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All Journal Jurnal Ilmu Komputer Teknika Jurnal Informatika Sinergi Telematika Jurnal Informatika dan Teknik Elektro Terapan InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sistemasi: Jurnal Sistem Informasi Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal CoreIT Information Management For Educators And Professionals (IMBI) Informatika Pertanian Jurnal SOLMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Komtika (Komputasi dan Informatika) JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Inotera Jurnal Infomedia MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JURIKOM (Jurnal Riset Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Informatika Kaputama (JIK) Jurnal Sistem Informasi Kaputama (JSIK) Jurnal Sains Riset Jurnal Sosial Humaniora Sigli JTIK (Jurnal Teknik Informatika Kaputama) JOURNAL OF INFORMATICS AND COMPUTER SCIENCE G-Tech : Jurnal Teknologi Terapan Jurnal Sistem Komputer dan Informatika (JSON) Medika Teknika : Jurnal Teknik Elektromedik Indonesia Idealis : Indonesia Journal Information System International Journal of Engineering, Science and Information Technology JUTECH : Journal Education and Technology Conten : Computer and Network Technology Brilliance: Research of Artificial Intelligence Jurnal Teknik Informatika dan Elektro (JURTIE) TECHSI - Jurnal Teknik Informatika Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Energi Elektrik Jurnal Bangun Abdimas IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Journal Of Artificial Intelligence And Software Engineering Jurnal Malikussaleh Mengabdi Jurnal Komtika (Komputasi dan Informatika) Jurnal Informatika Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Jurnal Pengabdian Masyarakat Teknologi Informasi (PERANTI)
Nurdin Nurdin
Universitas Malikussaleh
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ANALISIS RISIKO RANCANG BANGUN DAN IMPLEMENTASI JARINGAN TERPUSAT TERDISTRIBUSI MELALUI FIBER OPTIK LINGKAR KAMPUS IAIN LHOKSEUMAWE Rahmat, Rahmat; Nurdin, Nurdin
Jurnal Informatika dan Teknik Elektro Terapan Vol. 12 No. 3S1 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3S1.5462

Abstract

The development of fiber optic network infrastructure in campus environments is becoming increasingly important along with the increasing need for bandwidth to access increasingly high levels of internet content. However, the implementation of this infrastructure is not free from risks which need to be managed well so that the implementation process can run smoothly. Therefore, the author aims to carry out a risk management analysis of implementing fiber optic networks on the IAIN Lhokseumawe campus environment. This research methodology uses a qualitative approach with the steps of risk identification, risk analysis, risk assessment and risk management. The results of this research include identification of risks that may occur during the implementation process, risk analysis, and recommendations for managing these risks. The case study describes the condition of existing network infrastructure, fiber optic network topology planning, and identification of information technology (IT) risks that need attention. Thus, this research is expected to contribute to the development of fiber optic network infrastructure in the campus environment more effectively and well documented
PERBANDINGAN METODE MACHINE LEARNING MENGGUNAKAN METODE SUPPORT VECTOR MACHINE DAN ARTIFICIAL NEURAL NETWORK DALAM MEMPREDIKSI SERANGAN JANTUNG Sri Kurnia; Nurdin; Al Khaidar
Jurnal Informatika Kaputama (JIK) Vol 9 No 2 (2025): Volume 9, Nomor 2, Juli 2025
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v9i2.1020

Abstract

Penyakit jantung merupakan salah satu penyebab utama kematian di dunia, termasuk Indonesia, dengan prevalensi yang terus meningkat setiap tahunnya. Deteksi dini menjadi sangat penting untuk mencegah risiko fatal, namun metode konvensional sering kurang akurat. Penelitian ini membandingkan dua algoritma machine learning, yaitu Support Vector Machine (SVM) dan Artificial Neural Network (ANN), dalam memprediksi serangan jantung berdasarkan data kesehatan pasien. Evaluasi dilakukan menggunakan akurasi, validasi silang, dan Area Under Curve (AUC). Hasil menunjukkan bahwa SVM memiliki akurasi sebesar 0,80, rata-rata validasi silang 0,8120, dan AUC 0,89, sementara ANN mencatat akurasi 0,75, validasi silang 0,7127, dan AUC 0,81. Meskipun ANN unggul dalam efisiensi waktu pelatihan (1,99 detik), SVM menunjukkan performa klasifikasi yang lebih tinggi. Oleh karena itu, SVM lebih cocok untuk sistem yang mengutamakan akurasi, sedangkan ANN dapat diterapkan pada sistem dengan kebutuhan waktu cepat. Kata Kunci : Penyakit Jantung, Machine Learning, SVM, ANN, Prediksi
ANALISIS PERLINDUNGAN HAK CIPTA DAN DISTRIBUSI DIGITAL USER GENERATED CONTENT PADA INDUSTRI MUSIK: STUDI KASUS KHANA MEDIA RECORD DAN KHANA MEDIA NUSANTARA DENGAN PENDEKATAN FUZZY DAN NAIVE BAYES Sultan, Kana; Nurdin
Jurnal Informatika Kaputama (JIK) Vol 9 No 2 (2025): Volume 9, Nomor 2, Juli 2025
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v9i2.1025

Abstract

Transformasi digital di industri musik Indonesia telah membawa perubahan besar dalam distribusi karya musik, khususnya melalui platform digital dan User Generated Content (UGC). Namun, kemudahan distribusi ini juga menimbulkan tantangan baru dalam perlindungan hak cipta. Penelitian ini bertujuan menganalisis efektivitas perlindungan hak cipta dan pola distribusi digital UGC pada Khana Media Record dan Khana Media Nusantara. Metode yang digunakan adalah Fuzzy Logic untuk mengukur tingkat risiko pelanggaran hak cipta dan Naive Bayes untuk mengklasifikasikan pola distribusi legal dan ilegal. Hasil penelitian menunjukkan bahwa digitalisasi membuka peluang distribusi yang lebih luas, namun juga meningkatkan risiko pelanggaran hak cipta, terutama pada konten UGC. Rekomendasi strategis diberikan untuk penguatan sistem perlindungan hak cipta berbasis teknologi informasi. Kata Kunci: Digitalisasi, Hak Cipta, Distribusi Digital, User Generated Content, Fuzzy Logic, Naive Bayes, Industri Musik
IMPLEMENTASI SISTEM PENDUKUNG KEPUTUSAN MENGGUNAKAN METODE SMART UNTUK PEMILIHAN DESNITASI WISATA DI KOTA LHOKSEUMAWE Al Khaidar; Nurdin
JTIK (Jurnal Teknik Informatika Kaputama) Vol. 9 No. 2 (2025): Volume 9, Nomor 2, Juli 2025
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jtik.v9i2.1007

Abstract

Sektor pariwisata merupakan salah satu pilar penting dalam pembangunan ekonomi daerah. Kota Lhokseumawe memiliki beragam potensi wisata, namun wisatawan sering mengalami kesulitan dalam menentukan destinasi yang sesuai dengan preferensi mereka akibat informasi yang tersebar luas namun tidak terstruktur. Untuk mengatasi permasalahan tersebut, diperlukan Sistem Pendukung Keputusan (SPK) yang dapat membantu proses pemilihan destinasi wisata secara sistematis. Penelitian ini mengimplementasikan metode Simple Multi-Attribute Rating Technique (SMART) dalam pengembangan SPK untuk pemilihan destinasi wisata di Kota Lhokseumawe. Data diperoleh melalui survei lapangan dan studi dokumentasi dari berbagai sumber daring. Sistem mengevaluasi tujuh kriteria utama: fasilitas, jarak tempuh, transportasi umum, biaya masuk, aksesibilitas jalan, lahan parkir, dan tingkat kebersihan. Masing-masing alternatif destinasi wisata diberikan skor berdasarkan bobot kriteria yang telah ditentukan. Hasil implementasi menunjukkan bahwa Mesjid Islamic Center memperoleh skor tertinggi sebesar 0,883, diikuti oleh Pantai Jagu 0,500, Taman Riyadhah 0,463, Pantai Jomblang 0,379, dan Waduk Pusong 0,025.
RANCANG BANGUN SISTEM MONITORING KESEHATAN BERBASIS INTERNET OF THINGS (IOT) RAHMAD; NURDIN; CHAEROEN NIESA
JTIK (Jurnal Teknik Informatika Kaputama) Vol. 9 No. 2 (2025): Volume 9, Nomor 2, Juli 2025
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jtik.v9i2.1017

Abstract

Penelitian ini membahas sistem monitoring kesehatan berbasis Internet of Things (IoT) dengan menggunakan Arduino Uno dan pulse sensor untuk mendeteksi detak jantung (BPM) manusia. Sistem ini terdiri dari komponen utama seperti Arduino Uno, pulse sensor, OLED LCD, LED, dan buzzer. Pulse sensor yang dipasang pada jari mendeteksi sinyal denyut nadi, lalu mengirimkan data ke Arduino untuk dihitung sebagai BPM. Hasil perhitungan ditampilkan pada layar LCD. Jika BPM berada di luar batas normal, buzzer akan berbunyi dan LED menyala sebagai peringatan. Sistem ini dirancang untuk memantau detak jantung secara real-time dan memberikan respons otomatis saat kondisi tidak normal terdeteksi. Hasil pengujian menunjukkan bahwa alat ini berfungsi dengan baik dan mencapai tingkat keberhasilan sebesar 80%.
IMPLEMENTASI THINGSPEAK SEBAGAI DATABASE PADA ALAT DETEKSI BANJIR MENGGUNAKAN ESP32 Fauzan, Muhammad; Nurdin, Nurdin
CONTEN : Computer and Network Technology Vol. 4 No. 1 (2024): Juni 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/conten.v4i1.3596

Abstract

Abstract — Thingspeak is a website that is capable of storing readings from sensors sent by devices such as microcontrollers and is able to become a database for storing the results of the sensors sent. This tool is a series of simple tools that uses an ESP32 microcontroller and real-time monitoring media via smartphone. This flood detection tool using the HC-SR04 sensor consists of a tool frame made of iron, the HC-SR04 sensor and a panel box. The 12 V 5 Ah battery comes from a 50Wp solar panel and is the main source of power for this tool. The various electronic components in this tool include LCD, HC-SR04 sensor, relay and stampdown module. The HC-SR04 sensor plays a role in measuring water height in real time when placed on the river bank. When the sensor has detected a predetermined water level, it will send data to the microcontroller. The microcontroller will process the data and send it to a virtual application, which will display it virtually on the cellphone. Data will also be displayed on the LCD.
Clustering the Distribution of COVID-19 in Aceh Province Using the Fuzzy C-Means Algorithm Nurdin, Nurdin; Fitriani, Suci; Yunizar, Zara; Bustami, Bustami
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 6, No 3 (2022): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v6i3.8576

Abstract

COVID-19 is a virus that attacks the respiratory system in humans and spreads rapidly. The government has taken various ways to reduce the rate of transmission of COVID-19, including by providing a COVID-19 information center that can be accessed by anyone, but there is no grouping of regional zones with high to low COVID-19 cases. Therefore, a clustering process system for the spread of COVID-19 is needed so that it is able to provide information on clusters of COVID-19 distribution areas in Aceh with the highest case zone (red zone), medium case zone (yellow zone), and low case zone (green zone). The steps carried out in this study using the Fuzzy C-Means Algorithm are collecting data (input data), conducting the clustering process (determining the number of clusters, weighting rank, maximum iteration and epsilon), displaying clustering results. In this study, the authors collected COVID-19 data from 23 districts/cities in Aceh using 6 variables consisting of confirmed, in care, healed, died, suspected, and probable. The results of the clustering study on the spread of COVID-19 are as follows: One district/city in cluster 1 (red zone), the four districts/cities in cluster 2 (yellow zone), eighteen districts/cities in cluster 3 (green zone). Based on the results of this study, the Fuzzy C-Means Algorithm can be used and applied properly in clustering the spread of COVID-19 in the Province of Aceh. 
Pengenalan Pakaian Adat Aceh Berbasis Augmented Reality Menggunakan Metode Speed Up Robust Featured (SURF) gunawan, chicha rizka; Nurdin, Nurdin; Fajriana, Fajriana
Jurnal Komtika (Komputasi dan Informatika) Vol 7 No 2 (2023)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v7i2.9124

Abstract

Aceh Province, especially Langsa City, has a tourist attraction, namely the Langsa City Forest Park House (RTH). One of the most interesting rides in Langsa City Forest Park is Rumoh Aceh. Based on the results of visits and interviews by Rumoh Aceh officers, the large number of visitors from outside Aceh with one officer sometimes made it difficult for the officers to explain the information available about Rumoh Aceh, especially Acehnese traditional clothes, which were only displayed from a printed image, and provided no other information about these traditional clothes, so that many visitors did not know the diversity of designs and motifs of traditional clothes in Aceh. So, a medium was formed that could display Acehnese traditional clothing. The media uses augmented reality technology so that users can add virtual objects to the real environment to make it easier to use. This application uses the Speed Up Robust Featured (SURF) algorithm, which can process marker tracking quickly so that it can obtain better tracking speed times. The shortest distance from the marker to the camera that can show 3D objects is 20 cm, whereas the farthest distance that cannot show 3D objects is 100 cm. The best distance at which a marker can be detected is 20–80 cm. The best average detection time is 0.00049 s, and the average speed obtained is 1261.22 m/s at a distance of 60 cm. The Speed Up Robust Featured (SURF) algorithm can be used in the Augmented Reality-based Aceh Traditional Clothing Recognition application.
Single Tuition Fee Classification Using Light Gradient Boosting Machine with Confusion Matrix Analysis Khaidar, Al; Nurdin, Nurdin; Fajriana, Fajriana
Journal of Artificial Intelligence and Software Engineering Vol 5, No 4 (2025): Desember
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i4.8479

Abstract

Uang Kuliah Tunggal merupakan sistem pembiayaan pendidikan tinggi yang ditetapkan berdasarkan kemampuan ekonomi mahasiswa. Penetapan UKT yang masih dilakukan secara manual berpotensi menimbulkan subjektivitas dan ketidaktepatan klasifikasi. Penelitian ini bertujuan untuk mengembangkan model klasifikasi UKT berbasis data menggunakan metode Light Gradient Boosting Machine (LightGBM). Dataset yang digunakan terdiri dari 10.000 data mahasiswa Politeknik Negeri Lhokseumawe yang telah melalui tahap prapemrosesan dan transformasi fitur. Model dilatih menggunakan pembagian data latih dan data uji sebesar 80:20, serta dievaluasi menggunakan metrik akurasi, classification report, confusion matrix, dan 10-Fold Cross Validation. Hasil pengujian menunjukkan bahwa model LightGBM mencapai akurasi sebesar 98% pada data uji. Pengujian 10-Fold Cross Validation menghasilkan rata-rata akurasi sebesar 99,21% dengan standar deviasi 0,29%, yang menunjukkan stabilitas dan kemampuan generalisasi yang sangat baik. Hasil ini membuktikan bahwa LightGBM efektif dan andal untuk mendukung penetapan UKT yang lebih objektif dan berbasis data.
Comparison of Naive Bayes and Dempster Shafer Methods in Expert System for Early Diagnosis of COVID-19 Nurdin Nurdin; Erni Susanti; Hafizh Al-Kautsar Aidilof; Dadang Priyanto
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 1 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i1.2280

Abstract

COVID-19 is a respiratory infection disease caused by the corona virus. Transmission of this virus can spread very quickly so that the number of cases of the corona virus continues to grow and becomes an epidemic that spreads not only in Indonesia but also in other countries in the world. The purpose of this study is to build an expert system that is able to diagnose Covid-19 early by using a comparison of the Nave Bayes method and the Dempster Shafer method. The amount of data used in this study is 550 data, consisting of 500 training data and 50 testing data. While the variables used are symptoms related to COVID-19 as many as 17 symptoms consisting of G01, G02, G03, G04, G05, G06, G07, G08, G09, G10, G11, G12, G13, G14, G15, G16, G17. The diagnostic data consists of Suspected (PDP), Non-Suspected, and Close Contact (ODP). The results of the percentage test by comparing system diagnoses with expert diagnoses, for the nave Bayes method it has an accuracy of 96% with 48 diagnoses according to expert diagnoses from 50 tested data. Meanwhile, the Dempster Shafer method has an accuracy of 40% with 20 diagnoses according to expert diagnoses from 50 tested data. Based on the results of this study, the Naive Bayes and Dempster Shafer methods can be applied to an expert system for early diagnosis of COVID-19, from the results of the system testing the Naive Bayes method has better accuracy than the Dempster Shafer method.
Co-Authors - Miranda ., Muthmainah Adi Prasetyo Adzuha Desmi Afif Diapari Ma'aruf Lubis Afif Diapari Aflizar Aflizar Afrilia, Yesy Aidilof, Hafizh Al Kautsar Al Khaidar Alaiya, Azna Alqhifari, Azka Ama Zanati Amalia, Nova Amin Munthoha Aminsyah, Ansharulhaq Ananda Faridhatul Ulva Anas, Mukhtar Andri Alfitra Anggara, Aji Annisa Karima Arnawan Hasibuan Aynun, Aynun Aynun, Nur Azzanna, Maghriza bhakti wan khaledy Bustami Bustami Bustami Bustami Cesilia, Yolinda Chaeroen Niesa Chicha Rizka Gunawan Cut Agusniar Dadang Priyanto Dahlan Abdullah Dahlan Abdullah Darmansyah, Arif Desky, Muhammad Aulia Dewi Astika Erni Susanti Eva Darnila Fadlisyah Fadlisyah Fadlisyah Fahrozi, Fazar Fajriana Fajriana Fajriana, Fajriana Fasdarsyah Fasdarsyah fatimah Fatimah Fikhri, Aditya Aziz Fikran, Rifzan Fikri Fikri Gavinda, Virza Ginting, Andriyan gunawan, chicha rizka Gunawan, Chichi Rizka Hafizh Al Kautsar Aidilof Hafizh Al-Kautsar Aidilof Hamdhana, Defry Herman Fithra Hermansyah Hermansyah I Made Ari Nrartha Ilyana, Anis Imanda, Nanda Intan Nuriani Ira Wati Irwansyahputra Irwansyahputra Isa, Muzamir Ismun Naufal Iza Rifna Jessika, Jessika Jikti Khairina Julia Ulfah Khaidar, Al Khairina, Jikti Khairul Fuadi Khairul Khairul, Khairul Khairuni Khairuni Kurnia, Sri Kurniawati M Farhan Aulia Barus M Rizwan M Suhendri M. Ali, Rahmadi Marleni Marleni Maryana Maryana Maryana Maryana Maryana Maryana Maryana, Maryana Maulita, Maya Maya Juwita Dewi Maysura Meriatna Meriatna Muchlis ABD Muthalib Muchlis Abdul Muthalib Muhammad Daud Muhammad Faisal Muhammad fauzan Muhammad Fikry Muhammad Furqan, Muhammad Muhammad Hutomi Muhammad Iqbal Muhammad Johan Setiawan Muhammad Nasir Muhammad Riansyah Muhammad Ridha Mukti Qamal Muliana, Syarifah Munirul Ula Munirul Ula Mutammimul Ula Muzakir Nur Nadilla Baimal Puteri Nanda Imanda NELI SUSANTI, NELI Nunsina, Nunsina Nur, Muzakir Nurdin Nurdin Nurhabsah Nurhabsah Pradita, Cindy Cika Rahma Jihan Ananta Rahmad Rahmad Rahmad Rahmat Rahmat Raihan Putri Rasyada, Reza Dian Reza, Restu Rini Meiyanti Risawandi, Risawandi Riza Mirza Rizal S.Si., M.IT, Rizal Rizki Setiawan Rizki Suwanda Rizky Putra Fhonna Rizkya, Ghinni Robi Kurniawan Rusadi, Athirah Said Fadlan Anshari salamah salamah Salimuddin, Salimuddin Salsabila, Thifal Samudera, Brucel Duta Sapitri, Anggri Sari, Cut Jora Sayuti, Muhammad Siagian, Tania Annisa Siregar, Widyana Verawaty Siti Hajar Sri Kurnia Sri Kurnia Suci Fitriani, Suci Suhaili Sahibul Muna Sujacka Retno Sultan, Kana Suryana, Fitra Syahputra, Wawan Syandriani Harahap Taufik Taufik Taufiq Taufiq Taufiq Taufiq Taufiq Taufiq Uci Mutiara Putri Nasution Ulfah, Julia Ulva Fitriani Utomo, Muhammad Fikri Wahdana, Aldi Wan Dinulaqli Wan, Syahputra Wawan Wawan Yani, Muhamamd Yeni Yeni Yesy Afrilia Yesy Afrillia Yulisda, Desvina Zahrah, Violita Aditya Zahratul Fitri Zahratul Fitri, Zahratul Zalfie Ardian Zara Yunizar Zuraida Zuraida