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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 2 (2024)" : 60 Documents clear
LITERATURE REVIEW PENGGUNAAN ARTIFICIAL INTELLIGENCE (AI) DI KALANGAN MAHASISWA DALAM DUNIA PENDIDIKAN Nurjannah, Nurjannah; Tjahjono, Budi; Siregar, Sarah Veronica; Basyarewan, Humairoh
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1536

Abstract

Rapid digital transformation has changed the paradigm of higher education, with Artificial Intelligence (AI) becoming one of the key technologies that supports adaptive and personalized learning. However, its implementation faces significant challenges, such as issues of ethics, data privacy, and academic integrity. This research aims to evaluate the effectiveness and challenges of using AI in higher education, especially by students, as well as formulating strategic recommendations for integrating this technology responsibly. Using a literature review approach, this research analyzes trends, benefits, and barriers related to AI applications such as AI-Based Intelligent Assistants (AIIA). The research results show that AI can improve learning efficiency and provide a more personalized learning experience, but concerns about technology dependency, potential plagiarism, and ethical and social impacts remain major obstacles. This research concludes that although AI has great potential in higher education, its successful integration requires strategic policies that consider technical, pedagogical and ethical aspects. This study contributes to the development of AI technology management strategies in higher education, providing guidance for creating an inclusive, adaptive, and sustainable learning ecosystem.
PERANCANGAN PROTOTIPE SISTEM INFORMASI MANAJEMEN PPM PADA LPPM UNIVERSITAS TIMOR BERBASIS WEBSITE Baso, Budiman; Risald, Risald
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1742

Abstract

The rapid advancement of information technology has encouraged higher education institutions to improve the efficiency of managing Research and Community Service (PPM) activities. This study aims to design and develop a web-based PPM Management Information System prototype for LPPM Universitas Timor. Using the Research and Development (R&D) method, the study involves need analysis, system design, development, testing, and evaluation of the prototype. The system is designed to facilitate proposal management, status tracking, evaluation processes, and reporting. The research findings indicate that the prototype significantly enhances the efficiency of PPM management by providing a user-friendly interface and automated notification features. Testing with end-users, including lecturers and LPPM administrators, yielded positive feedback on ease of use and process transparency. However, improvements are needed in areas such as system performance when handling large documents and the addition of email-based reminder features. In conclusion, the developed prototype serves as a foundational framework for building more comprehensive PPM management systems in the future, supporting efficiency, productivity, and academic objectives at Universitas Timor.
APLIKASI PENCARIAN LOKASI KOST BAGI MAHASISWA DI KOTA SERANG MENGGUNAKAN ALGORITMA UCS Darip, Mochammad; Auliana, Sigit
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1419

Abstract

The availability of boarding houses or accommodations near campuses is often limited, particularly for universities located in urban areas. This scarcity leads to intense competition among students for strategic housing options. In Serang City, the capital of Banten Province, the student population increases every year, especially from outside the region. However, this growth creates a new problem: the limited availability of strategically located housing. To address this, an innovative solution is proposed by applying the Uniform Cost Search algorithm to identify optimal boarding house locations for students. The UCS algorithm efficiently determines the best routes or locations at minimal cost by considering distance and access to public transportation. This study employs a quantitative approach and simulates the UCS algorithm. The UCS model is used to design an application with a user interface created using Figma and developed in Dart. The implementation results show that the UCS algorithm effectively identifies the nearest accommodation. Simulations revealed that Wisma Mina Kost is the most strategic location, about 260 meters from the main road. Additionally, the application provides public transport route details, such as route 01 and travel paths. This information serves as a valuable recommendation for students seeking strategic accommodations in Serang City.
LITERATURE REVIEW OPTIMALISASI PENGELOLAAN SUMBER DAYA DAN MITIGASI RISIKO MELALUI BUSINESS INTELLIGENCE: PENDEKATAN STRATEGIS Siregar, Sarah Veronica; Tjahjono, Budi; Nurjannah, Nurjannah; Basyarewan, Humairoh
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1285

Abstract

Rapid business developments require organizations to be smarter in managing resources and reducing risks in order to remain competitive. This study aims to explore the strategic role of Business Intelligence (BI) in helping organizations achieve these goals. Through a comprehensive literature review, this study analyzes various BI tools and techniques used to optimize resources, such as labor, finance, and materials, and identify risks early. The results show that BI can improve operational efficiency by providing data-based insights, supporting better decision-making, and proactively mitigating risks. BI can help organizations monitor financial data in real time to prevent the risk of loss, or predict energy needs to prevent waste. In addition, a strategic approach to implementing BI, such as choosing the right tools and involving leaders, is a key factor in success. This study concludes that BI has great potential to help organizations become more resilient and efficient, while providing practical guidance for companies that want to use BI to manage resources and risks effectively.
KINERJA ALGORITMA BACKPROPAGATION DAN RNN DALAM PREDIKSI BEBAN JARINGAN Annisah, Wulan Nur; Harani, Nisa Hanum; Habibi, Roni
Jurnal Teknik Informasi dan Komputer (Tekinkom) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1586

Abstract

Bandwidth allocation optimization is crucial to ensure optimal network performance and user satisfaction. This research aims to identify the best machine learning algorithm between backpropagation and recurrent neural network (RNN) in predicting network load, using two different datasets. The main issue addressed is how to choose the right algorithm for network load prediction to optimize bandwidth allocation. The CRISP-DM methodology was used as the research framework, with four evaluation metrics: Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE). The results showed that the backpropagation algorithm provided the best performance on the data with the lowest evaluation matrix: MAE 0.0203, MSE 0.0007, RMSE 0.0281, and MAPE 20%. In conclusion, the backpropagation algorithm is more suitable for predicting bandwidth requirements compared to RNN based on the evaluation metrics used, making it reliable for bandwidth allocation optimization.
MODEL JARINGAN SARAF TIRUAN UNTUK PREDIKSI PERMINTAAN PRODUK UMKM DI PEMATANG SIANTAR Sonang, Sahat; Sinaga, Kalvin
Jurnal Teknik Informasi dan Komputer (Tekinkom) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1849

Abstract

This study aims to develop an Artificial Neural Network (ANN) model in predicting demand for MSME products in Pematangsiantar to optimize production and inventory management. The main problem faced by MSME actors is demand uncertainty which causes excess or shortage of stock, thus affecting business efficiency. The ANN model is applied with a guided learning approach using the backpropagation algorithm to analyze demand patterns based on historical sales data. Data were obtained from the Cooperatives and MSMEs Office of Pematangsiantar City and interviews with business actors. The research process includes data collection and pre-processing, variable selection, data sharing, model development, training, optimization, and evaluation using the Mean Absolute Deviation (MAD), Mean Squared Error (MSE), and Mean Absolute Percent Error (MAPE) metrics. The results of the study show that the ANN model with the backpropagation algorithm is able to provide accurate demand predictions, with a MAPE value below 10%, which indicates very good forecasting. The implementation of this model helps make it easier for MSMEs to make strategic decisions related to production and inventory, thereby increasing competitiveness in the market.
IMPLEMENTASI METODE CUSTOMER SATISFACTION INDEKS DALAM ANALISIS KEPUASAN PASIEN TERHADAP PELAYANAN KLINIK SALSABILA Alfiarini, Alfiarini; Apriadi, Deni
Jurnal Teknik Informasi dan Komputer (Tekinkom) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1328

Abstract

To support government programs in improving the quality of human resources through quality health services. Good service quality can be seen from the following factors, the first is physical evidence where customers will see direct evidence of the service provided, the second is reliability, namely the extent to which the company has a level of reliability in providing services, the third is responsiveness, where the service is provided. provided quickly, precisely and the information conveyed is clear, the third is guarantee, namely the service provided can provide trust and confidence, the fifth is empathy, where the company tries to understand what customers want. Currently, the Salsabila Clinic still has difficulty measuring the level of satisfaction with the services provided to patients, so the level of satisfaction cannot be measured whether the services provided are in line with expectations or not. To measure the level of service quality, there are many methods that can be used, one of which is the Customer Satisfaction Index (CSI) method. The results of measurement calculations using the CSI method can be used to determine the level of patient satisfaction with staff service, cleanliness and facilities at the Salsabila clinic. The results of this research are the patient satisfaction index for Salsabila Clinic services of 78% with a Satisfaction Likert scale
PENGEMBANGAN APLIKASI MOBILE UMKM UNTUK MENINGKATKAN PENJUALAN DAN JANGKAUAN PASAR Sirait, Erwin; Purba, Arifin Tua
Jurnal Teknik Informasi dan Komputer (Tekinkom) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1848

Abstract

Micro, small, and medium enterprises (MSMEs) play a crucial role in the Indonesian economy, including in Pematangsiantar City, which has more than 29,000 MSMEs. However, MSMEs face various challenges, such as tight competition, limited market access, and lack of adoption of digital technology. This study aims to develop a mobile application for MSMEs to improve operational efficiency, expand market reach, and increase competitiveness. The methods used include literature studies, data collection from local MSMEs, flowchart and ERD-based system design, and application testing to ensure its functionality. The application developed has key features such as product management, digital transactions, and integration with logistics partners and payment systems. The results of the study show that digitalization through mobile applications can increase market reach, accelerate transactions, and provide convenience in business management for MSME actors. Thus, digital transformation through this application has the potential to be an effective solution in increasing MSME growth and supporting business sustainability in the digital era.
ANALISA PERANCANGAN UI/UX APLIKASI ABSENSI BERBASIS MOBILE MENGGUNAKAN METODE USER CENTERED DESIGN Aditya, Reinaldi; Kurniawati, Laela
Jurnal Teknik Informasi dan Komputer (Tekinkom) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1671

Abstract

In the digital era, information systems play a crucial role in business operations, including in hospitals. Kartika Pulo Mas. Currently, employee attendance using fingerprints has several problems, such as long queues, identification difficulties, and high investment and maintenance costs. To overcome this problem, an online-based mobile attendance application was developed. However, the main challenge is UI/UX design that is less than optimal, thereby reducing user comfort and efficiency. The aim of this research is to design a User Interface for a mobile attendance application that suits user needs. This research uses the User Centered Design method, which consists of 4 stages, namely understanding the context of use (Understand context of use), specifying user requirements (Specify user requirements), designing design solutions (Design Solutions Process), and evaluating the design against user needs (Evaluate against requirements). Testing was carried out using the System Usability Scale method to meet user needs. The questionnaire distributed used a Likert scale and was answered by 21 respondents. The results of the design evaluation concluded that the final SUS score calculation result was that the average score obtained was 87.5, which is Grade A. This indicates that users are very satisfied with the mobile attendance application.
ANALISIS ULASAN APLIKASI TINDER MENGGUNAKAN ALGORITMA NAÏVE BAYES DENGAN OPTIMASI INFORMATION GAIN Ayyubi, Vieri Nurgracie Al; Utami, Nengah Widya; Dewi, Eka Grana Aristyana
Jurnal Teknik Informasi dan Komputer (Tekinkom) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1518

Abstract

Current technological developments are very rapid, including the scope of developments in information and communication technology. In this digital era, there are more and more types of applications, the existence of this online dating application makes it efficient and effective for people to interact by utilizing the application features available in the application, one of the applications is Tinder. The Tinder application is one of the most downloaded online dating applications, namely 67 million downloads. Users who download the Tinder application can provide reviews or comments on the application with the features provided on Google Play. Seeing the importance of reviews on an application, it is necessary to carry out sentiment analysis which aims to find out how Indonesian users respond to the online dating application Tinder through reviews on Google Play. The algorithm used to classify sentiment is the Naïve Bayes algorithm with the addition of feature selection with Information Gain. The research methodology used is Knowledge Discovery in Database. The results of research using the Naïve Bayes method get an accuracy of 68%, while using the Naïve Bayes method using the Information Gain feature selection gets an accuracy of 78%. Using the Naïve Bayes method using Information Gain feature selection produces higher accuracy results than without using Information Gain feature selection.

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