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Kab. jember,
Jawa timur
INDONESIA
INFORMAL: Informatics Journal
Published by Universitas Jember
ISSN : 2503250X     EISSN : -     DOI : -
Core Subject : Science,
Computer Science & IT
Arjuna Subject : -
Articles 7 Documents
 1 
Search results for , issue "Vol 2 No 2 (2017): INFORMAL - Informatics Journal" : 7 Documents clear
Rear Cover Oktalia Juwita
INFORMAL: Informatics Journal Vol 2 No 2 (2017): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

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Abstract

Sistem Pakar Untuk Mendeteksi Tingkat Resiko Penyakit Jantung Dengan Fuzzy Inferensi (Mamdani) Dany Suktiawan Irman Fiano; Agus Sidiq Purnomo
INFORMAL: Informatics Journal Vol 2 No 2 (2017): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

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Abstract

The development of information technology is needed to help and support in all areas one of the health field. Use of information technology in the field of health to reduce problems in clinical and non-clinical action. One of the problems encountered in the field of health is heart disease. The heart is one of the vital organs for humans. Because of the importance of this heart role, heart health must be maintained in order to function properly. Cardiac examination can be done in the hospital by handled by an internist. However, due to limited access and time for consultation with a medical specialist, it has to wait a relatively long time to find out the results of the examination. So it is necessary media to be able to help detect the risk of heart disease more easily and quickly. In this study will be designed an expert system to detect the risk of heart disease by implementing fuzzy inference (mamdani). Where this system will provide information about the level of risk of heart disease based on risk variables of heart disease that is blood pressure, blood sugar, cholesterol, Body Mass Index (BMI) and history of heart disease family. So it can help people in anticipating the risk of heart disease. Based on 20 data that have been tested against experts and systems, for patients detected having a small risk of heart disease have a percentage of 30%, for a moderate risk level has a percentage of 50%, for a large risk level has a percentage of 20%. As for the level of compliance based on the validation results of experts (doctors) and the system, obtained a percentage of 80% of the appropriate test data, and 20% of the test data is not appropriate.
Tourism, Art, and Unique Using Culture Products Promotion with Android-Based Applications Priza Pandunata
INFORMAL: Informatics Journal Vol 2 No 2 (2017): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

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Abstract

The Government of Banyuwangi is actively promoting tourism, one of the most intensively promoted and most desirable is tourism and the unique art of Using where the Using (or Osing) tribe is known as the indigenous people of Banyuwangi. Some of Osing's popular cultural and artistic products that are often promoted include several dance performances, traditional rituals and traditional villages. One of the potential promotional media that can be used is the use of mobile devices, due to the large number of mobile device users. Therefore, to support the promotion of tourism, art and cultural products of Osing and to help the tourists in obtaining tourism information in Banyuwangi, then an application based on Android tourism is made. To develop an Android-based application is done through a series of stages: Requirement Analysis, Literature review, Data Collection and Data Processing, Application Design and code, and Testing and Evaluation.
Sistem Berbasis Aturan Untuk Menentukan Tingkat Gangguan Manic Depression Guruh Wijaya; Sri Kusumadewi; Hepi Wahyuningsih
INFORMAL: Informatics Journal Vol 2 No 2 (2017): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

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Abstract

Manic Depression Disorder is often a trigger for people to do things beyond their normal behavior, can even lead to extreme behavior. There are several scales that can be used to indicate the extent of this disturbance. The most commonly used scales are the Depression Trend (BDI), the Anxiety Scale (TMAS), and the Suicidal Tendency Scale (SIBD). In this research will be built case-based system to determine the level of disturbance Manic Depression by using scale BDI, SIBD and TMAS. The subjects used were the inmates of Class IIA Jember by using a rule-based expert system. The rules are derived from literature studies and input from experts. To increase flexibility, the system is designed web-based. Expert systems are offered as second choice after specialist medical personnel. The results of this study are expected to be a reference for prisons and related parties to develop problem-based intervention programs, especially those related to prevention and curative programs in addressing these psychological problems
Rancang Bangun Aplikasi Customer Relationship Management (CRM) Untuk Identifikasi Tingkat Kepuasan Pelanggan Pada Perusahaan PT. TIKI Jalur Nugraha Ekakurir (JNE) Agen Mastrip Jember Menggunakan Metode K-Means Clustering Moch Bustommy Maulana; Slamin Slamin; Oktalia Juwita
INFORMAL: Informatics Journal Vol 2 No 2 (2017): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

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Abstract

The level of customer satisfaction is a benchmark to get a better benefit. One of the strategies that relates to creation of customer satisfaction is customer relationship management (CRM). Tiki Jalur Nugraha Ekakurir (JNE) Ltd. in Mastrip Jember agency is a company that experienced consumers degression after the emergence of competitors that offered better services. Because of that it is necessary to evaluate the service quality, facilities, and rates compatibility that can affect customer satisfaction. Therefore, CRM method is needed to know the level of customer satisfaction. Questionnaire is used as the method to collect the customers’ responses as the data. After that, the data which is the questionnaires that contain the customer’s responses is processed using K-Means clustering method as the grouping algorithm of respondents. K-means is algorithm clustering by grouping the data which has similar criteria by determining the center point of the cluster (centroid). There are 4 Clusters, the first cluster has a role as a very dissatisfied customer, the second cluster is not satisfied customer, the third cluster is satisfied customer and the fourth cluster has a role as a very satisfied customer. The application examination used 100 respondents with 80 respondents are training set and 20 respondents are test set. The result showed the cluster which has the most members is cluster 3, it means that there are so many customers satisfied with the services. The results of the training test set 100% accurate with the test set. Thus, the appropriate centroid coordinate is the one from the cluster in the last training set iteration.
Identifikasi Kerusakan Jaringan Histologi Pada Ginjal Dengan Fitur Tekstur Menggunakan Model Fitur Gray Level Coocurrence Matrix (GLCM) Zainul Arifin; Izzati Muhimmah; Ika Firdianingsih
INFORMAL: Informatics Journal Vol 2 No 2 (2017): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

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Abstract

Congestion is one type of damage that occurs in the histology of the kidney tissue, where there is excessive blood within the blood vessels of a particular area. In this research, we will design a system to detect congestion in the histology network of the kidneys using texture feature approach with gray level cooccurence matrix (GLCM) method, as well as using vector machine support method (SVM). The subject of data used is histology image of mouse kidney tissue using H & E staining obtained at medical faculty of Islamic university of indonesia. image data used as many as 50 congestion training images and 50 normal training images with the size 256 x 256 pixels. while the test image uses an average size of 3000 x 3000 pixels. the results of the experiments performed with cluster parameters k = 2 to k = 5 show good results, with an average class accuracy rate of 80%, and the accuracy of the segment is 96%.
Penerapan Metode Case Based Reasoning Pada Sistem Pakar Untuk Mendiagnosa Gangguan Tanaman Jeruk Semboro Yanuar Nurdiansyah; Riska Arimanudin
INFORMAL: Informatics Journal Vol 2 No 2 (2017): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

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Abstract

Orange is a flowering plant surnamed Citrus from Rutaceae tribe. Oranges are one of the most important fruit plants that are given top priority to be developed nationally. Jember regency is the centre of producer of Jeruk Siam in East Java which is often known as Jeruk Semboro. A lot of types of pests or diseases in oranges plants result in the need of an agricultural consultant who is able to diagnose pests or diseases that contribute oranges crops. However, time and cost are the reasons for oranges farmers not to consult experts so there is often a mistake in providing solutions to the plants that have been attacked. To overcome this problem, then built expert system to diagnose the disturbance of citrus plants by applying the method of case-based reasoning where this system can diagnose pest or disease of oranges plant by imitating expert way of work. Case Based Reasoning (CBR) is one method that uses artificial intelligence approach (artificial intelligent) which emphasizes problem solving on knowledge from previous cases. It is hoped that by applying the case based reasoning method to the expert system to diagnose the disturbance of citrus in citrus citrus plant is able to help the citrus farmers to diagnose the disturbance of orange either disturbance from pest or disease. This system has been through two testing methods, the first test using a comparison of manual calculations with the system, the second test using recapitulias evaluation results to test the accuracy of the diagnosis. Test results using both methods found that the Expert System to Diagnose Semboro Citrus Disorder has a validity and decision-making with a percentage of 80%.

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