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DATA VISUALISASI SEBAGAI PENDUKUNG INVESTIGASI MEDIA SOSIAL Pomalingo, Suwito; Sugiantoro, Bambang; Prayudi, Yudi
ILKOM Jurnal Ilmiah Vol 11, No 2 (2019)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Social media is an application that can make everyone interact with each other and can consume information by sharing content quickly, efficiently and real time. Various kinds of information about someone's activities that we can find on social media, making social media can help to conduct investigations. Some research, using visualization with several graph methods to facilitate the process of analyzing data on social media that is so abundant. But the data used only comes from one social media, while there is still a lot of information on other social media that can be used as data sources for analysis purposes. In this study visualization using the directed graph method will be carried out, then calculate the value of network property and the value of centrality to find out which nodes have many activities which will be carried out in depth searches to find patterns of interaction or activity. Based on the results of the calculated centrality, it is found that on Twitter and Instagram accounts there are many interactions, this can be seen in the value of the indegree and outdegree node. Based on the results of the analysis in this study, information that is important for investigating social media is obtained, such as information about user profiles, posts, comments, preferred social media pages, location, and timestamp, all of which are connected by a line that shows the relationship between the node.

The step construction of penalized spline in electrical power load data Rezzy Eko Caraka; Sakhinah Abu Bakar; Gangga Anuraga; M. A. Mauludin; Anwardi Anwardi; Suwito Pomalingo; Vidila Rosalina
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 2: April 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i2.8460

Electricity is one of the most pressing needs for human life. Electricity is required not only for lighting but also to carry out activities of daily life related to activities Social and economic community. The problems is currently a limited supply of electricity resulting in an energy crisis. Electrical power is not storable therefore it is a vital need to make a good electricity demand forecast. According to this, we conducted an analysis based on power load. Given a baseline to this research, we applied penalized splines (P-splines) which led to a powerful and applicable smoothing technique. In this paper, we revealed penalized spline degree 1 (linear) with 8 knots is the best model since it has the lowest GCV (Generelized Cross Validation). This model have become a compelling model to predict electric power load evidenced by of Mean Absolute Percentage Error (MAPE=0.013) less than 10%.

DATA VISUALISASI SEBAGAI PENDUKUNG INVESTIGASI MEDIA SOSIAL Suwito Pomalingo; Bambang Sugiantoro; Yudi Prayudi
ILKOM Jurnal Ilmiah Vol 11, No 2 (2019)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v11i2.443.143-151

Social media is an application that can make everyone interact with each other and can consume information by sharing content quickly, efficiently and real time. Various kinds of information about someone's activities that we can find on social media, making social media can help to conduct investigations. Some research, using visualization with several graph methods to facilitate the process of analyzing data on social media that is so abundant. But the data used only comes from one social media, while there is still a lot of information on other social media that can be used as data sources for analysis purposes. In this study visualization using the directed graph method will be carried out, then calculate the value of network property and the value of centrality to find out which nodes have many activities which will be carried out in depth searches to find patterns of interaction or activity. Based on the results of the calculated centrality, it is found that on Twitter and Instagram accounts there are many interactions, this can be seen in the value of the indegree and outdegree node. Based on the results of the analysis in this study, information that is important for investigating social media is obtained, such as information about user profiles, posts, comments, preferred social media pages, location, and timestamp, all of which are connected by a line that shows the relationship between the node.

COLLEGE ACADEMIC DATA ANALYSIS USING DATA VISUALIZATION Takdir Zulhaq Dessiaming; Siska Anraeni; Suwito Pomalingo
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 5 (2022): JUTIF Volume 3, Number 5, October 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.5.310

Data is a collection of information that contains a broad picture related to a situation. The amount of data is not necessarily better, because a large data set makes it difficult to convert data into information in a timely manner, especially in analyzing data which produces meaningful and relevant information which ultimately results in quick and appropriate action. Higher education management in Indonesia requires fast and accurate academic reports so that it can facilitate strategic decision making in order to improve the quality of education. This study aims to carry out a comprehensive process of analyzing academic data at universities to display them into interactive data visualizations, so that they can retrieve the information in it and make strategic decisions. The method used is a data visualization technique, which allows users to easily see the insights or insights contained in the data. The results obtained are data that has passed the preprocessing stage, can prepare data before being analyzed and processed to be used to make data visualization, so that the information obtained is more varied. This information can be used as a reference by academic managers to make strategic decisions.

Optimizing Patient Registration Process through Online Admission Application: A Scrum Approach Suwito Pomalingo; Fenina Adline Twince Tobing
Jurnal Bumigora Information Technology (BITe) Vol 5 No 1 (2023)
Publisher : Prodi Ilmu Komputer Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v5i1.3007

Background: The healthcare environment is dynamic and often changes rapidly, whether in terms of regulation, technology or patient needs. Handling these changes and iterations in a short period of time and without disrupting hospital operations is quite a challenge.Objective: The research was conducted with the aim of optimizing the patient registration process at Bahagia Hospital in Makassar through an online system.Methods: The focus of this research was the application of the Scrum method in developing the application. Various methods were employed in this study, including observation, literature review, and interviews to gather user requirements. In the application development process, a series of sprints comprising planning, execution, review, and retrospection stages were carried out. The resulting application was able to quickly respond to user needs and improve services for patients.Result: The test results showed a success rate of 90% in achieving sprints within the specified time frame, indicating that the team was able to meet the set targets in each sprint.Conclusion: The effectiveness of the Scrum method in developing this application was affirmed in this study, thus it can be utilized for future development of similar applications.

A Comparative Analysis of Forensic Similarity and Scale Invariant Feature Transform (SIFT) for Forensic Image Identification Al Jum'ah, Muhammad Na'im; Wijaya, Hamid; Pomalingo, Suwito
ILKOM Jurnal Ilmiah Vol 16, No 3 (2024)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v16i3.2357.371-381

The image manipulation process has contributed to the widespread dissemination of false information. image forensics can help law enforcement agencies in addressing the spread of false news or information issues through visual media. Forensic image identification can be conducted using various methods, including Scale Invariant Feature Transform (SIFT) and Forensic Similarity. This study compared two methods, SIFT and Forensic Similarity, for forensic image identification. The test results showed the SIFT method identified image forensics by detecting image similarity through calculation of the key point values of each image. The process of searching the key point values was performed to extract information from the image. A high key point value indicated a large amount of information obtained from the image extraction results. On the other hand, the Forensic Similarity method also performed image forensic detection by examining whether image patches shared the same forensic traces. The advantage of the Forensic Similarity method over the SIFT method was that Forensic Similarity was more detailed because it involved many processes. Thus, Forensic Similarity was able to find similarities between two image patch objects. Additionally, the results obtained from the Forensic Similarity method were more detailed in detecting image similarity by considering the key point matching value and Cosine Similarity. Several previous studies have already implemented the SIFT and Forensic Similarity methods for image forensics, but there was no research that directly compared these two methods. This is the strength of this research. However, this study only used three data samples from three different devices for data collection. Future research can use a larger sample size to observe the comparison results

Using Convolutional Neural Network and Saliency Maps for Cirebon Batik Recognition Aditiya, Yoga; Overbeek, Marlinda Vasty; Pomalingo, Suwito
ULTIMATICS Vol 17 No 1 (2025): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v17i1.4026

Cirebon Batik is one of Indonesia's cultural heritages that has its own unique patterns and motifs, reflecting the cultural richness and history of its region of origin. This study aims to address the challenges in classifying the complex motifs of Cirebon Batik by implementing Convolutional Neural Network (CNN) and Saliency Map methods. The three main motifs used are Mega Mendung, Singa Barong, and Keratonan. The dataset was obtained from various online sources and processed using image augmentation techniques. CNN is used to recognize complex visual patterns, while Saliency Map highlights important areas in the image that influence the model's decision. The results show that the developed CNN model achieved an accuracy of 82%, precision of 83%, recall of 82%, and F1-score of 82%. The use of Saliency Map provides better interpretability and enhances the understanding of the classification process

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