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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Sistem Komputer dan Informatika (JSON)
Rika Rosnelly
Universitas Potensi Utama, Medan
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Komparasi Metode Decision Tree, KNN, dan SVM Untuk Menentukan Jurusan Di SMK Novendra Adisaputra Sinaga; Ramadani Ramadani; Khoirunsyah Dalimunthe; Muhamad Sayid Amir Ali Lubis; Rika Rosnelly
Jurnal Sistem Komputer dan Informatika (JSON) Vol 3, No 2 (2021): Desember 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v3i2.3598

Abstract

The selection of majors for prospective vocational students is the first step in determining the next career. The determination of the major aims so that students can be directed in receiving lessons based on the ability and talent of students and of course when they have graduated have the skills to get a job if they do not continue their studies. Siti Banun Sigambal Private Vocational School is located in Labuhanbatu Rantau Prapat. In realizing one of the missions of SMK, namely Realizing quality learning in Vocational High School, SMK Siti Banun in determining the Department by conducting tests. In classifying data mining techniques can be used, among others Decision Tree, K-Nearest Neighbors (KNN) and Support Vector Machine (SVM). This research was conducted to compare the performance of Decision Tree, KNN and SVM algorithms in determining majors. Of the 245-test data used obtained SVM has an accuracy value of 89%, precision 87% while KNN has an accuracy value of 84%, precision 81% and Decision Tree has an accuracy value of 78% and precision of 75%.
Autoregressive Integrated Moving Average (ARIMA-Box Jenkins) Pada Peramalan Komoditas Cabai Merah di Indonesia Ridha Maya Faza Lubis; Zakarias Situmorang; Rika Rosnelly
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2927

Abstract

Chili is one of the main staples in making a dish and chili is one of the values in a commodity that has superior value, the price of chili often experiences price fluctuations or what is known as the price which is always changing. data taken from BPS (Central Bureau of Statistics) data nationally from January 2001 to December 2015 data, this study also aims to be able to predict national chili prices which will later be used in research, namely discussing the Autoregressive Integrated Moving Average (ARIMA) method. In this study, the identification of the model was carried out using two tests, namely the stationarity test and the correlation test. The stationarity test is the Augmented Dickey-Fuller (ADF) test, the Philips-Perron (PP) test and the Kwiatkowski-Philips-Schmidt-Shin (KPPS) test using Minitab 9.The chili commodity is a very important commodity in the Indonesian economy, because In terms of consumption, chilies have a very significant market share, which can be seen from data from the Central Statistics Agency (BPS) with an inflation weight value of 0.35%. From the research, it was found that for the selection of the best method, namely ARIMA (3,1,0) because it has the smallest MSE value and the forecasting results for the next 12 periods in January 2016 ranged from Rp. 11,868.2 to Rp. 28,315.5 and so on until December 2016.
Penerapan Algoritma C4.5 Dalam Memprediksi Ketersediaan Uang Pada Mesin ATM Firman Syahputra; Hartono Hartono; Rika Rosnelly
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2933

Abstract

This study aims to provide an evaluation of the availability of money in ATM machines using data mining. Data mining with the C4.5 algorithm is used to predict cash demand or total cash withdrawals at ATMs. To determine the need for ATM cash based on cash transaction data. It is hoped that this forecasting can help the monitoring department in making decisions about the money requirements that must be allocated to each ATM machine. The results of this study are expected to assist the ATM management unit in optimizing and monitoring the availability of money at an ATM machine for cash needs, so that it can provide optimal service to customers. Algortima C4.5 is an algorithm that is able to form a decision tree, where the decision tree will then generate new knowledge. The results of the test matched the data on the availability of money at the ATM machine. The results of implementing the C4.5 method on the availability of money at the ATM machine are seen from the travel time to the ATM location and also the remaining balance in the machine. The resulting decision tree model is to make the balance variable as the root, then the travel time as a branch at Level 1 with the variables fast, medium, long, and the bank becomes a branch at the last level (Level 2). Then the C4.5 algorithm was tested using the K-Fold Cross validation method with the value of fold = 10, it can be seen that the accuracy rate is 85%, the Precision value is 80% and the Recall value is 66.67%. While the AUC (Area Under Curve) value is 0.833, this shows that if the AUC value approaches the value 1, the accuracy level is getting better
Penentuan Kelas Menggunakan Algoritma K Medoids Untuk Clustering Siswa Tunagrahita Husin Sariangsah; Wanayumini Wanayumini; Rika Rosnelly
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 1 (2021): Januari 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i1.2547

Abstract

So far, the class placement of mentally retarded students is based on the age of entering the child when registering at SLB C Muzdalifah, the Intelligence Quotient (IQ) test has not been tried for mentally retarded students in classifying student classes. It is important to group mentally retarded children to make it easier for teachers to prepare programs and implement educational services. It is important for the school to understand that in mentally retarded children there are individual differences with very large variations. That is, being at almost the same age level (calendar age and mental age) and the same education level, in fact individual abilities differ from one another. Thus, of course, special strategies and programs are needed that are adapted to individual differences. This research was made to classify and analyze data mining for class clustering students with the K-Medoids algorithm to help group students who want to occupy classes according to their level of intellectual disability. From the grouping results obtained 3 clusters, which have the highest number of students is the moderate mental retardation class and the lowest cluster is mild mental retardation, the Muzdalifah special school can prepare classes based on grouping for teaching and learning activities.
Analisa Association Rule Pada Algoritma Apriori Untuk Minat Pembelian Alat Kesehatan Andi Rahmadsyah; Hartono Hartono; Rika Rosnelly
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 1 (2021): Januari 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i1.2658

Abstract

In the competition in the business world, especially the Medical Device industry, it requires developers to find an accurate strategy that can increase sales of goods. One way to overcome this problem is to continue to provide various types of medical devices in the warehouse. To find out what medical devices are purchased by consumers, market basket analysis techniques are carried out, namely analysis of consumer buying habits. In order to make it easier for companies to determine Buyers' interest in medical devices, a data mining method is needed which is accompanied by an a priori algorithm based on the purchasing process carried out by consumers based on the relationship between the products purchased. Based on the sample sales data for medical devices CV Andira Karya Jaya, amounting to 25 transactions and in this study a minimum support = 12% and a minimum confidence = 70% will be used. In the final stage, the results obtained are medical devices that are in demand by buyers at CV. Andira Karya Jaya, namely 1 M3 oxygen cylinder and 1 M3 troley of oxygen. Based on this data, CV. Andira Karya Jaya can provide supplies of medical devices that are of interest to buyers.
Analisis Perbandingan Metode Certainty Factor dan Teorema Bayes untuk Mendiagnosa Penyakit Autis Pada Anak Ramadhanu Ginting; Muhammad Zarlis; Rika Rosnelly
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2930

Abstract

This study discusses the design of a system that specifically addresses the problem of autism in children. Autism is a behavior that occurs to a person, especially a child, which makes social interaction difficult. The expert system is a system that represents the ability of an expert into a machine, where in this study, it discusses how to analyze 2 methods in an expert system, namely the Certainty Factor and the Bayes Theorem for diagnosing autism in children which aims to determine which method is the most appropriate and good to use. or implemented into an application. which will be useful later in determining the category of children with autism. Based on the research conducted by the author, a simple description of the comparative analysis of the Certainty Factor and Bayes Theorem methods is obtained where the Certainty Factor method has a calculation accuracy above 90%.
Implementasi Metode HSI pada Transformasi Ruang Warna Dalam Mendeteksi Kematangan Buah Mangga Udang Yuni Franciska Br Tarigan; Karina Andriani; Rika Rosnelly; Wanayumini Wanayumini
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4547

Abstract

Mango is a plant that is widely cultivated in Indonesia. Mango is a fruit that is popular and favored by almost the entire world population. Mango is not a native plant from Indonesia but is a fruit plant native to India that has a distinctive taste. The shelf life is very short because it is a fruit that is easily damaged or rotted in a certain period of time. The use of technology Digital image is an image that can be processed directly by a computer. A digital image can be represented by a matrix consisting of M columns and N rows, where the intersection between the columns and rows is called a pixel (picture element), which is the smallest element of an image. Image processing is a form of processing an image or image by numerical processing of the image, in this case, each pixel or point of the image is processed. One image processing technique utilizes a computer as software to process each pixel of an image. For image processing applications that perform object recognition, it will be easier if the object is identified using the difference in its hue value by limiting a certain value of the hue value to the object. The HSI color space model is a color space system similar to the performance of the human eye. HSI works by combining the color or grayscale contained in the image. Based on the reference value range of the Mango Shrimp fruit that has been determined in the process using the HSI method, it can be concluded that the test image of the Mango Shrimp fruit with a value of H=32 S=0.675 I=83 then the manga can be said to be ripe.
Co-Authors Andi Rahmadsyah Firman Syahputra Hartono Hartono Husin Sariangsah Karina Andriani Khoirunsyah Dalimunthe Muhamad Sayid Amir Ali Lubis Muhammad Zarlis Novendra Adisaputra Sinaga Ramadani Ramadani Ramadhanu Ginting Ridha Maya Faza Lubis Situmorang, Zakarias Wanayumini Yuni Franciska Br Tarigan