Engineering, Mathematics and Computer Science Journal (EMACS)
Engineering, MAthematics and Computer Science (EMACS) Journal invites academicians and professionals to write their ideas, concepts, new theories, or science development in the field of Information Systems, Architecture, Civil Engineering, Computer Engineering, Industrial Engineering, Food Technology, Computer Science, Mathematics, and Statistics through this scientific journal.
Articles
174 Documents
<![CDATA[Development of Mobile QR Warehouse Management Apllication Based on Flutter and Firebase ]]>
<![CDATA[Wairooy, Irma Kartika]]>;
<![CDATA[Dillwyn, Ignatius]]>;
<![CDATA[Yonathan, Kevin Putra]]>;
<![CDATA[Lay, Andre]]>
<![CDATA[ Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 6 No. 1 (2024): EMACS ]]>
Publisher : <![CDATA[Bina Nusantara University ]]>
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DOI: 10.21512/emacsjournal.v6i1.10921
<![CDATA[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.]]>
<![CDATA[Design of An Intelligent Tutoring System – Student Model: Predicting Learning Style ]]>
<![CDATA[Hawari, Nubli]]>;
<![CDATA[Oktavia, Tanty]]>
<![CDATA[ Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 6 No. 1 (2024): EMACS ]]>
Publisher : <![CDATA[Bina Nusantara University ]]>
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DOI: 10.21512/emacsjournal.v6i1.10938
<![CDATA[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.]]>
<![CDATA[Comparing CNN Architecture for Indonesian Speciality Cuisine Classification ]]>
<![CDATA[Wulandari, Ajeng]]>
<![CDATA[ Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 6 No. 1 (2024): EMACS ]]>
Publisher : <![CDATA[Bina Nusantara University ]]>
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DOI: 10.21512/emacsjournal.v6i1.11076
<![CDATA[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.]]>
<![CDATA[Calorie Tracking: A Mobile Application for Tracking Eating Patterns and Intake ]]>
<![CDATA[Gayatri, Nyoman Ayu Gita]]>;
<![CDATA[Soegiarto, Juan Xavier]]>;
<![CDATA[Sanjaya, Philips]]>;
<![CDATA[Tanujaya, Vincent]]>;
<![CDATA[Diporedjo, Nicholas]]>;
<![CDATA[Kusnandar, Aaron Medhavi]]>;
<![CDATA[Tjokro, Justin]]>;
<![CDATA[Chandra, Yulyanty]]>
<![CDATA[ Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 6 No. 1 (2024): EMACS ]]>
Publisher : <![CDATA[Bina Nusantara University ]]>
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DOI: 10.21512/emacsjournal.v6i1.11193
<![CDATA[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.]]>
<![CDATA[Use Case Diagram for Enhancing Warehouse Performance at PT. MDA Through the Implementation of 5S, Economic Order Quantity, Safety Stock, and Warehouse Management System ]]>
<![CDATA[Kurniawan, Michael Radius]]>;
<![CDATA[Hadiyanto, Hadiyanto]]>;
<![CDATA[Zulkarnaen, Joe Daniansyah Pahlevi]]>;
<![CDATA[Harito, Christian]]>
<![CDATA[ Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 6 No. 1 (2024): EMACS ]]>
Publisher : <![CDATA[Bina Nusantara University ]]>
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DOI: 10.21512/emacsjournal.v6i1.11204
<![CDATA[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.]]>
<![CDATA[Antiviral Medication Prediction Using A Deep Learning Model of Drug-Target Interaction for The Coronavirus SARS-COV ]]>
<![CDATA[Fredyan, Renaldy]]>
<![CDATA[ Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 6 No. 2 (2024): EMACS ]]>
Publisher : <![CDATA[Bina Nusantara University ]]>
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DOI: 10.21512/emacsjournal.v6i2.11290
<![CDATA[Graph convolutional neural networks (GCNs) have shown promising performance in modeling graph data, particularly for small-scale molecules. Message-passing neural networks (MPNNs) are an important form of GCN variant. They excel at gathering and integrating particular information about molecules via several repetitions of message transmission. This capability has resulted in major advances in molecular modeling and property prediction. By combining the self-attention mechanism with MPNNs, there is potential to improve molecular representation while using Transformers' proven efficacy in other artificial intelligence disciplines. This research introduces a transformer-based message-passing neural network (T-MPNN) that is intended to improve the process of embedding molecular representations for property prediction. Our technique incorporates attention processes into MPNNs' message-passing and readout phases, resulting in molecular representations that are seamlessly integrated. The experimental results from three datasets show that T-MPNN outperforms or equals cutting-edge baseline models in tasks involving quantitative structure-property connections. By studying case studies of SARS-COV growth inhibitors, we demonstrate our model's ability to graphically depict attention at the atomic level. This enables us to pinpoint individual chemical atoms or functional groups linked with desirable biological properties. The model we propose improves the interpretability of classic MPNNs and is a useful tool for investigating the impact of self-attention on chemical substructures and functional groups in molecular representation learning. This leads to a better understanding of medication modes of action.]]>
<![CDATA[Supply Chain Sustainability Measurement in Telecommunications Industry in Indonesia ]]>
<![CDATA[Nabil, Abdullah]]>;
<![CDATA[Asrol, Muhammad]]>
<![CDATA[ Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 6 No. 2 (2024): EMACS ]]>
Publisher : <![CDATA[Bina Nusantara University ]]>
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DOI: 10.21512/emacsjournal.v6i2.11307
<![CDATA[In the fiercely competitive telecommunications industry of Indonesia, the significance of innovation and perpetual improvement cannot be underestimated. It is imperative for businesses to explore the potential of sustainable supply chain management, as it allows for the integration of environmental, economic, and social dimensions. By implementing a comprehensive and thorough approach, this study offers a theoretical framework for measuring sustainable supply chain performance. Through qualitative and quantitative methods, you'll be able to identify the attributes that greatly impact the success of your sustainable supply chain management. On this research Analytic Hierarchy Process (AHP) utilize to define Consistency Ratio (CR) and weight between dimension using SuperDecisions software. Then, Multidimensional Scaling (MDS) is utilized to measure performance of supply chain sustainability. At the same time, a stress value also measured to indicate the sustainability measurement of one specific dimension is sufficient in accordance with existing condition or not. Next, to better indicate which attributes are most influential on improving dimensional sustainability performance, it is essential to conduct a sensitivity analysis and Montecarlo analysis for each attribute. In the end, this research successfully determined which attributes that influence sustainable supply chain management and measure the value of supply chain sustainability in the telecommunications industry in Indonesia.]]>
<![CDATA[Comparison HOR and AHP Methods in Risk Mitigation of Line Pipe Procurement ]]>
<![CDATA[Kholid, Muhammad Arwan]]>;
<![CDATA[Harito, Christian]]>
<![CDATA[ Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 6 No. 2 (2024): EMACS ]]>
Publisher : <![CDATA[Bina Nusantara University ]]>
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DOI: 10.21512/emacsjournal.v6i2.11320
<![CDATA[OCTG (Oil Country Tubular Goods) is a type of pipe used for oil and gas exploration activities. To meet the demands for the fulfillment of Line Pipe material needs at PT Pertamina EP. The results of the analysis and identification of risk factors from 3 Subjet Matter Expert (SME) in Line Pipe material procurement activities. From 13 Process Activities, 16 Risk Events (Ei) and 35 Risk Agents (Aj) were obtained. In House of Risk (HOR) 1, the results of the calculation of the Aggregate Risk Potentials (ARPj) value of 35 Risk Agents (Aj), the highest Aggregate Risk Potentials (ARPj) with a value of 810. In House of Risk (HOR) 2, the results of the calculation of the Effectiveness to Difficulty ratio (ETDk) value of 4 Preventive Action (PAk), the highest Effectiveness to Difficulty ratio (ETDk) value with a value of 4860. In the Analytic Hierarchy Process (AHP), the results of the calculation of the Consistency Ratio value of 5 Criteria Weight the highest Criteria value with a percentage of 45.4% and the Consistency Ratio of 4 Alternatives the highest Alternative value with a percentage value of 44.06%. The best alternative solution in the selection of mitigation strategies for contract type selection is “TFC (Technical Framework Contract)†with the highest percentage and value. The TFC (Technical Framework Contract) contract type is in accordance with the PTK-007 Revision 5 Chapter IV Contract guidelines.]]>
<![CDATA[Prediction of Sudden Cardiac Death with Feature Selection Using Particle Swarm Optimization ]]>
<![CDATA[David, David]]>;
<![CDATA[Muhamad Isa, Sani]]>
<![CDATA[ Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 6 No. 2 (2024): EMACS ]]>
Publisher : <![CDATA[Bina Nusantara University ]]>
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DOI: 10.21512/emacsjournal.v6i2.11326
<![CDATA[The heart, a vital organ responsible for pumping oxygenated blood through blood vessels, is susceptible to disturbances in heart rate that can have adverse effects. According to data from the World Health Organization (WHO) since 2000, this disease has experienced the most significant increase in fatalities, rising from over 2 million to 8.9 million deaths. The prediction of Sudden Cardiac Death (SCD) continues to gain attention as a promising approach to saving millions of lives threatened by the occurrence of the disease. In this study, we propose the utilization of Particle Swarm Optimization (PSO) as a feature selection method to train the Support Vector Machine (SVM) and Logistic Regression. By employing the proposed algorithm, SCD can be predicted up to 30 minutes before the onset with an accuracy of 92.5%, by using PSO and SVM. Features are extracted from Heart Rate Variability (HRV) analysis and Discrete Wavelet Transform (DWT) obtained from ECG records of MIT-BIH normal sinus rhythm database & MIT-BIH Sudden Cardiac Death Holter database dataset. This paper also compares feature selection algorithm of PSO and Analysis of Variance (ANOVA) and found that PSO is better in accuracy, recall, and F1-score.]]>
<![CDATA[Relationship Between Temperature and Humidity on Rainfall: A Multiple Linear Regression Analysis ]]>
<![CDATA[Purnama, Mohammad Dian]]>;
<![CDATA[Mustafidah, Mutia Eva]]>
<![CDATA[ Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 6 No. 2 (2024): EMACS ]]>
Publisher : <![CDATA[Bina Nusantara University ]]>
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DOI: 10.21512/emacsjournal.v6i2.11466
<![CDATA[Indonesia is one of the tropical countries in the world that has two seasons, the dry season and the rainy season. One of the biggest challenges in tropical countries is flooding caused by heavy rainfall. Not only does it cause flooding, rainfall also affects several sectors especially agriculture. Areas that have a lot of rain-fed agricultural land, especially rice fields, depend on rainfall because it determines crop yields. This study uses data from 12 sub-districts in Mojokerto district where agricultural activities are one of the pillars of the economy in the region. There are various factors associated with rainfall such as temperature and humidity. The data used is the year 2022 using multiple linear regression. Based on the results of the study, both predictor variables have a strong and positive relationship with rainfall with a correlation coefficient of 0.760007. With a significance level of 5% or 0.05, in the partial test, only the humidity variable has a significant effect on the amount of rainfall. While in the simultaneous test, both variables have a significant effect. These factors together have a coefficient of determination of 0.57761 or the contribution of the influence of the two predictor variables of 57.761% while the remaining 42.239% by other variables.]]>
