cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Jamaluddin
Contact Email
jamaluddin@methodist.ac.id
Phone
+6281397181985
Journal Mail Official
jamaluddin@methodist.ac.id
Editorial Address
Jl. Hang Tuah No. 8 Medan Sumatera Utara - Indonesia Kode Pos: 20152
Location
Kota medan,
Sumatera utara
INDONESIA
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi
Published by Universitas Methodist Indonesia
ISSN : 25988565     EISSN : 26204339     DOI : 10.46880
Core Subject : Economy, Science,
Computer Science & IT Economics, Econometrics & Finance
Sistem Informasi Sistem Informasi Manajemen Sistem Informasi Akuntansi Manajemen Basis Data Pengembangan Aplikasi Web dan Mobile Sistem Pendukung Keputusan Desain Grafis dan Multimedia Audit Sistem Informasi Topik-topik lain yang Relevan dengan bidang ilmu Manajemen Informatika Topik-topik lain yang Relevan dengan bidang ilmu Kompuerisasi Akuntansi
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 372 Documents
 34   35   36   37   38 
Perancangan Sistem Peringatan Dini Bencana Berbasis Website Terintegrasi BMKG dan Notifikasi Whatsapp Nuarta, I Wayan; I Putu Astya Prayudha; Ni Gusti Ayu Putu Harry Saptarini; Gde Brahupadhya Subiksa
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 10 No. 1 (2026): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol10No1.pp7-17

Abstract

Indonesia has a high level of disaster risk due to its geological conditions. Although the BMKG has provided early warning information, its dissemination has not been fully received by the public in a timely manner. Meanwhile, the widespread use of WhatsApp in Indonesia offers an opportunity to utilize it as a medium for delivering disaster-related information. This study aims to design a website-based disaster early warning system integrated with BMKG data and WhatsApp notifications based on provincial regions. The system was developed using the Waterfall method with PHP, MySQL, and a WhatsApp gateway service, utilizing earthquake and weather data that are updated automatically. The results indicate that the system operates according to functional requirements. WhatsApp notifications were successfully delivered with a 95% success rate and an average delivery time of 2.6 seconds. Black box testing showed 100% valid results, while the System Usability Scale evaluation achieved a score of 82.5, indicating a very good level of usability.
Optimalisasi Prediksi Klaim Kendaraan Bermotor Menggunakan Time Series Analysis dengan Pendekatan Variasi Kalender dalam Perusahaan Asuransi Umum Wijaya, Gede Rama Darma; R. Mohamad Atok
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 10 No. 1 (2026): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol10No1.pp1-6

Abstract

General insurance companies face significant challenges in predicting motor vehicle insurance claims due to seasonal fluctuations and calendar variations. This study aims to optimize the accuracy of claim predictions using the Autoregressive Integrated Moving Average (ARIMA) method combined with a calendar variation approach. Data analysed includes nominal claim values from January 2015 to December 2023. Regression analysis results show that calendar variations, specifically periods "before" and "during" the Eid al-Fitr holiday, significantly impact claim reductions. The best-fit time series model obtained is ARIMA (1,0,1)(0,1,1)4. This model satisfies white noise and normality assumptions for residuals, providing a robust framework for data-driven decision-making, reserve allocation, and operational readines.
Simulasi Reaksi Kimia Berbasis Algoritma Titrasi Menggunakan Python: Studi Kasus Reaksi Asam-Basa Azkia, Czidni Sika; Wibowo, Claudia Shinta Octa; Ayu Puspa Wirani
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 10 No. 1 (2026): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol10No1.pp45-52

Abstract

Learning acid–base titration concepts in schools is often constrained by limited laboratory facilities, making interactive and accessible digital simulations an effective alternative. This study aims to develop an acid–base titration simulation based on Python algorithms as an innovative learning medium. The simulation focuses on the reaction between a strong acid (HCl) and a strong base (NaOH) with predetermined volume and concentration parameters, displaying pH changes through a titration curve. The research method applies an algorithmic approach based on stoichiometric calculations, visualized using the Matplotlib library. The simulation results show that the model accurately represents pH changes from acidic conditions to the equivalent point and continues toward basic conditions, consistent with analytical chemistry theory. Validation was conducted through theoretical comparison, visualization against literature curves, and expert evaluation, resulting in an average score of 3.79 out of 4. This indicates that simulation is highly feasible for use in learning. The Python-based simulation not only enhances understanding of titration concepts but also serves as an alternative learning solution in schools with limited laboratory resources.
Perancangan Sistem Informasi Manajemen Kelelahan Driver Berbasis Web pada Honda Amartha Samarinda dengan Metode Self-Assessment dan Penjadwalan Delivery Afinda, Rifka Karin; Pratiwi, Heny; Pahrudin, Pajar
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 10 No. 1 (2026): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol10No1.pp70-78

Abstract

Kelelahan kerja pada driver merupakan faktor yang memengaruhi keselamatan berkendara, kualitas pelayanan, dan kinerja operasional Perusahaan. Pada Honda Amartha Samarinda, pemantauan kelelahan driver dan penjadwalan delivery masih dilakukan secara manual sehingga berpotensi menimbulkan ketidakefisienan dan kesalahan pencatatan. Penelitian ini bertujuan merancang Sistem Informasi Manajemen Kelelahan Driver berbasis web dengan metode self-assessment dan penjadwalan delivery untuk meningkatkan efektivitas monitoring dan distribusi tugas. Metode penelitian meliputi analisis kebutuhan sistem, perancangan menggunakan Unified Modeling Language (UML), perancangan basis data, dan implementasi sistem berbasis web. Metode self- assessment diterapkan melalui pengisian kuesioner oleh driver sebelum melakukan delivery untuk mengidentifikasi tingkat kelelahan, yang kemudian menjadi parameter dalam penjadwalan tugas secara terintegrasi. Sistem yang dirancang mampu menyajikan informasi tingkat kelelahan secara real-time, sehingga dapat membantu admin logistik dalam menentukan kelayakan penugasan, serta menghasilkan laporan monitoring sebagain bahan evaluasi manajemen. Hasil penelitian menunjukan bahwa sistem ini dapat meningkatkan efisiensi pengelola jadwal, mendukung pengambilan keputusan, serta berpotensi meningkatkan keselamatan dan produktivitas kerja driver.
Penerapan Algoritma K-Means Clustering Untuk Pengelompokan Data Absensi Siswa Menggunakan Teknologi QR Code Berbasis Web: Studi Kasus SMAN 2 Jombang Amruli, Danang Rifki; Vitadiar, Tanhella Zein
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 10 No. 1 (2026): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol10No1.pp53-61

Abstract

This study develops a web-based student attendance system using QR Code technology integrated with the K-Means Clustering algorithm. The system aims to improve accuracy and efficiency in managing attendance while classifying student discipline levels based on indicators of present, late, sick, excused, and unexcused. System development applies the Waterfall model. The K-Means algorithm groups students into three clusters: high, medium, and low attendance. Precision testing shows 95.56% accuracy compared to manual teacher assessment. The system supports school digitalization by providing automated attendance recording and data-driven discipline evaluation.
Evaluasi Model Convolutional Neural Network (CNN) dalam Klasifikasi Penyakit Daun Jagung Berbasis Web Menggunakan Citra Digital Santika, I Gusti Ngurah Arya; Ni Gusti Ayu Putu Harry Saptarini; I Putu Astya Prayudha; Gde Brahupadhya Subiksa
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 10 No. 1 (2026): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol10No1.pp98-106

Abstract

Corn leaf diseases such as blight and rust can reduce crop yields if they are not detected at an early stage. In Penatahan Village, the process of identifying these diseases is still carried out manually through visual observation, which may lead to misidentification due to the similarity of symptoms between different diseases. Therefore, a technology-based system is needed to assist the identification process in a more objective and efficient manner. This study aims to classify corn leaf diseases using the Convolutional Neural Network (CNN) method based on digital leaf images. The dataset used consists of 319 images categorized into three classes: healthy, blight, and rust, with 80% of the data used for training and 20% for validation. The model was developed using a transfer learning approach with the MobileNetV2 architecture and evaluated using a confusion matrix. The experimental results indicate that the model achieved an accuracy of 92.19%, indicating that the CNN method is capable of effectively classifying corn leaf diseases. The developed system can be utilized as a tool to assist in the rapid and objective identification of corn leaf diseases.
Klasifikasi Adopsi Berbasis Kecerdasan Buatan pada UMKM di Indonesia Menggunakan Algoritma Random Forest Dirgantara, Muhammad Ihsan; Sepriansyah, Fakhri; Izzatul Maula, Nulry; Daffazka, Farhan; Ditha Tania, Ken; Meiriza , Alsella
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 10 No. 1 (2026): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol10No1.pp35-44

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play a strategic role in the Indonesian economy; however, digital transformation based on artificial intelligence (AI) remains a significant challenge. This study aims to classify AI adoption among MSMEs in Indonesia using the Random Forest algorithm and to identify the factors that influence it. The dataset was obtained from the Zenodo repository, consisting of questionnaire results regarding AI adoption in MSMEs. The research stages included data cleaning, encoding, splitting the data into training (80%) and testing (20%) sets, implementing the Random Forest algorithm, evaluation, and result analysis. The evaluation results show an accuracy of 80.3% with an ROC-AUC of 0.884. The weighted precision, recall, and F1-score values are 81.2%, 80.3%, and 80.4%, respectively. These evaluation results indicate that the Random Forest algorithm performs well on this dataset. Furthermore, the feature importance analysis revealed several influential variables in AI adoption among MSMEs, including strategic decision-making (10.9%), digital leadership (8.3%), and respondent position (7.8%). In conclusion, the implementation of the Random Forest algorithm demonstrates strong performance in classifying AI adoption among MSMEs in Indonesia and highlights key influential variables such as strategic decision-making, digital leadership, and respondent position.
Implementasi Dynamic Rendering untuk Optimasi Efisiensi Server dan Indeksabilitas Pada Single Page Application Achmad, Niko; Moh Ahsan; Ainia Walidaroyani
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 10 No. 1 (2026): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol10No1.pp25-34

Abstract

The development of a Client Side Rendering (CSR)-based Single Page Application (SPA) has search engine indexability weaknesses, while Server Side Rendering (SSR) overloads server computation. This study aims to prove the efficiency of the Dynamic Rendering architecture as a middle-ground solution. Through Nginx configuration, the server detects the User-Agent to serve static pages (CSR) to human users and fully rendered pages (SSR) to bot crawlers. Experimental testing was conducted on a Virtual Private Server (VPS) using k6 with a constant load of 100 Virtual Users, Prometheus, and Grafana, as well as Document Object Model (DOM) validation via Google Search Console. The Mann-Whitney U Test results proved a significant performance difference with a p-value < 0.05. The implementation of Dynamic Rendering is highly efficient, capable of reducing CPU Utilization by 92.28% and Memory Usage by 5.14%, and increasing Request Per Second (RPS) capacity by 17.19%. Indexability validation also confirmed that crawlers successfully received the HTML document entirely. In conclusion, Dynamic Rendering is proven to be an effective architectural solution to minimize server load while ensuring optimal content visibility on search engines.
Media Pembelajaran Interaktif Berbasis Augmented Reality Pengenalan Anggota Tubuh dalam Bahasa Kutai untuk Sekolah Dasar Negeri 008 Samarinda Utara Sabirin, Ahmad; Heny Pratiwi; Yunita, Yunita
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 10 No. 1 (2026): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol10No1.pp18-24

Abstract

This study develops markerless Augmented Reality (AR) interactive learning media to introduce human body parts in the Kutai language as local content (Mulok) at SDN 008 Samarinda Utara. The primary issue stems from traditional methods—textbooks, 2D images, and conventional lectures—causing student boredom, low motivation, and shallow vocabulary mastery. This research aims to enhance learning motivation, conceptual understanding, and Kutai language proficiency through immersive experiences. The development follows the six-stage Multimedia Development Life Cycle (MDLC). The application was built on the Assemblr EDU platform (browser-based WebAR) using 3D models from Blender, interactive buttons, and Kutai language explanations. Black box testing was successful, while beta testing with ten students yielded an average score of 76.9% (Good category). This media supports immersive learning without additional installations, facilitating effective Mulok implementation at SDN 008. Future research is recommended to expand the respondent pool and integrate advanced interactive features, such as AR-based quizzes, audio narration, and animations, to further enhance overall media effectiveness. Exploring alternative platforms, including Unity and Zappar, is also encouraged. This tool represents a significant advancement in digitalizing regional language education, ensuring that local indigenous knowledge remains engaging and accessible for the younger generation in East Kalimantan.
Implementasi Algoritma AES-256 dalam Enkripsi Pengamanan Data pada PT Kallista Prima Azmi, Rifaldi Mahsyaf; Ikhwan, Ali
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 10 No. 1 (2026): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol10No1.pp62-69

Abstract

This study aims to implement the Advanced Encryption Standard (AES-256) algorithm to secure pharmaceutical product pricing data within a product management system, using the AB-VAS K – TABLET product as a case study. The background of this research is based on the importance of protecting pricing data—namely HNA, HNA+PPN, and HET—from risks of manipulation and unauthorized access in information systems. The method used includes system design, encryption and decryption processes using AES-256 with a 256-bit key length and 14 transformation rounds, as well as testing data integrity and sensitivity through the avalanche effect test. The results show that all pricing data were successfully transformed into ciphertext with no recognizable pattern and could be restored identically through the decryption process. The testing also demonstrated that a small change in plaintext produced a significant change in the resulting ciphertext, thereby increasing the security level of the system. With a key complexity of 2²⁵⁶, the implementation of AES-256 is considered effective in maintaining the confidentiality and integrity of pricing data and is suitable for application in pharmaceutical product management information systems.

Page 36 of 38 | Total Record : 372

 34   35   36   37   38 

Filter by Year

2017 2026


Reset
Filter By Issues
All Issue Vol. 10 No. 1 (2026): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi Vol. 9 No. 2 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi Vol. 8 No. 1 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi Vol. 7 No. 2 (2023): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi Vol. 7 No. 1 (2023): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi Vol. 6 No. 2 (2022): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi Vol. 6 No. 1 (2022): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi Vol. 5 No. 2 (2021): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi Vol. 5 No. 1 (2021): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi Vol. 4 No. 2 (2020): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi Vol. 4 No. 1 (2020): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi Vol. 3 No. 2 (2019): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi Vol. 3 No. 1 (2019): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi Vol. 2 No. 2 (2018): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi Vol. 2 No. 1 (2018): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi Vol. 1 No. 1 (2017): METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi More Issue