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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 JISTech (Journal of Islamic Science and Technology) JURNAL TEKNOLOGI DAN OPEN SOURCE JURNAL PENDIDIKAN TAMBUSAI Jurnal Nasional Komputasi dan Teknologi Informasi IJISTECH (International Journal Of Information System & Technology) JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Mantik JISKa (Jurnal Informatika Sunan Kalijaga) Technologia: Jurnal Ilmiah Jurnal Ilmu Komputer dan Bisnis Health Information : Jurnal Penelitian Journal of Applied Engineering and Technological Science (JAETS) JSR : Jaringan Sistem Informasi Robotik Jatilima : Jurnal Multimedia Dan Teknologi Informasi Journal of Computer System and Informatics (JoSYC) JIKA (Jurnal Informatika) INFOKUM Community Development Journal: Jurnal Pengabdian Masyarakat 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) Jurnal Teknik Informatika (JUTIF) 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 Jurnal Sains dan Teknologi JOMLAI: Journal of Machine Learning and Artificial Intelligence Data Sciences Indonesia (DSI) Internet of Things and Artificial Intelligence Journal Jurnal Ilmiah Teknik Informatika dan Komunikasi Jurnal Ilmu Komputer dan Sistem Informasi Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Nasional Komputasi dan Teknologi Informasi
Mhd Furqan
Universitas Islam Negeri Sumatera Utara
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences 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 Neuroscience Nursing Physics Public Health Social Sciences Transportation Other

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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.
Classification of Scholarships for Students in Schools Using the Naïve Bayes Method Rizki Siregar, Awal; Furqan, Mhd.
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 1 (2025): Article Research January 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i1.5417

Abstract

This research addresses the challenge faced by educational institutions in selecting scholarship recipients by implementing the Naïve Bayes algorithm. The objective of this study is to simplify and improve the accuracy of the scholarship selection process at MTs As-Syarif Kuala Beringin, using data from 50 students. The background highlights the importance of scholarships in providing equal educational opportunities, particularly for students with financial challenges. The research method involves the use of Naïve Bayes to calculate the probability of eligibility based on academic performance, economic background, and student activity. The results show that seven students met the scholarship criteria, demonstrating the efficiency and objectivity of the algorithm. The practical implications include the development of a user-friendly application that facilitates data input, scholarship criteria determination, and clear evaluation results. This system enhances transparency and reliability in decision-making. In conclusion, the Naïve Bayes algorithm proves to be an effective and efficient tool for scholarship selection, enabling a more equitable opportunity for students. Further research could focus on integrating additional data points or comparing the algorithm's performance with other classification methods to enhance system reliability.
Analisis Algoritma Sequential Search Pada Aplikasi Pencarian Berita Furqan, Mhd; Armansyah, A; Kurniawan, Riski Askia
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 8, No 2 (2023): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v8i2.622

Abstract

The algorithm is an approach to be able to compile and manage data efficiently. The Sequential Search algorithm is used to build a mobile-based news search application. The search function is used to validate the data itself. The Sequential Search algorithm has 2 possibilities, namely the best possibility (best case) and the worst case (worst case). In determining a possibility, it takes the complexity of the time algorithm. This study will analyze the Sequential Search algorithm in determining the 2 possibilities that occur in mobile applications. Data is one of the things needed in the development of an application. There are 100 data used by researchers as keywords and researchers will take 5 keywords, namely Earthquake, PDI, Indonesian Education, Floods, and Online Sales to determine the best case and worst case from the Sequential Search algorithm. In determining the speed of time required running time program in units of milliseconds (ms). So that the average time for the earthquake keyword is 0.014189 ms, the PDI keyword is 0.073763 ms, the Indonesian Education keyword is 0.169640 ms, the Flood keyword is 0.206307 ms, and the Online Selling keyword is 0.284086 ms. By obtaining the time from the test, the results of the complexity are also obtained, namely Tmin(n) = 0.014189 ms so that the best case is found in the Earthquake keyword and Tmax(n) = 0.284086 ms so that the worst case is found in the Online Selling keyword. And Tavg(n) = 0.1491375 ms. News API is HTTP REST API which is used to access news after keywords are found
Classification Of Rice Plant Diseases Using K-Nearest Neighbor Algorithm Based On Hue Saturation Value Color Extraction And Gray Level Co-Occurrence Matrix Features Siti Saniah; Mhd. Furqan
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 7 No. 2 (2024): Jurnal Teknologi dan Open Source, December 2024
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v7i2.3972

Abstract

This research aims to classify diseases in rice plants using the K-Nearest Neighbor (K-NN) algorithm based on Hue Saturation Value (HSV) color feature extraction and Gray Level Co-Occurrence Matrix (GLCM) texture. The main problem faced is how to identify the type of disease in rice plants automatically using digital images. Diseases such as Blight, Tungro, and Crackle often attack rice plants and require an accurate early detection system. Lack of understanding in recognizing disease symptoms manually often leads to errors in handling. For this reason, this research develops an image processing-based classification system that can detect diseases such as Blight, Tungro, and Crackle. The method used in this research is image processing which includes RGB to HSV color space conversion, texture feature extraction using GLCM, and classification using K-NN algorithm. The dataset consists of 240 images, divided into training data and testing data, namely 192 training data and 48 testing data. Tests were conducted by calculating accuracy at various values of the K parameter, namely K = 1, K = 3, and K = 5, to determine the effectiveness of the model in classifying plant diseases. The purpose of this study was to evaluate the accuracy of the system in identifying rice diseases and test the combination of HSV and GLCM features in improving classification performance. The results showed that using HSV and GLCM features together resulted in the highest accuracy at K=3 with an accuracy value of 75%. The system is expected to assist farmers in detecting plant diseases quickly and effectively, thus minimizing production losses and supporting agricultural sustainability
Analisis Sentimen Terhadap Tindakan Pemerintah Indonesia Untuk Menampung Sementara Pengungsi Etnis Rohingya Menggunakan Naive Bayes Classifier Gunawan, Irwan; Furqan, Mhd.
CESS (Journal of Computer Engineering, System and Science) Vol. 9 No. 2 (2024): July 2024
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v9i2.61808

Abstract

Etnis Rohingya merupakan penduduk asli di negara myanmar yang sebagian besar mayoritasnya beragama muslim. Konflik yang terjadi pada etnis tersebut dimulai sejak ditetapkannya kebijakan Burma Citizen Law oleh pemerintah myanmar. kebijakan ini berisi terkait penolakan pemerintah myanmar terhadap etnis Rohingya sebagai etnis resmi dan memutuskan jika etnis tersebut tidak termasuk dari negara Myanmar. Indonesia merupakan salah satu negara di ASEAN yang masih menampung sementara pengungsi Rohingya, tindakan ini dilakukan berdasarkan konsep Human Security dan mengacu pada Peraturan Presiden Republik Indonesia Nomor 125 Tahun 2016 Tentang Penanganan Pengungsi Dari Luar Negeri Pasal 4 Ayat 2 mengenai koordinasi penanganan pengungsi yang meliputi Penemuan, Penampungan, Pengamanan dan Pengawasan. Akibatnya, terjadinya cemburu sosial yang berdampak pada keberagamannya opini masyarakat dan menjadi isu yang sering dibicarakan. Penelitian ini bertujuan untuk mengetahui kecenderungan opini berdasarkan klasifikasi sentimen yang diperoleh melalui video YouTube. Manfaat dari penelitian ini adalah agar pemerintah indonesia dapat mengetahui tindakan tersebut cenderung positif atau negatif. Dalam penelitian ini menerapkan algoritma Naive Bayes Classifier dengan dataset berjumlah 7547 yang dibagi menjadi 6037 data latih dan 1510 data uji. Hasil Confussion Matrix pada penelitian ini menunjukan akurasi 93%.
Sentiment analysis of Faculty of Science and Technology students' satisfaction with the 2024 graduation using the Naïve Bayes method Siregar, Kalfida Eka Wati; Ramadani, Wily Supi; Sitepu, Anggi Jelita; Fadil, Ulfi Muzayyanah; Furqan, Mhd.
Internet of Things and Artificial Intelligence Journal Vol. 5 No. 2 (2025): Volume 5 Issue 2, 2025 [May]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v5i2.940

Abstract

Sentiment analysis of UINSU student graduation based on academic data is one of the efforts to understand the factors that affect the success of student studies. This research aims to analyze the sentiment of UINSU student graduation by utilizing academic data such as cumulative grade point average (GPA), number of credits taken, and other relevant attributes, using the Naive Bayes method. Naive Bayes was chosen because of its ability to classify data efficiently and accurately, even though the data used has noise or inconsistency. The research process begins with collecting student data from the university database, and then data cleaning is carried out to ensure the quality of the data used. Next, the data is processed and classified using the Naive Bayes algorithm in Weka software to predict graduation status based on academic parameters. The results show that the Naive Bayes method is able to produce quite high accuracy in predicting student graduation, with accuracy values ranging from 75% to more than 85% depending on parameter selection and data cleaning. GPA is the most influential attribute on the prediction results, while other attributes such as class activity and organizational experience also contribute, although not as much as GPA. These findings provide important insights for the campus in designing more effective academic coaching and planning programs and can be a reference in the development of data mining-based decision support systems to improve the quality of computer science graduates.
Analisis Pola Asosiasi Interaksi Pengguna pada Sistem Informasi Akademik Berbasis Web Menggunakan Algoritma Apriori Rizka; Pratama, Haris; Nabawy, Putri; Cahyadi, Bhagaskara; Furqan, Mhd.
Data Sciences Indonesia (DSI) Vol. 5 No. 1 (2025): Article Research Volume 5 Issue 1, June 2025
Publisher : Yayasan Cita Cendikiawan Al Kharizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/dsi.v5i1.5943

Abstract

Penelitian ini bertujuan untuk menganalisis pola frekuensi data pokok pengguna pada sistem informasi berbasis web menggunakan algoritma Apriori. Analisis ini penting untuk mengidentifikasi asosiasi antar item data yang sering muncul secara bersamaan, guna meningkatkan kualitas layanan sistem dan efisiensi pengambilan keputusan berbasis data. Metode yang digunakan dalam penelitian ini adalah pendekatan data mining dengan algoritma Apriori, yang mampu menemukan pola hubungan antar data dalam bentuk aturan asosiasi. Data yang digunakan berupa transaksi pengguna pada sistem informasi yang disimulasikan melalui dataset dummy, kemudian dianalisis menggunakan Google Colab dengan bahasa pemrograman Python. Hasil penelitian menunjukkan adanya pola hubungan antar fitur yang signifikan, seperti kombinasi halaman yang sering diakses bersama oleh pengguna. Kesimpulan dari penelitian ini adalah bahwa algoritma Apriori efektif dalam mengekstraksi pengetahuan tersembunyi dari data pengguna sistem informasi berbasis web, yang dapat digunakan untuk peningkatan pengalaman pengguna dan pengembangan fitur.
Co-Authors ., Zulpadli Abdul Halim Hasugian Adha, Rifki Mahsyaf Agpina, Pipi Agung Nugroho Ahmad Fakhri Ab. Nasir Ahmad Fauzi Aidil Halim Lubis Aisyah Nurrahmah Siregar Akmal, Muhammad Haikal Andita Utami Anggraini, Delia 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 Bagus Ageng Alfahri Basyir, Muhammad Khalidin Bintang Kurniawan Herman Bob Subhan Riza, Bob Subhan Br Rambe, Indri Gusmita Cahyadi, Bhagaskara Dalimunthe, Ayu Sahriani Daulay, Ikhsan Agus Martua Dea Alya Dewi Aulia Tanjung Diah Putri Kartikasari Dodyk Fahlome Elce, Furkan Fadil, Ulfi Muzayyanah Fadillah, Rini Fadlan, Aulia Fahrul Azis Nasution Faiza, Nayla fandi, Fandi Ahmad Farhan Amar Pramudya Farhan Sadli Siregar Farhan Sadly Siregar FIKRI HAIKAL Fikri Haikal Fredy Kusuma Ramadhani Gunawan, Irwan Hapisfatly Sir Harahap, Khaila Mukti Harahap, Raihan Rizieq Harahap, Rosa Linda Hasrul Hasibuan, Mhd Fikri Heri Santoso Hervilla Amanda R. Siregar 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 Jundi Haqqoni K Khairunnisa Khairi, Nouval Khairunnisa Khairunnisa Khairunnisa, K Kurniawan, Riski Askia Laila Nurzannah Lailatul Badria Lely Sahrani Lubis, Akbar Maulana M. Alfatoni Muarrip M. Fakhriza Mahendra, Rifandi Manza, Yuke Matondang, Toibatur Rahma Maulana Ihsan, Maulana Mey Hendra Putra Sirait Mhd Fadil Ramadhana Mhd Fikri Hasrul Hasibuan Mhd Galih Khairi Mhd Ikhsan Rifki Mhd Reza Alfani Miftahul Rizky Pulungan Muhammad Akbar Ramadhan Tanjung Muhammad Fadil Ramadhana Muhammad Farhan Muhammad Fathir Aulia Muhammad Ikhsan Muhammad Irfan Gurning Muhammad Luthfi Muhammad Naufal Shidqi Muhammad Ridzki Hasibuan Muhammad Rizki Munadi Munadi Nabawy, Putri Nabila, Siti Fadiyah Naina Nazwa Hasibuan Nasution, Afri Yunda Nasution, Irma Yunita Nasution, Romaito Nasution, Zulia Lestari Nayla Faiza Nazwa Aliya Muthmainnah Hasibuan Ningsih, Siti Alus Nur Bainatun Nisa Nur Shafwa Aulia Sitorus Nurhasanah Nurhasanah Nurul Hadi Muliani Hariadi Saputra Nurzannah, Laila Pane, Putri Pratiwi Pangestu, Dimas Panggabean, Alwi Andika Pratama, Haris Prayoga Elfanda Fachmi Hasibuan Putra, Suan Ekie Nanda Putri Salsa Nabila Putri, Alma Irawanti Radhifan Mardhi Raissa Amanda Putri Rakhmat Kurniawan R Ramadani, Wily Supi Ramadhan Nasution, Yusuf Ramadhani, Fredy Kusuma Razzaq H. Nur Wijaya Reza Muhammad Rifnandy, Muhammad Fauzan Rika Rosnelly, Rika Riswanda Ichsan Himawan Hasibuan Rivaldi Prima Nanda Rizka Rizki Ananda Rizki Siregar, Awal Rizqi Hidayat Tanjung RR. Ella Evrita Hestiandari Said Arrahman Salsabila Mahfuza Saparuddin Siregar Sembiring, Yogasurya Pranantha Shafa, Dafa Ikhwanu Sigit Muslim Anggoro Pratono 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 Syahputri Suci Wulandari Suhardi, S Suhardi, Suhardi Susan Mayang Sari Syamia, Nanda Tambak, Tiara Ayu Triarta Tanjung, Tegar Haryahya Tiara Bela Harahap Tria Elisa Wahyudin, Rahmat Wan Fadilla Rischa Wati, Putri Kurni Wicaksana, Agum Widiya Yuli Kartika Siregar Yusuf Ramadhan Nasution Yusuf Ramadhan Nasution Yusuf Ramadhan Nasution, Yusuf Ramadhan Zabni, Nur Hera Zahra Humaira Kudadiri Zaki Musyaffa Ziqra Addilah Zulnun, M. Ridho Azmuddin