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Jurnal Tekinkom (Teknik Informasi dan Komputer)
Published by Politeknik Bisnis Indonesia
ISSN : 26211556     EISSN : 26213079     DOI : https://doi.org/10.37600/tekinkom
Core Subject : Science,
Computer Science & IT
Jurnal TEKINKOM merupakan jurnal yang dimaksudkan sebagai media terbitan kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai isu Ilmu - ilmu komputer dan sistem informasi, seperti : Pemrograman Jaringan, Jaringan Komputer, Teknik Komputer, Ilmu Komputer/Informatika, Sistem Informasi, dan Multi Disiplin Penunjang Domain Penelitian Komputasi, Sistem dan Teknologi Informasi dan Komunikasi, dan lain-lain yang terkait. Artikel ilmiah dimaksud berupa kajian teori (theoritical review) dan kajian empiris dari ilmu terkait, yang dapat dipertanggungjawabkan serta disebarluaskan secara nasional maupun internasional.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 60 Documents
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Search results for , issue "Vol 7 No 1 (2024)" : 60 Documents clear
APLIKASI PENCEGAH PENIPUAN JUAL BELI AKUN MOBILE LEGENDS BERBASIS MOBILE MENGGUNAKAN FRAMEWORK FLUTTER Agil Fajar Dwi Prasetyo; Ade Eviyanti; Metatia Intan Mauliana
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1168

Abstract

The internet is a phenomenon in today's era, serving not only as a medium for information sharing but also permeating the realm of online gaming, particularly Mobile Legends. This online game, playable even on low specifications, offers not only pure entertainment but also a potential avenue for trade. However, this situation can give rise to fraudulent activities due to Mobile Legends' "hackback" feature, wherein sellers can reclaim the accounts they have sold to customers. To address these issues, the researcher has developed an application that can blacklist game IDs involved in fraudulent activities, thus preventing recurring scams. In the User Acceptance Testing (UAT), this application scored 86%, falling within the "strongly agree" range. It is hoped that this application will assist parties engaged in account transactions, protecting them from unscrupulous entities and mitigating potential losses.
PENERAPAN AUGMENTED REALITY DALAM PENGENALAN PERALATAN MANUFAKTUR PADA PRODI TEKNIK INDUSTRI UNIVERSITAS UNIVERSAL Kaharuddin Kaharuddin; Musliadi KH; Kurniawan Hamidi; Ilwan Syafrinal
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1040

Abstract

An effective learning process to produce quality education requires supporting facilities such as adequate practicum media, Industrial Engineering Universal University currently has limitations with practicum media, especially in the introduction of industrial engineering manufacturing tools, therefore alternative media such as AR technology are needed. The purpose of this study is to determine the effectiveness of learning and the overall quality of education from the application of AR-based applications. The application of this technology can be developed using the Game Development Life Cycle (GDLC) method through several stages. The development results were randomly tested on 40 respondents by applying three indicator features and five statements used and obtained presentation values ranging from 78% to 81% user satisfaction before the application with strong presentation. While from the results of the analysis carried out on each indicator used, the first stage with the highest percentage is Usability, followed by functional indicators and user interface indicators at the lowest percent.
RANCANG BANGUN APLIKASI UJI KEMIRIPAN GAMBAR AI GENERATIVE DAN GAMBAR BUATAN TANGAN MENGGUNAKAN METODE DEEP LEARNING Rifqi Alfaesta Prawiratama; Sumarno Sumarno; Irwan Alnarus Kautsar
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1192

Abstract

This research discusses the development of an application to test the similarity between AI Generative images and handmade images using deep learning methods. Artificial Intelligence (AI) technology has been applied to generative art through deep learning algorithms; however, there are still challenges related to copyright and originality of AI Generative art. The aim of this research is to develop an efficient model for classifying AI Generative art and handmade art. The classification model uses a Transformer approach, specifically exploiting the BEiT architecture, which shows highly satisfactory results in image classification tests. The high F1 score in each test reflects a good balance between precision and recall. The Transformer model outperforms previous methods using Convolutional Neural Network (CNN) and VGG16 models. It is expected that this model will be able to classify art more efficiently, assist in the detection of misuse, and mitigate legal risks related to copyright.
PENERAPAN METODE ANT COLONY OPTIMIZATION (ACO) DALAM MENENTUKAN JALUR ALTERNATIF SOLUSI KEMACETAN KOTA MEDAN William William; Rizky Syahputra Sitompul; Adilman Reliance Hia; Roy F. Hasudungan Malau; Saut Parsaoran Tamba; Mohammad Irfan Fahmi
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1221

Abstract

This research aims to analyze and implement the Ant Colony Optimization (ACO) method in determining alternative routes to reduce traffic congestion in Medan City. Against the background of significant congestion problems during rush hours, this research collects traffic data through surveys and observations to serve as input for the ACO algorithm. This method is inspired by the natural behavior of ants in searching for food, where ants collectively find the shortest route based on pheromone trails. Tests were carried out with variations in ACO parameters such as pheromone evaporation rate, number of ants, and iterations to analyze the effectiveness of alternative paths. The research results show that the application of this method can help reduce the burden on the road network and is proven to be able to reduce travel time by 37.5%, where the time needed from 40 minutes can be reduced to 25 minutes. The results of this research can contribute to the development of an intelligent transportation system that is adaptive to changes in traffic conditions and the needs of road users in the city of Medan.
PERANCANGAN ULANG UI/UX WEBSITE D’COFFEE CUP KE APLIKASI MOBILE DENGAN METODE DESIGN THINKING Icha Sinaga; Seftin Fitri Ana Wati; Anindo Saka Fitri
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1466

Abstract

D'Coffee Cup in Surabaya has implemented a web-based application for food ordering, yet it faces a significant issue due to the absence of direct payment features, resulting in long queues at the cashier. Initial usability testing revealed a score of 42.5 out of 100. A study utilizing the User Experience Questionnaire (UEQ) indicated low scores in attractiveness (-1.46), perspicuity (-1.15), efficiency (-1.65), dependability (-1.33), stimulation (-1.48), and novelty (-1.42), highlighting deficiencies in both the usability and aesthetics of the application’s UI design. Following a redesign process using the Design Thinking methodology (Empathize, Define, Ideate, Prototype, Testing), usability testing demonstrated a significant improvement with a usability score of 88, indicating an excellent level of usability. Additionally, UEQ testing results showed benchmark values for all six aspects above average: attractiveness (2.24), perspicuity (1.98), efficiency (2.15), dependability (1.93), stimulation (2.18), and novelty (2.03). Post-redesign usability testing demonstrated a significant improvement with a usability score of 88, indicating an excellent level of usability. Additionally, UEQ testing results showed benchmark values for all six aspects above average: attractiveness (2.24), perspicuity (1.98), efficiency (2.15), dependability (1.93), stimulation (2.18), and novelty (2.03).
IMPLEMENTASI MIKROKONTROLER NODEMCU ESP8266 SEBAGAI PENGENDALI PERANGKAT ELEKTRONIK BERBASIS VOICE ASSISTANT Muhammad Qosdy Jauharul Arzaq; Irwan Alnarus Kautsar; Azmuri Wahyu Azinar
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1262

Abstract

One prominent development is the concept of the Internet of Things (IoT), which connects various physical devices via an internet network. By leveraging platforms like the NodeMCU ESP8266, IoT enables integration between the digital and physical worlds, opening up new opportunities in device monitoring and control. This research aims to implement the NodeMCU ESP8266 microcontroller as a voice assistant-based electronic device controller, by designing and implementing electronic device control using the basis of the Internet of Things (IoT) on a smartphone platform by utilizing the sistem development life cycle (SDLC) model. The research results show that the NodeMCU ESP8266 microcontroller is capable of controlling electronic devices based on voice assistants well. The sistem is able to detect and process voice commands with high accuracy, as well as control connected electronic devices efficiently, with an average success percentage of voice commands of 96.5%.
KLASIFIKASI DATA MINING UNTUK PREDIKSI PENYAKIT KARDIOVASKULAR Nia Nuraeni
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1276

Abstract

According to the World Health Organization (WHO), cardiovascular diseases are one of the leading causes of death worldwide. Cardiovascular diseases involve heart and blood vessel conditions that commonly occur in communities. These conditions encompass various diseases such as coronary heart disease, heart failure, stroke, and peripheral vascular disease. Major risk factors include high blood pressure, high cholesterol, and smoking. Premature deaths due to heart diseases can be prevented by controlling the risk factors and identifying individuals at high risk of developing such diseases. One of the most effective ways to identify and predict heart diseases is through the use of data mining algorithms. Data mining algorithms can address issues in diagnosing cardiovascular or heart diseases by utilizing predictive models, such as Decision Tree, Naive Bayes, Logistic Regression, K-Nearest Neighbor, and others. In this study, identification was performed using classification algorithms including Naïve Bayes, Logistic Regression, Decision Tree Classifier, k-NN, SVM, XGBoost, and Random Forest. The highest accuracy, reaching 98%, was obtained from the Random Forest algorithm
ANALISIS PERBEDAAN ATENSI VISUAL CUSTOMER SHOPEE TERHADAP PRODUK FLASH SALE DENGAN PRODUK NORMAL BERBASIS EYE TRACKING Zabbrina Ayu Marcellina Tanjung; Dita Sari Vita L.S; Monalisa Br Sembiring Depari; Evta Indra; Deni Adha Akbari; Rizki Edmi Edison
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1368

Abstract

Shopee is known as the e-commerce platform that is most widely used by people in Indonesia. One of the advantages offered by this platform is flash sales on various products at certain times. This study aims to determine the visual attention patterns of shopee users when viewing websites with flash sale captions using eye tracker technology. A total of 63 participants who were divided into two groups based on their experience using shopee were shown four types of products, each of which had a flash sale display and a normal display. There were five regions of interest in each display and two types of functions, first time fixation and Dwell time, were analyzed. This study shows that even though the longest duration was used by participants to view the flash sale description region, the first region viewed by both groups of participants was the product region. We hope that this data can be a reference for e-commerce platform website design to increase attention to the main message.
OPTIMASI PENERAPAN ALGORITMA CONVOLUTION NEURAL NETWORK DALAM KLASIFIKASI TINGKAT KESEGARAN DAGING SAPI Sahera, Charisa Nur; Rahmawati, Yunianita; Dijaya, Rohman
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1122

Abstract

This research discusses optimizing the application of the Convolutional Neural Network (CNN) algorithm to overcome the problem of mixing fresh and non-fresh beef on the market. The focus of the research is classification of freshness levels in beef images using the CNN method with ADAM optimizer. Data collection involves open and private data. Image preprocessing is done with LabelEncoder and cv2. The research results show that this method is very effective in identifying and classifying the level of freshness in beef images. By determining optimal parameters, the model achieved the highest accuracy level of 98.50% at 10 epochs and a learning rate value of 0.001. Confusion matrix shows good results with a high number of True Positives. By applying CNN with the ADAM optimizer, it provides an effective solution to the problem of classifying beef freshness levels because this model is able to classify beef images well.
KLASIFIKASI DATA PENJUALAN UNTUK MEMPREDIKSI TINGKAT PENJUALAN PRODUK MENGGUNAKAN METODE DECISION TREE Demira Intan Suranda; Adi Nugroho
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1269

Abstract

A mature strategy is one of the keys so that a company can increase sales effectively and consistently. With recorded and accurate information, companies can make decisions quickly to predict what supplies consumers will need for the future. Aruna Boutique sells various types of Muslim clothing such as robes and headscarves with several brands of each type. The aim of this research is to determine the sales of the best-selling and least-selling products using the Decision Tree method with the ID3 algorithm. The tool used is a rapid miner using boutique sales transaction data from July - September. The results obtained in this research are the best-selling products Gamis 2 (Umama), veil 2 (DYN) and the less popular products Gamis 1 (Mahdani), veil 3 (Azara) with an accuracy value of 88.24%, which means that the method used it's good enough. Based on the rules obtained, information can be used to increase sales in terms of stock inventory, display and promotion strategies.

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