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Intelmatics
Published by Universitas Trisakti
ISSN : -     EISSN : 27758850     DOI : https://doi.org/10.25105/itm
Core Subject : Science,
Computer Science & IT
The IntelMatics Journal is a scientific journal published by the department of informatics engineering at Trisakti University. The purpose and objective of the publication of the IntelMatics journal are as a means of dissemination of international standard science in the field of software engineering, information security, and business analysis in the scope of data intelligence and visualization. Journal will be published every sixth month
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 8 Documents
 1 
Search results for , issue "Vol. 5 No. 1 (2025): January-June" : 8 Documents clear
Implementation of Odoo Erp At Petrodollar Coffeeatery & Roastery Aritonang, Bagus Aditya; Is Mardianto; Teddy Siswanto
Intelmatics Vol. 5 No. 1 (2025): January-June
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/v5i1.17614

Abstract

In carrying out business processes in Petro Dollar Coffeeatery & Roastery, of course, there are various problems such as in the recording, data collection, and warehousing sections related to efficiency matters. Currently, most of the process is still done manually using just conventional recording on paper, which results in work requiring more time and manpower. In addition, data and information owned by a department cannot automatically be accessed by other departments that are actually related to their business processes and need the data. By implementing ERP software such as Odoo 12.0, you can overcome existing problems because recording and data collection is done automatically and decisions can be made quickly and accurately. By implementing this system, it is expected to increase efficiency and effectiveness of performance and minimize errors in work.  
Analisis Sentimen dan Pemodelan Topik Ulasan PengunjungObjek Wisata Pulau Bali pada Situs Tripadvisor MenggunakanMetode Lexicon-Based dan Latent Dirichlet Allocation (LDA) Aulia, Muhammad Azka; Solihah, Binti; Zuhdi, Ahmad
Intelmatics Vol. 5 No. 1 (2025): January-June
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/v5i1.17619

Abstract

One sought-after type of information by internet users is related to tourist destinations. Hence, the need for information retrieval about a particular tourist spot they plan to visit. This study aims to analyze sentiments and identify the topics in the visitor reviews of Bali Island tourist attractions on TripAdvisor using Lexicon-based and Latent Dirichlet Allocation (LDA) methods. The data used for analysis consists of reviews from various tourist destinations on the island of Bali. For sentiment analysis, the author employs a Lexicon-based approach, focusing on both positive and negative sentiments. To identify the topics in the reviews, the author employs the LDA method to uncover the most frequently discussed topics. From 15,827 dataset, It is found that 87,6% of the responses are positive, 7.9% are negative, and the remaining 4.4% are neutral. As for the topic modeling results, the study identifies four main topics with the best coherence values based on the validation of topics with topic coherence. These four topics are: the first topic discusses experiences in Safari or Safari Park in Bali, the second topic talks about experiences in tourism in Kintamani, Bali, the third topic focuses on experiences in tourism in Nusa Penida, Bali, and the last topic discusses experiences in Scuba Diving activities
Web-Based Personnel Information System Development At Trisakti Pharmacy Fariz, Muhammad; Syaifudin; Salim, Agus
Intelmatics Vol. 5 No. 1 (2025): January-June
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/v5i1.17643

Abstract

In this day and age, technological developments are developing rapidly, in making it easier for workers to do many things. One of them is in the management of the staffing system which is very much needed for the Pharmacy business sector which still uses the system manually in recording staffing at the pharmacy, so the author aims to develop web-based staffing information system website at the Trisakti pharmacy, the author uses the waterfall method as an analysis method and for system design the author uses the System Development Life Cycle (SDLC). As well as the method for making the application using tools such as Sublime Text, MySQL, XAMPP as a database with the PHP and HTML programming languages. The development of the staffing system in this system aims to provide convenience for the Trisakti Pharmacy in managing attendance data, applying for leave, staffing, employee salaries and printing staffing reports and evaluating employee performance.
Sentiment Analysis And Topic Modelling Of Candidate News In The 2024 General Election On Twitter Social Media Using Latent Dirichlet Allocation (LDA) Method Ramadhan, Syahrul; Siswanto, Teddy; Sari, Syandra
Intelmatics Vol. 5 No. 1 (2025): January-June
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/v5i1.21058

Abstract

The use of Twitter as a platform to express public opinion regarding fuel subsidies in Indonesia. Through sentiment analysis using Support Vector Machine method and word-based lexicon, this study reveals that the majority of people are in favour of fuel price increase or subsidy policy change. The sentiment data obtained from this research, which includes positive, neutral and negative sentiments, provides a clear picture of the public's views on the issue. SVM classification method and validation with K-Fold Cross Validation were used to ensure the accuracy of sentiment analysis results obtained from Twitter data. This research is also expected to help society to gauge public opinion on news and candidates in elections. It helps understand how people respond to certain political issues and candidates and the results of sentiment analysis and topic modelling can provide a better understanding of the key issues that matter to voters. This can help candidates and political parties to craft more effective campaign messages and can also be used to detect hoaxes or false information that may spread on social media during elections. This is important for maintaining the integrity of the election.
Development of a Web-Based Tourist Bus Rental Application at PO Tali Jaya Firmansyah, Aldy; Siswanto, Teddy; Santoso, Gatot Budi
Intelmatics Vol. 5 No. 1 (2025): January-June
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/v5i1.21096

Abstract

Advancements in information and communication technology have revolutionized the transportation sector, including bus services provided by PO Tali Jaya in Cilegon, Banten. The main challenge faced is efficiently managing bus rentals, organizing customer data, managing rental reports, and improving service levels. This study proposes the use of a web-based bus rental application to enhance efficiency and service. Through interviews with customers and management, this system is designed to streamline the bus booking process and provide better operational access. The research references transportation management theory and web system development to meet industry standards. By utilizing the waterfall methodology with stages such as requirement system, analysis, design, coding, testing, and maintenance, a comprehensive and organized system is created. The final result is a web-based bus rental application with comprehensive features such as a calendar schedule for each bus, digitalized rental data archiving, and well-structured rental financial reports. It is expected that implementing this system will improve operational efficiency, simplify rental transaction data management, provide better services, and serve as a model for other transportation companies.
Brain Tumor Detection System Based on Convolutional Neural Network Febrianto, Nanang Dwi; Mardianto, Is; Rochman, Abdul; Najih, Muhammad
Intelmatics Vol. 5 No. 1 (2025): January-June
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/v5i1.22135

Abstract

Early detection of brain tumours is essential to improve the effectiveness of treatment. This study develops a Convolutional Neural Network (CNN) model to detect brain tumours from MRI images. Using a dataset of 4410 images, the model was trained and tested with several CNN architectures, such as EfficientNetB0, InceptionNetV3, ResNet, MobileNet, VGG16, Model 1. Results showed that the best model achieved 97.8% accuracy, thus being able to predict brain tumours with a high degree of reliability. These findings support the application of CNNs in medical detection systems to assist doctors in faster and more accurate diagnosis.
Redesigning the UI/UX of a Mobile-Based Employee Presence Application at PT. Menara Indonesia Using the Design Thinking Method Putri, Nabilah; Syaifuddin; Pratiwi, Dian
Intelmatics Vol. 5 No. 1 (2025): January-June
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/v5i1.22420

Abstract

A mobile-based presence application ensures accurate and efficient presence tracking. However, poor UI/UX can hinder productivity and user comfort. This study redesigns the UI/UX of PT. Menara Indonesia’s employee presence application using the Design Thinking method, which includes empathize, define, ideate, prototype, and test stages.The redesigned prototype was evaluated using the System Usability Scale (SUS), scoring 90 for administration and 80 for employees, indicating improved usability. The new design enhances comfort, efficiency, and ease of use, making the application more user-friendly. This study serves as a reference for future development in optimizing presence applications to better meet user needs.
The Opportunity of Ai Technology to Increase The Value Chain of Oil Palm Plantation Sediyono, Agung; Solihah, Binti
Intelmatics Vol. 5 No. 1 (2025): January-June
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/v5i1.22477

Abstract

Indonesia produced 58,4% of worldwide oil palm production, and the contribution of the plantation sub-sector in 2022 is 3,76% of PDB and 30,32% of the Agriculture, Forestry, and Fishery sectors. However, oil palm production in Indonesia is lack of productivity and efficiency compared to other countries, especially Malaysia.  Therefore, this paper tries to explore the opportunities of AI technology to increase the value chain of the oil palm plantation, especially in productivity and efficiency. The scope of exploration started from oil palm seeding, nursery,  planting,  and harvesting. Based on the oil palm plantation value chain review and the previous research works in AI implementation on value chain respectively, it can be concluded that AI technology has been explored to be implemented in oil palm plantations intensively. However, there is still enough room for improvement especially in accuracy rate and adoption feasibility for smallholder planters. Moreover, IoT and drone technology have a big potential to be adopted because the plantation is mostly hard-to-reach areas by humans, for instance high oil palm bunch, long distance journey for inspection and maintenance, wild animal threat, etc.  

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