Pub Date : 2023-05-01DOI: 10.18860/jrmm.v2i4.16808
Dewi Ismiarti, Jami'atu Sholichati Nafisah, Evawati Alisah, Imam Sujarwo
Fuzzy Time Series is a method used to predict data. Fuzzy Time Series is a development of time series analysis, where Fuzzy Time Series uses the concept of fuzzy sets as the basis for its calculations. In addition, Fuzzy Time Series has various methods such as Cheng and Lee Fuzzy Time Series. In this study, Fuzzy Time Series is used to predict data on the price development of cayenne pepper in Indonesia. By using these two methods, an analysis of the level of accuracy is then carried out using several methods. So that the results obtained in this study are the MAE value of the Cheng method 669,162 and the Lee method 502,285, the MSE value of the Cheng method 1.261.393 and the Lee method 699.030.1, the MPE value of the Cheng method 0,01% and the Lee method -0,02%, and The MAPE value of the Cheng method is 1,24% and the Lee method is 0.92%. The Lee method has a smaller error value than the Cheng method, so that the Lee method is declared to be better than the Cheng method.
{"title":"Perbandingan Uji Akurasi Fuzzy Time Series Model Cheng Dan Lee Dalam Memprediksi Perkembangan Harga Cabai Rawit","authors":"Dewi Ismiarti, Jami'atu Sholichati Nafisah, Evawati Alisah, Imam Sujarwo","doi":"10.18860/jrmm.v2i4.16808","DOIUrl":"https://doi.org/10.18860/jrmm.v2i4.16808","url":null,"abstract":"Fuzzy Time Series is a method used to predict data. Fuzzy Time Series is a development of time series analysis, where Fuzzy Time Series uses the concept of fuzzy sets as the basis for its calculations. In addition, Fuzzy Time Series has various methods such as Cheng and Lee Fuzzy Time Series. In this study, Fuzzy Time Series is used to predict data on the price development of cayenne pepper in Indonesia. By using these two methods, an analysis of the level of accuracy is then carried out using several methods. So that the results obtained in this study are the MAE value of the Cheng method 669,162 and the Lee method 502,285, the MSE value of the Cheng method 1.261.393 and the Lee method 699.030.1, the MPE value of the Cheng method 0,01% and the Lee method -0,02%, and The MAPE value of the Cheng method is 1,24% and the Lee method is 0.92%. The Lee method has a smaller error value than the Cheng method, so that the Lee method is declared to be better than the Cheng method.","PeriodicalId":270235,"journal":{"name":"Jurnal Riset Mahasiswa Matematika","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124048517","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}
Cryptography is one method that can be used to secure a message by hiding the original text. This study uses the One Time Pad (OTP) algorithm to secure a message and the Linear Congruential Generator (LCG) algorithm as a key generator. The purpose of this study is to describe the key generation process using the LCG algorithm, the encryption and decryption process of messages using the OTP algorithm. The process of encrypting and decrypting messages using the OTP algorithm requires a key as long as the original message and must be random. Therefore, a random number generation process is carried out using the LCG algorithm before encoding the message. The results of this study are the LCG algorithm is able to build dynamic keys with the condition that the length of the period must be greater than or equal to the length of the plaintext. The process of encoding messages using the OTP algorithm has a high level of security because the number of characters used is more and the process of sending messages is easier. The resulting ciphertext is a very random and unreadable message that is difficult to decipher.
密码学是一种可以通过隐藏原始文本来保护消息的方法。本研究使用One Time Pad (OTP)算法来保护讯息，并使用线性同余生成器(Linear Congruential Generator, LCG)算法作为密钥生成器。本研究的目的是描述使用LCG算法的密钥生成过程，以及使用OTP算法的消息加解密过程。使用OTP算法加密和解密消息的过程需要一个与原始消息一样长的密钥，并且必须是随机的。因此，在对消息进行编码之前，使用LCG算法进行随机数生成过程。本研究的结果是LCG算法能够在周期长度必须大于等于明文长度的条件下构建动态密钥。使用OTP算法对消息进行编码的过程具有很高的安全性，因为使用的字符数量更多，发送消息的过程也更容易。由此产生的密文是一个非常随机和不可读的消息，很难破译。
{"title":"Pengamanan Pesan Menggunakan Algoritma One Time Pad dengan Linear Congruential Generator sebagai Pembangkit Kunci","authors":"Jamilatul Maghfiroh, Turmudi Turmudi, Ellys Susanti","doi":"10.18860/jrmm.v2i3.16770","DOIUrl":"https://doi.org/10.18860/jrmm.v2i3.16770","url":null,"abstract":"Cryptography is one method that can be used to secure a message by hiding the original text. This study uses the One Time Pad (OTP) algorithm to secure a message and the Linear Congruential Generator (LCG) algorithm as a key generator. The purpose of this study is to describe the key generation process using the LCG algorithm, the encryption and decryption process of messages using the OTP algorithm. The process of encrypting and decrypting messages using the OTP algorithm requires a key as long as the original message and must be random. Therefore, a random number generation process is carried out using the LCG algorithm before encoding the message. The results of this study are the LCG algorithm is able to build dynamic keys with the condition that the length of the period must be greater than or equal to the length of the plaintext. The process of encoding messages using the OTP algorithm has a high level of security because the number of characters used is more and the process of sending messages is easier. The resulting ciphertext is a very random and unreadable message that is difficult to decipher.","PeriodicalId":270235,"journal":{"name":"Jurnal Riset Mahasiswa Matematika","volume":"198 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115839857","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 : 2023-03-01DOI: 10.18860/jrmm.v2i3.16415
B. Rahmatullah, Imam Sujarwo, Erna Herawati
Since the pandemic of Covid-19 was happened in Indonesia, the government shared the letter of The Ministry of Education and Higher Culture Education Directorate No.1, year 2020 about prevention of the spread of Corona Virus Disease (Covid-19) in higher education. Through the letter, The Ministry of Education and Culture gave an instruction for college to organize online learning and suggested students to study at their home. Online learning which was considered as a strategy then became a controversy because it needed adaption. This sudden change from normal learning to online learning caused many responses from students. The aim of this research was to analyze student sentiment or responses on online learning in this pandemic era of Covid-19 in Indonesia by using data which had been collected using questionnaire and processed using naïve bayes classifier method. This research was case study descriptive quantitative research. The research was done by collecting the data first. The data was collected through questionnaire with the question about their opinion on online learning in this pandemic Covid-19 era. The data was 157 student’s data opinion on online learning. After the data was collected, the data was cleaned first from question mark and the words which didn’t give an effect in sentiment analysis. After the data was cleaned, then the result of the classification will be showed as well as the accuracy which the model earned. The result showed that online learning had negative sentiment more than positive sentiment. The height of negative sentiment was caused by discomfort of student in online learning. The word which frequently showed was ‘tidak efektif’, ‘susah’, and ‘tugas’. The accuracy of this model was 75% when the result of this accuracy was good result in classification.
{"title":"Analisis Sentimen Mahasiswa Terhadap Perkuliahan Dalam Jaringan Menggunakan Metode Naïve Bayes Classifier","authors":"B. Rahmatullah, Imam Sujarwo, Erna Herawati","doi":"10.18860/jrmm.v2i3.16415","DOIUrl":"https://doi.org/10.18860/jrmm.v2i3.16415","url":null,"abstract":"Since the pandemic of Covid-19 was happened in Indonesia, the government shared the letter of The Ministry of Education and Higher Culture Education Directorate No.1, year 2020 about prevention of the spread of Corona Virus Disease (Covid-19) in higher education. Through the letter, The Ministry of Education and Culture gave an instruction for college to organize online learning and suggested students to study at their home. Online learning which was considered as a strategy then became a controversy because it needed adaption. This sudden change from normal learning to online learning caused many responses from students. The aim of this research was to analyze student sentiment or responses on online learning in this pandemic era of Covid-19 in Indonesia by using data which had been collected using questionnaire and processed using naïve bayes classifier method. This research was case study descriptive quantitative research. The research was done by collecting the data first. The data was collected through questionnaire with the question about their opinion on online learning in this pandemic Covid-19 era. The data was 157 student’s data opinion on online learning. After the data was collected, the data was cleaned first from question mark and the words which didn’t give an effect in sentiment analysis. After the data was cleaned, then the result of the classification will be showed as well as the accuracy which the model earned. The result showed that online learning had negative sentiment more than positive sentiment. The height of negative sentiment was caused by discomfort of student in online learning. The word which frequently showed was ‘tidak efektif’, ‘susah’, and ‘tugas’. The accuracy of this model was 75% when the result of this accuracy was good result in classification.","PeriodicalId":270235,"journal":{"name":"Jurnal Riset Mahasiswa Matematika","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133769207","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 : 2023-03-01DOI: 10.18860/jrmm.v2i3.16335
Laura Agustina, Imam Sujarwo, Muhammad Khudzaifah
The issue of message security or an information is very important. A science that studies about securing the confidentiality of messages using passwords is called cryptography. To enhance security, two algorithms are combined to secure messages. Super encryption is a concept that uses a combination of two or more substitution and permutation (transposition) cryptography techniques to obtain an algorithm that is more difficult to crack. The first thing to do is to encrypt the message using a substitution technique (Cipher Substitution), then re-encrypt it using a permutation technique (Cipher Transposition). In this study, two cryptographic algorithms will be combined to build super encryption using the Vigenere Cipher and Bifid Cipher algorithms to secure messages. The message encryption process is using the Vigenere Cipher algorithm for the first encryption process, then continued using the Bifid Cipher algorithm for the second encryption process. The encryption process is done the other way around, starting from the back of the encryption process. The combination of these two algorithms results in more secure message security.
{"title":"Membangun Super Enkripsi untuk Mengamankan Pesan","authors":"Laura Agustina, Imam Sujarwo, Muhammad Khudzaifah","doi":"10.18860/jrmm.v2i3.16335","DOIUrl":"https://doi.org/10.18860/jrmm.v2i3.16335","url":null,"abstract":"The issue of message security or an information is very important. A science that studies about securing the confidentiality of messages using passwords is called cryptography. To enhance security, two algorithms are combined to secure messages. Super encryption is a concept that uses a combination of two or more substitution and permutation (transposition) cryptography techniques to obtain an algorithm that is more difficult to crack. The first thing to do is to encrypt the message using a substitution technique (Cipher Substitution), then re-encrypt it using a permutation technique (Cipher Transposition). In this study, two cryptographic algorithms will be combined to build super encryption using the Vigenere Cipher and Bifid Cipher algorithms to secure messages. The message encryption process is using the Vigenere Cipher algorithm for the first encryption process, then continued using the Bifid Cipher algorithm for the second encryption process. The encryption process is done the other way around, starting from the back of the encryption process. The combination of these two algorithms results in more secure message security.","PeriodicalId":270235,"journal":{"name":"Jurnal Riset Mahasiswa Matematika","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125202295","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 : 2023-03-01DOI: 10.18860/jrmm.v2i3.16355
Anis Putri Rahmadhani, Ari Kusumastuti, Juhari Juhari
This study discusses the analysis of the Susceptible-Exposed-Infected-Recovered (SEIR) epidemic model using the fourth-order Runge-Kutta method on the spread of COVID-19 in Indonesia by taking into account the factors limiting community interaction and the percentage of vaccination as model parameters. The purpose of this study was to determine the application of the Susceptible–Exposed–Infected–Recovered (SEIR) model using the fourth-order Runge-Kutta method in dealing with COVID-19 in Indonesia. The steps in analyzing the model are to determine the stability of the model that produces local asymptotic stability, then carry out the implementation as well as simulation using the fourth-order Runge-Kuta method in dealing with COVID-19 in Indonesia. The calculation results show the effect of limiting community interaction and vaccination in reducing cases of COVID-19 infection. Where, when limiting public interaction, the number of cases of COVID-19 infection is lower than before the restrictions on community interaction were carried out, and the higher percentage of vaccinations also resulted in more sloping infection cases. This study provides information that if restrictions on community interaction continue to be carried out by continuing to increase the percentage of vaccinations, it is estimated that the daily graph of positive cases of COVID-19 will be increasingly sloping and close to zero. Thus, the addition of new cases will decrease and it is hoped that the COVID-19 pandemic will end soon.
{"title":"Analisis Model Epidemi SEIR Menggunakan Metode Runge-Kutta Orde 4 pada Penyebaran COVID-19 di Indonesia","authors":"Anis Putri Rahmadhani, Ari Kusumastuti, Juhari Juhari","doi":"10.18860/jrmm.v2i3.16355","DOIUrl":"https://doi.org/10.18860/jrmm.v2i3.16355","url":null,"abstract":"This study discusses the analysis of the Susceptible-Exposed-Infected-Recovered (SEIR) epidemic model using the fourth-order Runge-Kutta method on the spread of COVID-19 in Indonesia by taking into account the factors limiting community interaction and the percentage of vaccination as model parameters. The purpose of this study was to determine the application of the Susceptible–Exposed–Infected–Recovered (SEIR) model using the fourth-order Runge-Kutta method in dealing with COVID-19 in Indonesia. The steps in analyzing the model are to determine the stability of the model that produces local asymptotic stability, then carry out the implementation as well as simulation using the fourth-order Runge-Kuta method in dealing with COVID-19 in Indonesia. The calculation results show the effect of limiting community interaction and vaccination in reducing cases of COVID-19 infection. Where, when limiting public interaction, the number of cases of COVID-19 infection is lower than before the restrictions on community interaction were carried out, and the higher percentage of vaccinations also resulted in more sloping infection cases. This study provides information that if restrictions on community interaction continue to be carried out by continuing to increase the percentage of vaccinations, it is estimated that the daily graph of positive cases of COVID-19 will be increasingly sloping and close to zero. Thus, the addition of new cases will decrease and it is hoped that the COVID-19 pandemic will end soon.","PeriodicalId":270235,"journal":{"name":"Jurnal Riset Mahasiswa Matematika","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128340129","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 : 2023-03-01DOI: 10.18860/jrmm.v2i3.16753
U. Kt, Heni Widayani, A. Kusumastuti
Tuberculosis is an infectious disease caused by Mycobacterium tuberculosis. The disease is considered dangerous because it infects the lungs and other organs of the body and can lead to death. This study discusses a mathematical model for the spread of tuberculosis with two treatment sites as an effort to reduce the transmission rate of TB cases. Treatment for TB patients can be done at home and in hospitals. The purpose of this study was to construct a mathematical model and analyze the qualitative behavior of the TB spread model. The construction of the model uses the SEIR epidemic model which is divided into five subpopulations, namely susceptible subpopulations, latent subpopulations, infected subpopulations receiving treatment at home, and infected subpopulations receiving treatment at the hospital, and cured subpopulations. The analysis of qualitative behavior in the model includes determining the local and global equilibrium and stability points. The results of the analysis shows that the model has two equilibrium points, namely a disease-free equilibrium point and the endemic equilibrium point. The existence of endemic equilibrium point and the local and global stability of the two equilibrium points depend on the basic reproduction number denoted by . If , there is only disease-free equilibrium point. If , there are two equilibrium points, namely the disease-free equilibrium point and the endemic equilibrium point. Stability analysis shows that the disease-free equilibrium point is locally and globally asymptotically stable if . While, if , the endemic equilibrium point will be asymptotically stable locally and globally.
{"title":"Analisis Dinamik Model Infeksi Mikrobakterium Tuberkulosis Dengan Dua Lokasi Pengobatan","authors":"U. Kt, Heni Widayani, A. Kusumastuti","doi":"10.18860/jrmm.v2i3.16753","DOIUrl":"https://doi.org/10.18860/jrmm.v2i3.16753","url":null,"abstract":"Tuberculosis is an infectious disease caused by Mycobacterium tuberculosis. The disease is considered dangerous because it infects the lungs and other organs of the body and can lead to death. This study discusses a mathematical model for the spread of tuberculosis with two treatment sites as an effort to reduce the transmission rate of TB cases. Treatment for TB patients can be done at home and in hospitals. The purpose of this study was to construct a mathematical model and analyze the qualitative behavior of the TB spread model. The construction of the model uses the SEIR epidemic model which is divided into five subpopulations, namely susceptible subpopulations, latent subpopulations, infected subpopulations receiving treatment at home, and infected subpopulations receiving treatment at the hospital, and cured subpopulations. The analysis of qualitative behavior in the model includes determining the local and global equilibrium and stability points. The results of the analysis shows that the model has two equilibrium points, namely a disease-free equilibrium point and the endemic equilibrium point. The existence of endemic equilibrium point and the local and global stability of the two equilibrium points depend on the basic reproduction number denoted by . If , there is only disease-free equilibrium point. If , there are two equilibrium points, namely the disease-free equilibrium point and the endemic equilibrium point. Stability analysis shows that the disease-free equilibrium point is locally and globally asymptotically stable if . While, if , the endemic equilibrium point will be asymptotically stable locally and globally.","PeriodicalId":270235,"journal":{"name":"Jurnal Riset Mahasiswa Matematika","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122868030","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 : 2022-12-31DOI: 10.18860/jrmm.v2i2.15150
Amelia Vega, Imam Sujarwo, Muhammad Khudzaifah
An information is extremely easy to obtain when technology is evolving so fast and it is important to secure the information to avoid irresponsible parties who want to abuse it. Messages that are not safe will harm the owner of the message, therefore a lot of research is related to message security. This study aims to deepen the message security in encoded form using Galois Field polynomials with one of the symmetric encryption algorithms, namely the Hill Cipher algorithm. Encryption is the process of converting a message into a secret code while decryption is the reverse process. The encryption and decryption process in this discussion is carried out by changing the message character into Galois Field polynomial form, then operating calculations based on the Hill Cipher algorithm, and then changing the results of the calculation operations into character form again. Based on the modifications have been made, the encryption and decryption formulas will be multiplied by modulo in polynomials form. In this study, the encryption and decryption keys are in matrix form with elements in it are members of the Galois Field polynomial and the result is a random message of 256 characters in binary bit-8. From this research, we gain insight into the encoding that can be done using polynomials which can be used later in other forms of encoding.
{"title":"Enkripsi dan Dekripsi Pesan Menggunakan Polinomial Galois Field dengan Algoritma Hill Cipher","authors":"Amelia Vega, Imam Sujarwo, Muhammad Khudzaifah","doi":"10.18860/jrmm.v2i2.15150","DOIUrl":"https://doi.org/10.18860/jrmm.v2i2.15150","url":null,"abstract":"An information is extremely easy to obtain when technology is evolving so fast and it is important to secure the information to avoid irresponsible parties who want to abuse it. Messages that are not safe will harm the owner of the message, therefore a lot of research is related to message security. This study aims to deepen the message security in encoded form using Galois Field polynomials with one of the symmetric encryption algorithms, namely the Hill Cipher algorithm. Encryption is the process of converting a message into a secret code while decryption is the reverse process. The encryption and decryption process in this discussion is carried out by changing the message character into Galois Field polynomial form, then operating calculations based on the Hill Cipher algorithm, and then changing the results of the calculation operations into character form again. Based on the modifications have been made, the encryption and decryption formulas will be multiplied by modulo in polynomials form. In this study, the encryption and decryption keys are in matrix form with elements in it are members of the Galois Field polynomial and the result is a random message of 256 characters in binary bit-8. From this research, we gain insight into the encoding that can be done using polynomials which can be used later in other forms of encoding.","PeriodicalId":270235,"journal":{"name":"Jurnal Riset Mahasiswa Matematika","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126020418","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 : 2022-12-31DOI: 10.18860/jrmm.v2i2.14891
Farida Husna, Hairur Rahman, Juhari Juhari
Indonesia is known as a country with a majority Muslim population, this makes the need for clothing in Indonesia must also pay attention to the criteria for Muslim clothing, one of which is the hijab. Business developments in the fashion world, especially hijab, have become a trend setter at this time so that the large amount of data in the fashion business world creates conditions where there are businesspeople who have a lot of data but lack of information from that data. To deal with these conditions, it is necessary to classify the data. A classification is a process to find the same properties in a data set to be classified into different classes. One of the classification methods is the Decision tree using the C4.5 Algorithm. This research aims to determine the model and the accuracy of the C4.5 algorithm in classifying hijab sales from several hijab brands. The Decision tree model is obtained using the C4.5 algorithm with the first root being the price attribute, where the first root is the attribute that most affected the sale of the hijab. The result of calculating the accuracy value is 87% so that the Decision tree model and the classification process using the C4.5 Algorithm are classified as good. This research is expected to help businesspeople in the fashion sector, especially hijab, to find out the factors that influence consumer interest in a hijab product.
{"title":"Implementasi Data Mining Menggunakan Algoritma C4.5 pada Klasifikasi Penjualan Hijab","authors":"Farida Husna, Hairur Rahman, Juhari Juhari","doi":"10.18860/jrmm.v2i2.14891","DOIUrl":"https://doi.org/10.18860/jrmm.v2i2.14891","url":null,"abstract":"Indonesia is known as a country with a majority Muslim population, this makes the need for clothing in Indonesia must also pay attention to the criteria for Muslim clothing, one of which is the hijab. Business developments in the fashion world, especially hijab, have become a trend setter at this time so that the large amount of data in the fashion business world creates conditions where there are businesspeople who have a lot of data but lack of information from that data. To deal with these conditions, it is necessary to classify the data. A classification is a process to find the same properties in a data set to be classified into different classes. One of the classification methods is the Decision tree using the C4.5 Algorithm. This research aims to determine the model and the accuracy of the C4.5 algorithm in classifying hijab sales from several hijab brands. The Decision tree model is obtained using the C4.5 algorithm with the first root being the price attribute, where the first root is the attribute that most affected the sale of the hijab. The result of calculating the accuracy value is 87% so that the Decision tree model and the classification process using the C4.5 Algorithm are classified as good. This research is expected to help businesspeople in the fashion sector, especially hijab, to find out the factors that influence consumer interest in a hijab product.","PeriodicalId":270235,"journal":{"name":"Jurnal Riset Mahasiswa Matematika","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121568445","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 : 2022-12-31DOI: 10.18860/jrmm.v2i2.15668
Muhammad Aris Abdillah, Dewi Ismiarti
The coprime graph of a group G is a graph Γ_G with G is its set of vertices and any two distinct vertices are adjacent if and only if their order are relatively prime. Let p be a prime number, then G_p denotes the multiplicative group of 2×2 upper unitriangular matrices over ring of integers modulo p. The purposes of this research are to study the coprime graph Γ_(G_p ) and find the first and the second Zagreb eccentricity indices of Γ_(G_p ) for p≥3. The results of this research are as follows. First Zagreb eccentricity index of coprime graph Γ_(G_p )isE_1 (Γ_(G_p ))=4p-3. Second Zagreb eccentricity index of coprime graph Γ_(G_p )isE_2 (Γ_(G_p ))=2p-2.
{"title":"Indeks Eksentrisitas Zagreb Pertama dan Kedua Graf Koprima dari Grup Matriks Upper Unitriangular atas Ring Bilangan Bulat Modulo Prima","authors":"Muhammad Aris Abdillah, Dewi Ismiarti","doi":"10.18860/jrmm.v2i2.15668","DOIUrl":"https://doi.org/10.18860/jrmm.v2i2.15668","url":null,"abstract":"The coprime graph of a group G is a graph Γ_G with G is its set of vertices and any two distinct vertices are adjacent if and only if their order are relatively prime. Let p be a prime number, then G_p denotes the multiplicative group of 2×2 upper unitriangular matrices over ring of integers modulo p. The purposes of this research are to study the coprime graph Γ_(G_p ) and find the first and the second Zagreb eccentricity indices of Γ_(G_p ) for p≥3. The results of this research are as follows. First Zagreb eccentricity index of coprime graph Γ_(G_p )isE_1 (Γ_(G_p ))=4p-3. Second Zagreb eccentricity index of coprime graph Γ_(G_p )isE_2 (Γ_(G_p ))=2p-2.","PeriodicalId":270235,"journal":{"name":"Jurnal Riset Mahasiswa Matematika","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123688567","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 : 2022-12-31DOI: 10.18860/jrmm.v2i2.14899
Farrahdilla Sari, A. Kusumastuti, Hisyam Fahmi
Forecasting is importantly in accordance with the planning strategy; therefore it will affect the way of decision making. One of the forecasting methods is Artificial Neural Network with Backpropagation as the algorithm. This research aims to measure the accuracy of the network architecture which is being applied in order to calculate the prediction of the future’s apple paste product monthly demand which was obtained from CV. Bagus Agriseta Mandiri. The data which are being used are 36 monthly data from the year 2017, 2018 and 2019. Furthermore, the data obtained are normalized and divided into two, 66,66% as the data for training process and 33,33% as the data for testing process. Network architecture that is applied in this research is 12 : 10 :1, where 12 are neurons for input layer, 10 are neurons for one hidden layer and 1 is neuron for output layer. The Network with that framework obtained a result 20.161% for MAPE and 79.839% for the accuracy. That model is categorized as good enough for its forecasting ability. Moreover, the network was entirely validated using k-fold cross validation method with . The result obtained as follows: the average of MAPE is 47.079% and the average accuracy is 52.921%. According to it, the entire model can be categorized as good enough in order to run a forecast. As a comparison, another testing has been done with the same fold but different in the network architecture (model 6 – 8 – 1). The second model obtained results as follows: the average of MAPE is 26.74% and the average accuracy is 73.18%, so that the two prediction models’ ability are in the same category, it is good enough to run a forecast.
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