Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN - STMIK Sinar Nusantara)
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Sistem Pengelompokan Siswa Berdasarkan Tingkat Kedisiplinan Menggunakan Metode Naïve Bayes Classifier
Full text linkDiscipline is a very important thing in the educational process. Discipline will succeed if it is applied to students correctly. Student discipline is that every student follows every rule and order that has been set by the school. At SMK Muhammadiyah 2 Sukoharjo student discipline. Declining discipline at SMK Muhammadiah 2 Sukoharjo is marked by the increase in points of violation from students. The purpose of this study was to apply the nave Bayes method in the classification of student discipline levels at SMK Muhammadiyah 2 Sukoharjo. With this information will be obtained that can be used for information on which students need to be given Counseling Guidance to provide direction and guidance to students. The attributes used are cases of fights, not attending apples, not carrying out picket, not entering without explanation, arriving late, noisy in class. Test results with 490 records with a portion of 75% training data and 25% test data. And produces an accuracy of 76%
Prediksi Penjualan Kertas Menggunakan Metode Double Exponential Smoothing
Full text linkOne of the important thing in business is the inventory of goods and services. Business goal can be reached when business owner know how the number of their inventory. Printing business is using forecasting model in their purchasing raw materials to estimate and calculate their selling prediction. That model is used to minimize economic losses when the costumer canceled order because paper was ran out and to prevent paper damage does not occur date to storage that to long. Double Exponential Smoothing method is used in this research to predict the sales of Paper A and HVS A3+ paper and calculates the prediction error with MAPE (Mean Absolute Percentage Error). This study aims to make an accurate forecasting application. The prediction results from application are in the form of prediction calculations for sales in the following month which will be used to optimize the purchase of paper to be sold. In applying the research results of Paper A and HVS A3 +, the best alpha was obtained in the 12th period, namely 0.3 and 0.6 with a MAPE error of 12% and 18% and an accuracy rate of 88% and 82% where the alpha was used to predict period 13 and produces a forecast value of 446 for Paper A and 474 for HVS A3
Sistem Pakar Diagnosa Virus Corona Dengan Metode Naïve Bayes
Full text linkHumans being are faced with non-natural disasters which have bad effect for population on the world. This non-natural disaster is called Corona Virus Disease (COVID-19). This COVID-19 will become a pandemic in 2020. This types of COVID-19 is coming from the Orthocronavirinae. It belongs to the Coronaviridae and the Nidovirales. This type of that virus has caused some disease to birds, mammals and also human being. Therefore, the research was conducted. The result of this research will give the information about system which related the classification human being according to their transmission to the body. This research used naïve bayes method. The result of this research is diagnostic system with the level of accuracy 94%. Thus, COVID-19 diagnostic expert system used to know the level of COVID -19 infections to human being. It can help the user knowing the next treatment
Application Of Fuzzy C-Means Clustering for Mapping Agent
No full textStrict business competition in the field of mountain equipment providers and selling the same product makes the mapping of onsight agents needed to determine the priority of agents prioritized. Fuzzy C-means is one of the data grouping techniques in which the existence of each data point in a cluster is determined by the level of membership. The purpose of this study is to design and make applications for grouping agents. The research method used is direct interview to obtain information in the form of ordered item data. The design model uses the System Development Life Cycle (SDLC). The system design method used is the Unified Modeling Language (UML). Agent mapping system with web-based fuzzy c-means clustering uses the PHP and MySQL programming languages as the database. The results of this study are in the form of three data clusters that can be used to support decisions for priority and from 30 data agents, the first cluster consists of 15 agents, the second cluster consists of 1 agent, and the third cluster consists of 14 agent
Analisis Forensik Pada Aplikasi Peduli Lindungi Terhadap Kebocoran Data Pribadi
Full text linkPPeduli Lindungi Application is an application coming from the Ministry of Communication and Information Technology Indonesia which has function to tracking and stop spread of Coronavirus Disease (COVID-19). Its application has personal data which includes, registration number, date of birth, full name, address and telephone number. However, Peduli Lindungi Application is one of the factors which are caused of personal data breach. Digital forensics is a scientific field that has functions to find out facts and finding a crime case. It wishes that will get directions whether this application is safety or not. The researchers hope that the people will not be afraid to use Peduli Lindungi Application and also can support the government programs to prevent the spread of Covid-19. The result of forensic analysis with static and dynamic analysis models, it shows that Peduli Lindungi Application is safe to used and it is not as dangerous applications. The results of this analysis show that Peduli Lindungi application has their own permission configurations based on the users. There is no malware in the script or activities and there is no database and data stored in smartphone memory as well as some encrypted program data. Personal data breach is caused by lacking of people knowledge to protect their personal data. Moreover , sometimes people forget to protect their security of their smartphones
Sistem Seleksi Calon Siswa Bidik Misi Menggunakan Metode Simple Additive Weighting
Full text linkVocational Senior High School of Muhammadiyah 2 Sukoharjo, opens Student Scholarship of Bidik Misi to accept new students in every admission period of academic year. This school has difficulty to decide the candidates of scholarship grantee. In this research, there is solution by creating selection system to select the candidate of scholarship grantee using Simple Additive Weighting method. This research uses parents’ income, family living cost, students’ grades, and students’ achievement. This research also uses a Usecase Diagram to design the system. To test the system, this research uses Blackbox testing method. There are 25 valid questions in research result so that this application is suitable to select the new students. Based in its result, additive simple weighting method can be used as a method to support decision, especially in the selection of scholarship grantee candidates
Penentuan Penerima Bantuan Rumah Tidak Layak Huni Menggunakan Metode Simple Additive Weghting
Full text linkUninhabitable Housing Assistance (RTLH) is a government program which distribute to village office, it has purpose to improve the life quality of community. Poor people can life convenient with Uninhibitable Houses Assistence. Determination of social assistence construction of Uninhabitable Houses is going to do by relying on the intitution. The purpose of this research is creating a decision support system that can help to determine the appropriate poor people are receiving social assistence of Uninhabitable House (RTLH) using simple additive weighting (SAW) method. It is used the creteria such as, the monthly income, the occupation, the total of burden, the condition of house wall, the condition of house floor, the condition of house roof, and the condition of bathroom. The result of this research is the beneficial system for receiver of Uninhabitable Houses
Algoritma Apriori Untuk Penentuan Assosiasi Penjualan Barang
Full text linkThe increasing of selling basic needs make the company has to provide a lot of goods. The data will be growing up with increasing the transaction at Sari Bumi store. All this time, the selling basic needs at Sari Bumi Store unstructured well so that needed an application with produce important information that can decide marketing strategies. In this research, Apriori algorithm is used to determine association rules. This method was chosen because it is one of the classic data mining algorithms to look for patterns of relationships between one or more items in one dataset. A priori algorithms can help companies in developing marketing strategies. The result of this research is combination between 4 item set with a minimum support of 30% and minimum confidence of 60%
Rekomendasi Wisata Umbul dengan K-Means Clustering
Full text linkDistrict Klaten has many springs that are used by people for many things; one of them used for tourist attractions is umbul tourism. It is difficult to use K-Means Clustering Method for determine umbul tourism according to classification and spread in district Klaten. K-Means Clustering is a method of grouping data by taking parameters of a number clusters, and partitioning data into clusters, based on similarities between data in one cluster and dissimilarities between different clusters, the center of the cluster is the average of the cluster member values it called as centroid. The results of this study are grouping the umbul truism which are divided into three clusters namely Enough, Good and The Best. The result of the data, there are 4 umbul tourisms in the first cluster is Beautiful category, namely Tirtomoyo, Buto, Pancuran, and Besuki. In the third cluster of umbul tourism has good category, namely Tirto Mulyani umbul, Gedaren, Sumber Nila, Manten, Sigedang, and Kajen. In the best category in the second cluster has 8 umbul tourisms, namely Nila umbul, Tirto Mulyono, Ingas, Lumban Tirto, Ponggok, Tirto Raharjo, Jolotundo, and Tirtomulyono.Keywords: K-Means Clustering, Umbul, Umbul Category, Tourist Destinatio
Rekomendasi Barang Di Toko Elektrik Menggunakan Algoritma Apriori
Full text linkEach company or organization which wants to survive needs to determine the right business strategies. Sales data for products made by the company will get a lot of data. So it is very unfortunate if there is not repetition analyzing. Its offered variety products with a wide range of products, and sometimes the brand influence people to buy the product, to know the highest sales products, it needs to know the relationship between one product to others, one of them is existing algorithms in mining data algorithms. They are algorithms apriori to be informed, and it can help of this program, products which appear simultaneously knowable. The purpose of the research is to determine the recommendation of goods so that purchases of goods stock are efficient. Apriori algorithms including the type of association rules in mining data. The one-step analysis association phase which is gotten the attention of many researchers to produce efficient algorithms is the analysis of patterns of high frequency (frequent pattern mining). Important or not an association can be identified by the two benchmarks, namely: support and confidence. Support (support value) is the percentage of the combination of these items in the database, while confidence (value certainty) is a strong relationship between the items in the rules of the association. Apriori algorithm can be helpful for the development of marketing strategies. From the validity testing result, the data is efficient if the minimum support more than 10% and the minimum confidence of more than 50%. The calculation needs two different minimum support and minimum confidence to know the best result. The problem is how to increase sales, and find out the interest of buyers in the product. And the results are obtained to decide the layout of the products in the shop window as an effort to increase sales in the store.Keywords: Mining Data, Good Recommendations, Apriori, Algorith