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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 580 Documents
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Algoritma K-Nearest Neighbor dengan Euclidean Distance dan Manhattan Distance untuk Klasifikasi Transportasi Bus Dinata, Rozzi Kesuma; Akbar, Hafizal; Hasdyna, Novia
ILKOM Jurnal Ilmiah Vol 12, No 2 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i2.539.104-111

Abstract

K-Nearest Neighbor is a data mining algorithm that can be used to classify data. K-Nearest Neighbor works based on the closest distance. This research using the Euclidean and Manhattan distances to calculate the distance of Lhokseumawe-Medan bus transportation. Data that used in this research was obtained from the Organisasi Angkutan Darat Kota Lhokseumawe. The results of the test with k = 3 has obtained the percentage of 44.94% for Precision, 37.06% Recall, and 81.96% Accuracy for the performance of K-NN with Euclidean Distance. Whereas by using Manhattan Distance the result obtained was 45.49% for Precision, 36.39% Recall, and 84.00% Accuracy. The result shown that Manhattan Distance obtained the highest accuracy, with the difference of 2.04% higher than Euclidean Distance. It indicates that Manhattan Distance is more accurate than Euclidean Distance to classify the bus transportation.
Application of Knowledge Management System for Cattle Cultivation Kusnadi, Edi; Yanitasari, Yessy; Supriyadi, Supriyadi
ILKOM Jurnal Ilmiah Vol 13, No 1 (2021)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Cow are family animal bovinae and subfamily bovidae. Cow are raise for use in meat and milk. Beef production does not fullfill National beef demand. This is influenced by several factors, one of them is the cultivation pattern. But knowledge about cultivation is still scattered and unstructured. Knowledge Management System (KMS) offer a knowledge system that can be used to create, collect, store, maintain and disseminate knowledge. In this study KMS has been applied to cattle farming with the Knowledge Management System Life Cycle (KMSLC) method. The outcome of the research is a web based application regarding the management of cattle farming that have been tested by experts and users with an average test results stated good. The features of this KMS application are knowledge capture, knowledge sharing and knowledge application system, so they can share knowledge between one user and another. In addition, this application is equipped with a discussion forum that serves as a place to interact between fellow users or with experts.
Sistem Pendukung Keputusan Pemilihan Tumbuhan Berkhasiat Obat Menggunakan Metode Analytical Hierarchy Process-Weighted Product Wati, Masna; Maulana, Andi; Widians, Joan Angelina
ILKOM Jurnal Ilmiah Vol 12, No 3 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i3.671.219-227

Abstract

Kalimantan memiliki hutan dengan keanekaragaman hayatinya dan menjadi salah satu paru-paru dunia serta ditunjang juga dengan potensi pengetahuan pengobatan tradisional yang dimiliki berbagai etnis asli di Kalimantan. Umumnya pengetahuan pengobatan tradisional menggunakan tumbuhan berkhasiat obat dikuasai generasi tua. Generasi muda mulai kurang tertarik menggali pengetahuan ini sehingga akan membuat pengetahuan ini terkikis dan mulai ditinggalkan. Salah satu faktor penyebabnya karena kurangnya sebaran pengetahuan akibat dari pendokumentasian yang masih terpisah-pisah sehingga dibutuhkan sarana pendokumentasian. Sistem pendukung keputusan yang dibangun bertujuan untuk memberikan rekomendasi tumbuhan yang berkhasiat untuk mengobati atau menangani suatu penyakit serta dapat menjadi salah satu sarana pendokumentasian dengan memberikan informasi seputar tumbuhan berkhasiat obat. Sistem ini mengimplementasikan dua metode yaitu Analytical Hierarchy Process (AHP) digunakan pada tahap penentuan bobot kriteria dan Weighted Product (WP) yang digunakan untuk mengevaluasi alternatif tumbuhan berkhasiat obat. Sistem melibatkan 4 kriteria dalam pengambilan keputusan yaitu bagian yang berkhasiat, carapengolahan, cara penggunaan dan jenis tumbuhan serta terdapat 29 jenis tumbuhan berkhasiat obat untuk 33 jenis penyakit. Output dari sistem ini berupa urutan prioritas tumbuhan berkhasiat obat yang direkomendasikan pada suatu penyakit. Dengan dibuatnya Sistem Pendukung Keputusan penentuan tumbuhan berkhasiat obat etnis Kalimantan diharapkan mampu mempermudah dalam penentuan penggunaan tumbuhan berkhasiat obat.
Anti-WebShell PHP Backdoor Scanner pada Linux Server Sopaheluwakan, Christian Ronaldo; Chandra, Dian Widiyanto
ILKOM Jurnal Ilmiah Vol 12, No 2 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i2.596.143-153

Abstract

Backdoor or commonly also known as web shell is one of the malicious software that hackers use to maintain access systems that they have entered. Relatively few programs like Anti Web-Shell, PHP Backdoor Scanner circulating on the Internet, and can be obtained free of charge to deal with the issues above. But most of these programs have no actual database of signature behavior to deal with PHP backdoor / Shell nowadays. Then comes the contemporary Anti Web-Shell program that can deal with today's backdoor shell. This study uses an experimental method concerning previous similar studies and is implemented directly into the world of cyber security professional industries. By enriching the Regex dictionary signature and String Array Matching the actualized Anti Web-Shell program can detect more backdoor than similar programs that have existed in the past. The results of this study are in the form of a web application software in PHP extension. The application can minimize 100% of false positives and is twice as fast in scanning files because it is more specific in heuristic analysis scan.
Motion Detection of Objects in Home Security Systems Using Binary-Image Comparison Method Based on Robot Operating System 2 and Raspberry Pi Jalil, Abdul; Matalangi, Matalangi
ILKOM Jurnal Ilmiah Vol 13, No 1 (2021)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The purpose of this study to build a home security system based on object motion detection using Robot Operating System 2 (ROS2) and Raspberry Pi. ROS2 function in this study as a software that used to read and process the camera data then control the buzzer sound, while the Raspberry Pi hardware function to running the ROS2 on the top of Linux Ubuntu 18.04 operating system. Camera function to read the image and video data can be developing for input device to control the home security systems based on the object motion detection. The method has used to detect the object motion is Binary-Image Comparison (BIC), where this method worked by compare the value of the binary image object with the binary master to use it as a decision-making algorithm when the camera detecting the object movement based on object color. Object colors detected in this study are red, yellow, green, and blue. Each object colors are processes using OpenCV library in the ROS2 node service, after that all of the nodes will communicate through topics to communicating and exchanging the message data. This study result is the prototype has developed can give a buzzer sound warning to the user when the camera detecting the object motion based on the object's color.
Metode Double Exponential Smoothing pada Sistem Peramalan Tingkat Kemiskinan Kabupaten Pangkep Atussaliha, Nur Almar'; Purnawansyah, Purnawansyah; Darwis, Herdianti
ILKOM Jurnal Ilmiah Vol 12, No 3 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i3.607.183-190

Abstract

Peramalan adalah kegiatan memperkirakan kejadian yang akan terjadi berdasarkan historical data kuantitatif suatu kejadian. Peramalan sering digunakan oleh pemerintah dalam membuat suatu kebijakan. Salah satu kebijakan pemerintah adalah menurunkan angka kemiskinan setiap tahunnya. Penelitian ini bertujuan untuk membangun sistem Peramalan Tingkat Kemiskinan Kabupaten Pangkep berbasis desktop untuk memberikan gambaran jumlah tingkat kemiskinan periode selanjutnya. Dalam penelitian ini, metode peramalan yang digunakan adalah Double Exponential Smoothing dengan nilai alpha 0.001, 0.01, 0.2, 0.3, 0.5, 0.7, 0.8, 0.99, dan 0.999. Dengan menggunakan data angka kemiskinan dari tahun 2010 sampai 2019, diperoleh bahwa dari 9 nilai alpha yang digunakan, tingkat kesalahan terkecil yaitu 1.2% diberikan oleh alpha 0.5 yang diukur menggunakan metode Mean Absolute Percentage Error (MAPE). Adapun tingkat akurasi peramalan yang didapatkan jumlah kesalahan tiap alpha sebesar 95.394%.
Perbandingan Metode Sobel, Prewitt, Robert dan Canny pada Deteksi Tepi Objek Bergerak Supriyatin, Wahyu
ILKOM Jurnal Ilmiah Vol 12, No 2 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i2.541.112-120

Abstract

Computer vision is one of field of image processing. To be able to recognize a shape, it requires the initial stages in image processing, namely as edge detection. The object used in tracking in computer vision is a moving object (video). Edge detection is used to recognize edges of objects and reduce existing noise. Edge detection algorithms used for this research are using Sobel, Prewitt, Robert and Canny. Tests were carried out on three videos taken from the Matlab library. Testing is done using Simulik Matlab tools. The edge and overlay test results show that the Prewitt algorithm has better edge detection results compared to other algorithms. The Prewitt algorithm produces edges whose level of accuracy is smoother and clearer like the original object. The Canny algorithm failed to produce an edge on the video object. The Sobel and Robert algorithm can detect edges, but it is not clear as Prewitt does, because there are some missing edges.
Evaluation of Lambung Mangkurat University Student Academic Portal Using User Experience Questionnaires (UEQ) Sari, Yuslena; Novitasari, Novitasari; Pratiwi, Hani
ILKOM Jurnal Ilmiah Vol 13, No 1 (2021)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The student academic portal is one of the Academic Information Systems at Lambung Mangkurat University. The student academic portal can only be accessed by Lambung Mangkurat University students and can be used for academic guidance, managing student study plans, printing exam cards, filling out questionnaires, and viewing exam results (assessments). However, since its release in 2016, there has been no publication regarding evaluations on the website-based student academic portal. Evaluation is one of the stages in the Software Development Life Cycle (SDLC), this stage allows the user to provide an assessment of the system. This study aims to evaluate the student academic portal. Evaluation is carried out to determine user ratings of the existing system. The evaluation method used is the User Experience Questionnaire (UEQ). With this method, users can assess the ULM Student Academic Portal from various aspects, namely aspects of Novelty, Stimulation, Dependability, Efficiency, Perspicuity, and Attractiveness. The results of this study indicate that the Perspicuity aspect gets a high score while Novelty gets a low score.
Pemilihan Departemen Terbaik dengan Metode Additive Ratio Assessment Supriatna, Asep; Dedih, Dedih; Yanitasari, Yessy
ILKOM Jurnal Ilmiah Vol 12, No 3 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i3.679.228-235

Abstract

PT Djabesmen Lemah Abang adalah salah satu perusahaan yang mengadakan pemilihan departemen terbaik setiap tahunnya dengan menggunakan 5 kriteria yaitu ringkas, rapi, resik rawat serta rajin, kegiatan ini diikuti oleh 12 departemen yaitu accounting, planning and delivery, information and comunication tecnologies,  purchasing, human resource, warehouse, quality asurance, technical and development, maintenance asbes cement, maintenance royalboard, quality asurance royalboard, Gudang spare part. Di dalam program tersebut penilaian  masih mengunakan lembar cheklist yang di isi dan dihitung secara manual,  jika terjadi adanya hasil penilaian sama tinggi antar departemen maka pimpinan perusahaan akan secara subjektif menentukan pemenangnya. Maka dengan itu dibutuhkan suatu sistem penunjang keputusan , adapun metode yang di pilih yaitu metode  Additive Ratio Assessment (ARAS) dimana metode ini akan memilih semua kriteria berdasarkan nilai tertinggi atau nilai terendah untuk  di hitung dari data alternatif yang sudah disediakan. Hasil  penilaian dengan metode ARAS diperoleh bahwa bahwa nilai tertinggi adalah technical and development departement dengan nilai 1,0  dan nilai terendah adalah maintenance asbes cement department dengan nilai 0,56.
Perbandingan Metode Klasifikasi Support Vector Machine dan Naïve Bayes untuk Analisis Sentimen pada Ulasan Tekstual di Google Play Store Ilmawan, Lutfi Budi; Mude, Muhammad Aliyazid
ILKOM Jurnal Ilmiah Vol 12, No 2 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i2.597.154-161

Abstract

In this research, the performance of SVM classification method will be compared with other classification methods, by using the Naïve Bayes classification method. Naïve Bayes classification method is a light classification method and has a high accuracy if applied to the text classification according to some previous studies. The accuracy of the classifier is measured using the K-fold cross validation method whose results will be tabulated in a confusion matrix table, with a value of K = 3. In this study, the data processed are textual reviews of applications in the Indonesian language Google Play Store obtained from previous research. The test results obtained from the 3-fold cross-validation method produce that SVM Classifier has a higher value of accuracy when compared with the accuracy of the Naïve Bayes classifier, the SVM classifier gets an accuracy of 81.46% and Naïve Bayes classifier by 75.41%.

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