Engineering, MAthematics and Computer Science Journal (EMACS)

Machine Learning for Predicting Personality using Facebook-Based Posts

Derwin Suhartono — 2024-01-31

Social media contributes a lot to human life. People can share their thoughts through text, photos, and voice through social media. Information from social media can be useful, including in personality research. Personality can generally be known through personality tests. In this research, personality prediction is formed to determine personality through Facebook posts without using a personality test. We create a model based on big five personality traits using 5 machine learning algorithms: Support Vector Machine (SVM), Multinomial Naive Bayes, Decision Tree, K-Nearest Neighbor, and Logistic Regression. Data augmentation was also used for balancing the dataset value and trained using stratified 10-fold cross-validation. This research yields the highest f1 score on Openness using Multinomial Naive Bayes algorithm of 82.31% and the highest average is 68.62%. So the five supervised Machine Learning algorithms used in this research produced Multinomial Naive Bayes as the best algorithm to predict personality based on big five personality traits from user postings on Facebook.

An Experiment to Prevent Malicious Actors from Compromising Private Digital Assets Over a Public Network

Feliks Hartanto — 2024-01-31

In the current millennium, human society has immensely improved its ability to obtain and distribute information. This change on the other hand, has caused the majority of daily routines to actively involve the usage of computers and mobile devices, which in turn has made people rely heavily on the availability of internet access. This fact was taken advantage of, causing a massive increase in public networks by people or businesses to draw in customers or just as simple public service. This increase gives both ease and risks which this paper will address, specifically on the security measures in network devices that are nearby, and the solution proposed to provide complementary insight on securing the technologies. The authors of this paper supply the main point of the research through experimental efforts i.e., by testing the solution in a real-life scenario. The solution itself involves the configuration of a Raspberry Pi into a VPN server and rerouting all traffic into the Raspberry server so that it will be encrypted and safe from the dangers that will be mentioned in later parts of this paper. The result of the experiment shows that the proposed solution can successfully encrypt the targeted packet so it can’t be read by malicious attackers. Although the solution works it can’t be simply applied to every public network due to internet connection protocols and its inconvenience. Future research will involve the improvement or rework of the solution until the issues mentioned above are solved.

Optimization of Fraud Detection Model with Hybrid Machine Learning and Graph Database

Aan Albone — 2024-01-31

Machine learning and the graph database work well together. By concentrating on the relationships between fraudsters or fraud cases, graph databases can provide an additional layer of security, while machine learning uses statistics and data analytical tools to categorize information and identify patterns within data. In doing so, it can transcend rigid rules and scale human insights into algorithms. When combined with a graph, machine learning alone can increase the accuracy of fraud signals to 90% or higher. On its own, it can reach 70–80%. Graphs also improve machine learning's explainability.

Goods Storage Rental Application (YourStorage) Using the React Native Framework

Farhan Rifanto Hardjanto — 2024-01-31

The increase in online business today with quite high transactions means that business actors who sell their merchandise through marketplaces need temporary storage space that does not have a place to store goods. Based on this, the aim of this research is to build a goods storage rental application to make it easier for business actors to rent storage space online with flexible time periods. This type of research is quantitative research where the system development method uses SCRUM and the software architecture used is service-oriented (Microservice). The results of this research are in the form of an Android-based mobile application and as many as 75% of business respondents feel that the “YourStorage” application can help, 68.75% (22) of respondents stated that the application could help in controlling where goods are stored and 71.87% (23) of respondents stated that the application could make it easier to store goods according to required size

Two-Layer Shallow Water Equations with Momentum Conservative Scheme for Wave Propagation Simulation

Maria Artanta Ginting — 2024-01-31

In this paper, we discuss the implementation of momentum conservative scheme to shallow water equations (SWE). In shallow water model, the hydrodynamic pressure of the water is neglected. Here, the numerical calculation of mass and momentum conservation was applied on a staggered grid domain. The vertical interval was divided into two parts which made the computation quite efficient and accurate. Our focus is on the performance of the numerical scheme in simulating wave propagation and run-up phenomena, where the main challenge is to calculate the wave speed accurately and to count the non-linear term of the model. Here we also considered the wet and dry conditions of the topography. Three benchmark tests were picked out to validate the numerical scheme. A simulation of standing wave was carried out; the results were compared to the linear analytical solution and show a good fit. In addition, a simulation of harmonic wave propagation on a sloping beach was conducted, and the results closely align with the expected values from exact solution. Finally, we carried out a simulation of solitary wave with a sloping topography; and the results were compared to laboratory data. A good agreement was observed between the simulation results and experimental measurements.

Digital Game as A Media to Increase Cognitive Intelligence of 13-18 Years Old Teenagers

Ivan Sebastian Edbert — 2024-01-31

Nowadays, Cognitive Intelligence plays an essential role especially on making decisions. The growth of digital media makes public thinks that video games are addictive. They think that video games are addictive and damaging. Games are design to refresh, challenge and help people to train their problem solving. In this research, the researcher explored the cognitive development of teenagers aged 13-18 with a puzzle-based digital game. Participants were 15 students studying in junior and senior high school. Participants were given three tests: pre-test and post-test by IQ test and a Game Engagement Questionnaire (GEQ) to explore the game's engagement from the participants' perspective. The average of Pre-Test is 113.2, while the Post-Test is 118.33. This Show that after playing the games it increases the IQ of the students. The researcher also discovered that many factors could influence the outcome of participant IQ. The GEQ shows that the participants agreed that some of the puzzle-based game might be a good or bad influence on them.

Keywords: Cognitive Intelligence; Digital Games, Formal Operational Game-based Learning, Jean Piaget's Theory

Development of Mobile QR Warehouse Management Apllication Based on Flutter and Firebase

Irma Kartika Wairooy — 2024-01-31

Since the Covid-19 pandemic took place, the number of MSMEs (Micro, Small and Medium Enterprises) has increased. Running a good business requires good product management to minimize losses that occur due to errors in product management. This research aims to increase the efficiency of the product management process with the QR Scanner feature which can make things easier for MSME owners. This research was designed through various needs gathering steps which included literature studies, surveys and competitor analysis. The application design method used in the development of the QRHouse application will be based on the Object Oriented Programming (OOP) method which has many advantages ranging from its object-oriented nature so that the data structure will be more organized, and also has a variety of concepts that can be used for application development. Application development will also be supported through several UML diagrams consisting of use case diagram, use case description, activity diagram, class diagram, and sequence diagram. Each diagram will have a function that will make the application development process more organised and minimise the occurrence of errors and bugs during application development. The results of the research are an Android and iOS based mobile application called QRHouse. The testing methods used include User Acceptance Test, User Interface Survey, UI Evaluation with 8 Golden Rules, UX Evaluation with 5 Measurable Human Factors. The results of the research were achieved when the application developed succeeded in increasing efficiency in product stock management.

Design of An Intelligent Tutoring System – Student Model: Predicting Learning Style

Nubli Hawari — 2024-01-31

Education is very important for everyone, not only for acquiring knowledge but also for improving quality of life and well-being. An Intelligent Tutoring System (ITS) is a computer system that can provide personalized and adaptive learning assistance and support to students. This system is designed to offer effective guidance to students based on their individual abilities and learning styles. ITS utilizes artificial intelligence (AI) technology to understand students' abilities and provide guidance tailored to their needs. Recently, there have been methods to predict learning styles, such as through questionnaires on the EducationPlanner website, but these determinations are often too general. This study aimed to predict the learning styles used by specific students for specific subjects. Researchers conducted this study at XYZ University to determine the learning styles of certain students or groups. With this information, instructional materials and methods can be uniquely designed to cater to the needs of these groups. Based on the evaluation results, the study found that the Logistic Regression model was the best, with a precision of 0.5653 and a hamming loss value of 0.3468. This research demonstrates that information from six selected subjects (English, Religion, Civics, Arts, Physics, and Geography) can be used to determine students' learning styles.

Comparing CNN Architecture for Indonesian Speciality Cuisine Classification

Ajeng Wulandari — 2024-01-31

Indonesia's diverse and flavorful cuisine is a hidden gem, reflecting the nation's rich history and cultural tapestry. However, many of these culinary treasures remain undiscovered by a wider audience despite the popularity of beef rendang. This study represents a fascinating blend of technology and gastronomy, using smart computers to unravel the secrets of Indonesian flavors. This research employs one of the most popular neural networks methods called Convolutional Neural Network (CNN) to shine a light on many citizens' favorite regional specialty cuisine which is Padang cuisine from West Sumatra, Indonesia. Gathering a collection of 993 images from 9 various dishes, the machine is trained to automatically recognize these unique culinary delights. Among several different Convolutional Neural Network models trained and tested, DenseNet-201 emerged as the top performer, showcasing remarkable accuracy, precision, recall and f1-score higher than 0.90. By harnessing the power of advanced neural networks, we not only gain insights into the intricacies of the region's culinary traditions but also pave the way for a deeper appreciation and understanding of the cultural significance embedded in every bite. Beyond this research technological achievements, it also emphasizes the importance of preserving and promoting Indonesia's diverse culinary heritage and rich tapestry of global food heritage.

Calorie Tracking: A Mobile Application for Tracking Eating Patterns and Intake

Nyoman Ayu Gita Gayatri — 2024-01-31

A balanced regular calorie intake along with a good eating rules is an important factor to fullfill a healthy lifestyle and diet. Both are the main keys to preventing non-communicable diseases (NCDs) which are the largest contributors to world deaths. The effects produced through dietary regulation and calorie intake ideally will affect to the long term, so that consistency and adequate supporting media are needed. Judging from the time scale, action is needed since in, Early action is needed, especially for students who are in the transition period to maturity and independence. Technological developments in the digital era can be used to produce problem solutions ranging from fundamental aspects. Students themselves are familiar with the concept of the calorie tracker application (Craker) even though the majority have never used it. The purpose of this paper is to design the Craker application as a form of solution to regulate diet and calorie intake by applying the theory of human and computer interaction. The result of making this application is to monitor the number of calories consumed by knowing the number of calories in and out so that it is balanced according to the recommendations given based on the user’s profile, for the calorie tracker application we can divide it into three types of calorie tracker applications: web, mobile, and physical.

Use Case Diagram for Enhancing Warehouse Performance at PT. MDA Through the Implementation of 5S, Economic Order Quantity, Safety Stock, and Warehouse Management System

Michael Radius Kurniawan — 2024-01-31

An industrial water pump importing company relies on a network of distribution warehouses to efficiently manage the storage and delivery of its products to clients. This paper delves into the operational intricacies of the company, with a primary focus on sustaining a superior level of service to meet customer demands, all while attempting to minimize costs and achieve optimal inventory control. The central aspects explored in this research encompass the meticulous determination of the number of pipes needed and the optimal ordering times. To address this, the Probabilistic Economic Order Quantity (EOQ) method is used and supported by 5S concept, recognized for its ability to provide reasonably accurate estimates crucial for pivotal decision-making in inventory management. The utilization of the Probabilistic EOQ method in this context reflects the company's commitment to adopting sophisticated and proven methodologies to enhance decision-making accuracy and the warehouse area is more suitable by the 5S implementation principles. The research outcomes not only assist in refining the determination of Safety Stock levels but also contribute valuable insights into the precise quantities of goods that should be ordered. With an estimated demand for 196 units of carbon 6" in the following year, a safety stock of 13 units is required, while for carbon 4" with an estimated demand of 119 units, a safety stock of 8 units is required. These upcoming insights could encompass innovative strategies, technological implementations, or advances in supply chain optimization.

Editorial Page and Table of Content

Alexander Agung Santoso Gunawan — 2024-01-31