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All Journal Teknika Techno.Com: Jurnal Teknologi Informasi Jurnal Informatika PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal Teknologi Informasi dan Ilmu Komputer CESS (Journal of Computer Engineering, System and Science) JURNAL PENGABDIAN KEPADA MASYARAKAT Jurnal Ilmiah KOMPUTASI Sistemasi: Jurnal Sistem Informasi JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING IT JOURNAL RESEARCH AND DEVELOPMENT Indonesian Journal of Artificial Intelligence and Data Mining JRST (Jurnal Riset Sains dan Teknologi) Jurnal Teknovasi : Jurnal Teknik dan Inovasi Mesin Otomotif, Komputer, Industri dan Elektronika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jusikom : Jurnal Sistem Komputer Musirawas ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA JISTech (Journal of Islamic Science and Technology) Jurnal Teknologi Sistem Informasi dan Aplikasi JSiI (Jurnal Sistem Informasi) IJISTECH (International Journal Of Information System & Technology) Journal on Education JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Teknik Elektro dan Komputer TRIAC Jurnal Riset Informatika INFOMATEK: Jurnal Informatika, Manajemen dan Teknologi METIK JURNAL Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar Jurnal Mantik Journal of Information Systems and Informatics INFOKUM U-NET Jurnal Teknik Informatika Journal of Computer Networks, Architecture and High Performance Computing Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknik Informatika (JUTIF) IJISTECH Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Computer Science and Information Technology (CoSciTech) International Journal of Artificial Intelligence and Robotics (IJAIR) Jurnal Pendidikan dan Teknologi Indonesia Journal La Multiapp KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Info Sains : Informatika dan Sains Jurnal IPTEK Bagi Masyarakat Journal of Computer Science and Informatics Engineering Journal Of Human And Education (JAHE) Prisma Sains: Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram International Conference on Sciences Development and Technology STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Innovative: Journal Of Social Science Research Jurnal Pengabdian Masyarakat VISA: Journal of Vision and Ideas Cosmic Jurnal Teknik
Muhammad Siddik Hasibuan
Universitas Islam Negeri Sumatera Utara
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering 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 Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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Klasterisasi Wilayah Prioritas Vaksin Menggunakan Algoritma K-Means Clustering Rahmat Kurniawan; Muhammad Siddik Hasibuan; Riska Hasibuan
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 3 (2023): Desember 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i3.1334

Abstract

K-means clustering algorithm is a clustering method which is done by partition (partitional clustering). The use of clusters intends to partition a number of objects into groups where each object is into the closest group so that it will produce groups with significant differences. In addition, efforts have been made by the government to prevent wider disease transmission, among others, by implementing large-scale social restrictions and monitoring areas where there is a lot of migration of local and foreign residents as well as vaccinating. Looking at the data on the number of people who were infected, died from the Covid-19 virus until they recovered, which occurred in various regions in Indonesia. For this reason, it is necessary to cluster the area from the red, yellow, and green zones, which means for the red zone itself, it means that the area is a danger area and an area with a large number of viruses infected. This study aims to solve the problem, namely to produce applications that can provide information about priority areas for vaccines in North Sumatra, clustering the North Sumatra area, knowing vaccine priority areas using the K- Means algorithm. To find out the results of using the K-Means algorithm application, namely the application can classify Covid 19 cases in each Regency/City in North Sumatra Province into clusters of C1 (High), C2 (Medium) and C3 (Low). Based on the results of the clustering, Medan is in the C1 cluster with a distance value of 0.00 so that it can be prioritized for covid 19 vaccination activities. In the C2 (Medium) clustering there is one Regency, namely Deli Serdang with a 4th iteration value with a distance of 0.00. In the C3 (Low) cluster. Covid-19 case data from march-November 2021 in Nort Sumatra Province was calculated in 4 iterations until there there were no more data changes in the clustering process.
Application of the support vector machine algorithm in the classification of livable houses Mhd Furqan; Muhammad Siddik Hasibuan; Bela Sapitri
Jurnal Mantik Vol. 7 No. 3 (2023): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v7i3.4155

Abstract

Home is a basic need for humans in living life. Humans need a house to live and mingle with family. Having a decent home is the dream of every family. However, due to economic limitations, livable houses are difficult to realize. The government made the Rutilahu (Uninhabitable House) policy to reduce the number of uninhabitable houses. However, in practice there are still many misdirected targets. The Village Government is still carrying out the data classification process manually to determine which houses are livable and which are not. Processes that are still manual are old and inaccurate. For this reason, it is necessary to have a system to classify suitable and ineligible houses using the Support Vector Machine algorithm to make it more detailed so that later the assistance will not be misdirected. Support Vector Machine is a technique for maximizing margins, namely the distance that separates data classes by finding the best hyperplane. Determination of the classification of livable houses is based on four main indicators, namely the structure of the building, its area, sanitation, and clean water. This study took 642 data with 513 training data and 129 testing data and by using validation techniques using the confusion matrix obtained an accuracy of 80%. Thus the system built with the Support Vector Machine algorithm is quite good in the classification of livable houses
Sistem Pakar Membangun Kesuksesan Bisnis Ritel Syariah Menggunakan Metode Forward Chaining dan Certainty Factor Reza Adhitya Budiman; Ilka Zufria; Muhammad Siddik Hasibuan
Journal on Education Vol 6 No 3 (2024): Volume 6 Nomor 3 Tahun 2024
Publisher : Departement of Mathematics Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/joe.v6i3.5635

Abstract

Sharia Retail Business is a type of business that sells goods with a sharia-based retail system. The increasing number of expert systems made by westerners, it is a challenge to create an expert system that is in accordance with Islamic law. The number of Islamic people who like retail businesses such as Carrefour or Alfamart is a reason to create an expert system about retail business. The expert system was chosen because it makes it easier for users to master the concept of Islamic retail business through a knowledge base that is in accordance with sharia teachings. Regarding forward chaining, what is applied is reasoning based on rules that are made and selected to help users choose facts about retail businesses first that suit them, then conclusions are made on previously selected facts. The certainty factor applied is a method that defines belief in a fact and is used to overcome uncertainty in retail businesses. Sharia is applied to the retail business to make it easier for people to purchase goods in unit quantities. The problem in this study is that it is difficult to ascertain whether a retail transaction is sharia-based or not if only seen from the naked eye, in addition to going to a retail store at a cost, there is another solution, namely implementing an expert system in conducting sharia retail transactions. In conducting Islamic retail transactions, a method or algorithm is needed in building an expert system, this study uses Forward Chainning and Certainty Factor algorithms.
OPTIMASI KLASIFIKASI DECISION TREE DENGAN TEKNIK PRUNING UNTUK MENGURANGI OVERFITTING Syahputri, Cindy Novi; Hasibuan, Muhammad Siddik
Jurnal Sistem Informasi Vol 11 No 2 (2024)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v11i2.9161

Abstract

Penelitian ini bertujuan untuk mengoptimalkan klasifikasi Decision Tree menggunakan teknik pruning untuk mengurangi overfitting pada dataset penyakit jantung Kaggle. Overfitting adalah masalah umum dalam pembelajaran mesin, ketika model terlalu cocok dengan data pelatihan dan kehilangan kemampuannya untuk menggeneralisasi data baru dengan baik. Teknik pruning, termasuk prepruning dan postpruning, diterapkan untuk membatasi kompleksitas model dan meningkatkan kemampuannya dalam mengklasifikasikan data baru. Hasilnya menunjukkan bahwa model dengan postpruning memiliki performa terbaik, dengan akurasi 0,8841, recall 0,8571, presisi 0,8571, dan skor F1 0,8571. Sebagai perbandingan, model dengan prepruning memiliki akurasi sebesar 0,8333, recall sebesar 0,8304, presisi sebesar 0,8304, dan skor F1 sebesar 0,7434. Peningkatan metrik ini menegaskan bahwa postpruning lebih efektif dalam mengurangi overfitting dan meningkatkan kemampuan generalisasi model. Dengan demikian, teknik postpruning dapat dianggap sebagai metode unggulan dalam mengoptimalkan kinerja Decision Tree Classifier untuk klasifikasi penyakit jantung. Penelitian ini diharapkan dapat berkontribusi pada pengembangan model prediksi yang lebih akurat dalam diagnosis penyakit jantung, sehingga membantu upaya pencegahan dan pengobatan yang lebih baik. Kata Kunci: Decision Tree, Pruning, Prepruning, Postpruning, Overfitting, Heart Disease Dataset, Kaggle, Machine Learning, Classification, Model Optimization.
Penerapan Data Mining Menggunakan Metode Teknik Klasifikasi Untuk Melihat Potensi Kepatuhan Wajib Pajak Kendaraan Lestari, Rika Dinda; Hasibuan, Muhammad Siddik; Wahyuni, Sri
Journal of Computer Science and Informatics Engineering Vol 3 No 1 (2024): Januari
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v3i1.710

Abstract

Tujuan penelitian ini adalah untuk menguji kepatuhan wajib pajak kendaraan bermotor, dengan fokus pada Samsat Medan Selatan dan UPTD BAPENDA Kota Medan. Sumber utama pendanaan pembangunan dan pelayanan negara yang dapat dinikmati seluruh masyarakat adalah pajak, yang menyumbang lebih dari 70% pendapatan negara. Badan Pendapatan Daerah (Bapenda) mengelola Pajak Kendaraan Bermotor (PKB) yang tergolong pajak daerah dan ditangani oleh Kantor Bersama Sistem Administrasi Terpadu Satu Atap (SAMSAT). Kami dapat mengidentifikasi wajib pajak yang patuh dan tidak patuh dengan menggunakan sampel data wajib pajak kendaraan bermotor dari Samsat Medan Selatan, tepatnya pada bulan Mei 2023. Dalam penelitian ini, data mining diterapkan bersamaan dengan Teknik Klasifikasi menggunakan algoritma Naïve Bayesuntuk mengidentifikasi , dengan akurasi sebesar 70,91%, diantara 110 wajib pajak terdapat yang berpotensi patuh (nilai prior probability: 0,564) dan yang berpotensi tidak patuh (nilai prior probability: 0,436).
Penerapan Algoritma K-Means Untuk Mengetahui Tingkat Kepatuhan Wajib Pajak Kendaraan Bermotor Pada UPT Samsat Medan Selatan Asti, Dini; Hasibuan, Muhammad Siddik; Siregar, Putri Aprilia
Journal of Computer Science and Informatics Engineering Vol 2 No 4 (2023): Oktober
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v2i4.711

Abstract

Kepatuhan Wajib Pajak adalah tindakan menunjukkan patuh dan tertib terhadap kewajiban perpajakan dengan melakukan pembayaran pajak dan melaporkan pajak secara berkala oleh Wajib Pajak yang bersangkutan sesuai ketentuan perpajakan yang berlaku. Kelompok kepatuhan pajak kendaraan bermotor di samsat Medan Selatan dibagi menjadi banyak tingkatan dari rendah ke tinggi. Besaran iuran pajak kendaraan bermotor tergantung dari perhitungan dan pembayaran pajak terutang atas penghasilan yang diperoleh wajib pajak dan Pembayaran tunggakan pajak sebelum jatuh tempo. Tujuan penelitian ini adalah untuk mengetahui tingkat kepatuhan pajak kendaraan bermotor di sammsat Medan Selatan tahun 2023. Algoritma K-Means, yang digunakan melalui metode clustering, menggunakan tahapan KDD, yang mencakup 146 data, yang berasal dari data pembayaran pajak kendaraan bermotor di Samsat Medan Selatan pada tahun 2023. Nilai determinasi cluster sebesar 0,294 dihasilkan oleh hasil pengujian RapidMiner yang menggunakan perhitungan indeks Davies-Bouldin. Dalam cluster 0 ada sepuluh wajib pajak dengan kepatuhan tingkat sangat rendah, di cluster 1 ada 56 wajib pajak dengan kepatuhan tingkat sedang, di cluster 2 ada 19 wajib pajak dengan kepatuhan tingkat rendah; dan di cluster 3, ada 61 wajib pajak dengan kepatuhan tingkat tinggi.
Analisis Keamanan Jaringan Smart Grid PLN Menggunakan Metode Blockchain dalam Konteks Kemananan Cyber Ahmad Affandi Rasyad Nasution; Hasibuan, Muhammad Siddik
Journal of Computer Science and Informatics Engineering Vol 3 No 2 (2024): April
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v3i2.849

Abstract

Saat ini, listrik tidak bisa dipisahkan dari kehidupan sehari-hari. Hampir setiap tugas yang dilakukan manusia sehari-hari melibatkan penggunaan gadget bertenaga listrik. Sudah menjadi rahasia umum bahwa penggunaan energi listrik terus meningkat dari waktu ke waktu. Penerapan Teknologi Blockchain pada Sistem Keamanan Informasi menggunakan metodologi kualitatif, menganalisis dan meneliti berbagai sumber literatur terkait blockchain dan sistem keamanan informasi. Pendekatan ini akan mendukung pemahaman dan penilaian integrasi teknologi blockchain dengan sistem keamanan informasi. Hasil yang diperoleh dalam penelitian ini adalah . Jaringan pintar (smart grid) memiliki ketahanan terhadap bencana alam dan serangan. Smart Grid tidak hanya tahan terhadap serangan fisik, namun juga tahan terhadap serangan siber. Sebagian besar kemajuan ekonomi berasal dari sistem yang kompleks seperti jaringan pintar (smart grid). Pengguna panel surya, misalnya, mungkin membebani jaringan listrik dengan lonjakan listrik dari sumber-sumber ini. Penerapan teknologi blockchain pada sistem keamanan informasi menawarkan sejumlah keuntungan signifikan, termasuk solusi keamanan informasi yang kuat, penyimpanan data yang andal, jaminan integritas data, anonimitas pengguna, dan transparansi dalam data dan transaksi. Penting untuk membicarakan bagaimana teknologi blockchain dapat diterapkan untuk meningkatkan privasi pengguna dan sistem keamanan informasi.
PEMODELAN ALGORITMA AHP DAN SMART PADA SISTEM REKOMENDASI PENERIMA BANTUAN RUMAH LAYAK HUNI DI DESA SIALAMBUE Hasibuan, Bunga Lestari; Hasibuan, Muhammad Siddik; Rifki, Mhd.Ikhsan
JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI Vol 15 No 2 (2024): September
Publisher : UNIVERSITAS STEKOM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtikp.v15i2.894

Abstract

The Livable Home Assistance Program is determined by the Government based on Government Regulation Number 12 of 2021, namely looking at the walls of the house, roof of the house, bathroom, floor of the house and floor area of ​​the house. Sialambue Village is one of the places that receives this program, because the conditions in Sialambue Village also make it possible to participate in this program. Therefore, data collection needs to be done more objectively to get accurate data collection results. So this research was carried out using the AHP and SMART algorithms by applying them to the Matlab application
Lobster Sales Prediction Using Adaptive Neuro Fuzzy Inference System (ANFIS) In Simeulue District Sandira, Sri Delwis; Kurniawan, Rakhmat; Hasibuan, Muhammad Siddik
IJISTECH (International Journal of Information System and Technology) Vol 7, No 6 (2024): The April edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v7i6.339

Abstract

The rapid progress of technology and information is making the challenges of the past become a tantalizing reality of the fourth industrial revolution. Rapid technological progress is marked by major developments in all aspects of life, such as economics, education, health, social and cultural. In the economic world, increasingly sophisticated technological developments will help the work of business actors and force them to innovate and be creative in improving the quality, capacity and products produced. With the vast lobster market, lobster demand experiences a sharp increase every year along with an increase in prices which will provide profits for fishermen in Simeulue. Therefore, predictions of lobster sales are quite important for fishermen in Semeulue to predict lobster sales that will be marketed abroad and domestically the following day, so that fishermen can estimate the lobster seeds or lobster catch needed optimally. In the prediction process The sales data obtained is in the form of a sales history report from 2017 to 2022, then the data obtained will be calculated using the adaptive neuro fuzzy inference system (ANFIS) to then obtain sales prediction results for the following year. And using MAPE calculations with the results of lobster sales training data calculations, the accuracy yields above 99% with a value of 0.0000168031. Therefore, this research will discuss predictions of lobster sales using the adaptive neuro fuzzy inference system (ANFIS) in Simeulue Regency.
Prototype of pH and Water Temperature Control System in Discus Fish Farming Using IoT-based Sugeno Fuzzy Ahmad al-Badawi, Abdullah; Ikhsan, Muhammad; Siddik Hasibuan, Muhammad
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 6 No. 1 (2024): May 2024
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/ijair.v6i1.7524

Abstract

Challenges in cultivating discus fish often arise from abrupt pH and temperature fluctuations attributed to manual and sluggish intervention. An IoT-based prototype for automatic pH and water temperature regulation was developed to address this. The study aimed to evaluate the efficacy of the prototype in controlling pH levels and water temperature and to explore the application of IoT-based fuzzy logic in discus fish cultivation. Test data from the implemented tools and sensors revealed an error comparison value of 0.0132% and an accuracy level of 99.986% for pH measurement. In comparison, temperature sensing yielded an error value of 0% with 100% accuracy. The IoT-based fuzzy Sugeno system demonstrated regular and effective operation in regulating pH and water temperature in discus fish cultivation, showcasing superiority over manual handling systems in mitigating sudden environmental changes.
Co-Authors Abdul Halim Hasugian Ahmad Affandi Rasyad Nasution Ahmad al-Badawi, Abdullah Aidil Halim Lubis Aidil Halim Lubis Ali Darta Ananda, Rizkika Andi Andi Anisa Rahman Anisa Simanjuntak Armansyah Asti, Dini Aulia Nurhasanah, Dhea Aulia, Dhinanda Aulia, M. Arif Bela Sapitri Br Sembiring, Trisna Amanda Dicky Adityanta Sinuraya Efendi, Ayu Mahriza Agustin Erwin Nasution Fadhli Rizqi Haidar Pane Fatih Muhammad, Aji Haikal, Baginda Fikri Hamzah, Aldiva Handira, Dysa Harahap, Parlindungan Harahap, Raihan Hasibuan, Bunga Lestari Heri Santoso Hisbullah, Riki Hotmaidah Harahap Hutabarat, Dio Wahyu Habibi Ichsan Rafisyah Ilka Zufria Indah Permata Sari Ivan Prayuda Khairani Ritonga, Putri Kurniawan, Riski Askia Lestari, Rika Dinda Lipantri Mashur Gultom Lorena, Ayu Lubis, Muhammad Taufik Hakim Lubis, Putri Natasya Mahdiania, Diania Marpaung, Devi Aryani Mhd Furqan Mhd Ikhsan Rifki Mitha Rosadi Mrg, Ricky Aulia Muhammad Abi Muzaki Muhammad Dedi Irawan Muhammad Fadiga Muhammad Ikhsan Muhammad Zulfahmi Nasution Mukhairi Rizal, Muhammad Nasution, Yusuf Ramadhan Naufal, Rahmad Nazhifa Ahmad Fauzan Piramida, Piramida Pratama, Dian Agus Rahmat Kurniawan Rahmat Kurniawan R Rakhmat Kurniawan R Ramadhan, Rizky Syahrul Rangkuti, M. Naufal Reza Adhitya Budiman Riska Hasibuan Rosadi, Mitha Sandira, Sri Delwis Selian, Suci Nadillah Serdano, Akbar Sholihin, Sazili Siagian, Qori Azmi Ayasy Sinuraya, Dicky Adityanta Siregar, Putri Aprilia Sita Kirana Atikah Siti Nurhaliza Sofyan Sri Wahyuni Sriani Sriani Suendri Suhardi Suhardi Suhardi Suhardi, Suhardi Supiyandi Supiyandi Syahputra, Surya Syahputri, Cindy Novi Syaqila, Saidatus Tanjung, Tajuddin Tarigan, Mayang Safhira Triase Triase, Triase Utomo, Imam Yudhistira, Yudhistira Yusuf Karim Rambe Yusuf Ramadhan Nasution Yusuf Ramadhan Nasution, Yusuf Ramadhan