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All Journal Teknika Sistemasi: Jurnal Sistem Informasi Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Informatika Universitas Pamulang DoubleClick : Journal of Computer and Information Technology Jurnal Teknologi Sistem Informasi dan Aplikasi JURIKOM (Jurnal Riset Komputer) JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Teknologi Simtek : Jurnal Sistem Informasi dan Teknik Komputer METIK JURNAL Jurnal Kridatama Sains dan Teknologi Journal of Information Systems and Informatics Jurnal Ilmiah Sains dan Teknologi (SAINTEK) JATI (Jurnal Mahasiswa Teknik Informatika) JTIK (Jurnal Teknik Informatika Kaputama) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Community Development Journal: Jurnal Pengabdian Masyarakat TIN: TERAPAN INFORMATIKA NUSANTARA Journal of Computer Networks, Architecture and High Performance Computing Idealis : Indonesia Journal Information System Jurnal Teknologi Informasi dan Komunikasi Fitrah: Journal of Islamic Education Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Bulletin of Computer Science Research JUTECH : Journal Education and Technology Jurnal Algoritma Sistem Pendukung Keputusan dengan Aplikasi Jurnal Manajemen Informatika dan Bisnis Digital Innovative: Journal Of Social Science Research Jurnal Multidisiplin Sahombu The Indonesian Journal of Computer Science
Triase Triase, Triase
Universitas Islam Negeri Sumatera Utara Medan
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Augmented Reality as an Interactive Medium for Understanding Qur’anic Verses on the Phenomenon of Rain in Islamic Education Learning Samsudin, Samsudin; Triase, Triase; Zufria, Ilka
Fitrah: Journal of Islamic Education Vol. 6 No. 2 (2025): Desember (2025)
Publisher : Sekolah Tinggi Agam Islam Sumatera Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53802/fitrah.v6i2.1445

Abstract

Students’ understanding of kauniyah verses in the Qur’an, particularly regarding the phenomenon of rain, is often limited because the information presented is general and lacks integration with scientific explanations, resulting in varied interpretations. This study aims to develop an Augmented Reality (AR)-based learning media to visualize the process of rainfall based on QS. An-Nūr verse 43 and QS. Ar-Rūm verse 48. Support from tafsir ilmi and the water cycle theory is used to comprehensively understand the meaning of the verses. Students in the Information Systems Study Program are required to connect Qur’anic verses with scientific phenomena, but conventional media limit effective learning. The AR application, developed using Unity, Vuforia, and Blender, displays 3D animations of evaporation, transpiration, condensation, and precipitation phases. The development follows the Multimedia Development Life Cycle (MDLC) method, ensuring a procedural, interactive, and user-friendly approach. Testing results show that the application runs stably and effectively enhances understanding of the relationship between the verses, their interpretation, and natural phenomena in a contextual manner, implicating AR as an innovative model to enhance Qur'anic science literacy and digital learning experience.
Customer Billing Information System and Whatsapp Notification With Web-Based FCFS Method Risandi Alfariz; Muhammad Revandi Ananda; Triase, Triase
Jurnal Multidisiplin Sahombu Vol. 6 No. 01 (2026): Jurnal Multidisiplin Sahombu, January 2026
Publisher : Sean Institute

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

Abstract

Digital transformation in the public service sector is now crucial to support work efficiency and effectiveness. At the Tirtanadi Water Company (PDAM) in North Sumatra, customer scheduling and billing activities are already carried out using an application, but still face several obstacles, such as the rarity of ordinary people to open the application to view their bills, resulting in many people experiencing delays in paying their bills, resulting in continued arrears and resulting in interest accruals. To address these challenges, a web-based information system was developed that implements the First Come First Serve (FCFS) scheduling algorithm. This algorithm functions to manage queues and schedules based on the order of incoming requests, resulting in a more structured and fair process. The implementation of this system is expected to increase efficiency in the billing process and support more responsive and accurate customer service within the PDAM.
Transformasi Digital Manajemen Aset Infrastruktur: Optimalisasi Operasional PDAM melalui Sistem Pelacakan QR Code Berbasis Web Indra Putra Mahayudi; Zikri Ezza Alhira; Triase, Triase
JUMINTAL: Jurnal Manajemen Informatika dan Bisnis Digital Vol. 4 No. 2 (2025): November 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jumintal.v4i2.7406

Abstract

Pipeline network operations require fast and accurate asset identification, but manual processes in the field often cause delays in recording and data errors, contributing to increased Non-Revenue Water (NRW) levels. This article designs and evaluates a QR code-based pipeline asset management information system at Perumda/PDAM Tirtanadi to accelerate identification, organize history tracking, and improve maintenance information quality. The Rapid Application Development (RAD) approach was selected for its ability to accommodate dynamic operational requirements through iterative stakeholder involvement, reducing system failure risks compared to conventional waterfall methods. Qualitative data from field observations and structured interviews with operational staff were systematically transformed into Functional Requirement Specifications through requirement engineering frameworks. Functional evaluation was conducted through black-box testing and field workflow trials to assess scanning reliability, ease of use, and data consistency. The results demonstrate that the system operates stably with 100% functional test success rate, significantly improves asset traceability through real-time QR code scanning, and facilitates data-driven maintenance decision-making. Performance analysis indicates that QR code scanning reduces asset identification time by approximately 75% compared to manual document searching. The Model-View-Controller (MVC) architecture ensures system scalability for future Geographic Information System (GIS) integration. Further implementation is directed at GIS integration, refinement of data access policies in accordance with the Personal Data Protection Law (UU PDP), and expansion of coverage to other operational units. Thus, this system not only improves operational efficiency but also contributes to reducing water loss through faster damage handling, serving as a replicable model for other water utilities implementing technology-based asset management.
Rute Terpendek Pengiriman Katering Makanan Menggunakan Geographic Information System dengan Metode Dijkstra Adira, Muhammad Faris; Triase, Triase
Bulletin of Computer Science Research Vol. 6 No. 2 (2026): February 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i2.957

Abstract

The problem of determining catering delivery routes at UMKM Vfoodia in Medan City is still carried out manually and relies heavily on couriers’ experience, which may lead to inefficiencies, especially in cases of courier replacement and limited delivery time windows. This condition results in delivery delays and difficulties for couriers in understanding customer locations and delivery sequences. This study aims to develop a catering delivery route determination system based on Geographic Information System (GIS) using the Dijkstra algorithm. The system is developed as a web-based application accessible via Android devices to support both administrative and courier activities. GIS is utilized to visualize customer locations and road networks on a digital map, while the Dijkstra algorithm is applied to compute the shortest route between two points. In daily delivery operations involving multiple destinations, the Dijkstra algorithm is executed repeatedly, where the destination point is updated each time a customer delivery is completed. The system is integrated with the OpenRouteService API to obtain distance and travel time estimations and is equipped with a caching mechanism to reduce repetitive API calls. The contribution of this research lies in the application of the standard Dijkstra algorithm in a repetitive manner within a GIS-based system to support structured multi-destination catering delivery at the UMKM scale. Experimental results show that the system is able to generate the shortest delivery route with a minimum distance of 6.0 km in the test scenario and helps make the delivery process more organized and easier for couriers to understand. Therefore, the proposed system improves delivery efficiency and enhances the quality of catering delivery services at UMKM Vfoodia.
Analisis Komparasi Algoritma KNN dan Naive Bayes untuk Klasifikasi Pasien Rehabilitasi Narkoba di XYZ Putri Khairunnisa Nabilah; Triase, Triase
JURNAL RISET KOMPUTER (JURIKOM) Vol. 13 No. 1 (2026): Februari 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v13i1.9553

Abstract

The development of information technology in the field of data mining opens up significant opportunities to optimize data classification in the healthcare and rehabilitation sectors. LRPPN BI Medan currently faces challenges in determining rehabilitation programs because the decision-making process is still subjective and has not yet systematically utilized historical data. Inaccuracies in determining these programs can reduce recovery effectiveness and increase the potential for patient relapse. This study aims to apply and test the effectiveness of the KNN and Naïve Bayes algorithms in classifying rehabilitation programs based on patient criteria, such as duration of drug use, URICA test results, medical history, and addiction level. This study uses a quantitative approach with the Waterfall development method. This solution is proposed to overcome subjectivity through a data-based classification system that complements each other in accuracy and processing speed. The results of this study show that the Naive Bayes algorithm has a higher accuracy rate of 96.43%, while KNN has an accuracy of 94.29%.
A Penerapan Deep Learning untuk Identifikasi Citra Tanaman Obat Anti-inflamasi Menggunakan Algoritma CNN: Penerapan Deep Learning untuk Identifikasi Citra Tanaman Obat Anti-inflamasi Menggunakan Algoritma CNN Triase, Triase
The Indonesian Journal of Computer Science Vol. 12 No. 6 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i6.3470

Abstract

Deep Learning bagian kecerdasan buatan dan big data menggunakan mechine learning solusi paling menjanjikan untuk masalah big data. Mechine learning adalah metode matematis yang diterapkan untuk menciptakan model yang menggambarkan pola-pola dalam data. Tanaman obat adalah jenis tumbuhan yang diketahui memiliki manfaat dalam menjaga kesehatan dan mengobati penyakit. Penggunaan tumbuhan obat sering kali terkait erat dengan pengobatan tradisional, karena sebagian besar pemahaman tentang manfaatnya tidak didasarkan pada uji klinis laboratorium, melainkan berdasarkan pengalaman penggunaan yang telah teruji dari masa ke masa. Untuk memaksimalkan penggunaan tanaman obat dengan mengenali daun tanaman obat ini, maka deteksi citra daun anti-inflamasi akan diuji menggunakan algoritma CNN dengan tahapan scraping data dari bing, preprocessing data secara manual dan pelatihan data dengan 10 epoch berhasil identifikasi dan mengklasifikasikan dengan benar sekitar 16% dari semua instance positif yang ada dari data pengujian dan merupakan tingkat keberhasilan yang rendah, sehingga memiliki kinerja yang tidak memuaskan dalam tugas identifikasi.
Sistem Informasi Prediksi Harga Pembelian Mobil Bekas Menggunakan Algoritma Random Forest Darus, Muhammad Farhan Azmi; Triase, Triase
TIN: Terapan Informatika Nusantara Vol 6 No 11 (2026): April 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i11.9604

Abstract

The rapid growth of the used car market in Indonesia has increased the need for an objective and data-driven approach to determine appropriate purchase prices. One of the main challenges in used car transactions is the subjectivity in price determination, which often leads to discrepancies between sellers and buyers. This study aims to develop an information system for predicting used car purchase prices using the Random Forest algorithm. The dataset used in this study consists of 301 records with attributes including brand, model, production year, engine capacity, mileage, fuel type, transmission, and region. The research methodology involves data collection, preprocessing, dataset splitting, model development, and evaluation. The model performance is evaluated using Mean Absolute Error (MAE) and R-Squared (R²). The results show that the Random Forest model achieves an MAE value of 22.654 and an R² value of 0.958, indicating that the model can explain 95.8% of the variance in the data with relatively low prediction error. The developed system implements an input–process–output mechanism, where user-provided vehicle data are processed by the trained model to generate price predictions automatically. The system is able to provide fast, accurate, and objective price estimates, thereby supporting better decision-making and improving transparency and efficiency in used car transactions.
Co-Authors Abdillah, Muhammad Dimas Adira, Muhammad Faris Agil, Mashuril ahmad, Ahmad Rizky Ananda Purba Aidil, Elqi Rahmat Alda, Muhammad Anggini, Nurasiah Aninda Muliani Annisa, Tasya Ardhana, Muhammad Reza Asruri, Selfi Ayu, Kartika Dara Badri, Mohammad Darus, Muhammad Farhan Azmi Deliani, Safni Dewi, Siska Efita, Sinta Dara Eka Pratiwi Fadilah, Ulfa Fadilla, Sonya Rezky Fahriza Hasibuan, Alya putri Farhan Farhan Febiana, Indira Fikri, Muhammad Aulia Gunawan, Jaka Harahap, Muhammad Fadli Harahap, Raja Halomoan Sahilun Harahap, Sukma Ananda Hasibuan, Putri Indah Julia Hazwani, Nazla Helmi, Elsy Shafira Hutabarat, Dio Wahyu Habibi Ikhsan, Ramadhani Al Ilka Zufria Indra Putra Mahayudi Kerina, Akidah Nur Khairunnisyah, Siti Lubis, Farhan Rusdy Asyhary M. Iqbal Matanari, Hanif Kurniawan Mefalano, Arian Muhamad Alda Muhammad Dedi Irawan Muhammad Revandi Ananda Muhammad Siddik Hasibuan Muliani Harahap, Aninda Nasution, Erwin Pasaribu, Afifah Balqis Pratiwi, Agita Priyamita, Adinda Putri Khairunnisa Nabilah Putri Permana, Nabilah Putri, Lisa Amelia Rahmah, Nadila Alya Raissa Amanda Putri Raisyah, Shafira Isra Rakhmat Kurniawan R Rao, Sarah Rasyad, Ismi Hamidah Rendy Andika, Rendy Risandi Alfariz Risqullah, Fahira Khalisyah Roza, Yuda Fakhri Sahfitri, Fachira Nur Samsudin Samsudin Samsudin, Samsudin Sembiring, Muhammad Andyansyah Septiana Dewi Andriana, Septiana Dewi Sibarani, Fathiya Hasyifah Simatupang, Salmi Saputra Sinaga, Imam Adlin Syahputra, Iqbal Maulana Syarifudin, Zaini Syuhada, Muhammad Randa Tanjung, Khairunnisa Teguh Kurniawan Tri Yuliana Ulan, Tri Ulandari Wangi, Putri Sekar Yulia, Anisa Zikri Ezza Alhira Zulkifli Zulkifli