Articles
<![CDATA[COMPUTER VISION IDENTIFICATION OF SPECIES, SEX, AND AGE OF INDONESIAN MARINE LOBSTERS ]]>
<![CDATA[Yasir Hasan]]>;
<![CDATA[Kristian Siregar]]>
<![CDATA[ INFOKUM Vol. 9 No. 2, June (2021): Data Mining, Image Processing and artificial intelligence ]]>
Publisher : <![CDATA[Sean Institute ]]>
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<![CDATA[Lobster in Indonesia consists of various types of colors, shapes, and habitats. Documentation results from several studies in the field of fisheries show the dynamics and richness of this type of shrimp species that have a hard and large skeleton. It is necessary to apply this knowledge to the field of information technology and computerization. The application that is right on target for the community is the application that is felt to be useful in the activities of the community itself. The application of information on lobster diversity found in Indonesia in the form of computer technology is to create a knowledge-based lobster recognition computer. This computer technology is designed as a computer vision identification of species, sex, and age of Indonesian water lobsters. Lobster identification is built with three levels of structure, namely the introduction of the type of lobster, the introduction of the sex of the lobster, and the introduction of the age of the lobster. The identification of lobster species here uses color recognition and edge detection techniques from lobster body image data that has been stored in a python-based value library file. For gender recognition using edge detection and pattern recognition techniques from image data of the bottom of the lobster such as the image of the legs. Meanwhile, for the introduction of lobster age, the technique of measuring the length of the lobster carapace distance was used. All these objects can be identified by the features provided by OpenCV in Python language]]>
<![CDATA[Penerapan Algoritma Simplified Memory Bounded A* Pada Permainan Hangman Indonesia ]]>
<![CDATA[Muhammad Yusuf Batubara]]>;
<![CDATA[Mesran Mesran]]>;
<![CDATA[Yasir Hasan]]>
<![CDATA[ Jurnal Sistem Komputer dan Informatika (JSON) Vol 3, No 2 (2021): Desember 2021 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/json.v3i2.3586
<![CDATA[Learning Games are additional tools or facilities used to entertain and add insight to users. The use of learning games or education games is very suitable for children, teenagers and parents even at all ages. This educational game is very easy to reach and use because it is already in everyone's grasp, Hangman Game Mobile is a word game that aims to guess what the questioners mean by guessing the letters one by one so that they are arranged into a word. The Hangman game used to be only made from a piece of paper or on the blackboard in front of the students and asked the answer one by one to the students (students) so that with this activity there was a hangman game. Hangman game based on Android smartphone from several components that can be run inside the application such as letters, actors, hanging poles, ropes, answer columns. This research resulted in a Hangman game application aimed at Learning which was applied on an Android samartpone device and to be developed at a later date.]]>
<![CDATA[Pemanfaatan Desain Grafis Berbasis Android Untuk Promosi Produk Dan Bisnis Di Medsos ]]>
<![CDATA[Yasir Hasan]]>;
<![CDATA[Kristian Siregar]]>
<![CDATA[ Jurnal ABDIMAS Budi Darma Vol 2, No 1 (2021): Agustus 2021 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/pengabdian.v2i1.3150
<![CDATA[Komputer genggam yang canggih yaitu Android telah digunakan oleh siapa pun diseluruh dunia. Tersedia berbagai jenis apilkasi-aplikasigratis untuk membantu pe-kerjaan dan fitur layanan hiburan seperti tontonan yang dapat digunakan oleh pengguna smartphone atau tablet android. Selain itu, aplikasi desain grafis android juga sangat baik dan mampu menghasilkan karya yang berkualitas tinggi layaknya komputer multimedia. Upaya yang dilakukan dengan menyelenggarakan implementasi desain grafis berbasis android untuk promosi produk di medsos sangat penting guna menumbuhkan kesadaran masyarakat yang memiliki usaha untuk dapat memanfaatkan perangkat android sebagai alat membuat karya promosi produk mereka. Masyarakat pemilik usaha juga dapat meningkatkan ketertarikan minat pembeli dengan melihat gambar dan video di medsos]]>
<![CDATA[Computer Vision : Identifikasi Umur Ikan Koi Berbasis Android ]]>
<![CDATA[Yasir Hasan]]>
<![CDATA[ MEANS (Media Informasi Analisa dan Sistem) Volume 5 Nomor 1 ]]>
Publisher : <![CDATA[LPPM UNIKA Santo Thomas Medan ]]>
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DOI: 10.54367/means.v5i1.754
<![CDATA[Koi fish have a long life of more than 200 years, but in general Koi fish are currently around 50 to 70 years, this is due to inadequate facilities and lack of knowledge in Koi fish care. The age of koi fish can be known in several ways, such as knowing by looking at the annual signs or called Annulus and a daily called Circulus. This method is done by observing certain body parts in Koi fish. However, this method is not appropriate at this time and only people who have special expertise can know the age of koi fish. Utilization of computer technology can be used to determine the age of koi fish. The right technology that can be used is computer vision by utilizing a camera on a handheld computer device. In addition, the method that can be used is to process knowledge data on koi fish in the form of long frequencies or size distances. Better size distance in image processing is the Euclidean Distance method. Utilization of this applied technology to determine the age of koi fish is done by measuring the distance of the points specified on the koi fish object as the length of the koi fish. Of course, to do this the system must be equipped with knowledge about the size of koi fish in real terms.]]>
<![CDATA[Aplikasi Penentuan Jenis Ikan Koi Berdasarkan Pembacaan Komposisi Warna Berbasis Android ]]>
<![CDATA[Yasir Hasan]]>
<![CDATA[ Journal of Informatics Management and Information Technology Vol. 1 No. 1 (2021): January 2021 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/jimat.v1i1.96
<![CDATA[Purchasing koi fish can be done online and buyers will be satisfied because they can find out information on koi fish while surfing for information on koi fish that are sold online, but it is different from buying koi fish directly from the seller. Limited knowledge about the types of koi fish can make buyers confused and buy wrong. Buyers may ask directly to the seller, but the seller will not necessarily be fully served. The existence of an android application that can identify types of koi fish can help direct buyers and equip buyers to interact with sellers in koi fish transactions. Koi fish identification by android application is carried out by two determining factors. The first determining factor reads the color value by comparing the color value of the camera captured image with the values ??available in the database. The second determining factor is based on the texture motif found on the koi fish's body. The second determining factor is done if the first determining factor does not support determining the type of koi fish, such as the color composition is very complex to be compared.]]>
<![CDATA[Sistem Pendukung Keputusan Pemilihan Peserta FLS2N SMAN 1 Perbaungan Menggunakan Metode MABAC ]]>
<![CDATA[Zulkarnain Zulkarnain]]>;
<![CDATA[Yasir Hasan]]>
<![CDATA[ KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 2 No. 1 (2021): Agustus 2021 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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<![CDATA[Selection of students of SMAN 1 Perbaungan to find out results that are balanced with the training that has been carried out at the school. SMAN 1 The previous comparison was not good, because there were still students or students who were dissatisfied with the results and there was an unrealistic impression. Besides that, SMAN 1 Perbaungan also had difficulty processing student data because there were only 8 students selected. For this reason, students and SMAN 1 Perbaungan want a more systematic selection process with the help of computerized calculation of decision support systems. The selection process for FLS2N SMAN 1 Perbaungan participants uses the MABAC method. The adoption of a decision support system and the MABAC method can help SMAN 1 Perbaungan in selecting FLS2N participants both systematically and with more realistic ranking results]]>
<![CDATA[Self Organizing Maps (Kohonen) untuk Cluster Bidang Karya Ilmiah (Skripsi) Mahasiswa Berdasarkan Nilai-Nilai Matakuliah Pendukung Machine Learning ]]>
<![CDATA[Hery Sunandar]]>;
<![CDATA[Yasir Hasan]]>
<![CDATA[ Journal of Computer System and Informatics (JoSYC) Vol 3 No 4 (2022): August 2022 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/josyc.v3i4.2108
<![CDATA[The time for the preparation of scientific papers is considered too fast and not suitable for students due to several things in the scope of its preparation. One of the reasons is that the student is unable to complete and the supporting aspects of the field of scientific work being done, many students whose topics of scientific work are in machine learning or the like, but these students are unable to complete their scientific work because they do not understand the theoretical supporting knowledge of the machine learning field. So that it can make the student depressed or even harder to repeat his scientific work the next semester. The scope of machine learning courses are statistics and probability, matrix and linear algebra, algorithms and programming, and data structures. This research was conducted to overcome the problems faced by students, namely knowing the suitability group for the field of student scientific work they will be working on. So that in its preparation students can be responsible in their trial and are of higher quality. The clustering test with the self organizing maps (SOM) algorithm is more stable because the input according to the data owned is not random, only the weighting is done randomly but based on the uniform low (mins) and high (max) limit values. The desired number of clusters is two namely cluster 0 is able to do scientific work based on machine learning and cluster 1 vice versa. The SOM process for 40 student data with a target of two clusters and the results are cluster 0 = 14 students, cluster 1 = 26 students. The result is obtained by increasing the radius = 1, which previously this achievement was not successful if radius = 0.]]>
<![CDATA[Kombinasi Metode ROC dan Metode MAUT dalam Pemilihan Guru pada Madrasah Ibtidaiyah ]]>
<![CDATA[Ramadani II]]>;
<![CDATA[Pristiwanto Pristiwanto]]>;
<![CDATA[Yasir Hasan]]>
<![CDATA[ Bulletin of Data Science Vol 2 No 1 (2022): Oktober 2022 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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<![CDATA[Madrasah Ibtidaiyah Nurul Hidayah, Bandar Khalipah District, is one of the formal education infrastructure under the guidance of the Minister of Religion whose learning process is based on Islam at the elementary school level. This school is in need of Indonesian language teachers. The teacher is a teacher of a science and the teacher in general is a professional educator who has the main task of educating, directing, guiding, training, assessing, and evaluating his students, so in this case the author wants to help the school in the selection of Indonesian language teachers in Madrasah schools. Ibtidaiyah Nurul Hidayah, whose recruitment is still fairly manual. In this study the author has a solution and will solve the problem by applying the Rank Order Centroid (ROC) method and the Multy Attribute Utility Theory (MAUT) method, the author will combine the two methods to determine the best alternative in the selection of Indonesian language teachers in Madrasahs. Ibtidaiyah Nurul Hidayah. The results of the algorithm on the combination of the two methods show that Alternative 5 (A5) has the highest score of 0.832 and ranks 1, thus A5 is the best alternative that will be recommended for teacher selection at Madrasah Ibtidaiyah Nurul Hidayah. The application by combining the Rank Order Centroid (ROC) method and the Multi Attribute Utility Theory (MAUT) method can determine the best alternative in terms of teacher selection.]]>
<![CDATA[Aplikasi Pengekstrak Gambar Ke Excel dan Uji Ektraksi dengan Kirsch Untuk Deteksi Tepi ]]>
<![CDATA[Yasir Hasan]]>;
<![CDATA[Hery Sunandar]]>
<![CDATA[ MEANS (Media Informasi Analisa dan Sistem) Volume 8 Nomor 1 ]]>
Publisher : <![CDATA[LPPM UNIKA Santo Thomas Medan ]]>
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<![CDATA[Pixel extractor application to retrieve image pixel values and save them in Excel format. Matlab is often used for pixel extraction, but the transfer process to Excel is difficult and long if the image resolution is large. The placement of pixel values in Excel is useful for knowing the process of image processing mathematical formulas. The solution of this application is that the user can select images to be processed and the pixel extraction results are stored in three separate Excel sheets, namely red (R), green (G), blue (B), and Grayscale values. Convenience This is useful for analyzing pixel data for users. In this study, the extracted pixel values were tested using the Kirsch operator for edge detection. Doing a test of one Kirsch kernel on a grayscale sheet. This application is built using the Python programming language and the PySimpleGUI library to create an easy-to-use user interface.]]>
<![CDATA[Machine Learning Pengenalan Herpetofauna Dilindungi Di Indonesia ]]>
<![CDATA[Yasir Hasan]]>
<![CDATA[ KAKIFIKOM : Kumpulan Artikel Karya Ilmiah Fakultas Ilmu Komputer Volume 5 Nomor 2 Tahun 2023 ]]>
Publisher : <![CDATA[UNIKA Santo Thomas ]]>
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<![CDATA[The population of herpetofauna animals in Indonesia is decreasing due to hunting, habitat destruction, and illegal trade. Apart from that, there is very little introduction to Herpetofauna among reptiles and amphibian lovers. There are also many cases of ownership and buying and selling of reptiles and amphibians that end with the forced taking of these Herpetofauna animals and even imprisonment for not having permission from the government. The problem of lack of knowledge about the types of Herpetofauna is one of the causes of the rarity of these animals which will become extinct in the future. Therefore, more effective and efficient conservation support efforts are needed in the form of research based on artificial intelligence to identify protected Herpetofauna animals in Indonesia. This research uses Machine Learning technology and the method used for segmentation is Deep Learning which is included in the YOLO stage and is very supportive in edge detection, color change, and classification. The use of this technology is implemented in a GUI application built in Python which can be used as a detection tool for the types of herpetofauna found in nature, in captivity, or in reptile trading markets. Therefore, Machine Learning Research Herpetofauna is very important to contribute to the government's conservation efforts to protect Herpetofauna and is expected to be sustainable for future generations.]]>
