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All Journal Jurnal Informatika dan Teknik Elektro Terapan Inspiration: Jurnal Teknologi Informasi dan Komunikasi Journal of Embedded Systems, Security and Intelligent Systems
Nurhikmayana Janna
State Polytechnic Of Ujung Pandang
Computer Science & IT

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Expert System For Major Selection Determination At Universitas Muhammadiyah Sinjai Nurhikmayana Janna; Ingrid Nurtanio; Imran Taufiq
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol. 13 No. 1 (2023): Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Pusat Penelitian dan Pengabdian Pada Masyarakat Sekolah Tinggi Manajemen Informatika dan Komputer AKBA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v13i1.41

Abstract

The choice of major is very important to support the success of students in completing their studies well and on time. However, this is an important issue because, based on research by the Indonesia Career Center Network (ICCN) in 2017, 87 % of Indonesian students admit that the majors they chose do not suit their interests. And 71.7 % of workers have a profession that is not in accordance with their education. The obstacle faced by prospective students when choosing a major is that they do not know their interests, talents, and potential. Therefore, a system was created that could provide suggestions for majors that match the interests of prospective students. An expert system with the forward chaining method is used in the system. The method used in making this expert system application is the forward chaining method. This expert system process accepts the choices that are already available and have been filled in by the user. And the results of this expert system provide a solution for selecting majors based on the interests of prospective students. So that prospective students can determine the right major. From the results of the implementation and trials that have been carried out by researchers, a probability value is obtained that reaches 100 %, indicating that the system is functioning properly, and as many as 94 % of respondents stated that they strongly agree that the use of this application can help make it easier to determine majors at Universitas Muhammadiyah Sinjai.
IMPLEMENTASI TEMPLATE MATCHING DAN SEGMENTASI CITRA UNTUK DETEKSI KEABSAHAN DAN DENOMINASI UANG KERTAS PADA RASPBERRY PI Janna, Nurhikmayana
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 2 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i2.6547

Abstract

Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem otomatisasi untuk mendeteksi keaslian dan denominasi uang kertas Rupiah berbasis Raspberry Pi dengan metode template matching dan pemrosesan citra menggunakan OpenCV. Latar belakang penelitian ini didasarkan pada masih maraknya peredaran uang palsu yang berpotensi merugikan pelaku Usaha Mikro, Kecil, dan Menengah (UMKM). Dengan menggunakan kamera smartphone dan sinar ultraviolet, sistem dapat mendeteksi nominal dan keaslian uang berdasarkan fitur seperti serial number dan benang pengaman. Pengujian menunjukkan akurasi deteksi keabsahan dan nominal sebesar 91,5%. Hasil ini menunjukkan efektivitas metode yang digunakan dalam membantu transaksi keuangan yang lebih aman dan berpotensi untuk diimplementasikan secara luas sebagai solusi deteksi uang palsu yang hemat biaya dan praktis bagi pelaku UMKM. This study aims to design and implement an automation system to detect the authenticity and denomination of Rupiah banknotes based on Raspberry Pi with the template matching method and image processing using OpenCV. The background of this study is based on the rampant circulation of counterfeit money that has the potential to harm Micro, Small, and Medium Enterprises (MSMEs). By using a smartphone camera and ultraviolet light, the system can detect the nominal and authenticity of money based on features such as serial numbers and security threads. Testing shows an accuracy of detecting the validity and nominal of 91.5%. These results show the effectiveness of the method used in helping safer financial transactions and has the potential to be widely implemented as a cost-effective and practical counterfeit money detection solution for MSMEs.
Comparison of Efficiency 3D Rendering Methods for Augmented Reality: A Case Study of SRP, URP, and Light Estimation on a Mobile Device Sri Suci Indasari; Achmad Zulfajri Syaharuddin; Nurhikmayana Janna; Irmawati
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 2 (2025): June 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i2.8400

Abstract

This study examines the efficiency of 3D rendering methods in the development of Augmented Reality (AR) applications, which significantly impact visual quality, response speed, and device resource consumption. The main objective of this research is to analyze and compare three commonly used rendering methods in AR development: Standard Render Pipeline (SRP), Universal Render Pipeline (URP), and Light Estimation. Data collection was conducted through the implementation of an AR prototype application featuring two 3D objects (Earth and Mars), followed by testing the render latency for each method. The results showed that all three methods produced the same latency time of 0.03 seconds on a high-specification device. These findings suggest that, under the given testing conditions, the choice of rendering method has no significant impact on rendering latency. However, overall efficiency may still be influenced by other factors such as lighting conditions, hardware specifications, and marker quality.
Automatic Floor Stain Detection with Image Processing: A Practical Comparison of OpenCV and RGB Grayscale Conversion: Deteksi Noda Lantai Otomatis dengan Pemrosesan Citra: Komparasi Praktikal OpenCV dan Grayscale RGB Achmad Zulfajri Syaharuddin; Sri Suci Indasari; Nurhikmayana Janna; Andi Afdhal Hilmi
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 4 (2025): Desember 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i4.9805

Abstract

This research develops an image processing-based floor stain detection system using grayscale conversion and binary thresholding. Two conversion approaches are compared: (i) a simple RGB grayscale formula and (ii) a built-in OpenCV function. The system uses a fixed intensity threshold of T=80 and classifies a floor as “dirty” if the detected area exceeds 20% of the image. Experiments are conducted on three floor types (plain, dark, patterned), five stain types (coffee, oil, ink, plastic, chalk), and two lighting conditions. Results show that the performance of both methods is very close with an average difference of ≈0.07% and a maximum of 0.6%; the simple formula is suitable for resource-limited devices, while OpenCV is more robust to color/lighting variations. The main contributions of this paper are (1) a practical comparison of two grayscale conversion pathways for cleanliness monitoring, (2) a simple decision rule based on the percentage of dirty area that aligns with cleanliness perception, and (3) an analysis of implementation implications for real-time systems in cleaning robots/IoT. Future directions include adaptive thresholding and morphology integration to improve reliability in dynamic environments. (Replace the current abstract paragraph containing T=80 and the 20% rule with the version above. The 20% policy reference is already explained in your manuscript).
Co-Authors Achmad Zulfajri Syaharuddin Achmad Zulfajri Syaharuddin Andi Afdhal Hilmi Imran Taufiq Ingrid Nurtanio Irmawati Sri Suci Indasari Sri Suci Indasari