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All Journal SAMUDERA Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) CESS (Journal of Computer Engineering, System and Science) INFORMAL: Informatics Journal InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JOURNAL OF APPLIED INFORMATICS AND COMPUTING METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Sisfokom (Sistem Informasi dan Komputer) ILKOM Jurnal Ilmiah Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JISKa (Jurnal Informatika Sunan Kalijaga) JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Jurnal Informasi dan Teknologi JTIK (Jurnal Teknik Informatika Kaputama) Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Computer Science and Information Technology (CoSciTech) International Journal of Engineering, Science and Information Technology Multica Science and Technology jeti TECHSI - Jurnal Teknik Informatika Sisfo: Jurnal Ilmiah Sistem Informasi International Journal of Information System & Innovative Technology Multidisiplin Pengabdian Kepada Masyarakat (M-PKM) Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms Scientific Journal of Informatics International Journal of Information System and Innovative Technology Smatika Jurnal : STIKI Informatika Jurnal Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Rozzi Kesuma Dinata
Program Studi Teknik Informatika, Unversitas Malikussaleh, Aceh Utara 24351, Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Astronomy 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 Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Physics Public Health Social Sciences Transportation Other

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Comparative Analysis of K-Medoids and Purity K-Medoids Methods for Identifying Accident-Prone Areas in North Aceh Regency Hasdyna, Novia; Dinata, Rozzi Kesuma
Scientific Journal of Informatics Vol. 11 No. 2: May 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i2.3433

Abstract

Purpose: This study aimed to conduct a comprehensive comparative analysis between K-Medoids and Purity K-Medoids clustering methods for identifying accident-prone areas in North Aceh Regency. The analysis was carried out to provide valuable insights for policymakers and stakeholders to implement targeted interventions as well as improve road safety measures in the region. Methods: This study compared the performance of K-Medoids and Purity K-Medoids, on accident-prone area data in North Aceh Regency. The algorithm performance was measured using the Davies-Bouldin Index (DBI) method, where a low value signifies superior performance. Additionally, the number of iterations produced by K-Medoids and Purity K-Medoid methods were compared, with lower iterations indicating better performance. Result: The results showed that Purity K-Medoids had superior performance with an average of 2 iterations and DBI value of 0.7847 across 10 testing runs, while K-Medoids obtained 13.4 iterations and 1.5128, respectively. Novelty: The study offers valuable insights into the effectiveness and efficiency of clustering methods for identifying accident-prone areas, as guides for policymakers and stakeholders in implementing targeted interventions to improve road safety measures. Additionally, the results provide a methodological framework for evaluating clustering algorithms in similar geographical contexts, enhancing the understanding of their applicability and performance in real-world scenarios.
E-Arsip Surat Tugas Pada Kantor Badan Pusat Statistik (BPS) Kabupaten Langkat Berbasis Website Sujacka Retno, Rozzi Kesuma Dinata, Aina Rahmadani
Jurnal Elektronika dan Teknologi Informasi Vol 4 No 1 (2023): Maret 2023
Publisher : LPPM-UNIKI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5201/jet.v4i1.401

Abstract

BPS (Badan Pusat Statistik) is a non-ministerial government agency that is directly responsible to the President. The BPS office in Langkat Regency provides statistical data and information needed for sectoral and cross-sectoral planning and development. At the Langkat Regency BPS Office, the assignment letter management and archiving system is still carried out manually, by using a file cabinet. This manual data collection can make it difficult for officers to manage related to archiving letters and preparing reports so that this can hinder the performance of BPS officers. This research aims to overcome these problems by creating an e-archive system that aims to optimize the performance of officers at the Langkat Regency BPS office. The system was built using PHP and MySQL database.
Pengelompokan Daerah Padat Penduduk Untuk Penentuan Kawasan Perumahan di Kota Lhokseumawe Menggunakan K-Medoids Clustering Rozzi Kesuma Dinata, Furqan, Sujacka Retno
Jurnal Elektronika dan Teknologi Informasi Vol 4 No 1 (2023): Maret 2023
Publisher : LPPM-UNIKI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5201/jet.v4i1.407

Abstract

Lhokseumawe city is one of the cities in Aceh province which has the second largest population after the city of Banda Aceh. With an area of ​​181.06 KM2 the population in Lhoseumawe reached 207.2 thousand in 2019. K-medoids on the population density clustering system in the city of Lhokseumawe is an application for clustering population density with very dense, dense and not dense clusters, with total data from 68 villages in the city of Lhokseumawe from 2017 to 2021. This research uses data mining techniques in the data management process using the K-medoids clustering method.
Sistem Informasi Perpustakaan Prodi Teknik Informatika Universitas Malikussaleh Sujacka Retno, Rozzi Kesuma Dinata, Zeny Arsya Fortilla
Jurnal Elektronika dan Teknologi Informasi Vol 4 No 2 (2023): September 2023
Publisher : LPPM-UNIKI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5201/jet.v4i2.410

Abstract

There are various problems in the Informatics Engineering library at Universitas Malikussaleh, one of which is book management, where this data is very necessary for the book data collection process. Considering the problems faced by staff in the library section, an idea was formulated to create a data processing system based on an information system. Fast, high-quality and smooth data processing is needed by all types of organizations to assist in achieving work goals or objectives, especially in the library section. This research aims to overcome this problem by creating a system that aims to optimize the performance of staff in the Informatics Engineering library at Universitas Malikussaleh. The system is built on a desktop basis.
Pemetaan Titik Penumpukan Sampah di Kota Lhokseumawe Menggunakan Metode Ant Colony Optimization Suhaeymi, Rozzi Kesuma Dinata, Zara Yunizar
Jurnal Elektronika dan Teknologi Informasi Vol 4 No 2 (2023): September 2023
Publisher : LPPM-UNIKI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5201/jet.v4i2.413

Abstract

This research implements Ant Colony Optimization (ACO) to optimize waste collection routes in urban areas. The implementation utilizes the PHP, JS, and HTML programming languages, resulting in an interactive mapping application that facilitates community participation in identifying garbage accumulation locations. The research findings indicate that by employing ACO calculations with parameters α = 1.0 for pheromones and β = 2.0 for visibility, the best waste collection route was identified with a total distance of 9.565 km.The route begins at "Cunda Fish Market" (pheromone 0.1, visibility 3.321146121) heading towards "Beside the bus terminal" (distance 0.301 km), then continues to "Inpres Market" (pheromone 0.1, visibility 0.814261078, distance 1.228 km), "Pusong Lama Market" (pheromone 0.1, visibility 0.611779235, distance 1.635 km), "Lhokseumawe Reservoir behind the church" (pheromone 0.1, visibility 1.854365059, distance 0.539 km), and concludes at "Lhokseumawe State Polytechnic" (pheromone 0.1, visibility 0.170600122, distance 5.862 km).Each step reflects ant choices based on calculated probabilities, starting from the highest probability of 0.922322 in the first step to the lowest probability of 0.006391 in the last step. This research underscores the efficiency of the routes generated by ACO and demonstrates that bio-inspired algorithms such as ACO can be effectively applied to real logistics problems, providing responsive and adaptive solutions to the dynamics of urban environments.
Web-Based Asset Management Information System for Enhanced Asset Tracking at The Land Office of Bireuen District Rozzi Kesuma Dinata, Agus Maula Rizki
Jurnal Elektronika dan Teknologi Informasi Vol 5 No 1 (2024): Maret 2024
Publisher : LPPM-UNIKI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5201/jet.v5i1.419

Abstract

The management and tracking of assets at the Land Office of Bireuen District have become increasingly complex, necessitating the development of a more efficient and systematic approach. This study proposes the design and implementation of a web-based Asset Management Information System (AMIS) to optimize asset tracking processes. The system aims to provide real-time asset data, improve accuracy, and streamline the management workflow. Key features include asset registration, location tracking, maintenance scheduling, and reporting capabilities. By utilizing web technologies, the AMIS ensures accessibility and ease of use for authorized personnel. The implementation of this system is expected to significantly enhance asset management efficiency, reduce human error, and provide comprehensive data analytics for better decision-making. Initial testing and feedback from users indicate a substantial improvement in the overall asset management process at the Land Office of Bireuen District.
Penerapan Algoritma Random Forest dalam Deteksi dan Klasifikasi Ransomware Alvanof, Mulia; Bustami; Rozzi Kesuma Dinata
Jurnal Elektronika dan Teknologi Informasi Vol 5 No 2 (2024): September 2024
Publisher : LPPM-UNIKI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5201/jet.v5i2.488

Abstract

Ransomware is a type of malware that blocks access to computer systems or data until a ransom is paid by the victim. Ransomware attacks typically occur due to malicious files that are unknowingly downloaded and installed by the victim onto their computer system. Given the threats and potential losses posed, methods for detecting and classifying ransomware continue to be developed, one of which utilizes the Random Forest machine learning algorithm. Random Forest is chosen for its advantages in handling large datasets, short training time, high prediction accuracy, and its ability to reduce the risk of overfitting. Using 1380 ransomware samples from a dataset with 54 features, 10 best features were selected through Feature Selection where the built Random Forest model successfully predicted ransomware files with an accuracy of 98.79%.
Heart Disease Classification Based on Medical Record Data Using the Logistic Regression Method Iswari, Syahyana; Dinata, Rozzi Kesuma; Aidilof, Hafizh Al Kautsar
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 1 (2025): September 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i1.8867

Abstract

Heart disease remains one of the primary causes of mortality globally and poses a significant public health concern, including in Indonesia. Early identification of individuals at risk is essential for lowering death rates and enhancing the success of medical interventions. This research focuses on developing a classification model for heart disease using the Logistic Regression technique, utilizing data extracted from patient medical records. The dataset comprises 100 entries, each containing six key features: age, gender, blood pressure, heart rate, respiratory rate, and chest pain. The model was trained on 80% of the data and evaluated using the remaining 20%. Model performance was assessed using several metrics, including accuracy, precision, recall (sensitivity), F1-score, confusion matrix, and the ROC (Receiver Operating Characteristic) curve. The evaluation results revealed an accuracy of 95%, precision of 100%, recall of 88.89%, F1-score of 94.12%, and an AUC score of 0.99. These outcomes suggest that Logistic Regression is highly effective for classifying heart disease risk and can serve as a valuable tool in early detection systems supported by medical record data.
A Web-Based Decision Support System Implementation for Evaluating Premier Smartphone Brands Using Weighted Product Method Novia Hasdyna; Rozzi Kesuma Dinata; Sujacka Retno
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 13 No 02 (2023): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v13i02.939

Abstract

In the current modern era, smartphones have become an indispensable part of daily life, extensively utilized across a multitude of activities, particularly through online platforms. This underscores the imperative of aiding individuals in making precise decisions regarding the smartphone that aligns most with their needs. To address this exigency, the development of a Decision Support System (DSS) employing the Weighted Product method assumes paramount significance in this research. This DSS empowers users to select the most fitting smartphone by assigning weight values to various performance metrics. The criteria used in this research are price, RAM, ROM, battery capacity, and Android version. The successful implementation of this system streamlines the smartphone selection process, enabling users to make judicious choices that perfectly cater to their requirements while optimizing performance metrics.. In this research, Poco X3 Pro has the highest Vector V value of 0.255441, making it the best-recommended smartphone.
Implementation Of Support Vector Regression In Prediction Air Quakity Index In Banda Aceh City Rizky Fasya Ramdhani; Rozzi Kesuma Dinata; Ar Razi
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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

Abstract

Air quality is one of the important aspects in maintaining environmental balance and public health. Increasing air quality in the environment is a matter of concern. Therefore, a method that can predict the Air Quality Index (AQI) effectively is needed to be able to monitor and support decision making on environmental impacts. This study aims to predict the Air Quality Index in Banda Aceh City using the Support Vector Regression algorithm, with five main parameters used in the study, namely particulate matter , Sulfur dioxide, Nitrogen dioxide, Carbon monoxide , and Ozone . In this research, the Support Vector Regression algorithm was chosen because of its ability to handle non-linear data and also because it can provide accurate predictions on data. The prediction system designed will be web-based using the flask framework and MySQL database, while the Support Vector Regression modeling will be done on google colab for the media used. In the process of modeling the data will be divided into 80% training data and 20% test data to ensure the model can capture long and short-term patterns. The results of the prediction will be compared using the Root Mean Squarred Error (RMSE) and Mean Squarred Error (MSE) evaluation metrics. The results of the evaluation using both metrics yielded RMSE values of 1.9001 and MSE of 3.6015. These values indicate good performance of the model in predicting the data. This research is expected to provide insight for future similar research in terms of prediction using the Support Vector Regression algorithm.
Co-Authors ., Yustizar Ahmad Fauzi Abdillah Aidilof, Hafizh Al Kautsar Akbar, Hafizal Akram, Rizalul Alvanof, Mulia Andik Bintoro Annisa Afrilia Zahra Annisa Anya Regina Putri Ar Razi Ar Razi Ar Razi, Ar Razi Ardiansyah, Sakha Arif, M. Arif Saputra Arnawan Hasibuan Asrianda Asrianda Azrai Putra Barumun Daulay Badriana, Badriana Baringin Sianipar Berutu, Indah Fachlira Bustami Bustami Bustami Bustami Bustami Chaeroen Niesa Cut Fadhilah Deffiyani Eva Darnila Fadlisyah Fadlisyah Fadlisyah Fajri, T Irfan Fajriana, Fajriana Fiasari, Fiasari Fikria, Putri Fuadi, Wahyu Gadis Ayu Sofiana Hafizal Akbar Haried Novriando Hasan Tahir Hasmar, Muhammad Al Hafiz Irwanda Syahputra Iswari, Syahyana Jasmin, Nadya Khairul Muttaqin Khairunnisa Khairunnisa Khairunnisa Khairunnisa Lubis, Aulia Azzahra Ma'aruf Maryana Maryana Maryana Melita Saldila Muhammad Al Hafiz Hasmar Muhammad Alif Muhammad Arasyi Muhammad Arrayyan Muhammad Fikry Muhammad Iqbal Muhammad Nurfahmi Muhammad Rivai MUHAMMAD RIZAL Muhammad Rizal Munirul Ula Mursyidah Mursyidah Mutammimul Ula Mutasar Muttaqin Muttaqin Narita Taskia Novia Hasdyna Novianda Novianda Nur Azizah Nurwijayanti Rahmat Hidayat Rahmat Hidayat Rahmatin Nisak Risawandi, Risawandi Rizki Suwanda Rizky Fasya Ramdhani Safwandi Safwandi Safwandi Safwandi Sahputra, Ilham Said Fadlan Anshari Selly Alfika Suci Ramadani Sujacka Retno Sujacka Retno Syatriani Jauhari T Irfan Fajri Tahir, Hasan Ulfa, Septia Mulya Yafis, Balqis Yessy Afrillia Yesy Afrillia Zahratul Fitri Zahratul Fitri Zara Yunizar Zuboili, Zuboili Zulfa Zulfa