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ILKOM Jurnal Ilmiah
Published by Universitas Muslim Indonesia
ISSN : 20871716     EISSN : 25487779     DOI : -
Core Subject : Science,
Computer Science & IT
ILKOM Jurnal Ilmiah is an Indonesian scientific journal published by the Department of Information Technology, Faculty of Computer Science, Universitas Muslim Indonesia. ILKOM Jurnal Ilmiah covers all aspects of the latest outstanding research and developments in the field of Computer science, including Artificial intelligence, Computer architecture and engineering, Computer performance analysis, Computer graphics and visualization, Computer security and cryptography, Computational science, Computer networks, Concurrent, parallel and distributed systems, Databases, Human-computer interaction, Embedded system, and Software engineering.
Arjuna Subject : -
Articles 16 Documents
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Search results for , issue " Vol 10, No 2 (2018)" : 16 Documents clear
Sistem Pakar Penyakit Liver Menggunakan K- Nearest Neighbors Algoritm Berbasis Website Gobel, Citra Yustitya
ILKOM Jurnal Ilmiah Vol 10, No 2 (2018)
Publisher : Program Studi Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (461.614 KB)

Abstract

The liver is largest organ for humans, functioning as formation and secretion of bile, and as detoxification of toxins. Liver disease difficult to detect at early stage, but treatment of Liver disease in early stages will greatly help patients recovery. With increasing number Liver Patients other than caused by unhealthy lifestyle, also caused by delay factor handling early symptoms. So this research aims to design Expert System Liver Disease based Website, that it can facilitate access information society need information about liver disease. Website based system design using K-NN Method because it is considered flexible enough and has tolerance to data that is’not appropriate and based on natural language. Expert system as a tool in determining whether the patient was suffering from Liver disease or not with the concept of K-NN. The results discussion that system design with a simple model so that can be used by all community.
PEMERINGKATAN RISIKO KEAMANAN SISTEM JARINGAN KOMPUTER POLITEKNIK KOTA MALANG MENGGUNAKAN CVSS DAN FMEA Retna Mulya, Betta Wahyu; Tarigan, Avinanta
ILKOM Jurnal Ilmiah Vol 10, No 2 (2018)
Publisher : Program Studi Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (652.184 KB)

Abstract

The vulnerability of a computer network system is a weakness, lack or hole in the system, which can be exploited by attackers to carry out an attack that may endanger the confidentiality, integrity or availability of a system. The filling process requires a security vulnerability analysis according to the severity to determine the priority scales of handling. The analysis used in determining priority scales of handling is the combination of CVSS and FMEA-based analysis method. The analysis result from both methods shows that the numbers of risk priority and vulnerability become a benchmark in risk prioritizing and mitigation the risk to Politeknik Kota Malang party, with the priority order: ‘Singa’, ‘Sierra’, ‘Dino’, and ‘Leopard’. The priority scales show that the vulnerability levels, that must be handled, have number range between 40% up to 60%. The combination of CVSS and FMEA methods can determine the handling level based on the potential impacts caused by the vulnerability in computer network system of Politeknik Kota Malang.
SISTEM KONTROL INFORMASI AKTIVITAS LANSIA BERBASIS INTERNET OF THINGS (IoT) Wahyuningsih, Pujianti
ILKOM Jurnal Ilmiah Vol 10, No 2 (2018)
Publisher : Program Studi Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (479.446 KB)

Abstract

Elderly is a human phase are notabel to much do an activity because of physical factors and age. On doing daily activity the elderly should be kept by the family or nurse so in this research will be built a control system thatabel to detection of elderly activity and control an electronic device remotely using the Internet of Things (IoT). All of the elderly activity has detected based on sensor data input from the carpet, PIR sensor, DHT22 temperature sensor then processed in the Arduino Mega and Raspberry Pi. The function of Raspberry Pi is to connect all elderly information to the internet using node.js. Based on the information the family or nurse able to see the elderly activity remotely using website and able to control electronic device like a fan and heater by manually and automatically using the Internet of Things technology.
SISTEM INFORMASI PENCARIAN LOKASI PERGURUAN TINGGI DI MAKASSAR Irwan, Irwan; Atmajaya, Dedy
ILKOM Jurnal Ilmiah Vol 10, No 2 (2018)
Publisher : Program Studi Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (345.79 KB)

Abstract

Universities are generally spread in various locations even though in one province (district or city). This study specializes in universities in the city of Makassar. The college location has information related to spatial and non-spatial data, such as name, address and information related to the college. The problem faced in this study is that not everyone knows about universities in the city of Makassar, especially the location of the college. The method used in this study is the Haversine Formula and Euclidean method. Results of the study using the Haversine Formula method, the measurement of the distance of the closest trajectory to college are smaller or closer than using the Euclidean method. Because the Haversine Formula method ignores the height of hills and depths of valleys on the earths surface.  The purpose of this study is to facilitate in informing the general public who need information from universities in Makassar.
Klasifikasi Masyarakat Miskin Menggunakan Metode Naive Bayes Annur, Haditsah
ILKOM Jurnal Ilmiah Vol 10, No 2 (2018)
Publisher : Program Studi Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (382.324 KB)

Abstract

The main problem in the current poverty reduction effort is related to the fact that economic growth is not evenly distributed. The research will classify based on the data of poor people obtained from Tibawa District by using data mining technique. Attributes to be used in classifying the population are Age, Education, Work, Income, Dependent, Status (Married / Unmarried). The method to be used is the Naïve Bayes Classifier method, which is one of the classification techniques in data mining. Based on the research, it is concluded that, the classification system of the poor in the administrative area of Tibawa sub-district, Gorontalo regency can be engineered and Based on the result of confusion matrix testing with split validation technique, the use of naïve Bayes classification method to the dataset which has been taken on the research object obtained the level of accuracy 73% or included in the Good category. While the Precision value of 92% and Recall of 86%.
Pengenalan Angka Tulisan Tangan Menggunakan Jaringan Syaraf Tiruan Herman, Herman; Syafie, Lukman; Indra, Dolly
ILKOM Jurnal Ilmiah Vol 10, No 2 (2018)
Publisher : Program Studi Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (369.059 KB)

Abstract

Current technological developments spur the application of pattern recognition in various fields, such as the introduction of signature patterns, fingerprints, faces, and handwriting. Human handwriting has differences between one another and often handwriting is difficult to read or difficult to recognize and this can hamper daily activities, such as transaction activities that require handwriting. Even one of the biometric features of everyone is handwriting. One method that can be used to recognize handwriting patterns in the field of computer science is artificial neural networks (ANN) with the learning algorithm is backpropagation. Artificial neural networks are able to recognize something based on the past. This means that past data will be studied so as to be able to make decisions on new data. To recognize handwriting patterns using artificial neural networks, the characteristics of handwritten objects are extracted using an invariant moment. The results of training using artificial neural networks indicate that the correlation coefficient value is obtained on the number of hidden layer neurons by 30. The highest correlation coefficient value is 0.61382. The test results on the test data obtained an accuracy rate of 11.67% of the total test data.

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