cover
Contact Name
Prof. Dr. H. Jufriadif Na`am, S.Kom, M.Kom
Contact Email
jufriadifnaam@upiyptk.ac.id
Phone
+6287895670026
Journal Mail Official
jidt@upiyptk.ac.id
Editorial Address
Kampus Universitas Putra Indonesia YPTK Padang Jl. Raya Lubuk Begalung Padang, Sumatera Barat - 25221
Location
Kota padang,
Sumatera barat
INDONESIA
Jurnal Informasi dan Teknologi
ISSN : 27149730     EISSN : 27149730     DOI : https://doi.org/10.37034/jidt
Core Subject : Science,
Jurnal Informasi & Teknologi media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai penelitian Rekayasa Sistem, Teknik Informatika/Teknologi Informasi, Manajemen Informatika dan Sistem Informasi. Sebagai bagian dari semangat menyebarluaskan ilmu pengetahuan hasil dari penelitian dan pemikiran untuk pengabdian pada Masyarakat luas dan sebagai sumber referensi akademisi di bidang Teknologi dan Informasi.
Articles 13 Documents
Search results for , issue "2022, Vol. 4, No. 1" : 13 Documents clear
Prediction of the Number of Arrivals of Training Students With the Monte Carlo Method Sopi Sapriadi; Yuhandri Yunus; Rahmatia Wulan Dari
Jurnal Informasi dan Teknologi 2022, Vol. 4, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v4i1.168

Abstract

The simulation of predicting student arrivals for training is an estimate of the calculation of the arrival rate of students in a period to conduct training. The number of student visits is too many, sometimes inversely proportional to the programmers who carry out learning, this causes the ongoing service to be less than optimal. This study aims to predict student arrivals in the future better. The data processed in this study were 3 periods sourced from the administration of a private company in West Sumatra. The data will be processed and calculated using the Monte Carlo method. The data were tested with various possible elements using a random sample. A powerful numerical calculation tool by simulating statistical data, this simulation obtains accurate values ​​​​accurately from the physical form of the system that can be observed. The calculation implementation will be developed using an application-based system that will be built with the Hypertext Preprocessor (PHP) programming language. The system developed is easier and more relevant by applying Information Technology. The results obtained in predicting are 80% for 2017 and 84% for 2018. From the results of 80% accuracy in 2017 and 84% 2018 the system works very well to implement. Based on the results of data processing with the Monte Carlo method, it can be predicted that the number of student arrivals for training, as well as a good and fast decision-making process in the future.
Prediksi Pola Penjualan Produk Herbal Menggunakan Algoritma FP-Growth Supinah; Rezi Elsya Putra; Mohd. Iqbal
Jurnal Informasi dan Teknologi 2022, Vol. 4, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v4i1.167

Abstract

The pattern of sales is a necessity in a business, in increasing sales strategies setting patterns will help the business progress. The pattern of selling these herbal products can increase sales and convenience for sellers and buyers compared to manual settings. Setting the layout of herbal products can facilitate customers in the selection of interrelated products. Continuous product prediction can be easily recognized by the seller. The sales pattern prediction in this study uses transaction data as many as 33 sales transactions in less than the last three months originating from the sale of Batam HNI Bussiness Center 2 herbal products. Based on sales analysis using the FP-Growth algorithm can predict the pattern of sales of herbal products for the future. Furthermore, transaction data is processed using Rapidminer Studio version 9.0 software with 68 transaction data, then from the results of testing on this method the percentage of success is 80%. Comparison uses 10 sales data samples. Opportunities to choose interrelated products greatly help customers when shopping and predict future customer needs. The sales pattern prediction has helped to overcome the instability of herbal product supplies at Batam's HNI Bussiness Center 2.
Kebijakan Pembatasan Sosial Berkala: Prediksi Sikap Masyarakat Terhadap Telemedis Selama Pandemi COVID-19 Tiar Anindya Putri
Jurnal Informasi dan Teknologi 2022, Vol. 4, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v4i1.170

Abstract

Telemedicine can provide routine care services without the risk of contracting Covid-19 in online way in the government's policy for social restrictions and adaptation of new habits stages. This study was intended to assess attitudes in the direction of telemedicine at some stage in periodical social restrictions in Indonesia, then examine the general public's willingness to use the service within the future, and also examine the extent to which respondent have changed their minds about the service. This study uses two statistical analysis approaches. The first approach was a cross-sectional, descriptive, and correlational study conducted among adults aged over 19 years using social media networks. Then the second approach is Ordered Logistic Regression models on two questionnaire items for the dependent variable, specifically predicting willingness to apply telemedicine within the future and predicting changes in thoughts about telemedicine. Sixty-four percent of respondents agree and strongly agree that they need to use telemedicine during the periodical social restriction period of the COVID-19 pandemic. However, despite the availability of telemedicine during the COVID-19 pandemic, 46.92% of respondents tend to still like to go to clinics or hospitals. A total of 24.64% of respondents were hesitant to go to a clinic or hospital, and 28.44% of respondents were hesitant to go to a clinic or hospital. This makes telemedicine in Indonesia not yet considered a necessity, but is still considered the first solution that can be done on a periodic basis.
Kombinasi Tiga Algoritma Penjadwalan sebagai Upaya Meningkatkan Pelayanan Pelanggan pada Usaha Konveksi Siti Mutrofin; M. Dimas Ghifari Muafah; Mas’ud; Ahmad Farhan
Jurnal Informasi dan Teknologi 2022, Vol. 4, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v4i1.174

Abstract

Konveksi Fariasi is a convection that focuses on the production of t-shirts in Jombang. The problem is experienced by Konveksi Fariasi is scheduling the production of customer order shirts based on the order of arrival time or First In First Serve (FCFS), where the first arrival will get the first service. FCFS is not profitable for customers who order a small number of t-shirts that are not included in the First or Initial queue, because they have to wait for previous queues which may have more orders in the front queue. FCFS does not benefit the ordering of t-shirts that are not in the first line even though the order is small. From these problems, the current production scheduling system needs to be optimized. In this study, the data used are ordering data for September 2017. The results of data analysis and business processes, this study propose a combination of three scheduling algorithms as a solution to improve customer service. The algorithm consists of Dynamic Priority, Shortest Job First (SJF) and First in First Serve (FCFS). Dynamic Priority is useful for customers who want to prioritize their orders, SJF is useful for small orders, FCFS is useful for sorting according to the earliest date of arrival. The trial results of the combination of the three algorithms show better results than just using FCFS. The average waiting time is 664 days for the combination of the three proposed algorithms, compared if only using the FCFS algorithm which is 747 days.
Peramalan Jumlah Permintaan Produksi Menggunakan Jaringan Saraf Tiruan Algoritma Backpropagation Muhammad Thoriq
Jurnal Informasi dan Teknologi 2022, Vol. 4, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v4i1.178

Abstract

Artificial Neural Network (ANN) technique has developed rapidly in the field of estimation. ANN can predict based on data on events and related factors that existed in the past. ANN has advantages in parallel computing in classifying patterns. ANN is also capable of self-regulating the data to be processed without requiring an explicit function specification. The advantage of using ANN is the elimination of complex analytical and numerical iterative computations. The ANN method that is often used in prediction case studies is the Backpropagation Algorithm. This algorithm has the ability to solve problems in the real world by building trained methods that show good performance on large data scales and are able to overcome complex pattern recognition. This study aims to predict the demand for salt optimally using the ANN Method with the Backprogation Algorithm at PT. Kurnia Garam Prosperous Padang City. This forecasting is needed because of the high cost of production with the large number of requests that occur to be more effective. Proper forecasting will be able to optimize production so that it can reduce the required production costs. The data processed is salt production data from 2016 to 2018 at PT. Kurnia Garam Prosperous. The momentum results obtained are 3-9-1 for dividing the data into 2, namely 24 training data and 12 test data. The optimal prediction result is 0.98946, so this research is very helpful in forecasting optimal and efficient production costs.
Sistem Pakar dalam Menganalisis Penyakit Organ dan Jaringan Tubuh dengan Metode Perceptron dan Fitur Augmented Reality Eryanto Agusriadi; Finot
Jurnal Informasi dan Teknologi 2022, Vol. 4, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v4i1.180

Abstract

Diseases of organs and tissues of the body or in medicine are commonly referred to as anatomical pathology. Is a medical specialist who deals with the diagnosis of disease based on gross, microscopic and molecular examination of organs, tissues and cells. This procedure is used to identify abnormalities in the body and can help diagnose disease. This study aims that the results of the analysis of the perceptron method can help the doctors of the Putri Hijau Hospital in Medan City quickly and precisely in identifying and analyzing patients with anatomical pathologies. The data processed in this study were 50 patients from the hospital, sourced from one of the anatomical pathology specialists at the hospital. Then the results of the data that have been obtained from patients with the perceptron method using an android-based application. So that the results of the diagnosis of the patient's disease can be obtained. The results of research with this method produce a system that can assist anatomical pathology specialists to present disease diagnosis information at the Putri Hijau Hospital in Medan City. With the existence of an expert system in analyzing diseases of organs and body tissues, it can be recommended to help specialists in anatomical pathology to diagnose patients more quickly and precisely.
Analisis Faktor Risiko Kematian dengan Penyakit Komorbid COVID-19 menggunakan Algoritma ECLAT Sukma Evadini
Jurnal Informasi dan Teknologi 2022, Vol. 4, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v4i1.181

Abstract

The death rate due to infection with the COVID-19 virus is increasing. Throughout 2020, COVID-19 cases continued to increase with a total of 2,995,758 positive cases with a total death toll of 204,987 in more than 213 infected countries. The increasing number of deaths is certainly a problem that needs special attention. One of the factors that can affect the severity of COVID-19 infection is a medical condition. These medical conditions are referred to as comorbid or comorbid conditions. This study aims to analyze the risk factors for death of COVID-19 patients based on comorbid diseases using the Data Mining technique. The algorithm used is ECLAT. The results of this study are age and comorbid diseases have an influence on the patient's condition when discharged from the hospital with a support value of 25% and a confidence value of 100%.
Metode Vikor dalam Meningkatkan Kualitas Pembelajaran Terhadap Pemilihan Studi Club Junaidi
Jurnal Informasi dan Teknologi 2022, Vol. 4, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v4i1.182

Abstract

Club studies are more non-formal learning methods and emphasize the participation of members/participants. In club studies, students get more roles than in class lectures, so club studies can be used as a companion method to increase student insight. Club studies are also one of the alternative learning methods designed to improve student competence by emphasizing the active participation of students. By participating in the study club, students have the ability to increase student scores compared to those who do not participate in the study club, so there is a difference between students who take part in the study club and those who do not take part in the study club. Student competence is very necessary, especially in the era of global competition. To find student talent in determining the selection of club studies as an alternative method of learning level in order to improve student competence and improve the quality of learning with the best graduates. Based on the analysis of improving the quality of learning in students against the selection of club studies with several criteria that can be taken from the students themselves, the assessment consists of the value of supporting courses, attendance values ​​of supporting courses, practical test scores and interests. From the various criteria that students have, from this it can provide a determination in the selection of club studies according to the results of the criteria values ​​owned by students..
Identifikasi Objek pada Citra Thorax X-Ray Pasien COVID-19 dengan Metode Contrast Limited Adaptive Histogram Equalization (CLAHE) Dodi Andre Putra; Jufriadif Na` am; Yuhandri
Jurnal Informasi dan Teknologi 2022, Vol. 4, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v4i1.184

Abstract

Chest X-Ray radiography produces digital radiographic images of the chest area such as the lungs, heart, and ribs. This image can visualize the lung condition of COVID-19 patients. Examination of the lung condition of COVID-19 patients with X-Ray is easier, cheaper, and widely available in hospitals than other radiographic techniques. However, the results of the X-Ray radiography digital image have poor quality, so they need to be improved. Low image contrast is a factor in the difficulty of identifying thorax images of COVID-19 patients. Increase the contrast of the low thorax image of COVID-19 patients with Contrast Limited Adaptive Histogram Equalization (CLAHE) so that it is easier to observe concretely and more clearly. The images that were processed in this study were 100 thorax images of COVID-19 patients sourced from the radiology department of Bhayangkara Hospital, Padang Indonesia. Furthermore, the image is processed using digital image processing using Matlab software. The processing stages of the thorax image are converted into grayscale form. The resulting grayscale image is continued with contrast processing using the CLAHE method with Uniform, Rayleigh and Exponential distribution types. The calculation of the Peak Signal to Noise Ratio (PNSR) and Mean Square Error (MSE) values of the image results from the processing of each type of CLAHE was continued. The results of testing all images can be visually improved in contrast quality. The average MSE CLAHE Uniform, Rayleigh and Exponential results were 27.68, 25.86 and 26.33, respectively. The average values of CLAHE Uniform, Rayleigh and Exponential PNSR > 30 dB are 112.32 dB, 171.95 dB and 151.90 dB, which means the CLAHE image is similar to the original image. CLAHE Rayleigh gives the best results in terms of quality and quantity with a total of 85 images or an accuracy value of 85%, while CLAHE Exponential and CLAHE Uniform are 15% and 0%, respectively.
Behavior Analysis and Prediction of Civil Services Staff in Occupational Functional Positions Using C4.5 Algorithm Muhammad Isra
Jurnal Informasi dan Teknologi 2022, Vol. 4, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v4i1.186

Abstract

Functional positions are not positions that can be filled by every state civil apparatus, their filling is only based on certain expertise and skills as evidenced by certain certifications and/or assessments such as passing a competency test and for promotion to functional positions it is determined by credit numbers. In carrying out their professional duties, functional positions are also independent. The high interest of state civil servants in occupying functional positions, it is necessary to make rules to avoid subjectivity in choosing functional positions, as one solution is to use data mining techniques. Data mining has an important function or method to help get valuable information and increase knowledge for its users. Data mining can be used in various disciplines, such as education, health, agriculture and government. The C4.5 algorithm has the ability to resolve incomplete attribute values ​​and produce rules that are easy to understand, this is evidenced in determining the predictions of state civil apparatus occupying functional positions as evidenced by the test results using the confusion matrix, obtaining an accuracy of 92.54% with a ratio of 80% training data and 20 test data. The information gain value obtained from the education name attribute is the main factor in determining the position in functional positions.

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