IMPLEMENTASI DATA MINING UNTUK MENGETAHUI POLA PEMBELIAN OBAT MENGGUNAKAN ALGORITMA APRIORI

Competition in the business world requires entrepreneurs to think of finding a way or method to increase the transaction of goods sold. The purpose of this research is to provide drug stock data that is widely purchased by pharmacy customers at Kimia Farma, Green Lake branch in Jakarta. The algorithm used in this study is a priori to determine the relationship between the frequency of sales of drug brands most frequently purchased by customers. The association pattern formed with a minimum support of 40% and a minimum value of 70% confidence produces 17 association rules. The strong rules obtained are that if you buy a 500Mg Ponstan KPL @ 100, you will buy an Incidal OD 10Mg Cap with a support value of 59% and a confidence value of 84%. A priori algorithm can be used by companies to develop marketing strategies in marketing products by examining consumer purchasing patterns.

ANALISIS PERBANDINGAN PELACAKAN OBJEK MENGGUNAKAN ALGORITMA HORN-SCHUNCK DAN LUCAS-KANADE

Object tracking one of computer vision. Computer vision similar to human eye function. The difficulty is to detect presence an object and object tracking application made. Object tracking used in aircraft, track cars, human body detectors at airports, a regulator the number of vehicles pass and navigation tools on robots. This study is to identify objects that pass in frame. This research also count the number of objects that pass in one frame. Object tracking done by comparing two algorithms namely Horn-Schunck and Lucas-Kanade. Both algorithms tested using the Source Block Parameter and Function Block Parameter. The test carried out with video resolution 120x160 and the position camera is 2-4 m. The object tracking test is conducted in the duration of 110-120 seconds. Stages tracking object was thresholding, filtering and region successfully obtain object binary video. The Lucas-Kanade has faster in identifying objects compared to the Horn-Schunck algorithm.

KOMPRESI FILE MENGGUNAKAN ALGORITMA LEMPEL ZIV WELCH (LZW)

In the field of information technology, data communication is closely related to file delivery. The size of the file is sometimes a constraint in the delivery process. Large files will take longer delivery times compared to files with smaller sizes. Therefore, to handle the problem, one of them by means of compression. This study uses an experimental method with a waterfall development model with analysis, design, coding, and testing. This application applies the Ziv Welch Lempel (LZW) algorithm. The Ziv Welch Lemp Algorithm (LZW) is included in the lossless compression technique, which is a compression technique that does not change the original data. The result of a compression assessment used the Lempel Ziv Welch (LZW) algorithm shows the average rate of compression ratio and for all types of text files by 51.04% with an average of 2.56 seconds, for an image file type of 37.26% with an average time of 0.44 seconds. Based on the average percentage of the compression ratio for all file types tested using the LZW algorithm (Lemp Ziv Welch) is 40.40% with an average time required is 1.81 seconds.

PELUANG HUBUNGAN KARAKTERISTIK MAHASISWA BARU DENGAN MOTIVASINYA MASUK ILMU KOMPUTER

Various motivational factors can influence prospective new students at Pakuan University (Unpak) when choosing a Computer Science Department as their majors. In order to be able to compete for better quality, Unpak is expected to be able to improve its excellent service, so that the needs and desires of the new students when deciding to join the Computer Science Department can be fulfilled. In this study, a survey of new students from the Department of Computer Science about their motivation to join the Department is conducted to find out what new students want when they decide to join. Furthermore, based on the survey, the Chi-Square method and Bayes method are used to get the probability of the relationship between the characteristics of new students and their motivation to go to the College when choosing the Department. The results show that there is a significant relationship between the characteristics of new students with motivation, which can be seen from the Gender, Regional Origin, Previous Information about Computer Science program and Computer Science Program Media including those that are combined in the above categories, except for Gender. It shows the greatest opportunity occurred in the characteristics of new students to the motivation of 1; 0.806; 0.750 and 0.742.

PERBANDINGAN KINERJA METODE PRA-PEMROSESAN DALAM PENGKLASIFIKASIAN OTOMATIS DOKUMEN PATEN

This paper presents a performance analysis and comparison of several pre-processing methods used in automatic patent classification with graph kernels for Support Vector Machine (SVM). The pre-processing methods are based on the data transform techniques, namely data scaling, data centering, data standardization, data normalization, the Box-Cox transform and the Yeo-Johnson transform. The automatic patent classification is designed to classify an input of patent citation graphs into one of 10 possible classes of the International Patent Classification (IPC). The input is taken with various background conditions. The experiments showed that the best result is achieved when the pre-processing method is data normalization, achieving a classification accuracy of up to 85.33.15% for the KEHL and 93.80% for the KVHL. In contrast, for the KEHG, the preprocessing method application decreased the accuracy.

IMPLEMENTASI DATA MINING UNTUK MENGETAHUI POLA PEMBELIAN OBAT MENGGUNAKAN ALGORITMA APRIORI

Competition in the business world requires entrepreneurs to think of finding a way or method to increase the transaction of goods sold. The purpose of this research is to provide drug stock data that is widely purchased by pharmacy customers at Kimia Farma, Green Lake branch in Jakarta. The algorithm used in this study is a priori to determine the relationship between the frequency of sales of drug brands most frequently purchased by customers. The association pattern formed with a minimum support of 40% and a minimum value of 70% confidence produces 17 association rules. The strong rules obtained are that if you buy a 500Mg Ponstan KPL @ 100, you will buy an Incidal OD 10Mg Cap with a support value of 59% and a confidence value of 84%. A priori algorithm can be used by companies to develop marketing strategies in marketing products by examining consumer purchasing patterns.

KAMUS DIGITAL TANAMAN OBAT MENGGUNAKAN ALGORITMA ROCCHIO BERBASIS MOBILE

Digital dictionaries have been widely used to facilitate word processing and word search through digital media such as mobile phones. Society generally knows the efficacy and how to mix medicinal plants from the experience of previous parents or through books and writings. Searching through books or writings requires a short time compared to searching through digital media, one of which is a digital dictionary. The research aims to create a digital dictionary of mobile-based medicinal plants which has a search facility based on the words entered, for example, the contents of the medicinal plants. The digital dictionary application of medicinal plants uses a search method with the Rocchio algorithm with relevance feedback techniques to check the proximity of the query to the average document relevant to the level of similarity calculation through the stages of tokenizing, filtering, stemming, and Term Weighting with a total data of 200 medicinal plants.

PENENTUAN DAERAH PRIORITAS PELAYANAN AKTA KELAHIRAN DENGAN METODE K-NN DAN K-MEANS

Population Data is individual data or aggregate data that is structured as a result of Population Registration and Civil Registration activities. Birth Certificate is a Civil Registration Deed as a result of recording the birth event of a baby whose birth is reported to be registered on the Family Card and given a Population Identification Number (NIK) as a basis for obtaining other community services. From the total number of integrated birth certificate reporting for the 2018 Population Administration Information System (SIAK) totaling 570,637 there were 503,946 reported late and only 66,691 were reported publicly. Clustering is a method used to classify data that is similar to others in one group or similar data to other groups. K-Nearest Neighbor is a method for classifying objects based on learning data that is the closest distance to the test data. k-means is a method used to divide a number of objects into groups based on existing categories by looking at the midpoint. In data mining preprocesses, data is cleaned by filling in the blank data with the most dominating data, and selecting attributes using the information gain method. Based on the k-nearest neighbor method to predict delays in reporting and the k-means method to classify priority areas of service with 10,000 birth certificate data on birth certificates in 2019 that have good enough performance to produce predictions with an accuracy of 74.00% and with K = 2 on k-means produces a index davies bouldin of 1,179

SISTEM PENUNJANG KEPUTUSAN PEMILIHAN INDUK AYAM KUB TERBAIK DENGAN METODE FUZZY DAN VIKOR

Kampung Unggul Superior Chicken (KUB) is a native native chicken selection from the Animal Research Center (Balitnak). KUB chicken has the advantage of low incubation and high egg production, so it becomes a parent producer of many DOC (female line). Currently consumption of native chicken meat and eggs in the community from year to year has increased while its production has not been able to fully meet the needs of the community. Some of the problems in maintaining KUB hens are not optimal body weight, length of time in laying eggs and even a small amount of egg production quality from selected prospective broodies originating from KUB hens who have high productivity in laying eggs. to overcome these problems, an application system is needed, one of which is a decision support system application. This application can provide recommendations in the selection of the best KUB hens so that the hens can be maintained intensively so that the supply of chicken meat and eggs can meet the needs of the community. There are several methods that can be used to determine the selection of the best KUB Parent, including using the Vikor method. Vikor is used to overcome the problem of complex multi-criteria systems that focus on ranking and selection of an alternative, while to determine the weighting using the Fuzzy Method. The results of this study are in the form of an application system that can help breeders / enclosure technicians in determining the selection of the Best KUB Chicken Parent. The level of system accuracy using the Vikor and Fuzzy methods was obtained at 77.2% of the 9 test data used.

SISTEM PEMANTAUAN PERTUMBUHAN BATITA MENGGUNAKAN METODE FUZZY TSUKAMOTO

The growth of children under the age of three (toddlers) is one of the determinants of children's development in the future. One of the parameters of toddler growth assessment is determined by gender, age, height and weight. This research makes a system that can monitor toddler growth with web-based. The research method used is the System Life Development Cycle, which consists of planning, analysis, design, implementation and use. This system also uses the Tsukamoto fuzzy method to determine the membership set of each input variable. The gender criteria are divided into two classes, male and female, the age criteria are divided into three classes, the height criteria are three classes, and the weight criteria are divided into three classes. Based on the division of classes, the output of this study is the growth status of toddlers, namely poor growth, poor, normal and more. Based on the results of input data criteria and calculations using Tsukamoto fuzzy, the output obtained in the form of the status of the child's growth.