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INDONESIA
Jurnal Teknologi Komputer dan Informatika
Published by Politeknik Pajajaran ICB Bandung
ISSN : -     EISSN : 29871107     DOI : https://doi.org/10.59820/tekomin.v1i1.10
Core Subject : Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering
Information management, e-Government, E-business and e-Commerce, IT Governance and Audits, IT Service Management, IT Project Management, Information System Development, Software Engineering, Soft Computing, Data Mining, Multimedia Technology, Mobile Computing, Artificial Intelligence, Games Programming, Computer Vision, Image Processing, Embedded System, Augmented/Virtual Reality, Image Processing
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 31 Documents
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DETEKSI WAJAH DENGAN METODE HAAR CASCADE MENGGUNAKAN OPENCV (FACE DETECTION WITH HAAR CASCADE METHOD USING OPENCV) Rochmawati, Dwi Robiul
Jurnal Teknologi Komputer dan Informatika Vol 3 No 1 (2024): Jurnal Teknologi Komputer dan Informatika (TEKOMIN)
Publisher : LPPM Politeknik Pajajaran ICB Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59820/tekomin.v3i1.293

Abstract

Abstract Face detection is one of the most researched topics in the field of computer vision and digital image processing. The Haar Cascade method is one method that is often used to detect faces in an image or video. This method uses Haar features to identify faces by comparing them with existing faces in the database. This research aims to implement the Haar Cascade method to detect faces using the OpenCV library. The stages include image acquisition, image processing, face detection using Haar Cascade, and evaluation of detection results. The results show that the Haar Cascade method can detect faces quite well in various lighting conditions and viewing angles. Keywords: Face Detection; Haar Cascade; OpenCV
PERAN SISTEM PEMBAYARAN DIGITAL DALAM MENINGKATKAN PENJUALAN UMKM Hutahaean, Limbert; Shabrina, Alifia Rahma; Martiani, Yasmin; Syakduzzaman, Syakduzzaman; Yulia, Astri; Gunardi, Gunardi
Jurnal Teknologi Komputer dan Informatika Vol 3 No 1 (2024): Jurnal Teknologi Komputer dan Informatika (TEKOMIN)
Publisher : LPPM Politeknik Pajajaran ICB Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59820/tekomin.v3i1.325

Abstract

MSMEs (Micro, Small, and Medium Enterprises) have a crucial role in the economy, especially in developing countries like Indonesia. One of the main challenges faced by MSMEs is access to modern and efficient payment technology. This study aims to analyze the role of digital payment systems in increasing MSME sales. The research method used is a literature study by reviewing various relevant scientific literature. The results of the study show that the adoption of digital payment systems, such as electronic wallets (e-wallets), QRIS, and online bank transfers, can improve operational efficiency, reduce the risk of cash transactions, and expand the reach of the MSME market. The use of digital payment methods also allows MSMEs to increase financial transparency and more easily access financial services such as loans or investments. However, there are several challenges in implementing a digital payment system, including low digital literacy among MSME actors, limited technological infrastructure in several regions, and lack of socialization regarding the benefits of digitalization. Therefore, a comprehensive strategy is needed, such as increasing digital literacy and providing supporting infrastructure, to optimize the benefits of the digital payment system for MSMEs.
IMPLEMENTASI RETRIEVAL AUGMENTED GENERATION UNTUK EVALUASI PROPOSAL TUGAS AKHIR MAHASISWA Fanani, Ikhsan
Jurnal Teknologi Komputer dan Informatika Vol 3 No 2 (2025): Jurnal Teknologi Komputer dan Informatika (TEKOMIN)
Publisher : LPPM Politeknik Pajajaran ICB Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59820/tekomin.v3i2.336

Abstract

This research aims to develop a thesis title evaluation system based on Retrieval Augmented Generation (RAG), utilizing the thesis repository from the past year as a knowledge source. The system is developed by integrating a retrieval component that employs semantic embedding techniques to identify similar titles from the repository and a generative component that provides evaluation and improvement recommendations. The process includes preprocessing data from the thesis repository, implementing a sentence-transformers model to create a vector database, and integrating it with a Large Language Model (LLM). The test results on 20 new titles showed that the RAG system achieved an answer correctness score of 80%. The implementation also succeeded in automating and improving the objectivity of the evaluation process.
ANALISIS FAKTOR DAN POLA KEJADIAN BANJIR DI BANDAR LAMPUNG MENGGUNAKAN ARIMA, RANDOM FOREST, DAN XGBOOST Suaif, Ahmad; Sylvianti Rahayu, Eka
Jurnal Teknologi Komputer dan Informatika Vol 3 No 2 (2025): Jurnal Teknologi Komputer dan Informatika (TEKOMIN)
Publisher : LPPM Politeknik Pajajaran ICB Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59820/tekomin.v3i2.339

Abstract

Flooding is a significant environmental problem in Bandar Lampung City, influenced by various factors such as rainfall, humidity, etc. This study aims to analyze the factors that contribute to flooding and build a prediction model for flood patterns. The methods used include factor analysis with Random Forest Classifier and prediction model using ARIMA, Random Forest Regressor, and XGBoost Regressor. The results show that rainfall is the dominant factor with a feature importance value of 0.49. From the results of the comparison of prediction models, XGBoost Regressor provides the best performance with an RMSE value of 0.88, From the results of the comparison of prediction models, XGBoost Regressor provides the best performance with an RMSE value of 0.88 and MAE of 0.75, as well as a positive R2 value of 0.11. The conclusion of this study confirms that the ensemble learning-based machine learning method is superior to statistical models in predicting flood events.
PENGEMBANGAN APLIKASI VENDING TOKEN KWH METER PRABAYAR UNTUK MENINGKATKAN EFISIENSI PENGELOLAAN LISTRIK DI APARTEMEN DAN PERUMAHAN Sujana, Nana; Darmawan, Erwin; Sururi, Sururi
Jurnal Teknologi Komputer dan Informatika Vol 3 No 2 (2025): Jurnal Teknologi Komputer dan Informatika (TEKOMIN)
Publisher : LPPM Politeknik Pajajaran ICB Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59820/tekomin.v3i2.349

Abstract

Efficient electricity management remains one of the primary challenges in operating modern apartments and residential complexes. The prepaid KWH meter system offers an effective solution by enabling residents to monitor and control their electricity consumption independently. This study aims to develop a Prepaid KWH Meter Token Vending Application to enhance electricity management efficiency in such environments. The application is designed to help property managers generate, distribute, and monitor electricity tokens accurately and in an integrated manner. The research methodology includes five main stages: (1) Needs analysis, conducted through interviews and direct observation to identify problems and system requirements; (2) System design, including software architecture, user interface (UI/UX), and database design; (3) Web-based application development using the CodeIgniter framework and PHP; (4) Functionality test of the application was conducted using black box testing and User Acceptance Testing (UAT) to gather user feedback; and (5) Performance evaluation to measure the efficiency improvements achieved through the application. The testing results show that the application can deliver tokens quickly and accurately, supporting effective electricity monitoring by management. This application is expected to improve operational efficiency, optimize electricity costs, and enhance comfort for residents
ANALISIS KUALITAS CANVA SEBAGAI PLATFORM DESAIN ONLINE DAN MEDIA PEMBELAJARAN INTERAKTIF Ari Susanto, Agus; Kriya Almanfaluti, Istian
Jurnal Teknologi Komputer dan Informatika Vol 3 No 2 (2025): Jurnal Teknologi Komputer dan Informatika (TEKOMIN)
Publisher : LPPM Politeknik Pajajaran ICB Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59820/tekomin.v3i2.345

Abstract

This study aims to analyze the quality of Canva as an online design platform utilized in interactive learning, with a Systematic Literature Review (SLR) approach and using the WebQual 4.0 framework. Five relevant scientific articles were selected based on inclusion and exclusion criteria, then reviewed based on three main dimensions: usability, information quality, and service interaction quality. The results of the analysis show that Canva has a high level of usability, offers a charming and user-friendly interface. In addition, the quality of information is considered good because Canva provides various templates and educational design elements that support understanding of the material. However, the quality of service interaction is still relatively less than optimal, especially in the context of bold collaboration and interaction systems. Overall, Canva has proven effective in increasing student engagement and supporting creative visual learning processes. This study recommends improving user training and integrating Canva with digital learning systems so that users.
KLASIFIKASI EMOSI MENGGUNAKAN COMPUTER VISION DAN CONVOLUTIONAL NEURAL NETWORKS Nurdiyansah , Andri; Rochmawati, Dwi Robiul
Jurnal Teknologi Komputer dan Informatika Vol 3 No 2 (2025): Jurnal Teknologi Komputer dan Informatika (TEKOMIN)
Publisher : LPPM Politeknik Pajajaran ICB Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59820/tekomin.v3i2.411

Abstract

This research focuses on the development of an emotion classification system utilizing computer vision and Convolutional Neural Networks (CNN). This model was trained on the FER2013 dataset, which contains 35,809 facial images categorized into seven emotions. Metode seperti augmentasi data dan normalisasi piksel diterapkan untuk meningkatkan ketahanan model. The CNN architecture achieved an accuracy of 85%, demonstrating its effectiveness in recognizing emotions such as happiness and anger. This research highlights the potential integration of emotion-aware systems into applications such as human-computer interaction and personalized services, emphasizing technical innovation in AI-based solutions. Keywords: Emotion Classification; Computer Vision; CNN; FER2013; Deep Learning
PROTOTYPE PINTU OTOMATIS MENGGUNAKAN SENSOR ULTRASONIK BERBASIS ARDUINO UNO Darmawan, Erwin
Jurnal Teknologi Komputer dan Informatika Vol 4 No 1 (2025): Jurnal Teknologi Komputer dan Informatika (TEKOMIN)
Publisher : LPPM Politeknik Pajajaran ICB Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59820/tekomin.v4i1.416

Abstract

The development of automation systems continues to increase every year. One of them is the automation system on automatic doors. The use of human power in opening and closing the room door can be done automatically. Opening and closing the door can be done using electronic devices, making it easier to implement. In making this prototype, three main components are used, namely Ultrasonic Sensors, Arduino Uno Microcontrollers and Actuators in the form of servo motors. Ultrasonic sensors are used to detect the presence of humans who are about to go to the door, Servo Motors are used to open and close the door and the Microcontroller functions to process signals from ultrasonic sensors and provide output signals to the actuator. From the results of eight tests, In the entrance direction test, there were two failures out of eight tests.
INTERAKSI MANUSIA DAN AI: MEMBANGUN HUBUNGAN YANG BERKELANJUTAN Nurvitian, Adedayesa; Fitaloka, Fahira; Nur Janah, Anisa; Sukmawati, Adelia Dwi
Jurnal Teknologi Komputer dan Informatika Vol 2 No 2 (2024): Jurnal Teknologi Komputer dan Informatika (TEKOMIN)
Publisher : LPPM Politeknik Pajajaran ICB Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59820/tekomin.v2i2.302

Abstract

Rapid advances in artificial intelligence have opened up new opportunities for improved interactions between humans and machines. This study explores the various dynamics associated with the human-AI relationship, ranging from technical to ethical aspects. The aim of this research is to understand how harmonious collaboration between humans and AI can be established and sustained in the long term. It also highlights the important role of massive AI socialization and societal acceptance in creating a mutually supportive symbiosis. Through descriptive methods, this research provides deep insights into the implications of these interactions and offers recommendations to facilitate a sustainable relationship between humans and AI. Keywords: Interactions, Artificial Intelligence, Human, Machine, Collaboration
KECERDASAN BUATAN: PLAGIARISME DAN PERILAKU MANDIRI SISWA SEKOLAH MENENGAH ATAS DALAM PENGGUNAAN CHATGPT Adriansyah, Fajar; Aditya, Mochamad; Supriady, Mochammad Aldy; Ramadhan, Wildan
Jurnal Teknologi Komputer dan Informatika Vol 2 No 2 (2024): Jurnal Teknologi Komputer dan Informatika (TEKOMIN)
Publisher : LPPM Politeknik Pajajaran ICB Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59820/tekomin.v2i2.316

Abstract

Advances in artificial intelligence (AI) through platforms such as ChatGPT offer great potential in supporting high school students' learning, but also pose challenges such as plagiarism and decreased learning independence. This article explores the influence of ChatGPT on student behavior, analyzes the risks and benefits, and proposes strategies for ethical and effective use of AI. This study provides insights for educators and policymakers to maximize the positive impact of AI in education.

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