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All Journal CommIT (Communication & Information Technology) ComTech: Computer, Mathematics and Engineering Applications Engineering, Mathematics and Computer Science Journal (EMACS) International Journal of Computer Science and Humanitarian AI
Alexander Agung Santoso Gunawan
Bina Nusantara University
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics

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Face Recognition Performance in Facing Pose Variation Alexander Agung Santoso Gunawan; Reza A Prasetyo
CommIT (Communication and Information Technology) Journal Vol. 11 No. 1 (2017): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v11i1.1847

Abstract

There are many real world applications of face recognition which require good performance in uncontrolled environments such as social networking, and environment surveillance. However, many researches of face recognition are done in controlled situations. Compared to the controlled environments, face recognition in uncontrolled environments comprise more variation, for example in the pose, light intensity, and expression. Therefore, face recognition in uncontrolled conditions is more challenging than in controlled settings. In thisresearch, we would like to discuss handling pose variations in face recognition. We address the representation issue us ing multi-pose of face detection based on yaw angle movement of the head as extensions of the existing frontal face recognition by using Principal Component Analysis (PCA). Then, the matching issue is solved by using Euclidean distance. This combination is known as Eigenfaces method. The experiment is done with different yaw angles and different threshold values to get the optimal results. The experimental results show that: (i) the more pose variation of face images used as training data is, the better recognition results are, but it also increases the processing time, and (ii) the lower threshold value is, the harder it recognizes a face image, but it also increases the accuracy.
Color Extraction and Edge Detection of Nutrient Deficiencies in Cucumber Leaves Using Artificial Neural Networks Arie Qur'ania; Prihastuti Harsani; Triastinurmiatiningsih Triastinurmiatiningsih; Lili Ayu Wulandhari; Alexander Agung Santoso Gunawan
CommIT (Communication and Information Technology) Journal Vol. 14 No. 1 (2020): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v14i1.5952

Abstract

The research aims to detect the combined deficiency of two nutrients. Those are nitrogen (N) and phosphorus (P), and phosphorus and potassium (K). Here, it is referred to as nutrient deficiencies of N and P and P and K. The researchers use the characteristics of Red, Green, Blue (RGB) color and Sobel edge detection for leaf shape detection and Artificial Neural Networks (ANN) for the identification process to make the application of nutrient differentiation identification in cucumber. The data of plant images consist of 450 training data and 150 testing data. The results of identifying nutrient deficiencies in plants using backpropagation neural networks are carried out in three tests. First, using RGB color extraction and Sobel edge detection, the researchers show 65.36% accuracy. Second, using RGB color extraction, it has 70.25% accuracy. Last, with Sobel edge detection, it has 59.52% accuracy.
Hubungan Deret Bertingkat Berdasarkan Bilangan Eulerian dengan Operator Beda Alexander Agung Santoso Gunawan
ComTech: Computer, Mathematics and Engineering Applications Vol. 2 No. 1 (2011): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v2i1.2727

Abstract

Rank series defined as: is a generalization of the fixed rank series (the sum of powers), in which its closed solution has been found empirically by Jacob Bernoulli in 1731. This paper will explore the relationship between rank series and differential operator. To see this relationship, examples for the case m = 1.2 and α = 1.2. are provided. 
Discovering the Optimal Number of Crime Cluster Using Elbow, Silhouette, Gap Statistics, and NbClust Methods Noviyanti T. M. Sagala; Alexander Agung Santoso Gunawan
ComTech: Computer, Mathematics and Engineering Applications Vol. 13 No. 1 (2022): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v13i1.7270

Abstract

In recent years, crime has been critical to be analyzed and tracked to identify the trends and associations with crime patterns and activities. Generally, the analysis is conducted to discover the area or location where the crime is high or low by using different clustering methods, including k-means clustering. Even though the k-means algorithm is commonly used in clustering techniques because of its simplicity, convergence speed, and high efficiency, finding the optimal number of clusters is difficult. Determining the correct clusters for crime analysis is critical to enhancing current crime resolution rates, avoiding future incidents, spending less time for new officers, and increasing activity quality. To address the problem of estimating the number of clusters in the crime domain without the interference of humans, the research carried out Elbow, Silhouette, Gap Statistics, and NbClust methods on datasets of Major Crime Indicators (MCI) in 2014−2019. Several stages were performed to process the crime datasets: data understanding, data preparation, cluster modelling, and cluster validation. The first two phases were performed in the R Studio environment and the last two stages in Azure Studio. From the experimental result, Elbow, Silhouette, and NbClust methods suggest a similar number of optimum clusters that is two. After validating the result using the average Silhouette method, the research considers two clusters as the best clusters for the dataset. The visualization result of Silhouette method displays the value of 0,73. Then, the observation of the data is well-grouped. It is placed in the correct group.
Semantic Segmentation for Aerial Images: A Literature Review Yongki Christian Sanjaya; Alexander Agung Santoso Gunawan; Edy Irwansyah
Engineering, MAthematics and Computer Science (EMACS) Journal Vol. 2 No. 3 (2020): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v2i3.6737

Abstract

Semantic image segmentation is one of the fundamental applications of computer vision which can also be called pixel-level classification. Semantic image segmentation is the process of understanding the role of each pixel in an image. Over time, the model for completing Semantic Image Segmentation has developed very rapidly. Due to this rapid growth, many models related to Semantic Image Segmentation have been produced and have also been used or applied in many domains such as medical areas and intelligent transportation. Therefore, our motivation in making this paper is to contribute to the world of research by conducting a review of Semantic Image Segmentation which aims to provide a big picture related to the latest developments related to Semantic Image Segmentation. In addition, we also provide the results of performance measurements on each of the Semantic Image Segmentation methods that we discussed using the Intersectionover-Union (IoU) method. After that, we provide a comparison for each semantic image segmentation model that we discuss using the results of the IoU and then provide conclusions related to a model that has good performance. We hope this review paper can facilitate researchers in understanding the development of Semantic Image Segmentation in a shorter time, simplify understanding of the latest advancements in Semantic Image Segmentation, and can also be used as a reference for developing new Semantic Image Segmentation models in the future
Damage Classification on Bridges using Backpropagation Neural Network Victoria Ivy Tansil; Novita Hanafiah; Alexander Agung Santoso Gunawan; Dewi Suryani
Engineering, MAthematics and Computer Science (EMACS) Journal Vol. 3 No. 2 (2021): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v3i2.7406

Abstract

Bridge structures can be damaged due to various factors such as pressure, vibration, temperature, etc. This study aims to detect damaged on bridges early so that accidents that can occur due to the damaged-on bridge can be avoided. The research method is divided into designing a model, building the model, and evaluating the model. The result of this research is a program that can classify healthy or damaged bridges using vibration data of tested points on bridges.
User Experience Analysis of Duolingo Using User Experience Questionnaire Anderies Anderies; Cindy Agustina; Tania Lipiena; Ayunda Raaziqi; Alexander Agung Santoso Gunawan
Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 5 No. 3 (2023): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v5i3.9227

Abstract

The internet is one of the vital means for everyone to get various information easily and exact like they’re looking for. The use of internet-based learning that is applied in modern times is very influential in the field of education compared to the past, because it can develop language skills in a country, besides that increasingly sophisticated technology can help students learn in a structured manner. One of the impacts we can see or feel is on the learning process. With the internet, it is so much easier either for the students or the teachers. One of the well-known applications in the world is Duolingo. Duolingo is one of many applications that give so much influence to language learning applications. More than 300 million people already use Duolingo for their learning. The purpose of this experiment is to analyze the User Experience of the Duolingo application. The experimental method was applied using surveys distributed via social media. There are 103 Duolingo users who were willing to take the surveys and answer all of the questions given. The result of the survey showed Novelty’s scale has the lowest mean, and Perspicuity’s scale has the highest. That means some of Duolingo’s users found that the application is less interesting. Hence, that could affect the effectiveness of the application.
A Systematic Literature Review: Cyber Attack: Phishing Environments, Techniques, and Detection Mechanism Cindy Natasya; Irvin Irvin; Alexander Agung Santoso Gunawan
International Journal of Computer Science and Humanitarian AI Vol. 1 No. 1 (2024): IJCSHAI
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/ijcshai.v1i1.12155

Abstract

In this digital era, phishing has attacked many platforms such as email, website, message, link form. Phishing is an act of creating a website that is exactly like the original website that is used to take someone's personal data. Phishing causes loss of customer confidence to use any application or website. Most of the victims of phishing are people who do not understand phishing or an organization. This kind of cyber-attacks consist of various types and countermeasures that need to be considered for the public user to prevent phishing based on phishing techniques, educate individuals about these attacks, and encourage the use of phishing prevention techniques. This paper consists of types of phishing and awareness to wary of phishing to overcome them. Therefore, the goal of this study is to identify the most typical environments for phishing attacks in order to ascertain the most popular media and technique. The authors of this study plan to conduct a Systematic Literature Review (SLR) of studies that have been done on the subject that was just described. The authors come to the overall conclusion that a website is the ideal option for phishing attacks using social engineering techniques. Additionally, the authors offer numerous suggestions for preventing phishing with various techniques. However, the most effective defense against phishing attacks is identification of phishing attempts through education and training.
Systematic Literature Review of The Use of Music Information Retrieval in Music Genre Classification M. Aqila Budyputra; Achmad Reyfanza; Alexander Agung Santoso Gunawan; Muhammad Edo Syahputra
International Journal of Computer Science and Humanitarian AI Vol. 2 No. 1 (2025): IJCSHAI
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/ijcshai.v2i1.13019

Abstract

Emphasizing deep learning models such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), this article explores the application of Music Information Retrieval (MIR) techniques in music genre categorization. These algorithms outperform traditional methods in capturing complex audio patterns, showcasing their potential in advancing music classification tasks. Accurate genre classification critically depends on key features such as spectral, temporal, and timbral characteristics, which play a pivotal role in distinguishing musical styles. However, the performance of these models is heavily influenced by the quality and diversity of the training datasets. Additionally, challenges like model interpretability and reliance on large datasets are addressed. This research utilized a Systematic Literature Review (SLR) to investigate the capabilities of advanced MIR techniques in enhancing music categorization systems, particularly for educational applications and personalized music recommendations. The findings reveal that analyzing the importance of spectral, temporal, and timbral features—key components of MIR—can significantly boost the accuracy and reliability of music genre classification.
Developing Intelligent GeoDashboard Platform for the Downstream of Nickel, Bauxite, Cobalt, and Silica: Systematic Literature Review Andrea Sutanto; Raditya Tamam; Alexander Agung Santoso Gunawan
International Journal of Computer Science and Humanitarian AI Vol. 2 No. 2 (2025): IJCSHAI
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/ijcshai.v2i2.14415

Abstract

Indonesia possesses abundant natural resources, including nickel, bauxite, cobalt, and silica, which are essential for industries such as battery production, construction, and green technology. To maximize their economic value, the Indonesian government has implemented downstream policies that require domestic processing before export. Effective resource management is crucial for the success of these policies and the national economy. This study conducts a systematic literature review to examine how downstream policies are implemented in different countries (RQ1), analyze cases of downstream disputes and their solutions (RQ2), and explore the impact of technology and Global Value Chains (GVCs) on these policies (RQ3). A structured methodology is used to collect and analyze relevant literature, highlighting best practices and key challenges. Findings show that countries with strong regulations and technological innovation achieve better downstream outcomes. Past disputes reveal the need for strategic policymaking and technological adaptation to avoid risks. In this context, the PetaHilirisasi platform offers a smart solution by integrating geospatial technology and artificial intelligence to monitor and manage mineral resources efficiently. This platform helps optimize downstream processes, improve operational efficiency, and reduce environmental impact. PetaHilirisasi demonstrates the potential of digital solutions in strengthening Indonesia’s downstream sector. By leveraging technology, Indonesia can enhance the value of its natural resources while promoting sustainable development in the mineral industry,
Co-Authors Achmad Reyfanza Anderies Anderies Andrea Sutanto Arie Qur’ania Ayunda Raaziqi Cindy Agustina Cindy Natasya Dewi Suryani Edy Irwansyah Irvin Irvin Lili Ayu Wulandhari M. Aqila Budyputra Muhammad Edo Syahputra Novita Hanafiah Noviyanti T. M. Sagala Prihastuti Harsani Raditya Tamam Reza A Prasetyo Tania Lipiena Triastinurmiatiningsih, Triastinurmiatiningsih Victoria Ivy Tansil Yongki Christian Sanjaya