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Dian Anggraini
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INDONESIA
Journal of Software Engineering, Information and Communication Technology
Published by Universitas Pendidikan Indonesia
ISSN : 27741656     EISSN : 27741699     DOI : https://doi.org/10.17509/seict
Core Subject : Science, Education, Engineering,
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering
The Journal of Software Engineering, Information and Communication Technology promotes research in the broad field of science and technology (including such disciplines as Agriculture, Environmental Science, etc.) with particular respect to Indonesia, but not limited to authorship or topical coverage within the region. Contributions are expected from senior researchers, project managers, research administrators and PhD students at advanced stages of their research, representing both public organizations and private industry. Equally, the journal if intended for scholars and students, reseachers working at research organizations and government agencies, and also for enterprises undertaking applied R&D to lead innovations. The editorial contents and elements that comprise the journal include: Theoretical articles Empirical studies Practice-oriented papers Case studies Review of papers, books, and resources. As far as the criteria for evaluating and accepting submissions is concerned, a rigorous review process will be used. Submitted papers will, prior to the formal review, be screened so as to ensure their suitability and adequacy to the journal. In addition, an initial quality control will be performed, so as to ensure matters such as language, style of references and others, comply with the journals style. Focus And Scope Software engineering Information technology Data Science AI/ML Cloud Computing, Big Data and Social Computing Image Processing Applied Informatics Database Technologies and Applications Digital Information Computation and Retrieval Information Security Human Computer Interaction Multimedia and Game Data Mining Ubiquitous Computing Business Intelligence and Knowledge Management Iot Software Engineering Education
Arjuna Subject : Ilmu Komputer (semua kategori) - Perangkat Lunak
Articles 7 Documents
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Search results for , issue "Vol 4, No 2: Desember 2023" : 7 Documents clear
Software Development of Food Combining Guidelines Using Smartphone-Based On Android In Bandung Widianto, Mochammad Haldi
Journal of Software Engineering, Information and Communication Technology (SEICT) Vol 4, No 2: Desember 2023
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (210.513 KB) | DOI: 10.17509/seict.v2i1.34253

Abstract

The number of applications circulating, some researchers do not want to be left behind, one of which is a food-based application that can be used as an Android mobile-based food combination guide. Examples of food applications that are used to overcome the problem of vitamins, minerals and energy needed by the body. Basically, food applications are needed to help citizens by determining the food consolidation menu. Providing information in the form of how much health content and plans will be carried out, this aims to provide information. To get recipe suggestions, clients are initially required to select a photo image from the camera. After the application will send image suggestions to clarify and get the label name of the ingredients, by getting a signal to the system to send the ingredients to the nutritionist to collect the ingredients. Once developed, the framework shows the side effects of labeling and collecting ingredients in the application. Once an ingredient is selected, the system sends the component name to Food2Fork to get the recipe. The recipe will be displayed before being displayed to the system. The test results can be ascertained that the Android application can work well.
Searching for the Fastest Route to Tourist Attractions with the Kruskal Algorithm in the C++ Programming Language Roseandree, Billdan Satriana; Mulyana, Amanda Jayanti; Fuji, Raymico; Pratama, Aldini Hegle; Purnama, Purnama
Journal of Software Engineering, Information and Communication Technology (SEICT) Vol 4, No 2: Desember 2023
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/seict.v4i2.59506

Abstract

In the tourism industry, it is important to find the fastest way to various attractions. In this research, the use of efficient and accurate algorithms facilitates the travel planning process. One algorithm that has proven effective in solving this problem is Kruskal's algorithm. The purpose of this research is to implement Kruskal's algorithm in C++ programming language to find the fastest route between tourist destinations. In this research, the C++ programming language is used to implement the Kruskal algorithm. Information about tourist attractions and distances between tourist destinations are presented in a graph. Kruskal's algorithm is used to find the shortest path using the concept of MST (minimum spanning tree). The result of this research is a C++ program that can use Kruskal's algorithm to find the fastest route between tourist destinations based on the shortest distance. The program leads to a number of tourist destinations that must be visited to get the fastest route. Using Kruskal's algorithm, the program successfully finds the fastest route between tourist destinations, considering the shortest distance. Thus, this research provides an efficient and accurate solution to the problem of determining the fastest route in the tourism industry. The resulting program can be a useful guide for tourists when planning their trips and optimizing time and effort to visit various tourist attractions.
Prediction of Mobile Phone Ratings with SVM Regression Model Ramdhani, Arya Dwi; Budi, Fahri Admana; Dimulya, Rizky
Journal of Software Engineering, Information and Communication Technology (SEICT) Vol 4, No 2: Desember 2023
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/seict.v4i2.64392

Abstract

Mobile is a communication tool that has capabilities such as computers that are easy to carry anywhere with various functions for human life. Mobile phones certainly have quite interesting trends, such as the emergence of models, types, and brands which of course vary. The purpose of this study was to determine the prediction of mobile phone ratings based on various criteria using the SVM method. These criteria include price, camera, internal memory, storage, color and so on. From the SVM model, the regression type gets predictive results, where there are values that are adjusted to the model. Although the accuracy is not good, in the prediction process the difference is not too far, but slightly different. The more you add related features, the the training accuracy will be better.
Comparison of Machine Learning Algorithms in the Role of Hepatitis Patient Disease Classification Fernando, Daud; Huwaidi, Faris; Ananto, Muhammad Hafidz; Pramadya, Sahrial
Journal of Software Engineering, Information and Communication Technology (SEICT) Vol 4, No 2: Desember 2023
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/seict.v4i2.64393

Abstract

Hepatitis is one of the diseases with the highest patient percentage. about a third of the world population are afflicted with hepatitis. In several cases, patients show symptoms while in the other cases, patients show no symptoms. hepatitis is commonly caused by hepatitis A, B, C, D or E virus and yellow fever virus (YFV). hepatitis can be detected through blood test. From the blood sample, we could extract information like Alanine Transferase (ALT), bilirubin, creatine, Alkaline Phosphatase (ALP), Aspartate Aminotransferase (AST) and Gamma Glutamyl Transferase (GGT) levels, the levels of these compound will be able to determine whether the patient is afflicted or not. To raise the information processing effectiveness, machine learning can be applied to help processing the information. Several algorithms like support vector machine (SVM), decision tree, K-Nearest Neighbor (KNN), Random Forest and X-Gradient Boost (XGBoost) can be used to process hepatitis data. This research is aimed to determine which algorithm has the highest accuracy in diagnosing hepatitis.
Geometry and Color Transformation Data Augmentation for YOLOV8 in Beverage Waste Detection Itikap, Sabar Muhamad; Abdurrahman, Muhammad Syahid; Soewono, Eddy Bambang; Gelar, Trisna
Journal of Software Engineering, Information and Communication Technology (SEICT) Vol 4, No 2: Desember 2023
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/seict.v4i2.64400

Abstract

In the bottle sorting process in real world, there are some beverage packaging waste that is deformed. Deformed objects can result in detection errors by an object detection system. Detection errors can also occur in attributes that share similar feature maps. Detection errors can be caused by models that are unable to generalize to the data. Several methods have been devised to prevent such issues, with data augmentation being one of them. To increase the variety of data, data enhancement techniques will be utilized. This research employs a data augmentation technique that concentrates on geometry transformations such as scaling and rotation, as well as color transformations such as hue, saturation, and brightness. Additionally, a combination of geometry and color transformations was conducted, resulting in a total of 39 experimental scenarios. This study demonstrates that data augmentation can affect the model's performance in terms of accuracy and the number of detection results. The combined method of scaling and rotation, which is applied to the original data, reveals the optimal experimental scenario with an accuracy of 88.4%.
The Investigation of Convolution Layer Structure on BERT-C-LSTM for Topic Classification of Indonesian News Headlines Fabillah, Dzakira; Auliarahmi, Rizka; Setiarini, Siti Dwi; Gelar, Trisna
Journal of Software Engineering, Information and Communication Technology (SEICT) Vol 4, No 2: Desember 2023
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/seict.v4i2.63742

Abstract

An efficient and accurate method for classifying news articles based on their topics is essential for various applications, such as personalized news recommendation systems and market research. Manual classification methods are tedious, prompting the use of deep learning techniques in this study to automate the process. The developed model, BERT-C-LSTM, combines BERT, the convolutional layer from CNN, and LSTM, leveraging their individual strengths. BERT excels at transforming text into context-dependent vector representations, The design of the classification model employs a blend of convolutional layers and LSTM, referred to as C-LSTM. The convolutional layer possesses the capability to extract salient elements, including keywords and phrases, from input data. On the other hand, the Long Short-Term Memory (LSTM) model exhibits the ability to comprehend the temporal context present in sequential data. This study aims to investigate the influence of the convolutional layer structure in BERT-C-LSTM on the classification of Indonesian news headline categorized into eight topics. The results indicate that there are no significant differences in accuracy between BERT-C-LSTM model architectures with a single convolutional layer and multiple parallel convolutional layers and the models using various filter sizes. Furthermore, the BERT-C-LSTM model achieves an accuracy that is not much different from the BERT-LSTM and BERT-CNN models, with accuracies reaching 92.6%, 92.1%, and 92.7%, respectively.
Design of Web-Based Incoming and Outgoing Letter Archiving Software for the West Kalimantan Provincial Inspectorate Julianto, Sebri
Journal of Software Engineering, Information and Communication Technology (SEICT) Vol 4, No 2: Desember 2023
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/seict.v4i2.61867

Abstract

The Inspectorate of West Kalimantan Province is a government agency that has the duty and responsibility to realize quality governance. The West Kalimantan Inspectorate Secretariat has a Sub-section for Administration and General Affairs which has task of managing incoming and outgoing mail. Manual recording requires a relatively long time and also creates recurring problems in terms of searching letter data. It is hoped that this filling design can be used as a system recommendation to be applied to the West Kalimantan Provincial Inspectorate in the administration and general section. The system design method in this study uses the system development life cycle (SDLC) method with the waterfall model. Data collection was carried out by observation, interview, and literature study. This research produced an information system to help manage correspondence activities. Forms created are limited to issues in creating views of incoming mail, outgoing mail, login pages, job title pages, home pages and user pages.

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