19 cases.","PeriodicalId":30660,"journal":{"name":"Jurnal Nasional Teknik Elektro","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42317162","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 : 2022-03-29DOI: 10.25077/jnte.v11n1.899.2022
Z. E. Fitri, Ari Baskara, Abdul Madjid, A. M. N. Imron
Pitaya is another name for dragon fruit which is currently a popular fruit, especially in Indonesia. One of the problems related to determining the quality of dragon fruit is the postharvest sorting and grading process. In general, farmers determine the grading system by measuring the weight or just looking at the size of the fruit, of course, this raises differences in grading perceptions so that it is not by SNI. This research is a development of previous research, but we changed the type of dragon fruit from white dragon fruit (Hylocereus undatus) to red dragon fruit (Hylocereus costaricensis). We also adapted the image processing and classification methods in previous studies and then compared them with other classification methods. The number of images in the training data is 216, and the number of images in the testing data is 75. The comparison of the accuracy of the three classification methods is 84% for the KNN method, 85.33% for the Naive Bayes method, and 86.67% for the Backpropagation method. So that the backpropagation method is the best classification method in classifying the quality grading of red dragon fruit. The network architecture used is 4, 8, 3 with a learning rate of 0.3 so that the training accuracy is 98.61% and the testing accuracy is 86.67%.
{"title":"Comparison of Classification for Grading Red Dragon Fruit (Hylocereus Costaricensis)","authors":"Z. E. Fitri, Ari Baskara, Abdul Madjid, A. M. N. Imron","doi":"10.25077/jnte.v11n1.899.2022","DOIUrl":"https://doi.org/10.25077/jnte.v11n1.899.2022","url":null,"abstract":"Pitaya is another name for dragon fruit which is currently a popular fruit, especially in Indonesia. One of the problems related to determining the quality of dragon fruit is the postharvest sorting and grading process. In general, farmers determine the grading system by measuring the weight or just looking at the size of the fruit, of course, this raises differences in grading perceptions so that it is not by SNI. This research is a development of previous research, but we changed the type of dragon fruit from white dragon fruit (Hylocereus undatus) to red dragon fruit (Hylocereus costaricensis). We also adapted the image processing and classification methods in previous studies and then compared them with other classification methods. The number of images in the training data is 216, and the number of images in the testing data is 75. The comparison of the accuracy of the three classification methods is 84% for the KNN method, 85.33% for the Naive Bayes method, and 86.67% for the Backpropagation method. So that the backpropagation method is the best classification method in classifying the quality grading of red dragon fruit. The network architecture used is 4, 8, 3 with a learning rate of 0.3 so that the training accuracy is 98.61% and the testing accuracy is 86.67%.","PeriodicalId":30660,"journal":{"name":"Jurnal Nasional Teknik Elektro","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47420797","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 : 2022-03-29DOI: 10.25077/jnte.v11n1.985.2022
Pinto Anugrah, Rizki Wahyu Pratama
Mosque is an important building for Muslims worldwide for doing religious activities, such as daily prayers, weekly discourses, and annual celebrations. In many places, mosques are considered appropriate buildings for rooftop solar photovoltaics (PV) installation. This study provides a techno-economic analysis of an on-grid PV system in a great mosque. As a case study, Masjid Tablighiyah Garegeh in Bukittinggi is chosen, which is currently under construction with an expected capacity of up to 1,400 people. This study uses HOMER software as a tool to assess optimum configuration for an on-grid PV system. There are four options that is considered in this study: PV-grid, PV-battery-grid, battery-grid, and grid only system . Optimization results showed that both configurations with PV have promising performance; however, an on-grid PV system without battery system is the most optimum configuration. A 40 kWp PV equipped with a 27 kW converter has the least net present cost with USD 6,902, while the cost of energy when implementing the system is only about USD 4.8 cent per kWh. By implementing the system, 57.2 MWh of electricity will be produced from the PV.
{"title":"Techno-Economic Simulation of On-grid PV System at a New Grand Mosque in Bukittinggi using HOMER","authors":"Pinto Anugrah, Rizki Wahyu Pratama","doi":"10.25077/jnte.v11n1.985.2022","DOIUrl":"https://doi.org/10.25077/jnte.v11n1.985.2022","url":null,"abstract":"Mosque is an important building for Muslims worldwide for doing religious activities, such as daily prayers, weekly discourses, and annual celebrations. In many places, mosques are considered appropriate buildings for rooftop solar photovoltaics (PV) installation. This study provides a techno-economic analysis of an on-grid PV system in a great mosque. As a case study, Masjid Tablighiyah Garegeh in Bukittinggi is chosen, which is currently under construction with an expected capacity of up to 1,400 people. This study uses HOMER software as a tool to assess optimum configuration for an on-grid PV system. There are four options that is considered in this study: PV-grid, PV-battery-grid, battery-grid, and grid only system . Optimization results showed that both configurations with PV have promising performance; however, an on-grid PV system without battery system is the most optimum configuration. A 40 kWp PV equipped with a 27 kW converter has the least net present cost with USD 6,902, while the cost of energy when implementing the system is only about USD 4.8 cent per kWh. By implementing the system, 57.2 MWh of electricity will be produced from the PV.","PeriodicalId":30660,"journal":{"name":"Jurnal Nasional Teknik Elektro","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47026044","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 : 2022-03-29DOI: 10.25077/jnte.v11n1.937.2022
Z. Arifin, Aries Jehan Tamamy, Hery Pamungkas, Dita Ayu Mayasari, M. A. Heryanto
The COVID-19 pandemic that has occurred to date has resulted in the loss of many lives. This is due to the ease with which the COVID-19 virus spreads. According to the latest research published by the WHO, the virus can spread through the medium of objects, one of the easies object to spread virus is money. The spread of the COVID-19 virus can be done through money transactions that have previously been used by people infected by the virus. This is because COVID-19 virus can survive for more than 72 hours. To prevent this, it is necessary to sterilize so that the virus in the money can be neutralized. The technology that can be used for disinfection in this tool is Ultra Violet (UV) light and Ozone Generator. Many studies have shown that UV rays and ozone gas (O3) are able to kill viruses that are on the surface of objects. The ability of UV rays and ozone gas (O3) can kill viruses in money because UV rays and ozone gas (O3) have radiation that is quite harsh, so that if exposed to human skin continuously it can cause damage to skin tissue. In this study, to overcome this problem, a device that is automatically able to carry out the disinfection process in the room is made by utilizing UV light. Infaq Sterilization Box with UV and Ozone (BIUZ) can kill viruses in money, it is also easy to operate and safe. The size of the tool made is adjusted to the object or partner of the research activity, namely the Central Java Great Mosque Manager (PP MAJT). The need for partners is that the tool is able to carry out the sterilization process of infaq money provided by the congregation, both in the form of paper and coins effectively.
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