Pub Date : 2022-05-25DOI: 10.14421/jiska.2022.7.2.122-133
Sri Rahayu, Hamdani Hamdani, Ramadiani Ramadiani
One of the professions in the marine sector that is mostly occupied by people living in coastal areas is seaweed cultivation. Seaweed is one of the marine product commodities with great potential to be developed in Indonesia because it has high economic value. One of the areas that are included as producers of Eucheuma Cottonii seaweed is Nunukan Island, which is located in Nunukan Regency, North Kalimantan Province. The main factor that determines success in seaweed cultivation activities is the selection of land locations. Errors in site selection can lead to crop failure and low quality of the seaweed produced. The purpose of this study is to create a decision support system to facilitate and assist the community in selecting the best location for seaweed cultivation quickly and precisely according to the criteria using the Analytical Hierarchy Process (AHP) method to calculate the criteria weights and the Simple Additive Weighting (SAW) method for performing alternative ratings. The criteria used were 7, namely depth, pH, current speed, brightness, temperature, salinity, and dissolved oxygen, while alternative data were 11 points of seaweed cultivation locations on Nunukan Island. Based on the results of the implementation of the two methods, recommendations for two locations for seaweed cultivation are Sei Banjar I and Sei Banjar II with the same preference value of 0.937 which is the highest value compared to other alternatives.
{"title":"Pemilihan Lokasi Budidaya Rumput Laut Menggunakan Metode Analytical Hierarchy Process (AHP) dan Simple Additive Weighting (SAW)","authors":"Sri Rahayu, Hamdani Hamdani, Ramadiani Ramadiani","doi":"10.14421/jiska.2022.7.2.122-133","DOIUrl":"https://doi.org/10.14421/jiska.2022.7.2.122-133","url":null,"abstract":"One of the professions in the marine sector that is mostly occupied by people living in coastal areas is seaweed cultivation. Seaweed is one of the marine product commodities with great potential to be developed in Indonesia because it has high economic value. One of the areas that are included as producers of Eucheuma Cottonii seaweed is Nunukan Island, which is located in Nunukan Regency, North Kalimantan Province. The main factor that determines success in seaweed cultivation activities is the selection of land locations. Errors in site selection can lead to crop failure and low quality of the seaweed produced. The purpose of this study is to create a decision support system to facilitate and assist the community in selecting the best location for seaweed cultivation quickly and precisely according to the criteria using the Analytical Hierarchy Process (AHP) method to calculate the criteria weights and the Simple Additive Weighting (SAW) method for performing alternative ratings. The criteria used were 7, namely depth, pH, current speed, brightness, temperature, salinity, and dissolved oxygen, while alternative data were 11 points of seaweed cultivation locations on Nunukan Island. Based on the results of the implementation of the two methods, recommendations for two locations for seaweed cultivation are Sei Banjar I and Sei Banjar II with the same preference value of 0.937 which is the highest value compared to other alternatives.","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41856616","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 learning process through various interactions and learning experiences has a considerable influence on developing student activity to improve the quality of education. The teacher is the most important factor in determining the success of students in the implementation of the process. The development of the quality and activeness of students in learning is a basic element as a form of success in the learning process which of course not all students have a level of speed in understanding material. This is a concern for schools in improving the quality of education. The purpose of this study was to classify the level of activity of students at SMP ABC using the correlation between grades and the level of student activity who would be recommended to take part in competitions or prospective scholarship recipients. The data source that we used in this study came from the State Junior High School ABC which consists of several variables, including student attendance data, academic scores, psychomotor scores, and affective values. The method used in this research is the Clustering method with the K-means Algorithm. The results of this study can be grouped into 3 clusters including cluster 0 indicating active students as many as 30 students, cluster 1 showing inactive students as many as 8 students, and cluster 2 indicating less active students as many as 21 students.
{"title":"Implementasi Algoritma K-Means Clustering Seleksi Siswa Berprestasi Berdasarkan Keaktifan dalam Proses Pembelajaran","authors":"Falih Pramataning Dewi, Priskila Siwi Aryni, Yuyun Umaidah","doi":"10.14421/jiska.2022.7.2.111-121","DOIUrl":"https://doi.org/10.14421/jiska.2022.7.2.111-121","url":null,"abstract":"The learning process through various interactions and learning experiences has a considerable influence on developing student activity to improve the quality of education. The teacher is the most important factor in determining the success of students in the implementation of the process. The development of the quality and activeness of students in learning is a basic element as a form of success in the learning process which of course not all students have a level of speed in understanding material. This is a concern for schools in improving the quality of education. The purpose of this study was to classify the level of activity of students at SMP ABC using the correlation between grades and the level of student activity who would be recommended to take part in competitions or prospective scholarship recipients. The data source that we used in this study came from the State Junior High School ABC which consists of several variables, including student attendance data, academic scores, psychomotor scores, and affective values. The method used in this research is the Clustering method with the K-means Algorithm. The results of this study can be grouped into 3 clusters including cluster 0 indicating active students as many as 30 students, cluster 1 showing inactive students as many as 8 students, and cluster 2 indicating less active students as many as 21 students.","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44303260","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 : 2022-05-25DOI: 10.14421/jiska.2022.7.2.100-110
Bekti Cahyo Hidayanto, Jessica Patricia Halim, Aura Febriyanti Puspa Sari, M. Alrifqi, Nur Aini Rakhmawati, Izzat Aulia Akbar
Instagram is a social media that has a shopping feature. Instagram can be used for digital advertising, and among them is paid promotion. Paid promotion is a service to promote goods/services on social media. This service offers advantages such as a broad market segment, low cost, and easy technical implementation. Many online shops are willing to spend a lot of money to be promoted. Unfortunately, online shop owners usually do not know how Instagram users respond when they see a paid promotion. Therefore, the purpose of this study is to find out how Instagram users respond to the paid promotion on Instagram. User response data was taken from a questionnaire, then analyzed using the CRI method with the AISAS concept by using 4 models: AISAS, AISS, AIAS, and AIS. As the result, four models showed the CRI is below 50% (AISAS: 2,8%; AIAS: 3%; AISS: 4,5%; AIS: 8,4%). Considering the result, the respondents do not give a good response to the paid promotion service.
{"title":"Respons Pengguna Instagram terhadap Periklanan Paid Promote di Instagram dengan Metode CRI Berkonsep AISAS","authors":"Bekti Cahyo Hidayanto, Jessica Patricia Halim, Aura Febriyanti Puspa Sari, M. Alrifqi, Nur Aini Rakhmawati, Izzat Aulia Akbar","doi":"10.14421/jiska.2022.7.2.100-110","DOIUrl":"https://doi.org/10.14421/jiska.2022.7.2.100-110","url":null,"abstract":"Instagram is a social media that has a shopping feature. Instagram can be used for digital advertising, and among them is paid promotion. Paid promotion is a service to promote goods/services on social media. This service offers advantages such as a broad market segment, low cost, and easy technical implementation. Many online shops are willing to spend a lot of money to be promoted. Unfortunately, online shop owners usually do not know how Instagram users respond when they see a paid promotion. Therefore, the purpose of this study is to find out how Instagram users respond to the paid promotion on Instagram. User response data was taken from a questionnaire, then analyzed using the CRI method with the AISAS concept by using 4 models: AISAS, AISS, AIAS, and AIS. As the result, four models showed the CRI is below 50% (AISAS: 2,8%; AIAS: 3%; AISS: 4,5%; AIS: 8,4%). Considering the result, the respondents do not give a good response to the paid promotion service.","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48744722","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 : 2022-05-25DOI: 10.14421/jiska.2022.7.2.91-99
Qomariyah, M. U. Siregar
Universities as educational institutions have very large amounts of academic data which may not be used properly. The data needs to be analyzed to produce information that can map the distribution of students. Student academic data processing utilizes data mining processes using clustering techniques, K-Means and K-Medoids. This study aims to implement and analyze the comparison of which algorithm is more optimal based on the cluster validation test with the Davies Bouldin Index. The data used are academic data of UIN Sunan Kalijaga students in the 2013-2015 batch. In the k-Means process, the best number of clusters is 5 with a DBI value of 0.781. In the k-Medoids process, the best number of clusters is 3 with a DBI value of 0.929. Based on the value of the DBI validation test, the k-Means algorithm is more optimal than the k-Medoids. So that the cluster of students with the highest average GPA of 3,325 is 401 students.
{"title":"Comparative Study of K-Means Clustering Algorithm and K-Medoids Clustering in Student Data Clustering","authors":"Qomariyah, M. U. Siregar","doi":"10.14421/jiska.2022.7.2.91-99","DOIUrl":"https://doi.org/10.14421/jiska.2022.7.2.91-99","url":null,"abstract":"Universities as educational institutions have very large amounts of academic data which may not be used properly. The data needs to be analyzed to produce information that can map the distribution of students. Student academic data processing utilizes data mining processes using clustering techniques, K-Means and K-Medoids. This study aims to implement and analyze the comparison of which algorithm is more optimal based on the cluster validation test with the Davies Bouldin Index. The data used are academic data of UIN Sunan Kalijaga students in the 2013-2015 batch. In the k-Means process, the best number of clusters is 5 with a DBI value of 0.781. In the k-Medoids process, the best number of clusters is 3 with a DBI value of 0.929. Based on the value of the DBI validation test, the k-Means algorithm is more optimal than the k-Medoids. So that the cluster of students with the highest average GPA of 3,325 is 401 students.","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41559135","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 : 2022-05-25DOI: 10.14421/jiska.2022.7.2.83-90
Imam Riadi, Sunardi, F. Nani
Nowadays developments in information technology are growing rapidly, especially in email. Email became one that almost the whole world had. Email is one of the results of developments in information and communication. Email is widely used to exchange information by sending and receiving data, such as document files, pictures, letters, and others. So much for the crimes that often occur in emails. Email crimes that often occur among them are email spoofing. Email spoofing is a forgery that occurs in the header of the email. So, the email is sent as if it were a valid email. Email spoofing is often used in spamming activities. Crimes committed by cybercrime must leave evidence such as IP Address, sender's email, and time of sending the email. This research will do forensics on email spoofing. The research uses the Live Forensics method, where the computer is used in a powered-on state. The research also uses the NIST (National Institute of Standards Technology) research flow. The email that will be analyzed is in the email header section using 3 tools, namely tracer email analyzer, email dossier, and mail header analysis. This analysis will compare and check the accuracy of the email headers using these tools. Emails suspected of email spoofing will be proven using tools. Based on the 'form' received' and 'Message-ID' headers. Based on the results, the tool that meets the value after the analysis is tracer email analysis.
{"title":"Analisis Forensik pada Email Menggunakan Metode National Institute of Standards Technology","authors":"Imam Riadi, Sunardi, F. Nani","doi":"10.14421/jiska.2022.7.2.83-90","DOIUrl":"https://doi.org/10.14421/jiska.2022.7.2.83-90","url":null,"abstract":"Nowadays developments in information technology are growing rapidly, especially in email. Email became one that almost the whole world had. Email is one of the results of developments in information and communication. Email is widely used to exchange information by sending and receiving data, such as document files, pictures, letters, and others. So much for the crimes that often occur in emails. Email crimes that often occur among them are email spoofing. Email spoofing is a forgery that occurs in the header of the email. So, the email is sent as if it were a valid email. Email spoofing is often used in spamming activities. Crimes committed by cybercrime must leave evidence such as IP Address, sender's email, and time of sending the email. This research will do forensics on email spoofing. The research uses the Live Forensics method, where the computer is used in a powered-on state. The research also uses the NIST (National Institute of Standards Technology) research flow. The email that will be analyzed is in the email header section using 3 tools, namely tracer email analyzer, email dossier, and mail header analysis. This analysis will compare and check the accuracy of the email headers using these tools. Emails suspected of email spoofing will be proven using tools. Based on the 'form' received' and 'Message-ID' headers. Based on the results, the tool that meets the value after the analysis is tracer email analysis.","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48000656","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 : 2022-01-25DOI: 10.14421/jiska.2022.7.1.1-9
Kevin Rafi Adjie Putra Santoso, Asmaul Husna, Nadia Widyawati Putri, Nur Aini Rakhmawati
In this era, technology is increasingly sophisticated, this is evidenced by the number of people using the internet via cell phones, laptops, and other communication tools. One of the developments of this technology is social media such as Instagram. Along with technological developments, Instagram users can upload and share photos and videos using hashtags (#) so that other users can find the results of their posts. Instagram has now become one of the social media used by more than 1 billion people in the world. In this study, the authors wanted to know the dominant topics discussed through the hashtag covidindonesia. This research was conducted using the Latent Dirichlet Allocation (LDA) method. The analysis was carried out after doing text mining on 84 captions from various users on Instagram. To determine the optimal number of topics, by looking at the value of perplexity and topic coherence. The results obtained are the top 5 topics that are the content material in the uploaded video. These topics include covidindonesia, covid_19, pandemics in Indonesia, and discussion of covid-19 virus mutations.
{"title":"Analisis Topik Tagar Covidindonesia pada Instagram Menggunakan Latent Dirichlet Allocation","authors":"Kevin Rafi Adjie Putra Santoso, Asmaul Husna, Nadia Widyawati Putri, Nur Aini Rakhmawati","doi":"10.14421/jiska.2022.7.1.1-9","DOIUrl":"https://doi.org/10.14421/jiska.2022.7.1.1-9","url":null,"abstract":"In this era, technology is increasingly sophisticated, this is evidenced by the number of people using the internet via cell phones, laptops, and other communication tools. One of the developments of this technology is social media such as Instagram. Along with technological developments, Instagram users can upload and share photos and videos using hashtags (#) so that other users can find the results of their posts. Instagram has now become one of the social media used by more than 1 billion people in the world. In this study, the authors wanted to know the dominant topics discussed through the hashtag covidindonesia. This research was conducted using the Latent Dirichlet Allocation (LDA) method. The analysis was carried out after doing text mining on 84 captions from various users on Instagram. To determine the optimal number of topics, by looking at the value of perplexity and topic coherence. The results obtained are the top 5 topics that are the content material in the uploaded video. These topics include covidindonesia, covid_19, pandemics in Indonesia, and discussion of covid-19 virus mutations.","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49220227","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 : 2022-01-25DOI: 10.14421/jiska.2022.7.1.46-55
Tri Widodo, Adam Sekti Aji
Intrusion Detection System (IDS) is one of the technology to ensure the security of computers. IDS is an early detection system in the event of a computer network attack. The IDS will alert the computer network administrator in the event of a computer network attack. IDS also records all attempts and activities aimed at disrupting computer networks and other computer network attacks. The purpose of this study is to implement IDS on network systems and analyze IDS logs to determine the different types of computer network attacks. Logs on the IDS will be analyzed and will be used as leverage to improve computer network security. The research was carried out using the Network Forensic Investigation Framework proposed by Pilli, Joshi, and Niyogi. The stages of the Network Forensic Investigation Framework are used to perform network simulations, analysis, and investigations to determine the types of computer network attacks. The results show that the Network Forensic Investigation Framework facilitates the investigation process when a network attack occurs. The Network Forensic Investigation Framework is effectively used when the computer network has network security support applications such as IDS or others. IDS is effective in detecting network scanning activities and DOS attacks. IDS gives alerts to administrators because there are activities that violate the rules on the IDS.
{"title":"Pemanfaatan Network Forensic Investigation Framework untuk Mengidentifikasi Serangan Jaringan Melalui Intrusion Detection System (IDS)","authors":"Tri Widodo, Adam Sekti Aji","doi":"10.14421/jiska.2022.7.1.46-55","DOIUrl":"https://doi.org/10.14421/jiska.2022.7.1.46-55","url":null,"abstract":"Intrusion Detection System (IDS) is one of the technology to ensure the security of computers. IDS is an early detection system in the event of a computer network attack. The IDS will alert the computer network administrator in the event of a computer network attack. IDS also records all attempts and activities aimed at disrupting computer networks and other computer network attacks. The purpose of this study is to implement IDS on network systems and analyze IDS logs to determine the different types of computer network attacks. Logs on the IDS will be analyzed and will be used as leverage to improve computer network security. The research was carried out using the Network Forensic Investigation Framework proposed by Pilli, Joshi, and Niyogi. The stages of the Network Forensic Investigation Framework are used to perform network simulations, analysis, and investigations to determine the types of computer network attacks. The results show that the Network Forensic Investigation Framework facilitates the investigation process when a network attack occurs. The Network Forensic Investigation Framework is effectively used when the computer network has network security support applications such as IDS or others. IDS is effective in detecting network scanning activities and DOS attacks. IDS gives alerts to administrators because there are activities that violate the rules on the IDS.","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48191947","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 : 2022-01-25DOI: 10.14421/jiska.2022.7.1.56-67
Daru Prasetyawan, Rahmadhan Gatra
Student academic performance is one measure of success in higher education. Prediction of student academic performance is important because it can help in decision-making. K-Nearest Neighbor (K-NN) algorithm is a method that can be used to predict it. Normalization is needed to scale the attribute value, so the data are in a smaller range than the actual data. Feature selection is used to eliminate irrelevant features. Data cleaning from outliers in the dataset aims to delete data that can affect the classification process. In the classification process, the dataset is divided into a training set by 80% and a validation set by 20% using the cross-validation method. The classification model that is formed is tested using data that is separate from the training data and is evaluated using a confusion matrix. As an evaluation, the K-NN model has 95.85% average accuracy, 95.97% average precision, and 95.84% average recall.
{"title":"Algoritma K-Nearest Neighbor untuk Memprediksi Prestasi Mahasiswa Berdasarkan Latar Belakang Pendidikan dan Ekonomi","authors":"Daru Prasetyawan, Rahmadhan Gatra","doi":"10.14421/jiska.2022.7.1.56-67","DOIUrl":"https://doi.org/10.14421/jiska.2022.7.1.56-67","url":null,"abstract":"Student academic performance is one measure of success in higher education. Prediction of student academic performance is important because it can help in decision-making. K-Nearest Neighbor (K-NN) algorithm is a method that can be used to predict it. Normalization is needed to scale the attribute value, so the data are in a smaller range than the actual data. Feature selection is used to eliminate irrelevant features. Data cleaning from outliers in the dataset aims to delete data that can affect the classification process. In the classification process, the dataset is divided into a training set by 80% and a validation set by 20% using the cross-validation method. The classification model that is formed is tested using data that is separate from the training data and is evaluated using a confusion matrix. As an evaluation, the K-NN model has 95.85% average accuracy, 95.97% average precision, and 95.84% average recall.","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48635187","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 : 2022-01-25DOI: 10.14421/jiska.2022.7.1.33-45
Imam Riadi, Abdul Fadlil, Fahmi Auliya Tsani
Cryptography is one of the most popular methods in data security by making data very difficult to read or even unreadable. One of the well-known techniques or algorithms in cryptography is Vigenere Cipher. This classic algorithm is classified as a polyalphabetic substitution cipher-based algorithm. Therefore, this algorithm tends to only handle data in text form. By this research, a console-based application has been developed which is made from PHP programming language to be able to encrypt and decrypt digital image media using Vigenere Cipher. The encryption process is done by first converting a digital image into a base64 encoding format so that the encryption process can be carried out using the tabula recta containing the radix-64 letter arrangement used for base64 encoding. Conversely, the decryption process is carried out by restoring the encrypted file using radix-64 letters, so we get the image file in the base64 encoding format. Then, the image with the base64 encoding format is decoded into the original file. The encryption process took less than 0,2 seconds and 0.19 seconds for the decryption process and 33.34% for average file size addition on the encrypted file from the original file size. Testing on ten different images with different sizes and dimensions showed a 100% success rate which means this research was successfully carried out.
{"title":"Pengamanan Citra Digital Berbasis Kriptografi Menggunakan Algoritma Vigenere Cipher","authors":"Imam Riadi, Abdul Fadlil, Fahmi Auliya Tsani","doi":"10.14421/jiska.2022.7.1.33-45","DOIUrl":"https://doi.org/10.14421/jiska.2022.7.1.33-45","url":null,"abstract":"Cryptography is one of the most popular methods in data security by making data very difficult to read or even unreadable. One of the well-known techniques or algorithms in cryptography is Vigenere Cipher. This classic algorithm is classified as a polyalphabetic substitution cipher-based algorithm. Therefore, this algorithm tends to only handle data in text form. By this research, a console-based application has been developed which is made from PHP programming language to be able to encrypt and decrypt digital image media using Vigenere Cipher. The encryption process is done by first converting a digital image into a base64 encoding format so that the encryption process can be carried out using the tabula recta containing the radix-64 letter arrangement used for base64 encoding. Conversely, the decryption process is carried out by restoring the encrypted file using radix-64 letters, so we get the image file in the base64 encoding format. Then, the image with the base64 encoding format is decoded into the original file. The encryption process took less than 0,2 seconds and 0.19 seconds for the decryption process and 33.34% for average file size addition on the encrypted file from the original file size. Testing on ten different images with different sizes and dimensions showed a 100% success rate which means this research was successfully carried out.","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45210660","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 : 2022-01-25DOI: 10.14421/jiska.2022.7.1.68-74
Asdar, R. Saputra, Ika Purwanti Ningrum
A letter is a form, stroke, or symbol writing system. Any information obtained from a sentence depends on the letters are written clearly. Finding written hijaiyah letters can be recognized by humans, but will be difficult if a computer tries to recognize them. The reason system is difficult is because of the large variety of different letters. This study aims to make it easier for someone to learn to recognize hijaiyah letters by using the Local Binary Pattern method for the feature extraction process. The results of feature extraction will take the maximum value of the histogram of each letter. And results feature extraction will be carried out classification process using the Fuzzy K-Nearest Neighbor algorithm until finally hijaiyah letters can be recognized. Based on experimental results that have been carried out, the highest level of accuracy is obtained when the amount of training data is 154 data and the number of data testing is 29 data, resulting in an accuracy rate of 96.55%.
{"title":"Pengenalan Pola Huruf Hijaiyah dengan Metode Local Binary Pattern Menggunakan Algoritma Fuzzy K-Nearest Neighbor","authors":"Asdar, R. Saputra, Ika Purwanti Ningrum","doi":"10.14421/jiska.2022.7.1.68-74","DOIUrl":"https://doi.org/10.14421/jiska.2022.7.1.68-74","url":null,"abstract":"A letter is a form, stroke, or symbol writing system. Any information obtained from a sentence depends on the letters are written clearly. Finding written hijaiyah letters can be recognized by humans, but will be difficult if a computer tries to recognize them. The reason system is difficult is because of the large variety of different letters. This study aims to make it easier for someone to learn to recognize hijaiyah letters by using the Local Binary Pattern method for the feature extraction process. The results of feature extraction will take the maximum value of the histogram of each letter. And results feature extraction will be carried out classification process using the Fuzzy K-Nearest Neighbor algorithm until finally hijaiyah letters can be recognized. Based on experimental results that have been carried out, the highest level of accuracy is obtained when the amount of training data is 154 data and the number of data testing is 29 data, resulting in an accuracy rate of 96.55%.","PeriodicalId":34216,"journal":{"name":"JISKA Jurnal Informatika Sunan Kalijaga","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44676408","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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