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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

Author-ID : 2406700

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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PERANCANGAN APLIKASI SISTEM PAKAR METODE FUZZY MULTY CRITERIA DECISION MAKING PADA PENYAKIT DERMATITIS MANUSIA Sholihin, Sazili; Santoso, Heri; Hasibuan, Muhammad Siddik
Jusikom : Jurnal Sistem Komputer Musirawas Vol 8 No 2 (2023): Jusikom : Jurnal Sistem Komputer Musi Rawas DESEMBER
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jusikom.v8i2.2223

Tujuan penelitian ini untuk membantu pihak medis dalam mendiagnosis penyakit dermatitis manusia, dengan merancang aplikasi sistem pakar yang memanfaatkan metode Fuzzy Multi-Kriteria Decesion Making yang dapat diakses dalam sebuah aplikasi berbasis web. Cara kerja penerapan Fuzzy Multy Criteria Decision Making dalam mendiagnosis penyakit dermatitis manusia adalah sebagai berikut: a) Tahap perencanaan, yaitu ilustrasi rencana kerja. b) Tahap pengumpulan data, yaitu dengan cara studi literatur, observasi, dan wawancara. c) Tahap perancangan, yaitu membuat alur sistem kerja. d) Tahap pengujian, yaitu menguji aplikasi dengan kriteria yang ditentukan. e) Tahap penerapan, yaitu aksi nyata di lingkungan medis. Berdasarkan penelitian yang telah dilakukan, didapat hasil: a) 4 jenis penyakit dermatitis yang dialami manusia, diantaranya: dermatitis atopik, dermatitis kontak, dermatitis seroboik, dan dermatitis statis. b) Terdapat 16 gejala penyakit dermatitis yang dialami manusia yaitu ruam, kering, rapuh, gatal, melepuh, warna kulit, kemerahan, gatal parah, kulit seperti terbakar, ketombe, kulit terbakar, ketombe, kulit terkelupas, rambut rontok, iritasi kulit, perih, sakit ketika berdiri, dan memar. 16 gejala tersebut dibuktikan dari kecocokan setiap nilai, mulai dari nilai fuzzy tertinggi yaitu 1, nilai fuzzy tengah yaitu 0,9 dan fuzzy terendah yaitu 0,85.

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

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

TEXT CLUSTERING IN KARO LANGUAGE USING TF-IDF WEIGHTING AND K-MEANS CLUSTERING Br Sembiring, Trisna Amanda; Hasibuan, Muhammad Siddik
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.5.1462

The aim of this research is to see how many presentations there are between dialects and look for clusters. There is also a method used for weighting, namely tf-idf, there are several steps used in this method, namely starting from the tokenizing process, transform cases, stopwords filter and token filter. to search for clusters using the k-means clustering method on rapidminer. The results of this research obtained a tf-idf weighting value, namely ginger dialect 37.5% for the number of word occurrences and 62.5% for the total of all words documented. Furthermore, for the Julu dialect, it was 37.5% for the number of word occurrences and 62.5% for the total of all words documented. The Singaporean Lau dialect accounts for 38% of the number of word occurrences and 62% of the total number of words documented. The singteruh deleng lau dialect accounts for 38% of the number of word occurrences and 62% of the total number of words documented. The Liang Melas dialect accounts for 38% of the number of word occurrences and 62% of the total number of words documented. Based on k-means clustering, it produces cluster 0: 68 items, cluster 1: 3 items, cluster 2: 15 items, cluster 3: 10 items, cluster 4: 4 items with a total sample of 100 items. The conclusion obtained is that the Ginger dialect and the Julu dialect are identical, while the Singaporean Lau dialect, the Teruh Deleng and Liang Melas dialects are also identical.

Classification of Watermelon Ripeness Levels Using HSV Color Space Transformation and K-Nearest Neighbor Method Efendi, Ayu Mahriza Agustin; Sriani, Sriani; Hasibuan, Muhammad Siddik
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.3999

Watermelons had high appeal due to their sweet taste, refreshing nature, and numerous benefits. However, consumers often faced difficulties in selecting suitable fruit because of the subtle differences between fully ripe and half-ripe watermelons. One important indicator of a watermelon’s ripeness was the yellowish pattern on its skin. In this study, the proposed use of digital image processing methods, specifically the HSV Color Space Transformation, was aimed at extracting watermelon images and employing the K-Nearest Neighbor (K-NN) method to classify them into two categories: "Ripe" and "Half-Ripe." HSV (Hue Saturation Value) was a color extraction method used to convert colors from the RGB model. The Hue component indicated the type of color, Saturation measured the purity of the color, and Value measured the brightness of the color on a scale from 0 to 100%. In this research, the K-Nearest Neighbor (K-NN) method was applied to classify watermelon images based on the extraction of skin color features. This method compared a new image (test data) with training images to determine classification based on the nearest distance with a parameter of k=3. The data used consisted of 120 images, with 92 images used as training data and 28 images as test data. Experimental results showed an accuracy of 89%, with 25 images correctly classified and 3 images misclassified.

Penerapan Sistem Pendukung Keputusan Dalam Memilih Supplier Menggunakan Metode Analytical Hierarchy Process (AHP) Mahdiania, Diania; Hasibuan, Muhammad Siddik
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 1 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i1.38269

PT. LSP (Langkat Sawit Hijau Pratama) is a palm oil factory, where palm fruit or palm kernels are processed into palm oil (unfinished crude oil) which can be further processed into cooking oil, industrial oil or fuel. To get the best crude oil, superior and quality palm oil is needed, so a Decision Support System is needed in choosing suppliers to maintain good quality palm oil. A decision support system (DSS) in selecting suppliers is important because the right supplier can have a positive impact on company performance. Using a Decision Support System (DSS) with the Analytical Hierarchy Process (AHP) method in selecting suppliers can increase efficiency and effectiveness in decision making, as well as help companies choose the right suppliers and have the potential to have a positive impact on company performance. This research aims to determine the performance of the Analytical Hierarchy Process (AHP) in the Supplier selection Decision Support System and utilize the Decision Support System using the Analytical Hierarchy Process (AHP) method in making decisions as part of the consideration in choosing the right supplier. The results of this research show that by comparing decisions with the Saaty theory, priority weightings for each criterion and sub-criteria are obtained consistently or CR < 0.1. Price Criteria (0.0699), Capacity Criteria (0.2289), Quality Criteria (0.5081), Arrival Criteria (0.1932). Having obtained the final score, the best supplier has been determined using the Analytical Hierarchy Processes method, namely the BEST supplier with a total of 0.5870, and the last position is the TANI9 supplier with a total of 0.0958.

Penerapan Sistem Pendukung Keputusan dalam Memilih Supplier Menggunakan Metode Analytical Hierarchy Process (AHP) Mahdiania, Diania; Hasibuan, Muhammad Siddik
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 1 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i1.39286

Best Student Classification using Ensemble Random Forest Method Mrg, Ricky Aulia; Hasibuan, Muhammad Siddik
Sistemasi: Jurnal Sistem Informasi Vol 13, No 3 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i3.4101

Education at Madrasah Aliyah Negeri 1 Medan considers religious values, ethics, leadership, and participation in extracurricular activities as an integral part of student character building. Therefore, it is necessary to develop a classification system that integrates these various aspects to ensure that the best students not only excel in academic exams but also have strong social, leadership, moral and extracurricular abilities. The purpose of this research is to implement the Random Forest Ensemble method in predicting the best students of MAN 1 Medan and build a system in predicting the best students of MAN 1 Medan using the Random Forest Ensemble method. The data used is 550 divided into 385 data as Training data and 165 Testing data. In the implementation of Random Forest with three decision trees formed from entropy calculations on 385 training data, followed by testing using 10 testing data from a total of 165 existing data, the results show that the model predicts 8 data as class 1 (best students) and 2 data as class 0 (normal students) from a total of 10 testing data. From the test results using 385 training data and 165 testing data, the Random Forest model predicted 70 data as the best students (class 1) and 95 data as normal students (class 0) with high precision for both classes (0.94 for class 0 and 0.99 for class 1), as well as high recall for both classes (0.92 for class 0 and 0.99 for class 1) The overall accuracy reached 0.96, confirming the model's ability to classify the data well overall.

Clustering Medical Record Data on Diabetes Disease using Divisive Analysis Clustering Method Tarigan, Mayang Safhira; Hasibuan, Muhammad Siddik
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.4380

Diabetes is a chronic disease characterized by high levels of sugar (glucose) in excess of normal limits, about 1.5 million deaths each year are directly attributed to diabetes. The purpose of this study is to obtain the optimal cluster analysis results on grouping medical record data on diabetes and obtain the silhouette coefficient value of the optimal cluster analysis results on grouping medical record data on diabetes at TK-II Putri Hijau Kesdam I / B Hospital, Medan-North Sumatra by using the divisive analysis algorithm and determining the variables that cause the patient to develop diabetes. The results showed that the optimal cluster using the divisive analysis algorithm was 2 clusters with a value of 0.468582 which stated that the cluster structure formed in this grouping was the right cluster. And for variables that cause patients to develop diabetes, namely age (X2) and blood sugar level (X8). it is because these two variables have the highest average value among the two clusters and all these variables.

Pengatur Kelembaban dan Suhu Kumbung Jamur Tiram Otomatis Menggunakan Mikrokontroller Atmega328 dengan Logika Fuzzy Berbasis Iot Muhammad Abi Muzaki; Rakhmat Kurniawan; Muhammad Siddik Hasibuan
VISA: Journal of Vision and Ideas Vol. 4 No. 3 (2024): VISA: Journal of Vision and Ideas
Publisher : IAI Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/visa.v4i3.3023

Fungi live by taking other products from dead organisms and usually only grow in moist places. It is known that the living environment of mushrooms can grow well at a temperature of 16°C - 30°C with a humidity of 80 - 95%. there are several obstacles for mushroom cultivators in oyster mushroom cultivation, seeing changes in temperature and humidity that often occur to increases and decreases in temperature and humidity can occur at any time. To make it easier for farmers to monitor changes in temperature and humidity in mushroom kumbung, an automatic control system is needed that can provide information related to temperature and humidity in real time and when the temperature and humidity are not appropriate, the control system can help maintain temperature and humidity by spraying water, the system This control uses the Atmega328 Microcontroller as a data processor. This control system is designed using fuzzy logic which is expected to help provide the best temperature and humidity in the mushroom kumbung area by using a DHT11 sensor to detect temperature and humidity, and the help of ESP8266 which was developed into an Internet of things to make it easier to monitor temperature and humidity. in real time. In this study, the fuzzy Sugeno method is used because this method is suitable for finding temperature and humidity levels that often change. With this fuzzy logic method, a mathematical circuit is obtained which is used to represent ambiguity, and lack of information.

Peningkatan Akurasi Named Entity Recognition (NER) Dengan Fine-Tuning BERT Pada Dataset Bahasa Indonesia Fatih Muhammad, Aji; Hasibuan, Muhammad Siddik
CESS (Journal of Computer Engineering, System and Science) Vol. 10 No. 2 (2025): Juli 2025
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v10i2.67219

Named Entity Recognition (NER) merupakan salah satu tugas utama dalam bidang Natural Language Processing (NLP) yang bertujuan untuk mengenali dan mengklasifikasikan entitas seperti nama orang, organisasi, lokasi, dan tanggal di dalam teks. Meskipun banyak penelitian telah dilakukan untuk bahasa sumber daya tinggi seperti bahasa Inggris, bahasa Indonesia masih menghadapi keterbatasan, baik dari segi dataset maupun kompleksitas linguistik. Penelitian ini bertujuan untuk meningkatkan akurasi sistem NER berbahasa Indonesia dengan melakukan fine-tuning pada model BERT pra-latih, khususnya IndoBERT, menggunakan dataset NERGRIT yang telah dianotasi. Proses penelitian mencakup tahap pra-pemrosesan data, tokenisasi, pelatihan model, dan evaluasi kinerja menggunakan metrik precision, recall, dan F1-score. Model yang telah di-fine-tune diuji dengan berbagai kalimat dan menunjukkan peningkatan akurasi yang signifikan dibandingkan model dasar. Namun demikian, masih ditemukan beberapa permasalahan seperti prediksi berlebihan dan ketidaksesuaian pelabelan entitas. Hasil penelitian ini membuktikan bahwa fine-tuning BERT dapat secara signifikan meningkatkan performa NER dalam teks berbahasa Indonesia. Penelitian ini memberikan kontribusi terhadap pengembangan teknologi NLP bahasa Indonesia serta membuka peluang penerapan pada chatbot cerdas, sistem pemrosesan dokumen, dan analisis opini publik. Penelitian ini menunjukkan pendekatan yang berbeda dibandingkan studi terdahulu dengan mengadopsi dataset NERGRIT, yang mencakup 2.090 kalimat dan 41.871 token, serta mencakup 8 kategori entitas utama, seperti PER, ORG, LOC, DATE, MONEY, PRODUCT, EVENT, dan LAW. Dataset ini belum banyak digunakan dalam publikasi ilmiah, sehingga memberikan kontribusi orisinal dalam eksperimen pengembangan sistem NER untuk Bahasa Indonesia. Penelitian ini juga menggunakan model IndoBERT yang telah di-fine-tune sebelumnya pada dataset serupa, yaitu model hendri/nergrit, namun dilakukan pelatihan ulang (re-fine-tuning) guna meningkatkan kinerja pada konteks lokal dan sintaksis khas Bahasa Indonesia. Secara kuantitatif, penelitian ini berhasil meningkatkan performa model secara signifikan. Sebelum dilakukan fine-tuning, model dasar menghasilkan skor F1 sebesar 72,38%. Setelah melalui proses fine-tuning menggunakan dataset NERGRIT, model mencapai nilai F1-score sebesar 83,67%, dengan nilai precision sebesar 85,12% dan recall sebesar 82,24%. Peningkatan sebesar lebih dari 11 poin F1-score ini menunjukkan efektivitas pendekatan fine-tuning pada model BERT untuk NER Bahasa Indonesia. Selain evaluasi metrik klasik, penelitian ini juga menyertakan analisis kesalahan (error analysis) untuk mengevaluasi fenomena over- prediction dan ketidaksesuaian label entitas pada token umum. Analisis ini mengungkap bahwa meskipun model berhasil mengenali entitas seperti nama orang dan lokasi dengan confidence tinggi, masih terdapat kesalahan pada token non-entitas yang ikut dilabeli secara tidak akurat. Penambahan analisis kualitatif ini menjadi poin keunggulan yang jarang ditemui pada penelitian sejenis. Dengan demikian, kontribusi penelitian ini tidak hanya terletak pada pencapaian performa, tetapi juga pada pendekatan evaluatif yang menyeluruh, serta pemanfaatan dataset dan model yang relatif baru dalam lingkup NLP Bahasa Indonesia.

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

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