ILKOM Jurnal Ilmiah
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.
Articles
580 Documents
<![CDATA[Fruit recognition system using color filters and histograms ]]>
<![CDATA[Budi Sugandi]]>;
<![CDATA[Rahmi Mahdaliza]]>
<![CDATA[ ILKOM Jurnal Ilmiah Vol 13, No 2 (2021) ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia ]]>
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DOI: 10.33096/ilkom.v13i2.822.140-147
<![CDATA[Nowadays, many children and adults do not know the type or name of fruits, especially if the fruit is a rare one. In this paper, a system was developed that can recognize fruit names in real time using a camera as a visual sensor. The camera captured the image and processed using image processing. This paper proposed a method using HSL color filters, RGB histograms and shapes of fruit objects to detect and recognize fruits. The proposed method was divided into two processes, namely the training and testing processes. The training process was carried out to obtain a database of each fruit. The first process of training was object detection using an HSL color filter. The calculation of the RGB histogram was conducted on the HSL color filtered object. After that, the object's roundness was measured. Meanwhile, the testing process was done by looking for the similarity of the histogram data of the test object with the reference object by using the histogram distance equation. The similarity of the object was determined by the distance value of the histogram of the tested fruit with the referenced fruit. Similar objects would have histogram distances less than the threshold values. Tests were implemented in several types of fruit. The test results showed the system could recognize fruit names accurately.]]>
<![CDATA[SISTEM INFORMASI PENCARIAN LOKASI PERGURUAN TINGGI DI MAKASSAR ]]>
<![CDATA[Irwan Irwan]]>;
<![CDATA[Dedy Atmajaya]]>
<![CDATA[ ILKOM Jurnal Ilmiah Vol 10, No 2 (2018) ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia ]]>
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DOI: 10.33096/ilkom.v10i2.251.232-236
<![CDATA[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 earth's surface. The purpose of this study is to facilitate in informing the general public who need information from universities in Makassar.]]>
<![CDATA[Identification of chicken egg fertility using SVM classifier based on first-order statistical feature extraction ]]>
<![CDATA[Shoffan Saifullah]]>;
<![CDATA[Andiko Putro Suryotomo]]>
<![CDATA[ ILKOM Jurnal Ilmiah Vol 13, No 3 (2021) ]]>
Publisher : <![CDATA[Prodi Teknik Informatika FIK Universitas Muslim Indonesia ]]>
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DOI: 10.33096/ilkom.v13i3.937.285-293
<![CDATA[This study aims to identify chicken eggs fertility using the support vector machine (SVM) classifier method. The classification basis used the first-order statistical (FOS) parameters as feature extraction in the identification process. This research was developed based on the processs identification process, which is still manual (conventional). Although currently there are many technologies in the identification process, they still need development. Thus, this research is one of the developments in the field of image processing technology. The sample data uses datasets from previous studies with a total of 100 egg images. The egg object in the image is a single object. From these data, the classification of each fertile and infertile egg is 50 image data. Chicken egg image data became input in image processing, with the initial process is segmentation. This initial segmentation aims to get the cropped image according to the object. The cropped image is repaired using image preprocessing with grayscaling and image enhancement methods. This method (image enhancement) used two combination methods: contrast limited adaptive histogram equalization (CLAHE) and histogram equalization (HE). The improved image becomes the input for feature extraction using the FOS method. The FOS uses five parameters, namely mean, entropy, variance, skewness, and kurtosis. The five parameters entered into the SVM classifier method to identify the fertility of chicken eggs. The results of these experiments, the method proposed in the identification process has a success percentage of 84.57%. Thus, the implementation of this method can be used as a reference for future research improvements. In addition, it may be possible to use a second-order feature extraction method to improve its accuracy and improve supervised learning for classification.]]>
<![CDATA[PENGEMBANGAN MODEL SIMULASI SISTEM DINAMIK UNTUK MENINGKATKAN EFISIENSI SISTEM OPERASIONAL TRANSPORTASI ]]>
<![CDATA[Amaliah Faradibah]]>;
<![CDATA[Erma Suryani]]>
<![CDATA[ ILKOM Jurnal Ilmiah Vol 11, No 1 (2019) ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia ]]>
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DOI: 10.33096/ilkom.v11i1.413.67-76
<![CDATA[If transport continues to increase, plus manufacturers competing to produce interesting transportation on the market, thus allowing the improvement of the transport users. If the increase occurs, it will cause congestion. Congestion was a factor that greatly affect the efficiency of the transport system, where the transportation system is a form of attachment and the interconnected between the passenger, shuttles and infrastructure that interact in order to transfer people or goods, which is covered in an order, either by natural or artificial or engineered. It takes the right planning strategies in addressing conditions congestion such as implementation of reconfiguration of the route network, a program that using dynamical systems in proper design and planning, and the determination of the most appropriate scenario can improve the efficiency of the transportation system. This research uses scenario through reconfiguration of network routes to improve the efficiency of the transportation system. in this study, this scenario is considered to be the most appropriate to increase the efficiency of vehicle travel time by way of the transfer of light vehicle routes that will go towards the Urip Sumoharjo street because it results in a reduction in travel time by 1.2% of travel time before the scenario.]]>
<![CDATA[PENGENDALIAN PARABOLA BERGERAK MENGGUNAKAN MIKROKONTROLER ]]>
<![CDATA[Matalangi Matalangi]]>
<![CDATA[ ILKOM Jurnal Ilmiah Vol 9, No 1 (2017) ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia ]]>
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DOI: 10.33096/ilkom.v9i1.113.78-85
<![CDATA[Penelitian bertujuan merancang pengendalian parabola bergerak menggunakan Mikrokontroler, Aktuator sebagai penggerak untuk menggerakan parabola kearah timur dan kebarat dan switch sebagai titik tempu pada parabola sehingga dapat berbalik arah timur dan barat, program merumuskan untuk dapat menggerakkan parabola kearah barat dan timur hingga mendapatkan sinyal dan mencapai kemiringan dari 70 derajat ke barat hingga 120 derajat kearah timur.Hasil penelitian ini adalah perancangan dan pembuatan Pengendali Parabola Bergerak. Pengendalian parabola bergeraka ini terbuat dari bahan aluminium berbentuk lingkaran. Dengan ukuran Linkaran 170cm dan tinggi 150cm. Desain Pengendalian Parabola Bergerak ini terdiri dari 4 komponen utama, dimana komponen pertama sebagai Tiang penopang payung, komponen kedua digunakan sebagai penerima sinyal, komponen ketiga sebagai penerima yang menerima sinyal dari LNB, komponen yang keempat digunakan sebagai pengontrol dari parabola yang menggerakkan Payung parabola ke titik focus satelit yang di kendalikan dan control oleh mikrokontroler.]]>
<![CDATA[Identifikasi Hama Kelapa Sawit menggunakan Metode Certainty Factor ]]>
<![CDATA[Joan Angelina Widians]]>;
<![CDATA[Farahdina Nur Rizkyani]]>
<![CDATA[ ILKOM Jurnal Ilmiah Vol 12, No 1 (2020) ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia ]]>
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DOI: 10.33096/ilkom.v12i1.526.58-63
<![CDATA[The lack of knowledge of palm oil farmers and general public about pests in palm oil plants will result in a lack of crop yields on these plants. The resulted in the impact of many palm oil farmers who cut down trees as an effort to eradicate of pests. The limitations of an experts makes handling palm oil plan pests difficult so it is necessary to have an experts system that is able to identify pests of palm oil and how to control them based on knowledge given directly by human experts. The inference is Forward chaining by tracing the rules based on the answers of users. And then calculated by Certainty Factor method. The result of calculation is in the form of a percentage value of confidence and user can immediately find out the type of pests identified and how to control it. This research found 7 (seven) types of pests that attack palm oil are fire caterpillar Setothosea asigna, caterpillars Dasychira inclusa, bag caterpillar Metisa plana, horn beetle Oryctes rhinoceros, termite Coptotermes curvignathus, wild rat Rattus tiomanicus, dan wild pig Sus crofa. The biggest pest attact on palm oil is Termite Coptotermes Curvignathus is 88,8%]]>
<![CDATA[PENERAPAN METODE CERTAINTY FACTOR UNTUK SISTEM PAKAR DIAGNOSA PENYAKIT DIABETES MELITUS PADA RSUD BUMI PANUA KABUPATEN POHUWATO ]]>
<![CDATA[Annahl Riadi]]>
<![CDATA[ ILKOM Jurnal Ilmiah Vol 9, No 3 (2017) ]]>
Publisher : <![CDATA[Prodi Teknik Informatika FIK Universitas Muslim Indonesia ]]>
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DOI: 10.33096/ilkom.v9i3.162.309-316
<![CDATA[Diabetes Melitus (DM) atau biasa disebut diabetes merupakan penyakit gangguan metabolik menahun akibat pankreas tidak memproduksi cukup insulin atau tubuh tidak dapat menggunakan insulin yang diproduksi secara efektif. Penderita Diabetes Melitus di Kabupaten Pohuwato mengalami peningkatan sebanyak 8,5% setiap Tahun. Sistem pakar adalah program komputer yang menirukan penalaran seorang pakar dengan keahlian pada suatu wilayah pengetahuan tertentu. Sistem pakar mencoba mencari solusi, memberikan saran atau kesimpulan yang konsisten terhadap permasalahan yang ditemukannya. Penelitian ini akan dirancang menggunakan Aplikasi Dreamweaver dan bahasa pemrograman PHP, serta database MySQL. Harapan penulis, sistem ini dapat membantu masyarakat dalam mendiagnosa penyakit Diabetes Melitus. Melalui aplikasi ini, pengguna dapat melakukan konsultasi dengan sistem layaknya berkonsultasi dengan seorang pakar untuk mendiagnosa gejala yang terjadi pada pengguna serta menemukan solusi atas permasalahan yang dihadapi. Hasil pengujian sistem diperoleh nilai Cylomatic complexity = 5 dengan jumlah Region (R)= 5, Node (N)= 10, Edge (E)=13 Predicate Node (P) = 4.]]>
<![CDATA[Forensic storage framework development using composite logic method ]]>
<![CDATA[Helmi Rachman]]>;
<![CDATA[Bambang Sugiantoro]]>;
<![CDATA[Yudi Prayudi]]>
<![CDATA[ ILKOM Jurnal Ilmiah Vol 13, No 1 (2021) ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia ]]>
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DOI: 10.33096/ilkom.v13i1.811.58-66
<![CDATA[Increasing number of information technology users allows possibility for crimes to take advantage of information technology to continue increasing either directly and indirectly. Criminals often use computer devices to commit crimes. This is a major concern so that the need for handling digital evidences becomes significantly urgent. Therefore, a forensic storage framework is required for managing digital evidences. This framework is designed by applying the composite logic method to determine role model of each variable or the initial pattern of the stages to be collaborated. Composite logic produces a role model that is to generate patterns in order to achieve the same goal. This method collaborates framework for handling the pre-existing hdd, ssd, and vmware to be in turn combined into a forensic storage framework. Based on the results of the test, this study proposes a new framework called forensic storage framework which comprises of four main stages, namely preparation, collection, analysis and report. The advantage of this framework is that it can be used to handle digital evidences in four storages which are SSD, HDD, VmWare, and cloud.]]>
<![CDATA[Klasifikasi Masyarakat Miskin Menggunakan Metode Naive Bayes ]]>
<![CDATA[Haditsah Annur]]>
<![CDATA[ ILKOM Jurnal Ilmiah Vol 10, No 2 (2018) ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia ]]>
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DOI: 10.33096/ilkom.v10i2.303.160-165
<![CDATA[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%.]]>
<![CDATA[Pendeteksian Tepi Objek Menggunakan Metode Gradien ]]>
<![CDATA[Dolly Indra]]>
<![CDATA[ ILKOM Jurnal Ilmiah Vol 8, No 2 (2016) ]]>
Publisher : <![CDATA[Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia ]]>
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DOI: 10.33096/ilkom.v8i2.48.69-75
<![CDATA[Pada tahap melakukan ekstraksi ciri (feature extraction) faktor yang sangat penting adalah kemampuan untuk mendeteksi keberadaan tepi di dalam citra. Tujuan penelitian ini adalah menggunakan konsep matematis untuk melakukan fungsi pendeteksian tepi. Uji coba yang dilakukan menggunakan matlab versi R2009a dengan menggunakan citra masukan berupa citra abu-abu (grayscale). Setiap citra diuji dengan menggunakan 3 cara yaitu menggunakan metode gradien citra, gradien Prewitt dan gradien Sobel. Cara kerja dari metode gradien terdiri dari gradien horizontal arah x menghasilkan tepi objek berupa garis vertikal dan diagonal dari citra input, gradien arah vertikal y menghasilkan tepi objek berupa garis horizontal dan diagonal dari citra input sedangkan total gradien merupakan gabungan dari gradien arah x dan gradien arah y sedangkan cara kerja dari untuk metode gradien Prewitt dan Sobel, pemilteran dilakukan secara parsial dengan arah yang berlawanan dengan arah fungsi turunan pertama, bila pemilteran dilakukan dalam arah y maka turunan pertama dari hasil pemilteran dilakukan dalam arah x. Pendeteksian tepi menggunakan gradien Prewitt dan Sobel merupakan hasil gabungan dari konvolusi gradien Prewitt/Sobel arah x dengan gradien Prewitt/Sobel arah y. Hasil uji coba dari penelitian ini memperlihatkan bahwa pendeteksian  tepi menggunakan gradien Sobel lebih tajam dibandingkan dengan gradien Prewitt dan gradien citra.]]>
