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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 80 Documents
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Application of IOT Technology in The Control of Organic Waste Processing Machines with PT100 Sensors and Heaters for Fertilizer Healing and Animal Feeding Dharma, Ricardo; Budi Santoso, Gatot; Mardianto, Is
Intelmatics Vol. 4 No. 2 (2024): Juli-Desember
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/v4i2.20913

Abstract

Waste is one of the major problems in Indonesia that still has to be resolved, because it has many negative impacts on the environment and health. Waste can be divided into two types: organic and inorganic waste. The increase in waste and the limited capacity of the Integrated Waste Disposal Sites (TPST) will cause waste to accumulate. Therefore, organic waste will have a negative impact on the environment if not managed properly, one of the efforts to reduce its impact is to process organic waste into fertilizer and animal food with new innovations in Internet of Thing (IOT) technology that can be used as an improvement in the agricultural sector. The manufacture of waste processing machines into fertilizer and animal food uses PT100 sensors as temperature control sensors from waste, PLC as data processing integration, HMI cloud and HMI haiwell are used as hardware that displays visual temperature data. This research shows that the use of PT100 sensors in waste processing machines has a significant effect on machine performance. In the process of making fertilizer, the PT100 sensor can regulate the temperature accurately, for example, when the temperature is set at 80℃ and exceeds the limit, the heater will turn off and the temperature decreases to 60℃. IoT technology allows real-time monitoring and control of temperature through mobile phones and HMIs, as well as providing Telegram notifications for high or low temperature warnings.
Analysis Of Topic Movement & Conversation Membership On Twitter Using K-Means Clustering Sediyono, Agung; Valentino Hutagalung, Josua; Solihah, Binti
Intelmatics Vol. 4 No. 2 (2024): Juli-Desember
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/v4i2.21002

Abstract

Humans are born to socialize with each other. Social media is one of the media to be able to socialize with each other. Twitter is one of the social media that contains hundreds of millions of tweets where the tweet contains news, products that are currently popular, even about the daily life of users who can change. Social Context Analysis is a tool to analyze social changes and individual needs in society from time to time. In this study, the author uses the K-means Clustering method to group topics on Twitter. In its implementation, this research is expected to be able to see the occurrence of topic movements and membership movements on Twitter topics.
Implementation Enterprise Resource Planning (ERP) ODOO Version 15.0 Manufacturing Module at CV. Razzaq Berkah Mulia Setiawan, Ibnu Fajar; Siswanto, Teddy; Sugiarto, Dedy
Intelmatics Vol. 4 No. 2 (2024): Juli-Desember
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/v4i2.21073

Abstract

In the modern era, digitalization has had a significant impact on various business fields, with technology being the main key in fascilitating company performance. Digitalization of company systems is now an obligation, data integration is essential for analysis that supports company progress. ERP is software that simplifies company operations by integrating various business application modules such as Inventory, Accounting, Sales, Point of Sales, Manufacturing, Contact, Website, and Purchasing. CV Razzaq Berkah Mulia, which has the potential to compete with international furniture companies, has not fully adopted information systems in its management. This lack of digitalization can lead to losses and recording errors that hinder their business performance. An optimized and valid implementation of Odoo ERP is essential to improve the quality and operational efficiency of CV Razzaq Berkah Mulia. This Implementation will go through several phases, namely Discovery and Planning, Design, Development, Testing, Deployment, and Support. At the Discovery and Planning stage, the company needs will be identified and an implementation strategy will be planned. The Design stage will design the system as per requirements, while the Development Stage will involve the creation and configuration of the system. At the testing stage, the system willl be tested to ensure its functionality, and the Deployment stage will involve launching the system into the operational environtment. Finally, the Support stage will provide post-implementation support.  The final result of this development can be accepted and implemented for the implementation of Odoo at CV. Razzaq Berkah Mulia through UTAUT with a satisfaction value of Performance Expectancy 88%, Effort Expectancy 88%, Supporting Facilities 88,4%, Facilitating Conditions 91%, Attitude Towards Technology 89,2%, Behavioral Intention 90,8%.
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.
PERFORMANCE COMPARISON OF TWITTER SENTIMENT ANALYSIS USING FASTTEXT SVM AND TF-IDF SVM: A CASE STUDY ON ELECTRIC MOTORCYCLES Sulaba, Wishnu Abhinaya; Solihah, Binti; Sari, Syandra
Intelmatics Vol. 4 No. 2 (2024): Juli-Desember
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/v4i2.18145

Abstract

Electric motorcycles are trending on Twitter as two-wheeled vehicles different from those using fossil fuels. Electric motorcycles rely on batteries charged using electricity. However, there are many opinions about electric motorcycles on social media, especially Twitter. Yet, tweets and comments on Twitter often contain irrelevant words that can affect sentiment analysis. In this study, sentiment analysis was conducted on 8,000 data from Twitter using FastText and TF-IDF as word embedding techniques, along with Support Vector Machine (SVM) as the classification technique. The aim of this research is to compare the performance of SVM using different feature extraction techniques, namely FastText and TF-IDF. The results of this study are expected to be beneficial for electric vehicle manufacturers and individuals interested in electric vehicles. In this comparison, the performance of TF-IDF and FastText feature extraction in sentiment classification with SVM will be evaluated. SVM performance is assessed based on accuracy, precision, recall, and F1-score for each feature extraction technique used. The test results show an average accuracy above 83%, with the highest values being 86% for accuracy, 79% for precision, 52% for recall, and 58% for F1-score.  
COMPARATIVE SENTIMENT ANALYSIS OF VISITOR REVIEWS FOR WATERBOM BALI TOURIST ATTRACTION ON TRIPADVISOR SOCIAL MEDIA USING RANDOM FOREST AND NAÏVE BAYES CLASSIFICATION Hilmi, Hilmi Abdul Gani; Solihah, Binti; Sari, Syandra
Intelmatics Vol. 4 No. 2 (2024): Juli-Desember
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/v4i1.19278

Abstract

With the advancement of technology, especially the internet, the role of the internet as the primary source of information in global life is becoming increasingly crucial. This is particularly true in the context of searching for information about tourist destinations before visiting them. TripAdvisor is a website designed for searching travel destinations and attractions. On this platform, users can provide reviews and see comments from other travelers regarding various tourist destinations, including Waterbom Bali. To gain insights into visitors' perspectives and enhance services for them, the overwhelming number of reviews can be analyzed for sentiment to understand whether travelers' views tend to be positive, negative, or neutral. In this research, the Random Forest and Naïve Bayes methods are employed to conduct sentiment analysis. Scraping data from Waterbom Bali resulted in a dataset of 5750 entries. Despite data imbalance after labeling positive, negative, and neutral sentiments, class imbalance techniques will be applied. The sentiment analysis method, comparing Random Forest and Naïve Bayes, is implemented using the Word2Vec feature extraction method to evaluate its effectiveness. Experimental results show significant differences between the two methods. In Random Forest, after undersampling, an accuracy of 24% was obtained, while oversampling resulted in an accuracy of 98%. Meanwhile, for Multinomial Naïve Bayes, after undersampling, an accuracy of 36% was achieved, and oversampling yielded an accuracy of 97%.
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.

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