Article Per Year (5 Year)
p-Index From 2020 - 2025
12.69
P-Index
This Author published in this journals
All Journal JURNAL SISTEM INFORMASI BISNIS Techno.Com: Jurnal Teknologi Informasi Scientific Journal of Informatics CESS (Journal of Computer Engineering, System and Science) Sinkron : Jurnal dan Penelitian Teknik Informatika Zero : Jurnal Sains, Matematika, dan Terapan JISTech (Journal of Islamic Science and Technology) JURNAL TEKNOLOGI DAN OPEN SOURCE JURNAL PENDIDIKAN TAMBUSAI J-SAKTI (Jurnal Sains Komputer dan Informatika) IJISTECH (International Journal Of Information System & Technology) JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Mantik JISKa (Jurnal Informatika Sunan Kalijaga) Technologia: Jurnal Ilmiah Health Information : Jurnal Penelitian Journal of Applied Engineering and Technological Science (JAETS) JSR : Jaringan Sistem Informasi Robotik Jatilima : Jurnal Multimedia Dan Teknologi Informasi JIKA (Jurnal Informatika) INFOKUM Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) El-Qist : Journal of Islamic Economics and Business (JIEB) Journal of Computer Networks, Architecture and High Performance Computing Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) IJISTECH Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Walisongo Journal of Information Technology Syntax: Journal of Software Engineering, Computer Science and Information Technology Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Instal : Jurnal Komputer Jurnal Teknisi J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Mandiri IT Jurnal Pustaka Data : Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer JOMLAI: Journal of Machine Learning and Artificial Intelligence Data Sciences Indonesia (DSI) Internet of Things and Artificial Intelligence Journal Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Mhd Furqan
Universitas Islam Negeri Sumatera Utara
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

Published : 93 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 93 Documents
Search

 5   6   7   8   9 
KLASIFIKASI PENYAKIT PADA DAUN CABAI MENGGUNAKAN GRAY LEVEL CO-OCCURRENCE MATRIX DAN K-NEAREST NEIGHBOR Pulungan, Miftahul Rizky; Furqan, Mhd; Rifki, Mhd Ikhsan
Syntax : Journal of Software Engineering, Computer Science and Information Technology Vol 5, No 2 (2024): Desember 2024
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/syntax.v5i2.5386

Abstract

Penyakit tanaman cabai dapat menyebabkan penurunan produksi yang signifikan, sehingga membuat keberlanjutan pertanian dan pangan. Penelitian ini mengembangkan sistem untuk mengkategorikan daun cabai menggunakan Gray Level Co-occurrence Matrix (GLCM) untuk ekstraksi tekstur dan K-Nearest Neighbors (KNN) untuk klasifikasi. Data citra daun cabai yang digunakan meliputi jenis penyakit virus mosaik cabai, layu fusarium, virus kuning, dan bercak daun. Proses tersebut meliputi pemilihan citra, ekstraksi fitur menggunakan GLCM, dan klasifikasi menggunakan KNN. Hasil penelitian menunjukkan bahwa rasio tersebut dapat mencapai hingga 90%, tergantung pada parameter K. Temuan ini penting bagi dunia pertanian, karena dapat menjadi dasar pengembangan sistem deteksi dini berbasis teknologi, sehingga petani dapat mengambil tindakan lebih cepat dan efektif dalam mengendalikan penyebaran penyakit. Implementasi metode ini memiliki potensi besar untuk meningkatkan efisiensi pengelolaan tanaman, mengurangi kerugian ekonomi, dan mendukung pertanian berkelanjutan.Kata kunci: Penyakit daun cabai, K-Nearest Neighbor, GLCM, Klasifikasi. ABSTRACT Chili plant diseases can cause significant production declines, thus making the sustainability of agriculture and food. This study develops a system to categorize chili leaves using Gray Level Co-occurrence Matrix (GLCM) for texture extraction and K-Nearest Neighbors (KNN) for classification. The chili leaf image data used includes types of chili mosaic virus diseases, fusarium wilt, yellow virus, and leaf spots. The process includes image selection, feature extraction using GLCM, and classification using KNN. The results of the study show that the ratio can reach up to 90%, depending on the K parameter. This finding is important for the world of agriculture, because it can be the basis for the development of a technology-based early detection system, so that farmers can take faster and more effective action in controlling the spread of disease. The implementation of this method has great potential to improve the efficiency of crop management, reduce economic losses, and support sustainable agriculture. Keywords: Chile leaf disease, K-Nearest Neighbor, GLCM, Classification.
Implementasi Steganografi Menggunakan Metode Spread Spectrum Dalam Pengamanan Data Teks Pada Citra Digital Nasution, Yusuf Ramadhan; Furqan, Mhd.; Sinaga, Meri
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 4, No 2 (2020): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v4i2.226

Abstract

Various techniques are used to protect digital information, especially information that is kept secret from people who are not entitled to the right of access to information, one of which is the technique of steganography. Steganography technique is a technique used to secure data by inserting or hiding data into an object without changing the shape of the object; one of the objects is a digital image. The steganography technique also has several methods, namely the Spread Spectrum method. Spread Spectrum is a method of communication where information signals are spread across all available frequencies by selecting where to insert data at low frequencies and adding pseudo-noise (PN). This study secures text data with the Spread Spectrum steganography technique on digital image objects by the steps of changing the value of the RGB pixel image and text data into binary, spreading the text data, followed by key generation and the modulation process of spreading text data with the generated key results. To produce a stegano image with an RGB pixel value that changes the value of 0 to 1 value that does not affect the color reproduction of the RGB pixel image.
Klasifikasi Penyakit Kulit Menggunakan Algoritma Naïve Bayes Berdasarkan Tekstur Warna Berbasis Android Furqan, Mhd.; Nasution, Yusuf Ramadhan; Fadillah, Rini
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.421

Abstract

The Skin is an important part of the human body which is used to protect organs from external disturbances (radiation, heat, sharp objects, etc.). the surface of the skin is divided into several textures, namely soft, rough, and supple. The skin also stores fat and is supple. The skin also stores fat and nerves which help in the process of human senses, the skin can also experience bacterial interference that can cause disease, the easiest thing to identify affected skin is through visuals (images). This research is to implement the naive bayes algorithma to classify android based skin diseases in helping the identification process of skin diseases based on visual form (color). Based on the results of the study that the classification of skin diseases (eczema, acne, chicken pox, etc). can be indentified through the naive bayes method and can obtain an accuracy of 75%.
Algoritma Genetika Untuk Perancangan Aplikasi Penjadwalan Mata Pelajaran Furqan, Mhd; Armansyah, A; Ananda, Rizki
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.476

Abstract

The schedule is one of the important activities to help the teaching and learning process in schools, the schedule planning process is still done manually so there are still conflicting schedules between classes. because of the large number of classes and a lot of time ordering a certain day so that sometimes up to 3 times the revision schedule, and the implementation of learning becomes late. To overcome this, one of the appropriate ones is used so that the scheduling process can run well. One of the algorithms used for scheduling the genetic algorithm is one of the improvement algorithms that can be used in various types of problems such as scheduling, the schedule will be tested on classes that clash, which are selected randomly. random or random in each class, the test will be asked to input or fill in the crossover probability number = 0.70 and mutation probability = 0.40 and the number of generations = 1000, then executed. After that it will occur and program execution in the form of selection, crossover, and mutation that will occur in the background of the screen, so that the results of applying 17 classes and 1 laboratory room using the genetic algorithm method can be used to compile a list of lessons.
Algoritma K-Means Untuk Segmentasi Kematangan Buah Jeruk Berdasarkan Kemiripan Warna Furqan, Mhd; Sriani, S; Aulia, Atiqah
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.437

Abstract

The condition of citrus fruits can be determined by looking at several parameters, one of which is color, larger pores, and even yellow skin. So far, the identification of the maturity level of citrus fruits by farmers and consumers has used manual techniques, for example paying attention to the color, pores and peel of the orange product. Such identification will be very large and fluctuating developmental days because people have visual impairments in recognizing, fatigue, and judgment on great development. Barriers to strategy guidance require innovations that can complete the development process impartially, and with clearer results. One of them is the segmentation process using yahoo k-means. The segmentation process aims to divide or separate the image into several (local) districts based on the specified attributes. The k-means algorithm will cluster data with similar attributes assembled into one set and data with various qualities assembled into different sets. From the results of taking pictures from 6 angles, namely front, back, top, bottom, and right and left using 8 datasets, it produces 48 images, and by testing the clustering results, ripe oranges produce 6 and 2 ripe.
Penentuan Kualitas Bibit Padi Menggunakan Metode Fuzzy Mamdani Furqan, Mhd.; Sriani, S; Hasugian, Abdul Halim; Hsb, Munawir Siddik
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 2 (2021): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v5i2.354

Abstract

the agriculture sector still faces fairly basic challenges, namely the quality problem and the increase in competitiveness through productivity and efficiency. This research determines the criteria for the best quality types of rice seeds and how to apply the Fuzzy Mamdani Method, to determine the quality of rice seeds in order to assist farmers in determining the quality of the best rice seeds. Mamdani fuzzy method is one example of a method that can help the optimal decision making process to solve practical problems. The problem solved is the determination of the best quality of rice seeds, based on established criteria, namely the type of rice, the shape of the rice, the color of the seeds, the age of the seeds, and roots. This is done to reinforce the output or output of each input variable membership. Then after the output input output variable is determined, the implementation of the rules for each parameter is carried out. After that do defuzzyfication with the centroid method. So that the output of one parameter is 60 with verry good information. This system was built with a website application where the application is able to help users to determine the quality of rice seeds and obtain information about the best seeds.
IMPLEMENTASI TEXT MINING DALAM IDENTIFIKASI CYBER HATE SPEECH MENGGUNAKAN SUPPORT VECTOR MACHINE Furqan, Mhd; Putri, Raissa Amanda; Daulay, Ikhsan Agus Martua
Jurnal Informatika Vol 8, No 4 (2024): JIKA (Jurnal Informatika)
Publisher : University of Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/jika.v8i4.12581

Abstract

Media sosial sekarang menjadi tempat bagi orang untuk menyampaikan pendapat mereka dan ada banyak cara untuk menyampaikan pendapat tersebut, baik positif maupun negatif. Salah satu contohnya adalah ujaran kebencian dunia maya, juga dikenal sebagai ujaran kebencian dunia maya, yang merupakan bentuk ekspresi yang dilakukan untuk menyebarkan rasa kebecian seperti pencemaran nama baik, penistaan agama, rasisme, dan pelanggaran hak asasi manusia. Penelitian ini dilakukan untuk bisa mengidentifikasi cyber hate speech dalam bentuk teks pada X, yang dibagi 2 kelas yaitu pencemaran nama baik dan penistaan agama. metode yang digunakan adalah SVM (Support Vector Machine) pada penelitian ini dilakukasn beberapa proses seperti pengumpulan data, pelabelan secara manual, pra-proses data dengan text mining, pembobotan dengan tf-idf, klasifikasi dengan merancang model klasifikasi metode support vector machine dan klasifikasi menggunakan data latih dan data uji. Ada 800 data tweet yang digunakan untuk pencemaran nama baik dan penistaan agama dalam bahasa Indonesia, dengan 80% adalah 640 data latihan dan 20% adalah 160 data uji. Hasil pengujian Metode SVM menunjukkan akurasi 96%.
RECOGNITION OF CALLIGRAPHY WRITING PATTERNS USING THE ZERNIKE MOMENT METHOD AND SUPPORT VECTOR MACHINE Furqan, Mhd.; Sriani, Sriani; Himawan Hasibuan, Riswanda Ichsan
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 7, No 4 (2024): November 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i4.2362

Abstract

Abstract: One of the great arts of Islam that is very attached to Muslims is the art of calligraphy. The art of writing in calligraphy is of many types because the art of calligraphy is generally handwritten by someone called khatat and each khatat has its own technique for writing calligraphy. There fore there are many variations of calligraphy writing, even with the same type of writing. With so many variations of the type of calligraphy writing, technological innovation is needed to recognize variations of each type of calligraphy. Types of calligraphy diwani, diwaji jali, naskhi and tsuluts are the objects of this study. The Zernike Moment method is a feature extraction method that has the advantage of being invariant to rotate (resistant to rotation) and can help identify calligraphy types well based on their features. And the Support Vector Machine method is a good method for identifying calligraphy types by finding the best hyperplane. The combination of the Zernike Moment method and the Support Vector Machine is proven to produce good accuracy in recognizing calligraphy types based on their features, the accuracy obtained in identifying calligraphy types is 95%. Keywords: Pattern Recognition, Zernike Moment, Support Vector Machine, Calligraphy Abstrak: Salah satu seni besar Islam yang sangat melekat di kalangan umat Islam adalah seni kaligrafi. Seni menulis kaligrafi banyak macamnya karena seni kaligrafi umumnya ditulis tangan oleh seseorang yang disebut khatat dan setiap khatat mempunyai teknik penulisan kaligrafi tersendiri. Oleh karena itu terdapat banyak variasi penulisan kaligrafi, bahkan dengan jenis tulisan yang sama. Dengan banyaknya variasi jenis tulisan kaligrafi, diperlukan inovasi teknologi untuk mengenali variasi setiap jenis kaligrafi. Jenis kaligrafi diwani, diwaji jali, naskhi dan tsuluts menjadi objek penelitian ini. Metode Zernike Moment merupakan salah satu metode ekstraksi ciri yang mempunyai kelebihan yaitu bersifat invarian terhadap rotasi (tahan terhadap rotasi) dan dapat membantu mengidentifikasi jenis-jenis kaligrafi dengan baik berdasarkan ciri-cirinya. Dan metode Support Vector Machine merupakan metode yang baik untuk mengidentifikasi jenis kaligrafi dengan mencari hyperplane terbaik. Kombinasi metode Zernike Moment dan Support Vector Machine terbukti menghasilkan akurasi yang baik dalam mengenali jenis kaligrafi berdasarkan ciri-cirinya, akurasi yang didapat dalam mengidentifikasi jenis kaligrafi adalah 95%. Kata kunci: Pengenalan Pola, Momen Zernike, Mesin Vektor Pendukung, Kaligrafi
Implementasi Steganografi Menggunakan Metode Spread Spectrum Dalam Pengamanan Data Teks Pada Citra Digital Nasution, Yusuf Ramadhan; Furqan, Mhd.; Sinaga, Meri
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 4, No 2 (2020): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1176.184 KB) | DOI: 10.30645/j-sakti.v4i2.226

Abstract

Various techniques are used to protect digital information, especially information that is kept secret from people who are not entitled to the right of access to information, one of which is the technique of steganography. Steganography technique is a technique used to secure data by inserting or hiding data into an object without changing the shape of the object; one of the objects is a digital image. The steganography technique also has several methods, namely the Spread Spectrum method. Spread Spectrum is a method of communication where information signals are spread across all available frequencies by selecting where to insert data at low frequencies and adding pseudo-noise (PN). This study secures text data with the Spread Spectrum steganography technique on digital image objects by the steps of changing the value of the RGB pixel image and text data into binary, spreading the text data, followed by key generation and the modulation process of spreading text data with the generated key results. To produce a stegano image with an RGB pixel value that changes the value of 0 to 1 value that does not affect the color reproduction of the RGB pixel image.
Klasifikasi Penyakit Kulit Menggunakan Algoritma Naïve Bayes Berdasarkan Tekstur Warna Berbasis Android Furqan, Mhd.; Nasution, Yusuf Ramadhan; Fadillah, Rini
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.421

Abstract

The Skin is an important part of the human body which is used to protect organs from external disturbances (radiation, heat, sharp objects, etc.). the surface of the skin is divided into several textures, namely soft, rough, and supple. The skin also stores fat and is supple. The skin also stores fat and nerves which help in the process of human senses, the skin can also experience bacterial interference that can cause disease, the easiest thing to identify affected skin is through visuals (images). This research is to implement the naive bayes algorithma to classify android based skin diseases in helping the identification process of skin diseases based on visual form (color). Based on the results of the study that the classification of skin diseases (eczema, acne, chicken pox, etc). can be indentified through the naive bayes method and can obtain an accuracy of 75%.
Co-Authors Abdul Aziz Abdul Halim Hasugian Adha, Rifki Mahsyaf Agpina, Pipi Ahmad Fakhri Ab. Nasir Ahmad Fauzi Aidil Halim Lubis Aisyah Nurrahmah Siregar Akmal, Muhammad Haikal Anwar, Mufti Husain Apriansyah, Yuda Ardyanti, Tiwy Armansyah Armansyah Armansyah Armansyah Armansyah Armansyah Armansyah, A Aulia, Atiqah Aulia, Muhammad Arief Aulia, Muhammad Fathir Aulia, Rafif Risdi Badria, Lailatul Br Rambe, Indri Gusmita Cahyadi, Bhagaskara Daulay, Ikhsan Agus Martua Elce, Furkan Fadil, Ulfi Muzayyanah Fadillah, Rini Fahrul Azis Nasution Faiza, Nayla Fakhriza, M. fandi, Fandi Ahmad Fauzan Irsyad FIKRI HAIKAL Gunawan, Irwan Harahap, Khaila Mukti Harahap, Raihan Rizieq Harahap, Rosa Linda Hasrul Hasibuan, Mhd Fikri Himawan Hasibuan, Riswanda Ichsan HP, Kiki Iranda Hsb, Dinda Umami Hsb, Munawir Siddik Hutagalung, Muhammad Wandisyah R Ilham Fuadi Nasution Imam Zaki Husein Nst Iskandar, Rozai Ismail Pulungan Januar, Bagus juwita sari K Khairunnisa Kartikasari, Diah Putri Khairi, Nouval Khairunnisa Khairunnisa Khairunnisa, K Kurniawan, Riski Askia Lely Sahrani Lubis, Akbar Maulana M. Fakhriza Mahendra, Rifandi Maulana Ihsan, Maulana Mey Hendra Putra Sirait Mhd Ikhsan Rifki Mhd Reza Alfani Muhammad Akbar Ramadhan Tanjung Muhammad Farhan Muhammad Ikhsan Muhammad Naufal Shidqi Muhammad Ridzki Hasibuan Muhammad Rizki Munadi Munadi Nabawy, Putri Nabila, Siti Fadiyah Nasution, Afri Yunda Nasution, Irma Yunita Nasution, Zulia Lestari Ningsih, Siti Alus Nugroho, Agung Nurhasanah Nurhasanah Nurhidayati Nurhidayati Nurul Hadi Muliani Hariadi Saputra Nurzannah, Laila Pangestu, Dimas Panggabean, Alwi Andika Pratama, Haris Prayoga Elfanda Fachmi Hasibuan Prayogi, Ahmad Pulungan, Miftahul Rizky Putra, Suan Ekie Nanda Putri, Alma Irawanti Raissa Amanda Putri Rakhmat Kurniawan R Ramadani, Wily Supi Ramadhani, Fredy Kusuma Razzaq H. Nur Wijaya Reza Muhammad Rifnandy, Muhammad Fauzan Rizka Rizki Ananda Rizki Siregar, Awal Rizqi Hidayat Tanjung RR. Ella Evrita Hestiandari Saparuddin Siregar Saputri Nasution, Intan Widya Sembiring, Yogasurya Pranantha Shafa, Dafa Ikhwanu Sinaga, Meri Siregar, Dzilhulaifa Siregar, Hervilla Amanda R. Siregar, Kalfida Eka Wati Sitepu, Anggi Jelita Siti Saniah Siti Sarah Harahap Siti Sumita Harahap Sitorus, Nur Shafwa Aulia Solly Aryza Sri Rahmadani Sri Wahyuni Sriani Sriani Sriani Sriani Sriani, S Suci Wulandari Suhardi Suhardi Suhardi Suhardi Suhardi, S Susan Mayang Sari Syamia, Nanda Tambak, Tiara Ayu Triarta Tanjung, Tegar Haryahya Toibatur Rahma Matondang Tria Elisa Wan Fadilla Rischa Wati, Putri Kurni Widiya Yuli Kartika Siregar Yusuf Ramadhan Nasution Yusuf Ramadhan Nasution, Yusuf Ramadhan Zabni, Nur Hera Ziqra Addilah