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All Journal Paradikma: Jurnal Pendidikan Matematika JURNAL PENELITIAN SAINTIKA Jurnal IPTEK JURNAL PENGABDIAN KEPADA MASYARAKAT Journal of Tropical Biodiversity and Biotechnology Jurnal KARISMATIKA JTT (Jurnal Teknologi Terpadu) Indonesian Journal of Artificial Intelligence and Data Mining BAREKENG: Jurnal Ilmu Matematika dan Terapan bit-Tech Jurnal Sains dan Teknologi JATI (Jurnal Mahasiswa Teknik Informatika) PHI: Jurnal Pendidikan Matematika SKANIKA: Sistem Komputer dan Teknik Informatika Journal of Soft Computing Exploration Djtechno: Jurnal Teknologi Informasi Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) INCODING: Journal of Informatics and Computer Science Engineering Instal : Jurnal Komputer Archive: Jurnal Pengabdian Kepada Masyarakat PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer Journal of Artificial Intelligence and Engineering Applications (JAIEA) Blend Sains Jurnal Teknik Journal of Student Research EINSTEIN (E-JOURNAL) Ocean Engineering: Jurnal Ilmu Teknik dan Teknologi Maritim Innovative: Journal Of Social Science Research Asian Journal of Applied Education Lencana: Jurnal Inovasi Ilmu Pendidikan Journal of Informatics and Data Science (J-IDS) Journal of Mathematics, Computation and Statistics (JMATHCOS) Darma Abdi Karya: Jurnal Pengabdian Kepada Masyarakat Journal of Information Technology
Said . Iskandar
Universitas Negeri Medan
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology 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 Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Pengembangan Website Dengan Algoritma K-Nearest Neighbor (KNN ) Dalam Klasifikasi Perkembangan Prestasi Siswa Terhadap Hasil Belajar (Studi Kasus SD Negeri 107396 Paluh Merbau) Siburian, Rulli Prasetio Bane; Refisis, Nice Rejoice; Rangkuti, Yulita Molliq; Napitupulu, Elvis; AI Idrus, Said Iskandar
Innovative: Journal Of Social Science Research Vol. 4 No. 5 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i5.12832

Abstract

Pemahaman perkembangan intelektual anak di SD sangat penting sebagai acuan pendidikan. SD Negeri 107396 Paluh Merbau, yang masih menggunakan metode manual untuk mengklasifikasikan nilai siswa, menjadi tempat ideal untuk penelitian ini. Tujuan penelitian adalah menganalisis efektivitas algoritma K-Nearest Neighbor (KNN) dalam klasifikasi perkembangan siswa berdasarkan hasil belajar dan membangun website sebagai platform pengumpulan data dan implementasi KNN. Prestasi siswa diukur melalui nilai ujian semester, ujian harian, tugas, sikap, dan absensi. Data dikumpulkan secara dokumenter dan dianalisis dengan mengurutkan jarak data uji ke data latih dari yang terkecil hingga terbesar, menggunakan k=1 hingga k=10. Hasil klasifikasi mayoritas menunjukkan prestasi Rafa Rifa'i berada di kategori kelas 0 (di bawah rata-rata). Penelitian ini menunjukkan bahwa algoritma KNN efektif dalam klasifikasi prestasi siswa, memberikan wawasan untuk meningkatkan strategi pembelajaran.
Determining Tourist Destination Priorities Using Website-Based Particle Swarm Optimization Methods (Case Study : North Padang Lawas Regency) Salsabila, Aqila; Molliq Rangkuti, Yulita; Muslim Karo Karo, Ichwanul; Iskandar Al-Idrus , Said
Journal of Mathematics, Computations and Statistics Vol. 7 No. 2 (2024): Volume 07 Nomor 02 (Oktober 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i2.4233

Abstract

. Optimization of tourist routes is very important to minimize travel time and reduce travel costs. This study focuses on optimizing tourist routes in North Padang Lawas Regency using Multi Attribute Utility Theory (MAUT), and Particle Swarm Optimization (PSO) in the context of the Traveling Salesman Problem (TSP). This study discusses problems such as the lack of priority of tourist destinations and the need for shorter travel times. The research process includes problem identification, literature review, data collection through field observations and interviews, and data processing with MAUT to prioritize destinations. The identified priority destinations are Hotel Sapadia Gunung Tua, Barumun Nagari, Batik Sekar Najogi, Durian and Manggis Agrotourism, Rumah Makan Holat Alhamdulillah, Waterboom Gunung Tua, and Candi Bahal I, II, III. Furthermore, PSO is applied to determine the optimal travel route. PSO finds a route with a total travel time of 351 minutes, although the three-day travel time is extended to 375 minutes.
DEVELOPMENT OF MATHEMATICS STUDENT WORKSHEET WITH THINK TALK AND WRITE (TTW) APPROACH TO INCREASE STUDENT MATHEMATICAL COMMUNICATION SKILLS IN SMK NEGERI 14 MEDAN Simbolon, Mula Tua Elia; Al Idrus, Said Iskandar
PHI: Jurnal Pendidikan Matematika Vol 8, No 2 (2024): Oktober, 2024
Publisher : Universitas Batanghari Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33087/phi.v8i2.386

Abstract

The mathematical communication skills of students at SMK Negeri 14 Medan are quite low and this can be seen from the results of observations made by researchers on students. Therefore this research was conducted to develop a student worksheet that can be used by students and teachers in the learning process. This student worksheet uses the Think Talk and Write approach and is considered capable of being valid, practical, and effective in helping students learn and improving students' mathematical communication skills. research is a type of research and development research using the ADDIE model. the ADDIE model consists of the Analysis, Design, Develop, Implementation, and Evaluation stages. from the results obtained it was found that the student worksheet was valid with a score of 88%. then this student worksheet is also practical to use as seen from the results of the student questionnaire and teacher questionnaire. then the effectiveness of student worksheets is also classified as medium in improving students' mathematical communication skills seen from the N-Gain obtained by students is 5.8
IDENTIFIKASI JENIS PENYAKIT PADA TANAMAN CABAI RAWIT MENGGUNAKAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK (CNN) DI DESA BINTANG KECAMATAN SIDIKALANG Josafat Simanjutak, Todo; Saputra S, Kana; Syahputra, Hermawan; Iskandar Al Idrus, Said; Febrian, Didi
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 1 (2025): JATI Vol. 9 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i1.12403

Abstract

Cabai rawit merupakan jenis tanaman terna atau setengah merdu, memiliki tinggi sekitar 50-120 cm dengan umur bisa mencapai 3 tahun, Prospek cabai rawit cukup menjanjikan untuk memenuhi kebutuhan domestik dan ekspor Namun, produksi justru menurun. Salah satu faktor penyebab rendahnya produksi tanaman cabai adalah adanya gangguan penyakit yang menyerang. Identifikasi penyakit tanaman menjadi langkah penting dalam pemeliharaan dan perawatan, termasuk pada cabai rawit.metode yang digunakan dalam penelitian ini adalah Metode CNN (Convolutional Neural Network) dengan LeNet-5 sebagai arsitekturnya.Penelitian ini berhasil mengembangkan sistem berbasis Convolutional Neural Network (CNN) menggunakan arsitektur LeNet-5 untuk mengidentifikasi dan mengklasifikasi enam kelas penyakit pada tanaman cabai rawit di Desa Bintang, Kecamatan Sidikalang, dengan kinerja yang cukup baik ditunjukkan oleh akurasi 86%, presisi 87%, recall 86%, dan f1-score 86%.Untuk meningkatkan performa sistem, disarankan untuk melakukan eksperimen lebih lanjut dengan mengoptimalkan hyperparameter seperti learning rate dan jumlah epoch, memperluas dataset dengan variasi citra, mengeksplorasi arsitektur model yang lebih modern seperti AlexNet atau ResNet, serta menggunakan perangkat keras dengan spesifikasi yang lebih tinggi untuk efisiensi dan kecepatan pemrosesan yang lebih baik.
Implementation of text summarization on indonesian scientific articles using textrank algorithm with TF-IDF web-based Sihombing, Jeremia Jordan; Arnita, Arnita; Al Idrus, Said Iskandar; Niska, Debi Yandra
Journal of Soft Computing Exploration Vol. 5 No. 3 (2024): September 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i3.475

Abstract

The development of information technology has significantly changed how information is accessed, necessitating readers to absorb content efficiently and make quick decisions. To address this challenge, this research developed a text summarization system specifically for Indonesian scientific articles using a web-based implementation of the TextRank and TF-IDF algorithms. TextRank was selected for its capability to identify key sentences without requiring training data, while TF-IDF was employed to weight words based on their frequency within the document. The dataset comprised 100 scientific articles in Indonesian from the Unimed Kode Journal, covering the years 2022-2024. The summarization process included several critical stages: text preprocessing, TF-IDF weighting, cosine similarity calculation, and sentence ranking. The resulting summaries were rigorously evaluated by language experts and website specialists using a Likert scale to assess both the quality of the summaries and the usability of the system. The findings demonstrated that the system effectively generated summaries that retained essential information from the original articles, with the highest accuracy observed at a 50% compression rate (88.533%). Additionally, the system achieved good performance at 40% compression (85.133%) and 30% compression (81.26%). The web-based system allows users to input article text and quickly obtain a summary, offering a practical tool for researchers and readers to efficiently comprehend academic content.
Website based classification of karo uis types in north sumatra using convolutional neural network (CNN) algorithm Purba, Boy Hendrawan; Syahputra, Hermawan; Idrus, Said Iskandar Al; Taufik, Insan
Journal of Soft Computing Exploration Vol. 5 No. 4 (2024): December 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i4.500

Abstract

Indonesia is one of the largest archipelagic countries in the world. It has abundant cultural diversity including nature, tribes. One of the tribes in Indonesia is the Batak Karo tribe. Batak Karo is a tribe that inhabits the Karo plateau area, North Sumatra, Indonesia. Batak Karo has various cultures, one of which is a traditional cloth known as uis. Unfortunately, the Karo Batak community, especially the younger generation, has insufficient knowledge of the types of uis. Thus, a solution that is easily accessible both in terms of time, cost and experts in recognizing Uis is needed. This research aims to build a website-based application that can classify the types of Karo Uis. This research uses Convolution neural network (CNN) using Alex Net architecture, to get the best model this research compares several hyper parameters, namely learning rate of 10-1 to 10-4, and data division with a ratio of 70:30 and 80:20. The best model falls on a ratio of 70:30 and a learning rate of 10-4 with an accuracy of 98%, and a validation accuracy of 99%, then the model is stored in h5 format in this study successfully builds and implements the model into a web-based application.
Penerapan Metode SMART Pada Sistem Pendukung Keputusan Penentuan Penerima Bantuan Sosial Bagi Keluarga Miskin Simanungkalit, Ada Novisari D.; Khairani, Nerli; Indra, Zulfahmi; Al Idus, Said Iskandar
bit-Tech Vol. 7 No. 2 (2024): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v7i2.1814

Abstract

Kemiskinan merupakan permasalahan utama yang dihadapi banyak negara di dunia, termasuk Indonesia, yang menghambat tercapainya kesejahteraan masyarakat karena berdampak pada rendahnya kualitas sumber daya manusia dan sulitnya memenuhi kebutuhan dasar. Salah satu upaya untuk mengatasi kemiskinan adalah melalui pemberian bantuan sosial kepada keluarga miskin. Namun, penyaluran bantuan ini sering kali tidak berjalan optimal akibat data penerima yang tidak akurat, sehingga memicu konflik dan protes. Penelitian ini bertujuan untuk menentukan kelayakan penerimaan bantuan sosial bagi keluarga miskin di Gereja Bethel Pembaruan Duri dengan menggunakan Metode SMART (Simple Multi Attribute Rating Technique). Penelitian ini dilakukan melalui beberapa tahapan, seperti identifikasi masalah, studi lapangan, kajian literatur, analisis, penerapan metode, serta pengujian dan validasi hasil. Data penelitian mencakup informasi dari 70 jemaat, meliputi nama, alamat, jumlah tanggungan, status pernikahan, tingkat pendidikan kepala keluarga, penghasilan, dan pengeluaran rumah tangga. Hasil penelitian menunjukkan bahwa jemaat dengan nilai akhir >=0,65 layak menerima bantuan, nilai antara >= 0,50 hingga  <=0,64 dipertimbangkan lebih lanjut berdasarkan jumlah tanggungan dan penghasilan, sementara nilai <= 0,49 dianggap tidak layak. Penelitian ini menyimpulkan bahwa Metode SMART efektif dalam menentukan kelayakan penerimaan bantuan sosial, karena mampu meminimalkan masalah ketidakakuratan data penerima, sehingga membantu meningkatkan efisiensi dan keadilan dalam proses distribusi bantuan sosial.
Smoking Violation Detection System Using YOLO in Non-Smoking Areas in Medan City Ananda Hatmi, Reza; Al Idrus , Said Iskandar; Indra, Zulfahmi; Niska, Debi Yandra
Bahasa Indonesia Vol 16 No 05 (2024): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The city of Medan has recorded a significant increase in the percentage of smokers in recent years. This is in line with the increase in the prevalence of smokers nationally. There are a lot of deaths caused by smoking habits in Indonesia every year. To reduce the negative impact of cigarettes and protect public health, the Medan City government has issued a Regional Regulation on Smoke-Free Areas (KTR). Even though there are regulations regulating non-smoking areas in the city of Medan, it turns out that the level of compliance of the people of Medan is still very low. This research aims to create a system that can detect smoking violations in the smoke-free area of Medan city. This study uses the YOLOv5l model to detect cigarettes. The researcher collects and analyzes the necessary datasets. The dataset is divided into data training, validation, and testing. The model evaluated using test data got a fairly good mAP score. The model is also dieva.
Automatic Classifier of Road Condition and Early Warning System for Potholes Manurung, Jeremia; As, Mansur; Nasution, Hamidah; Al Idrus, Said Iskandar; Saputra S, Kana
Indonesian Journal of Artificial Intelligence and Data Mining Vol 8, No 1 (2025): March 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v8i1.31866

Abstract

Damaged roads can have a negative impact on road users and can fatally cause accidents. One sign of a damaged road is the presence of holes in the road. This research aims to develop an Android application that can display the location of potholes and provide early warning to driver in Simalungun Regency - North Sumatra. This research implements the Convolutional Neural Network (CNN) algorithm using the transfer learning techniques on the pre-trained MobileNetV3 model for automatic classification of road conditions. The dataset used in the research consisted of 22.538 images which were divided into two classes, namely pothole and normal. This research uses dataset with a ratio of 60:20:20, 70:20:10 and 80:10:10. MobileNetV3 large variant with a dataset ratio of 60:20:20 shows the best value with an F1-Score of 0,9035. The model was further converted to Tensorflow Lite with an F1-Score of 0.8985. This research succeeded in implementing the trained and evaluated model along with early warning of potholes via audiovisual in Android application. Application functionality testing that is carried out using black box testing, showing that the application can run well.
Motorcycle License Plate and Driver Face Verification Using Siamese Neural Network Model Pane, Yeremia Yosefan; S, Kana Saputra; Al Idrus, Said Iskandar; Syahputra, Hermawan
Indonesian Journal of Artificial Intelligence and Data Mining Vol 8, No 1 (2025): March 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v8i1.31750

Abstract

The security and efficiency of vehicle access management systems have become a primary concern for various institutions, including universities, offices, and public facilities. Effective access management not only enhances security but also improves the flow of incoming and outgoing vehicles, reduces congestion, and enhances user experience. This research aims to develop a vehicle plate detection system and driver face recognition using the Siamese Neural Network model to optimize traffic at the gate. The methods used include the application of deep learning algorithms, specifically the Siamese Neural Network, to verify the driver's face and the use of You Only Live Once (YOLO) to detect and recognize vehicle plates in real-time. Data was collected through direct capture with the researcher's camera. The model was trained and tested using a dataset containing images of vehicle license plates and driver faces. The results showed that the developed model was able to detect and recognize the vehicle plate and the driver's face with a fairly high accuracy, namely in the object detection results getting bounding box validation is 1.05 and class loss validation is 0.95, and 0.85 mAP. As well as in training using the Siamese Neural Network, the highest result is 0.82 with a learning rate of 10e-5 with 30 epochs. It is hoped that this system can be one of the innovations that can be applied in government agencies, universities, industries, etc.
Co-Authors Adidtya Perdana Ahmad Landong Alfattah Atalarais Ananda Hatmi, Reza Angga Warjaya Arifin, Khusnul Arnah Ritonga Arnita Arnita Arnita Arnita Arnita Asiah Asiah Billroy A Ginting Buulolo, Fatizanolo Chairunisah Chairunisah, Chairunisah Citra Citra Debi Yandra Niska Dechy Deswita Indriani.S Devi Juliana Napitupulu Diah Retno Wahyuningrum Dian Septiana DIdi Febrian Eka Nainggolan, Rinay Eko Prasetya, Eko Elvis Napitupulu, Elvis Fadlan Isa Damanik Fadlan Isa Damanik Farhan Ramadhan, Haikal Fauziyah Harahap Fira Dilla Fitria, Amanda Hermawan Syahputra Hermawan Syahputra Ichwanul Muslim Karo Karo Ihsan Zulfahmi Inna Muthmainnah Insan Taufik Izwita Dewi Josafat Simanjutak, Todo Josua Christian Kana Saputra S Kana Saputra S Khairani, Nerli Kuraini, Atifa Nuzulul Lazuardi Lazuardi Lubis, Afiq Alghazali Luge, Miclyael Malik Fajri, Maulana MANSUR AS Manullang, Sudianto Manurung, Jeremia Marpaung, Faridawaty Mika . Layakana Molliq Rangkuti, Yulita Mualiawan Firdaus Muhammad Noer Fadlan Muhammad Rifqi Maulana Muthmainnah, Inna Nabila, Rinjani Cyra Nafisa, Anti Nada Nasution, Hamidah . Nice R Refisis Niska, Debi Yandra Nurkhalizah, Rezeki Nurliani Manurung Olga Laura Mahlona Pane, M Iqbal Anata Pane, Yeremia Yosefan Puji Prastowo, Puji Purba, Boy Hendrawan Rahmani . . Ramadhani, Fanny Refisis, Nice Rejoice Reza Al Alif Reza Al Alif Rovita Indah Ayu Ningtias Salsabila, Aqila Siburian, Rulli Prasetio Bane Sihombing, Jeremia Jordan Simamora, Elmanani Simanjorang, Rio Givent A Simanungkalit, Ada Novisari D. Simbolon, Mula Tua Elia Sinaga, Marlina Setia Siregar, Ary Prandika Sri Mulyana Sri Mulyana Suryani, Nita Susiana Susiana Susiana Susiana Syarida Aini, Desti Tarigan, Dewan Dinata Tarigan, Yosua Yosephine Trisna Utami Putri Wahabi Hasibuan, Rahman Warjaya, Angga Wilma Handayani Yuanita Rachmawati Yulita Molliq Rangkuti Yulita Molliq Rangkuti Yulita Molliq Rangkuti Yusuf, Yusnaeni Zufahmi Indra Zulfahmi Indra, Zulfahmi