Y. Sibaroni, S. S. Prasetiyowati, Mitha Putrianty Fairuz, Muhammad Damar, Rafika Salis
This study proposes several alternative optimal routes on traffic-prone routes using Ant Colony Optimization (ACO) and Firefly Algorithm (FA). Two methods are classified as the metaheuristic method, which means that they can solve problems with complex optimization and will get the solution with the best results. Comparison of alternative routes generated by the two algorithms is measured based on several parameters, namely alpha and beta in determination of the best alternative route. The results obtained are that the alternative route produced by FA is superior to ACO, with an accuracy of 88%. This is also supported by the performance of the FA algorithm which is generally superior, where the resulting alternative route is shorter in distance, time, running time and there is no influence on the alpha parameter value. But in each iteration, the number of alternative routes generated is less. The contribution of this research is to provide information about the best algorithm between ACO and FA in providing the most optimal alternative route based on the fastest travel time. The recommended alternative path is a path that is sufficient for cars to pass, because the selection takes into account the size of the road capacity.
{"title":"Performance Analysis of ACO and FA Algorithms on Parameter Variation Scenarios in Determining Alternative Routes for Cars as a Solution to Traffic Jams","authors":"Y. Sibaroni, S. S. Prasetiyowati, Mitha Putrianty Fairuz, Muhammad Damar, Rafika Salis","doi":"10.15575/join.v7i1.797","DOIUrl":"https://doi.org/10.15575/join.v7i1.797","url":null,"abstract":"This study proposes several alternative optimal routes on traffic-prone routes using Ant Colony Optimization (ACO) and Firefly Algorithm (FA). Two methods are classified as the metaheuristic method, which means that they can solve problems with complex optimization and will get the solution with the best results. Comparison of alternative routes generated by the two algorithms is measured based on several parameters, namely alpha and beta in determination of the best alternative route. The results obtained are that the alternative route produced by FA is superior to ACO, with an accuracy of 88%. This is also supported by the performance of the FA algorithm which is generally superior, where the resulting alternative route is shorter in distance, time, running time and there is no influence on the alpha parameter value. But in each iteration, the number of alternative routes generated is less. The contribution of this research is to provide information about the best algorithm between ACO and FA in providing the most optimal alternative route based on the fastest travel time. The recommended alternative path is a path that is sufficient for cars to pass, because the selection takes into account the size of the road capacity.","PeriodicalId":32019,"journal":{"name":"JOIN Jurnal Online Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76747574","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}
Hasbi Atsqalani, Nur Hayatin, Christian Sri Kusuma Aditya
Sentiment analysis is a computational study of a sentiment opinion and an overflow of feelings expressed in textual form. Twitter has become a popular social network among Indonesians. As a public figure running for president of Indonesia, public opinion is very important to see and consider the popularity of a presidential candidate. Media has become one of the important tools used to increase electability. However, it is not easy to analyze sentiments from tweets on Twitter apps, because it contains unstructured text, especially Indonesian text. The purpose of this research is to classify Indonesian twitter data into positive and negative sentiments polarity using Support Vector Machine and Query Expansion Ranking so that the information contained therein can be extracted and from the observed data can provide useful information for those in need. Several stages in the research include Crawling Data, Data Preprocessing, Term Frequency – Inverse Document Frequency (TF-IDF), Feature Selection Query Expansion Ranking, and data classification using the Support Vector Machine (SVM) method. To find out the performance of this classification process, it will be entered into a configuration matrix. By using a discussion matrix, the results show that calcification using the proposed reached accuracy and F-measure score in 77% and 68% respectively.
{"title":"Sentiment Analysis from Indonesian Twitter Data Using Support Vector Machine And Query Expansion Ranking","authors":"Hasbi Atsqalani, Nur Hayatin, Christian Sri Kusuma Aditya","doi":"10.15575/join.v7i1.669","DOIUrl":"https://doi.org/10.15575/join.v7i1.669","url":null,"abstract":"Sentiment analysis is a computational study of a sentiment opinion and an overflow of feelings expressed in textual form. Twitter has become a popular social network among Indonesians. As a public figure running for president of Indonesia, public opinion is very important to see and consider the popularity of a presidential candidate. Media has become one of the important tools used to increase electability. However, it is not easy to analyze sentiments from tweets on Twitter apps, because it contains unstructured text, especially Indonesian text. The purpose of this research is to classify Indonesian twitter data into positive and negative sentiments polarity using Support Vector Machine and Query Expansion Ranking so that the information contained therein can be extracted and from the observed data can provide useful information for those in need. Several stages in the research include Crawling Data, Data Preprocessing, Term Frequency – Inverse Document Frequency (TF-IDF), Feature Selection Query Expansion Ranking, and data classification using the Support Vector Machine (SVM) method. To find out the performance of this classification process, it will be entered into a configuration matrix. By using a discussion matrix, the results show that calcification using the proposed reached accuracy and F-measure score in 77% and 68% respectively.","PeriodicalId":32019,"journal":{"name":"JOIN Jurnal Online Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88830332","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}
Y. A. Gerhana, Aaz Muhammad Hafidz Azis, D. R. Ramdania, Wildan Budiawan Dzulfikar, A. R. Atmadja, D. Suparman, Ayu Puji Rahayu
Abstract— Speech recognition technology is used in learning to read letters in the Qur'an. This study aims to implement the CNN algorithm in recognizing the results of introducing the pronunciation of the hijaiyah letters. The pronunciation sound is extracted using the Mel-frequency cepstral coefficients (MFCC) model and then classified using a deep learning model with the CNN algorithm. This system was developed using the CRISP-DM model. Based on the results of testing 616 voice data of 28 hijaiyah letters, the best value was obtained for accuracy of 62.45%, precision of 75%, recall of 50% and f1-score of 58%.
{"title":"Automatic Detection of Hijaiyah Letters Pronunciation using Convolutional Neural Network Algorithm","authors":"Y. A. Gerhana, Aaz Muhammad Hafidz Azis, D. R. Ramdania, Wildan Budiawan Dzulfikar, A. R. Atmadja, D. Suparman, Ayu Puji Rahayu","doi":"10.15575/join.v7i1.882","DOIUrl":"https://doi.org/10.15575/join.v7i1.882","url":null,"abstract":"Abstract— Speech recognition technology is used in learning to read letters in the Qur'an. This study aims to implement the CNN algorithm in recognizing the results of introducing the pronunciation of the hijaiyah letters. The pronunciation sound is extracted using the Mel-frequency cepstral coefficients (MFCC) model and then classified using a deep learning model with the CNN algorithm. This system was developed using the CRISP-DM model. Based on the results of testing 616 voice data of 28 hijaiyah letters, the best value was obtained for accuracy of 62.45%, precision of 75%, recall of 50% and f1-score of 58%.","PeriodicalId":32019,"journal":{"name":"JOIN Jurnal Online Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89100127","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}
Music interest is diverse yet enticing to be a part of knowledge discovery. It influences how people feel, study, work, etc. A lot of things are to be considered in producing brand new music with its correlation to its genre. We have already collected the dataset that we can utilize in this research, which is the history of every song listened to by several users in a total of 20.000 records from a million song dataset. This study implements the Apriori algorithm which can handle a large amount of data while simplifying the data to create a recommendation system where the result is a pattern from the music genre according to the interests of each user with the help of the RapidMiner tool. The purpose of this research is that the pattern which has been found can become a reference for music producers in terms of making or distributing their brand-new music. The result of the best combination of genres states that listeners of the rock genre will also hear the pop genre with a combination frequency of 50, support value of 21.2%, and confidence value of 51%.
{"title":"Implementation of Apriori Algorithm for Music Genre Recommendation","authors":"Michael Henry, Wiryanata Chandra, Amalia Zahra","doi":"10.15575/join.v7i1.819","DOIUrl":"https://doi.org/10.15575/join.v7i1.819","url":null,"abstract":"Music interest is diverse yet enticing to be a part of knowledge discovery. It influences how people feel, study, work, etc. A lot of things are to be considered in producing brand new music with its correlation to its genre. We have already collected the dataset that we can utilize in this research, which is the history of every song listened to by several users in a total of 20.000 records from a million song dataset. This study implements the Apriori algorithm which can handle a large amount of data while simplifying the data to create a recommendation system where the result is a pattern from the music genre according to the interests of each user with the help of the RapidMiner tool. The purpose of this research is that the pattern which has been found can become a reference for music producers in terms of making or distributing their brand-new music. The result of the best combination of genres states that listeners of the rock genre will also hear the pop genre with a combination frequency of 50, support value of 21.2%, and confidence value of 51%.","PeriodicalId":32019,"journal":{"name":"JOIN Jurnal Online Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75898952","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}
With the entry into the era of Industrial Revolution 4.0, the development of digitization of various aspects at the village level began. The level of use of mobile devices in the commercial transactions of society is now a massive number of users. It happens not only in large transactions but also in small transactions. With the community's high interest in the use of smartphone devices, this is a different opportunity to explore the potential of each village by helping the community, tiny and medium enterprises in conducting transactions, sales, and marketing online through the village government website. The village information system itself requires an e-commerce feature on its page to help small and medium enterprises in the area to sell products online through a simple page display. This research aims to design and develop new features of the village system that plays a role in the field of e-commerce with the Direct Message transaction method. The system development methodology used is Agile with Scrum as a framework. The Agile Model is a short-term development model that requires rapid adaptation and development to changes in any form. This e-commerce feature is for local communities, especially Micro, Small, and Medium Enterprises, so their products' marketing reach is even more outstanding while being recorded in the village system.
{"title":"E-Commerce For Village Information System Using Agile Methodology","authors":"L. Fitriani, Prayoga Hakim, R. M. Al Haq","doi":"10.15575/join.v7i1.825","DOIUrl":"https://doi.org/10.15575/join.v7i1.825","url":null,"abstract":"With the entry into the era of Industrial Revolution 4.0, the development of digitization of various aspects at the village level began. The level of use of mobile devices in the commercial transactions of society is now a massive number of users. It happens not only in large transactions but also in small transactions. With the community's high interest in the use of smartphone devices, this is a different opportunity to explore the potential of each village by helping the community, tiny and medium enterprises in conducting transactions, sales, and marketing online through the village government website. The village information system itself requires an e-commerce feature on its page to help small and medium enterprises in the area to sell products online through a simple page display. This research aims to design and develop new features of the village system that plays a role in the field of e-commerce with the Direct Message transaction method. The system development methodology used is Agile with Scrum as a framework. The Agile Model is a short-term development model that requires rapid adaptation and development to changes in any form. This e-commerce feature is for local communities, especially Micro, Small, and Medium Enterprises, so their products' marketing reach is even more outstanding while being recorded in the village system.","PeriodicalId":32019,"journal":{"name":"JOIN Jurnal Online Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79330407","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}
Iman Setiawan, J. Junaidi, Fadjryani Fadjryani, Fika Reski Amaliah
Central Sulawesi Province in Indonesia has great potential for horticultural commodities, namely local red onion Palu. In the current climate change, local farmers are still watering plants in the conventional way. The automatic watering system simplifies the work of local farmers. This device uses a soil moisture sensor as a soil moisture detector and Arduino as a program brain. This study aims to determine the position of soil moisture sensor, the optimal length of watering time and analyze the quality of data stored. The experiment was carried out using a Completely Randomized Design (CRD). The position of the soil moisture sensor was analyzed by Profile Analysis. The optimal length of watering time was determined by Analysis of Variance (ANOVA) and Least Significant Difference (LSD). The quality of data stored was determined by a number of missing values and frequency of watering. The results showed that in soil planting media the position of soil moisture sensor had no significant effect, while in others planting media (water and combination of water and soil) the position of the sensor had a significant effect. The optimal watering time was 3 seconds. The stored data has low quality in terms of missing values and lack of consistency.
{"title":"Automatic Plant Watering System for Local Red Onion Palu using Arduino","authors":"Iman Setiawan, J. Junaidi, Fadjryani Fadjryani, Fika Reski Amaliah","doi":"10.15575/join.v7i1.813","DOIUrl":"https://doi.org/10.15575/join.v7i1.813","url":null,"abstract":"Central Sulawesi Province in Indonesia has great potential for horticultural commodities, namely local red onion Palu. In the current climate change, local farmers are still watering plants in the conventional way. The automatic watering system simplifies the work of local farmers. This device uses a soil moisture sensor as a soil moisture detector and Arduino as a program brain. This study aims to determine the position of soil moisture sensor, the optimal length of watering time and analyze the quality of data stored. The experiment was carried out using a Completely Randomized Design (CRD). The position of the soil moisture sensor was analyzed by Profile Analysis. The optimal length of watering time was determined by Analysis of Variance (ANOVA) and Least Significant Difference (LSD). The quality of data stored was determined by a number of missing values and frequency of watering. The results showed that in soil planting media the position of soil moisture sensor had no significant effect, while in others planting media (water and combination of water and soil) the position of the sensor had a significant effect. The optimal watering time was 3 seconds. The stored data has low quality in terms of missing values and lack of consistency.","PeriodicalId":32019,"journal":{"name":"JOIN Jurnal Online Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75445951","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}
Keystroke Dynamics Authentication (KDA) is a technique used to recognize somebody dependent on typing pattern or typing rhythm in a system. Everyone's typing behavior is considered unique. One of the numerous approaches to secure private information is by utilizing a password. The development of technology is trailed by the human requirement for security concerning information and protection since hacker ability of information burglary has gotten further developed (hack the password). So that hackers can use this information for their benefit and can disadvantage others. Hence, for better security, for example, fingerprint, retina scan, et cetera are enthusiastically suggested. But these techniques are considered costly. The advantage of KDA is the user would not realize that the system is using KDA. Accordingly, we proposed the combination of Naïve Bayes and MHR (Mean of Horner’s Rule) to classify the individual as an attacker or a non-attacker. We use Naïve Bayes because it is better for classification and simple to implement than another. Furthermore, MHR is better for KDA if combined with the classification method which is based on previous research. This research showed that False Acceptance Rate (FAR) and Accuracy are improving than the previous research.
{"title":"Analysis of the Combination of Naïve Bayes and MHR (Mean of Horner’s Rule) for Classification of Keystroke Dynamic Authentication","authors":"Zamah Sari, Didih Rizki Chandranegara, Rahayu Nurul Khasanah, Hardianto Wibowo, Wildan Suharso","doi":"10.15575/join.v7i1.839","DOIUrl":"https://doi.org/10.15575/join.v7i1.839","url":null,"abstract":"Keystroke Dynamics Authentication (KDA) is a technique used to recognize somebody dependent on typing pattern or typing rhythm in a system. Everyone's typing behavior is considered unique. One of the numerous approaches to secure private information is by utilizing a password. The development of technology is trailed by the human requirement for security concerning information and protection since hacker ability of information burglary has gotten further developed (hack the password). So that hackers can use this information for their benefit and can disadvantage others. Hence, for better security, for example, fingerprint, retina scan, et cetera are enthusiastically suggested. But these techniques are considered costly. The advantage of KDA is the user would not realize that the system is using KDA. Accordingly, we proposed the combination of Naïve Bayes and MHR (Mean of Horner’s Rule) to classify the individual as an attacker or a non-attacker. We use Naïve Bayes because it is better for classification and simple to implement than another. Furthermore, MHR is better for KDA if combined with the classification method which is based on previous research. This research showed that False Acceptance Rate (FAR) and Accuracy are improving than the previous research.","PeriodicalId":32019,"journal":{"name":"JOIN Jurnal Online Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75984985","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 paper provides a data visualization and analysis of the COVID-19 vaccination program. Important information such as which countries have the highest vaccination rates and numbers. In addition to the types of vaccines used and used by countries in the world, an infographic on the geographic distribution of vaccine use is also shown. To model the obtained data, daily vaccination rates were modeled by linear regression in which five sample countries with different vaccination ranges were processed using data science approach, namely, linear regression. The modeling results show a gradient coefficient that represents an increase in vaccine rates. The prediction results showed that the highest rate of increase in daily vaccination was 1,826,126 additional vaccines per day.
{"title":"Data Visualization of COVID-19 Vaccination Progress and Prediction Using Linear Regression","authors":"H. H. Nuha, Ahmad Abo Absa","doi":"10.15575/join.v7i1.736","DOIUrl":"https://doi.org/10.15575/join.v7i1.736","url":null,"abstract":"This paper provides a data visualization and analysis of the COVID-19 vaccination program. Important information such as which countries have the highest vaccination rates and numbers. In addition to the types of vaccines used and used by countries in the world, an infographic on the geographic distribution of vaccine use is also shown. To model the obtained data, daily vaccination rates were modeled by linear regression in which five sample countries with different vaccination ranges were processed using data science approach, namely, linear regression. The modeling results show a gradient coefficient that represents an increase in vaccine rates. The prediction results showed that the highest rate of increase in daily vaccination was 1,826,126 additional vaccines per day.","PeriodicalId":32019,"journal":{"name":"JOIN Jurnal Online Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84606801","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}
Zulham Zulham, Ega Evinda Putri, Buyung Solihin Hasugian
The Medan Marelan Health Center is one of the health centers in the city of Medan. The supply of medicines is considered necessary so that these medicines can still be available at any time with various types and functions. In order not to experience difficulties in distributing medicines and anticipating the supply of medicines in the Puskesmas, research was carried out using the Data Mining method. In this study, a test will be carried out on the Association Rule which is used as a solution to problems with the pattern of the drug procurement system, and will display information about the value of support and confidence from each Data Mining process. Tests in this study using Weka Software to determine the procurement of drugs that are often needed. Information obtained from the stages of the FP-Growth Algorithm is to produce patterns in the procurement of medicines, and an itemset combination pattern has been formed using the FP-Growth Algorithm method so that the results of this study can be used in drug supply effectively and efficiently.
{"title":"Pattern Analysis of Drug Procurement System With FP-Growth Algorithm","authors":"Zulham Zulham, Ega Evinda Putri, Buyung Solihin Hasugian","doi":"10.15575/join.v7i1.841","DOIUrl":"https://doi.org/10.15575/join.v7i1.841","url":null,"abstract":"The Medan Marelan Health Center is one of the health centers in the city of Medan. The supply of medicines is considered necessary so that these medicines can still be available at any time with various types and functions. In order not to experience difficulties in distributing medicines and anticipating the supply of medicines in the Puskesmas, research was carried out using the Data Mining method. In this study, a test will be carried out on the Association Rule which is used as a solution to problems with the pattern of the drug procurement system, and will display information about the value of support and confidence from each Data Mining process. Tests in this study using Weka Software to determine the procurement of drugs that are often needed. Information obtained from the stages of the FP-Growth Algorithm is to produce patterns in the procurement of medicines, and an itemset combination pattern has been formed using the FP-Growth Algorithm method so that the results of this study can be used in drug supply effectively and efficiently.","PeriodicalId":32019,"journal":{"name":"JOIN Jurnal Online Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79049071","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}
Infrastructure Section, Information and Communication Technology Development Division, South Tangerang City Communication and Information Office, one of the main tasks and functions is to provide services and management of internet network infrastructure for all Regional Apparatus Organizations (OPD) in South Tangerang City. The implementation of the Infrastructure Section is constrained by the problem of employee competence that has not reached the standard in internet network management and service, from these problems the researcher intends to evaluate governance using the COBIT 5 framework and ISO/IEC 38500 with recommendations for improvement in the Infrastructure Section. This study uses PAM (Process Assessment Model) with the Guttman scale to determine the results and level of capability. The use of COBIT 5 in this research will focus on the domain of EDM (Evaluate Direct Monitor) point 04, Ensure Resource Management and MEA (Monitor, Evaluate and Assessment) point 01, Performance and Conformance. The results and the level of capability obtained during the research were level 2 Managed Process with a value of 2.46 with a gap of 0.54. The level expected by the Infrastructure Section is at level 3 Established Process with a value of 3.00. Recommendations for achieving Level 3 are used ISO/IEC 38500.
{"title":"Evaluation of Information Technology Governance Using COBIT 5 and ISO/IEC 38500","authors":"Tubagus Toifur, Kusrini Kusrini, A. Budi","doi":"10.15575/join.v7i1.814","DOIUrl":"https://doi.org/10.15575/join.v7i1.814","url":null,"abstract":"Infrastructure Section, Information and Communication Technology Development Division, South Tangerang City Communication and Information Office, one of the main tasks and functions is to provide services and management of internet network infrastructure for all Regional Apparatus Organizations (OPD) in South Tangerang City. The implementation of the Infrastructure Section is constrained by the problem of employee competence that has not reached the standard in internet network management and service, from these problems the researcher intends to evaluate governance using the COBIT 5 framework and ISO/IEC 38500 with recommendations for improvement in the Infrastructure Section. This study uses PAM (Process Assessment Model) with the Guttman scale to determine the results and level of capability. The use of COBIT 5 in this research will focus on the domain of EDM (Evaluate Direct Monitor) point 04, Ensure Resource Management and MEA (Monitor, Evaluate and Assessment) point 01, Performance and Conformance. The results and the level of capability obtained during the research were level 2 Managed Process with a value of 2.46 with a gap of 0.54. The level expected by the Infrastructure Section is at level 3 Established Process with a value of 3.00. Recommendations for achieving Level 3 are used ISO/IEC 38500.","PeriodicalId":32019,"journal":{"name":"JOIN Jurnal Online Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81603743","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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