Microclimate variables are important factors that affect adaptive thermal comfort. These factors include air temperature, solar radiation, air humidity, and wind speed. This study focuses on discussing microclimate variables, specifically air temperature and air humidity. This is based on previous research indicating that the most influential climate variables are air temperature, solar radiation, and air humidity. This study is a field research aimed at comparing air temperature and air humidity between campus 1 and campus 2 of Khairun University, due to differences in geographical elevation. Measurements were taken in March. The variables of air temperature and air humidity were measured inside the building. The research results show significant differences between campus 1 and campus 2. These differences can be associated with the perceived adaptive thermal comfort by the users. The thermal sensation results direct that the majority of users in campus 2 feel cool, while the majority of users in campus 1 feel comfortable or neutral. These findings provide a strong basis for improving adaptive thermal comfort in both campuses by considering optimal air temperature and air humidity settings.
{"title":"The Influence of Latitude on the Climatic Characteristics of Classroom in Campus 1 and Campus 2 of Khairun University in Achieving Adaptive Thermal Comfort","authors":"None Tayeb Mustamin, None Nasrullah, None Sayyid Quraisy, None Aswar Masri","doi":"10.47577/technium.v17i.10083","DOIUrl":"https://doi.org/10.47577/technium.v17i.10083","url":null,"abstract":"Microclimate variables are important factors that affect adaptive thermal comfort. These factors include air temperature, solar radiation, air humidity, and wind speed. This study focuses on discussing microclimate variables, specifically air temperature and air humidity. This is based on previous research indicating that the most influential climate variables are air temperature, solar radiation, and air humidity. This study is a field research aimed at comparing air temperature and air humidity between campus 1 and campus 2 of Khairun University, due to differences in geographical elevation. Measurements were taken in March. The variables of air temperature and air humidity were measured inside the building. The research results show significant differences between campus 1 and campus 2. These differences can be associated with the perceived adaptive thermal comfort by the users. The thermal sensation results direct that the majority of users in campus 2 feel cool, while the majority of users in campus 1 feel comfortable or neutral. These findings provide a strong basis for improving adaptive thermal comfort in both campuses by considering optimal air temperature and air humidity settings.","PeriodicalId":490649,"journal":{"name":"Technium","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135216475","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}
Biomass is one of the agricultural waste that can be used as an alternative fuel substitute that is converted first into a briquette, the goal is to become an environmentally friendly fuel. Corn cobs and rice straw are one of the most common types of agricultural products in East Java, therefore alternative fuel potentials that will be obtained will also be higher. Research conducted that is aimed at finding out the characteristics of solid fuel (briquettes) include: Braket's heat values, briquette water content, briquette gray content and drop tests on briquettes using a mixture of corn cobs and rice straw. Variation of a mixture between corn cobs and rice straw of 1 kg, where 1 kg of corn cob and rice straw uses a mixture ratio of 90%: 10%, 80%: 20%, 70%: 30%and 60%: 40%by using flour adhesive kanji of 0.001 kg. Also uses two pressure variations, namely: A = 2500 kPa and B = 5000 kPa used in briquettes. The results of research from the briquette characteristics such as: the highest heat value using a 90% corn cob mixture and 10% rice straw obtained at 5546.74 Cal/gram. The most optimal water content uses an emphasis load of 5000 kPa using a 90% corn cob mixture and 10% rice straw obtained a value of 11.30%. The most optimal ash content also uses an emphasis load of 5000 kPa using a 90% corn cob mixture and 10% rice straw obtained a value of 20.58%. While the drop test value on the briquette uses a 5000 kPa pressing load using a 60% corn cob mixture and 40% rice straw obtained a value of 11.10% the large reduction of pasticles when dropped from a height.
{"title":"Solid Biomass Uses A Mixture Of Agricultural Waste As An Alternative Fuel","authors":"None Rullie Annisa, None Ibnu Irawan, None Rifky Yusron, None Yusril Arifiyanto","doi":"10.47577/technium.v17i.10120","DOIUrl":"https://doi.org/10.47577/technium.v17i.10120","url":null,"abstract":"Biomass is one of the agricultural waste that can be used as an alternative fuel substitute that is converted first into a briquette, the goal is to become an environmentally friendly fuel. Corn cobs and rice straw are one of the most common types of agricultural products in East Java, therefore alternative fuel potentials that will be obtained will also be higher. Research conducted that is aimed at finding out the characteristics of solid fuel (briquettes) include: Braket's heat values, briquette water content, briquette gray content and drop tests on briquettes using a mixture of corn cobs and rice straw. Variation of a mixture between corn cobs and rice straw of 1 kg, where 1 kg of corn cob and rice straw uses a mixture ratio of 90%: 10%, 80%: 20%, 70%: 30%and 60%: 40%by using flour adhesive kanji of 0.001 kg. Also uses two pressure variations, namely: A = 2500 kPa and B = 5000 kPa used in briquettes. The results of research from the briquette characteristics such as: the highest heat value using a 90% corn cob mixture and 10% rice straw obtained at 5546.74 Cal/gram. The most optimal water content uses an emphasis load of 5000 kPa using a 90% corn cob mixture and 10% rice straw obtained a value of 11.30%. The most optimal ash content also uses an emphasis load of 5000 kPa using a 90% corn cob mixture and 10% rice straw obtained a value of 20.58%. While the drop test value on the briquette uses a 5000 kPa pressing load using a 60% corn cob mixture and 40% rice straw obtained a value of 11.10% the large reduction of pasticles when dropped from a height.","PeriodicalId":490649,"journal":{"name":"Technium","volume":"32 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135217252","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 : 2023-11-01DOI: 10.47577/technium.v17i.10069
None Muhammad Haris Irham, None Abdul Mubarak, None Munazat Salmin, None Rosihan
This research discusses the use of a Convolutional Neural Network (CNN) with the MobileNetV2 model in the real-time detection of human facial expressions. This research aims to develop a human face expression detection system using deep learning algorithms. This study used the observation data collection method and obtained secondary data from the FER2013 data set which contains 28,709 training samples, 3,859 validation data sets, and 3,859 test samples, for a total of 35,887 images with a resolution of 48x48 and seven categories of facial expressions. The training results showed that the CNN model using MobileNetV2 achieved an accuracy of 57% in the training process and 51% in the validation process. Based on the analysis of these results, testing using a confusion matrix with an accuracy of 51% concluded that the model was unable to properly recognize patterns of data with disgust and fear categories, leading to low accuracy. Some factors contributing to the system's inability to recognize expressions were due to similarities between facial expressions such as sad and fearful, or sad and disgusted. This study provides new insights into the development of technology for detecting human facial expressions using deep learning and the MobileNetV2 model.
{"title":"Detecting Face Expressions in Real-Time Using Convolutional Neural Network (CNN) Algorithm","authors":"None Muhammad Haris Irham, None Abdul Mubarak, None Munazat Salmin, None Rosihan","doi":"10.47577/technium.v17i.10069","DOIUrl":"https://doi.org/10.47577/technium.v17i.10069","url":null,"abstract":"This research discusses the use of a Convolutional Neural Network (CNN) with the MobileNetV2 model in the real-time detection of human facial expressions. This research aims to develop a human face expression detection system using deep learning algorithms. This study used the observation data collection method and obtained secondary data from the FER2013 data set which contains 28,709 training samples, 3,859 validation data sets, and 3,859 test samples, for a total of 35,887 images with a resolution of 48x48 and seven categories of facial expressions. The training results showed that the CNN model using MobileNetV2 achieved an accuracy of 57% in the training process and 51% in the validation process. Based on the analysis of these results, testing using a confusion matrix with an accuracy of 51% concluded that the model was unable to properly recognize patterns of data with disgust and fear categories, leading to low accuracy. Some factors contributing to the system's inability to recognize expressions were due to similarities between facial expressions such as sad and fearful, or sad and disgusted. This study provides new insights into the development of technology for detecting human facial expressions using deep learning and the MobileNetV2 model.","PeriodicalId":490649,"journal":{"name":"Technium","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135161112","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 some areas the distribution of telecommunications networks is not evenly distributed, one example is in the city of Ternate. Several areas in the city of Ternate. The purpose of this study is to determine the quality of the 4G LTE network from providers in the city of Ternate, namely (Telkomsel and Indosat) using the G-Nettrack Pro application, the parameters measured are rsrp or network strength, The method used in this study is the drive test, The results showed that the RSRP distribution of Telkomsel operators in Sasa Village had a percentage of 43.05% with a sample of 155. Meanwhile, Indosat operators had a percentage of 34.83% with a sample of 117, the RSRP distribution of Telkomsel operators in Gambesi Village had a percentage of 42.02% with a sample of 133. While Indosat Operators have a percentage of 24.64% with a sample of 70, RSRP Distribution of Telkomsel Operators in the Stadium Village has a percentage of 64.29% with a sample of 117. Meanwhile, Indosat Operators have a percentage of 53.05% with a sample of 87, Distribution of RSRP Telkomsel Operators in Kelurahan Stadiums have a percentage of 57.76% with a sample of 145. Meanwhile, Indosat Operators have a percentage of 37.18% with a sample of 87.
{"title":"Comprative Analysis of 4G Network Quality Between Telkomsel and Indosat Operators Using the G-Net Track Pro Application in the City of Ternate","authors":"None Irwan Abdullah, None Zulaeha Mabud, None Fahrizal Djohar, None Fedi Haryanto H Tjan","doi":"10.47577/technium.v17i.10062","DOIUrl":"https://doi.org/10.47577/technium.v17i.10062","url":null,"abstract":"In some areas the distribution of telecommunications networks is not evenly distributed, one example is in the city of Ternate. Several areas in the city of Ternate. The purpose of this study is to determine the quality of the 4G LTE network from providers in the city of Ternate, namely (Telkomsel and Indosat) using the G-Nettrack Pro application, the parameters measured are rsrp or network strength, The method used in this study is the drive test, The results showed that the RSRP distribution of Telkomsel operators in Sasa Village had a percentage of 43.05% with a sample of 155. Meanwhile, Indosat operators had a percentage of 34.83% with a sample of 117, the RSRP distribution of Telkomsel operators in Gambesi Village had a percentage of 42.02% with a sample of 133. While Indosat Operators have a percentage of 24.64% with a sample of 70, RSRP Distribution of Telkomsel Operators in the Stadium Village has a percentage of 64.29% with a sample of 117. Meanwhile, Indosat Operators have a percentage of 53.05% with a sample of 87, Distribution of RSRP Telkomsel Operators in Kelurahan Stadiums have a percentage of 57.76% with a sample of 145. Meanwhile, Indosat Operators have a percentage of 37.18% with a sample of 87.","PeriodicalId":490649,"journal":{"name":"Technium","volume":"133 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135161841","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 : 2023-11-01DOI: 10.47577/technium.v17i.10073
None Raudha Hakim, None Nurmaiyasa Marsaoly, None Muhammad Arby Somadayo
Land transportation mode is the main means of transportation to reach campus II Unkhair Gambesi which can be accessed using motorbikes and public transportation. Ternate City is one of the cities in North Maluku Province which has many important activities in the fields of education, politics, and economy. In addition, the center of government of North Maluku province is also still in the Ternate City area, so it also has an impact on the development of the lives of the people of Ternate City. This study aims to determine the effect of cost and travel time on the selection of transportation modes between private vehicles (motorcycles) and public transportation using the state preference method. This study uses the Stated preference method used for an approach by using respondents' opinions on various alternative options on the attributes of travel costs and travel time to transportation modes Private Vehicles (Motorcycles) and Public Transportation Case Study: Central Ternate – Campus II Unkhair Gambesi. The results of this study used linear regression analysis and the binary logit method. And it can be concluded that the chance of choosing a Private Vehicle (Motorcycle) is 74% while the chance of choosing public transportation is 26%.
{"title":"Study of Transportasi Mode Selection to Khairun University Campus with Binary Logit Method","authors":"None Raudha Hakim, None Nurmaiyasa Marsaoly, None Muhammad Arby Somadayo","doi":"10.47577/technium.v17i.10073","DOIUrl":"https://doi.org/10.47577/technium.v17i.10073","url":null,"abstract":"Land transportation mode is the main means of transportation to reach campus II Unkhair Gambesi which can be accessed using motorbikes and public transportation. Ternate City is one of the cities in North Maluku Province which has many important activities in the fields of education, politics, and economy. In addition, the center of government of North Maluku province is also still in the Ternate City area, so it also has an impact on the development of the lives of the people of Ternate City. This study aims to determine the effect of cost and travel time on the selection of transportation modes between private vehicles (motorcycles) and public transportation using the state preference method. This study uses the Stated preference method used for an approach by using respondents' opinions on various alternative options on the attributes of travel costs and travel time to transportation modes Private Vehicles (Motorcycles) and Public Transportation Case Study: Central Ternate – Campus II Unkhair Gambesi. The results of this study used linear regression analysis and the binary logit method. And it can be concluded that the chance of choosing a Private Vehicle (Motorcycle) is 74% while the chance of choosing public transportation is 26%.","PeriodicalId":490649,"journal":{"name":"Technium","volume":"128 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135161846","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 : 2023-11-01DOI: 10.47577/technium.v17i.10041
None Untari
The development of a food estate area in Merauke requires the availability of adequate resources in terms of quality and quantity. The research objective is to analyze the availability of resources in the development of industrial estates based on agricultural production produced in the development of food estates . The research was conducted in the food estate development area, namely Merauke Regency, analyzing secondary data. The data were analyzed from spatial data and then analyzed using a qualitative descriptive analysis approach. Some observation indicators are data on the availability of agricultural land for cultivation, analysis of potential water sources and needs, availability of human resources, and supporting infrastructure. The results of the analysis show that the availability of Merauke's land resources for the food estate is sufficient in terms of quantity and quality for agricultural cultivation, but has not been supported by adequate human resources, namely farmers and agricultural extension workers. Likewise with the availability of water resources and infrastructure facilities such as road networks, ports, electricity, and irrigation networks, it is necessary to revitalize existing facilities and add basic infrastructure networks for the development of a food estate area in Merauke.
{"title":"Availability of Land, Water, Human and Technology Resources in the Development of Food Estate Areas in Merauke-Indonesia","authors":"None Untari","doi":"10.47577/technium.v17i.10041","DOIUrl":"https://doi.org/10.47577/technium.v17i.10041","url":null,"abstract":"The development of a food estate area in Merauke requires the availability of adequate resources in terms of quality and quantity. The research objective is to analyze the availability of resources in the development of industrial estates based on agricultural production produced in the development of food estates . The research was conducted in the food estate development area, namely Merauke Regency, analyzing secondary data. The data were analyzed from spatial data and then analyzed using a qualitative descriptive analysis approach. Some observation indicators are data on the availability of agricultural land for cultivation, analysis of potential water sources and needs, availability of human resources, and supporting infrastructure. The results of the analysis show that the availability of Merauke's land resources for the food estate is sufficient in terms of quantity and quality for agricultural cultivation, but has not been supported by adequate human resources, namely farmers and agricultural extension workers. Likewise with the availability of water resources and infrastructure facilities such as road networks, ports, electricity, and irrigation networks, it is necessary to revitalize existing facilities and add basic infrastructure networks for the development of a food estate area in Merauke.","PeriodicalId":490649,"journal":{"name":"Technium","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135162026","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}
The importance of occupational safety and health (OHS) in the construction industry, especially in the construction project of the operating room at Dr.H. Chasan Boesoirie Ternate Hospital. This study used a questionnaire method and direct observation of respondents involved in the project. The results showed that the project had met occupational standards safety, but there was a need for improvement in the availability of flammable materials and evacuation routes. The company provides adequate PPE and health facilities. Prioritizing OHS in the project can avoid losses and prevent accidents, thus providing long-term benefits.
{"title":"Occupational Safety and Health (OSH) in Construction Projects in Ternate City","authors":"None Endah Harisun, None Hery Purnomo, None Suhartini Suhartini","doi":"10.47577/technium.v17i.10057","DOIUrl":"https://doi.org/10.47577/technium.v17i.10057","url":null,"abstract":"The importance of occupational safety and health (OHS) in the construction industry, especially in the construction project of the operating room at Dr.H. Chasan Boesoirie Ternate Hospital. This study used a questionnaire method and direct observation of respondents involved in the project. The results showed that the project had met occupational standards safety, but there was a need for improvement in the availability of flammable materials and evacuation routes. The company provides adequate PPE and health facilities. Prioritizing OHS in the project can avoid losses and prevent accidents, thus providing long-term benefits.","PeriodicalId":490649,"journal":{"name":"Technium","volume":"142 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135162041","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 : 2023-11-01DOI: 10.47577/technium.v17i.10054
None Mukma Inna, None Achmad Fuad, None Abdul Mubarak, None Amal Khairan, None Arifandy Mario Mamonto, None Rosihan
The Information and Communication Technology Unit (ICTU) is a technical implementation unit in the field of information and communication technology development and management. Currently, Khairun University's ICTU is undertaking a software development project, one of which involves creating an application called "Permata". In the process of developing this application, one of the common challenges faced is estimating the project costs for software development, as the developers do not yet have a standard method to determine the costs of software development. The objective of this research is to produce a Use Case Point application for estimating the costs of software development at ICTU, Khairun University. The Use Case Point (UCP) method is derived from the Function Point Analysis (FPA) method and aims to provide a simple estimation method oriented toward software project objects. The software objects involved in this method are Actor Types (UAW), Use Case Weight (UUCW), Technical System Development Complexity (TF), and Development Environment Complexity (EF). The estimated time value for developing the Permata application is 1,389.844855 man-hours, equivalent to approximately 1.904 months. The estimated cost for the Permata application is Rp129,099,127.
{"title":"Use Case Point Methods For Analysis of Software Development Cost In Information Communication Technology Units of Khairun University","authors":"None Mukma Inna, None Achmad Fuad, None Abdul Mubarak, None Amal Khairan, None Arifandy Mario Mamonto, None Rosihan","doi":"10.47577/technium.v17i.10054","DOIUrl":"https://doi.org/10.47577/technium.v17i.10054","url":null,"abstract":"The Information and Communication Technology Unit (ICTU) is a technical implementation unit in the field of information and communication technology development and management. Currently, Khairun University's ICTU is undertaking a software development project, one of which involves creating an application called \"Permata\". In the process of developing this application, one of the common challenges faced is estimating the project costs for software development, as the developers do not yet have a standard method to determine the costs of software development. The objective of this research is to produce a Use Case Point application for estimating the costs of software development at ICTU, Khairun University. The Use Case Point (UCP) method is derived from the Function Point Analysis (FPA) method and aims to provide a simple estimation method oriented toward software project objects. The software objects involved in this method are Actor Types (UAW), Use Case Weight (UUCW), Technical System Development Complexity (TF), and Development Environment Complexity (EF). The estimated time value for developing the Permata application is 1,389.844855 man-hours, equivalent to approximately 1.904 months. The estimated cost for the Permata application is Rp129,099,127.","PeriodicalId":490649,"journal":{"name":"Technium","volume":"136 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135162046","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 : 2023-11-01DOI: 10.47577/technium.v17i.10098
None Akhmad Tajuddin Tholaby MS
The Short Moving Average (SMA) forecasting method is one of the most widely used forecasting methods, especially for processing data with a high level of variation and is not linear with time. However, opportunities to develop and improve forecasting performance using the SMA method are still wide open. The performance of a forecasting method can be seen from the distribution of errors. SMA does not see and does not sort the type of input data that will be processed into a forecast value, whether the input data has small or large variations, or has outlier data. If the input data has an outlier, then that outlier can make the forecasting performance not good. One of the efforts to improve SMA forecasting performance is by filtering outlier data. In this study, a comparison was made of the forecasting results for SMA using outlier filtering with the forecasting results for SMA not using outlier filtering. The next step is to compare the error values, namely those that produce the smallest Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE) values. From the results of the study it can be seen that the performance of SMA using the Boxplot filtering method gives better forecasting results than those without using outlier filtering.
{"title":"Comparison of Forecasting Accuracy Using the Short Moving Average (SMA) Method Using Boxplot Outlier Filtering and Not Using Outlier Filtering for Data that has a high level of variation","authors":"None Akhmad Tajuddin Tholaby MS","doi":"10.47577/technium.v17i.10098","DOIUrl":"https://doi.org/10.47577/technium.v17i.10098","url":null,"abstract":"The Short Moving Average (SMA) forecasting method is one of the most widely used forecasting methods, especially for processing data with a high level of variation and is not linear with time. However, opportunities to develop and improve forecasting performance using the SMA method are still wide open. The performance of a forecasting method can be seen from the distribution of errors. SMA does not see and does not sort the type of input data that will be processed into a forecast value, whether the input data has small or large variations, or has outlier data. If the input data has an outlier, then that outlier can make the forecasting performance not good. One of the efforts to improve SMA forecasting performance is by filtering outlier data. In this study, a comparison was made of the forecasting results for SMA using outlier filtering with the forecasting results for SMA not using outlier filtering. The next step is to compare the error values, namely those that produce the smallest Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE) values. From the results of the study it can be seen that the performance of SMA using the Boxplot filtering method gives better forecasting results than those without using outlier filtering.","PeriodicalId":490649,"journal":{"name":"Technium","volume":"5 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135162048","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 : 2023-11-01DOI: 10.47577/technium.v17i.10044
None Johan Karim, None Damis Hardiantono, None Hariyanto Hariyanto
National energy policy and renewable energy development policy towards 23% in 2025, the first target is to increase solar energy capacity as a priority where development includes rooftop solar power plants, large scale solar power plants, and floating solar power plants. The legal basis for the development of renewable energy is the policies of the central government and regional governments through regulations made. South Papua with the potential of Rawa Biru which is one of the sources of clean water in Merauke. Rawa Biru with a watershed area (DAS) of 4,791.671 km2 and an actual water body area of 95 ha. Simulation is done using Google Earth and Solargis software. Potential of floating PV in Rawa Biru with data maps, solar azimuth and PV configurations. Area of 95 ha floating PV potential 53,25 MWp, generating potential 79,93 GWh/year and area of 8 ha floating PV potential 2,14 MWp, generating potential 3,24 GWh/year.
{"title":"Floating Photovoltaic Potential in the Rawa Biru Area of South Papua Province","authors":"None Johan Karim, None Damis Hardiantono, None Hariyanto Hariyanto","doi":"10.47577/technium.v17i.10044","DOIUrl":"https://doi.org/10.47577/technium.v17i.10044","url":null,"abstract":"National energy policy and renewable energy development policy towards 23% in 2025, the first target is to increase solar energy capacity as a priority where development includes rooftop solar power plants, large scale solar power plants, and floating solar power plants. The legal basis for the development of renewable energy is the policies of the central government and regional governments through regulations made. South Papua with the potential of Rawa Biru which is one of the sources of clean water in Merauke. Rawa Biru with a watershed area (DAS) of 4,791.671 km2 and an actual water body area of 95 ha. Simulation is done using Google Earth and Solargis software. Potential of floating PV in Rawa Biru with data maps, solar azimuth and PV configurations. Area of 95 ha floating PV potential 53,25 MWp, generating potential 79,93 GWh/year and area of 8 ha floating PV potential 2,14 MWp, generating potential 3,24 GWh/year.","PeriodicalId":490649,"journal":{"name":"Technium","volume":"84 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135166812","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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