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Jurnal Teknologi Informasi dan Multimedia
Published by Puslitbang Sekawan Institute Nusa Tenggara
ISSN : 27152529     EISSN : 26849151     DOI : https://doi.org/10.35746/jtim.v2i1
Core Subject : Science,
Computer Science & IT
Cakupan dan ruang lingkup JTIM terdiri dari Databases System, Data Mining/Web Mining, Datawarehouse, Artificial Integelence, Business Integelence, Cloud & Grid Computing, Decision Support System, Human Computer & Interaction, Mobile Computing & Application, E-System, Machine Learning, Deep Learning, Information Retrievel (IR), Computer Network & Security, Multimedia System, Sistem Informasi, Sistem Informasi Geografis (GIS), Sistem Informasi Akuntansi, Database Security, Network Security, Fuzzy Logic, Expert System, Image Processing, Computer Graphic, Computer Vision, Semantic Web, Animation dan lainnya yang serumpun dengan Teknologi Informasi dan Multimedia.
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Articles 296 Documents
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Optimalisasi Model Ensemble Learning dengan Augmentasi dan SMOTE pada Sistem Pendeteksi Kualitas Buah Syahroni Hidayat; Taofan Ali Achmadi; Hanif Ardhiansyah; Hanif Hidayat; Rian Febriyanto; Abdulloh Abdulloh; Intan Ermawati
Jurnal Teknologi Informasi dan Multimedia Vol. 6 No. 1 (2024): May
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v6i1.406

Abstract

Fruit quality is an important factor in selecting fruit for consumption because it affects consumer health and satisfaction. Identification of fruit quality has become the focus of research, and one of the approaches used is a non-destructive approach through measuring the gases produced by the fruit. Machine learning can be used to process this gas data and build system models that can classify fruit quality. This research discusses the application of the DCS-OLA and Stacking dynamic ensemble learning algorithms to build a fruit quality detection system model. The basic methods used to build models are Logistic Regression, Decision Tree, Gaussian Naïve Bayes, and Mul-ti-Layer Perceptron. The fruit used is mango with a shelf life of 7 days and Srikaya (sugar apple) with a shelf life of 4 days. The condition of the initial dataset is unbalanced. The research results show that trimming the mango dataset to only 4 days according to the shelf life of sugar apple helps reduce the difference in shelf life between the two. Then jittering and balancing techniques are used to increase and balance the number of datasets between the two types of fruit. High accuracy is achieved by the DCS-OLA ensemble and stacking ensemble by combining the basic methods of Logistic Regression and Decision Tree, especially in balanced dataset conditions. In conclusion, the use of ensemble learning in detecting fruit quality has great potential for real-world applications. However, further validation is needed with larger datasets and a wider variety of conditions.
Pengembangan Sistem Informasi Bank Sampah untuk Optimalisasi Pengelolaan Data Nuraini, Fina; Sutopo, Joko
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol 5 No 3 (2023): November
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v5i3.409

Abstract

Bank Sampah Sumber Rejeki in Cilacap City provides an opportunity for customers to deposit waste and receive monetary rewards. Unfortunately, current data management is still manual through unstructured notebooks, potentially resulting in data loss due to notebook damage, difficulty in finding customer information, and delays in making performance reports. This research aims to develop a website-based management information system that is tailored to the needs of the sampah bank. This system includes customer data management, recording waste deposit transactions, recording customer balance withdrawals, and improving waste bank data security. Data was collected through direct interviews with the manager of Sumber Rejeki Waste Bank. The development method used is Feature Driven Development (FDD) using the PHP programming language and MySQL database. In addition, testing this system also involves the black box testing method to ensure the functionality is as expected. The result of this research is a web-based system that is significant in improving the efficiency of managing customer data, transactions, and waste bank performance reports. The implementation of this system reduces the risk of errors and data loss due to manual recording and provides easier access for customers to view transaction history in the waste bank.
Implementasi Augmented Reality Sebagai Media Edukasi Tanaman Hias Berbasis Marked Based Alif Syahdan; Sri Wulandari
Jurnal Teknologi Informasi dan Multimedia Vol. 5 No. 3 (2023): November
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v5i3.410

Abstract

Ornamental plants are plants that we often encounter in the community and in public places, such as in the yard, in the park or in the school yard. Ornamental plants are usually very popular with people, especially housewives, because ornamental plants have their own characteristics and benefits, such as the snake plant (Sansevieria) which has benefits for the environment, namely it can absorb air pollution. In society, especially housewives, it is difficult to care for ornamental plants, so that the plants they cultivate often wilt or die. Therefore, media to increase education about ornamental plants must be improved to help people who want to cultivate ornamental plants. This research uses Marked Based Augmented Reality as a learning medium for the public in introducing and caring for ornamental plants. Augmented Reality is an example of technology that can visualize an object from the virtual world to the real world with a 3D object shape in real time. In this research, the Software Development Life Cycle or Waterfall (SDLC) method was used as the research method. The Software Development Life Cycle method or Waterfall model (SDLC) has five stages, namely data collection, software analysis, software design, implementation and software testing. Based on the results of black box testing, all functions in this application have run well on every Android smartphone used. Testing with the System Usability Scale (SUS) Re-spondents also got a score of 84%, so the application was declared acceptable.
Rancang Bangun Aplikasi pengelola Data Pekerja Berbasis Website Di BRI Kendari Cabang Samratulangi Auliya Rahman Asdar; Muhammad Akbar Asad Ishaq; Rizal Adi Saputra
Jurnal Teknologi Informasi dan Multimedia Vol. 5 No. 3 (2023): November
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v5i3.412

Abstract

The large number of workers managed makes it difficult for BRI officers at the Samratulangi branch to manage them. Management of employee data at the Samratulangi branch of BRI was previously managed via Microsoft Excel. Management carried out manually causes several problems, including the difficulty of identifying workers whose work terms have expired and the number of workers being managed is quite large and takes a long time. This problem can be solved by building a worker data management application. Application development is carried out using the prototype method. In this research, the application is designed to be able to manage workers' data well, be able to manage workers' attendance, know the active status of workers, and be able to issue Specified Time Work Agreement Decree in a timely manner. Based on the prototype method, researchers carry out the communication stage to obtain information about the problems faced by users. At the Quick plan and Modeling quick design stage, researchers began to design the UML and display in prototype form to then create a User Interface. Next, at the Feedback and Delivery stage, researchers ask for feedback and suggestions regarding the application that has been created which will then be developed and improved according to user input. So the system is created so that users can run the system according to their needs. Based on the test results using a blackbox, the system is designed according to its function and use.
Pengembangan Aplikasi Pose Detection untuk Asesmen Kemajuan Fisioterapi Pasien Pasca Stroke dari Jarak Jauh Febry Putra Rochim; Anan Nugroho; Sri Sukamta; Ahmad Zein Al Wafi; Muhammad Fathurrahman; Amelia Damayanti; Hildatul Wardah
Jurnal Teknologi Informasi dan Multimedia Vol. 5 No. 4 (2024): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v5i4.415

Abstract

Assessment has an important role in determining the diagnosis and subsequent treatment plan. In an effort to increase access and effectiveness of rehabilitation, this research aims to develop a mobile application that is able to report the results of post-stroke patient pose assessment remotely. Telemedicine approaches in post-stroke rehabilitation have become increasingly popular, allowing patients to access rehabilitation services remotely. This is especially beneficial for patients who live in remote areas or have limited mobility. Telemedicine also allows for real-time patient monitoring, allowing adjustments to rehabilitation plans as needed. The mobile app is designed to provide easy access to rehabilitation programs that can be tailored to individual patient needs. In addition to making access easier, this application is equipped with a monitoring feature that allows health professionals to follow patient progress in detail. Data collected from patients' daily exercise and activities provides valuable insight into their progress, which can be used in tailoring rehabilitation plans in real-time. The development of this mobile application technology has great potential to improve rehabilitation outcomes for post-stroke patients. Testing by three experts with two experts as healthy patients and stroke patients, as well as one patient who acts as a medical personel to monitor, shows that from the graph, healthy patients tend to be consistent. On the other hand, post-stroke patients tend to be inconsistent. These results indicate that this application is effective for identifying patient movements during the rehabilitation process. Although there are several obstacles, such as delays in predictions on some devices, this application has great potential to improve the quality of life of post-stroke patients. Thus, the development of a pose detection application for remotely assessing the progress of physiotherapy in post-stroke patients has great potential in improving rehabilitation outcomes. The app facilitates patient access to appropriate, personalized and effective care, while providing medical personnel with objective and accurate data for monitoring and adjusting rehabilitation plans. This is a significant step in advancing the care of post-stroke patients.
Analisis Segmentasi Pelanggan pada Bisnis dengan Menggunakan Metode K-Means Clustering pada Model Data RFM Sisilia Fhelly Djun; I Gede Aris Gunadi; Sariyasa Sariyasa
Jurnal Teknologi Informasi dan Multimedia Vol. 5 No. 4 (2024): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v5i4.434

Abstract

The development of business strategies, particularly in the marketing of SMEs, requires the utilization of business intelligence as the foundation for objective decision-making. This research aims to develop a business intelligence scheme for SMEs and design targeted assistance strategies for SME support institutions. The implementation of business intelligence involves leveraging transactional data from SMEs to ascertain customer segmentation and correlating it with Customer Relationship Management (CRM) strategies. Transactional data is processed into a Recency, Frequency, Monetary (RFM) data model. Customer segmentation is achieved through a clustering process using the K-Means algorithm, and the results yield distinct profiles for SME customers. Evaluation processes are conducted to determine the optimal solution for the number of customer segments. Evaluation methods, including the Elbow Method, Silhouette Scores, and Davies–Bouldin Index, are employed to determine the optimum cluster. The evaluation results indicate that the optimum cluster is 3, with the best Silhouette Score being 0.548 and Davies–Bouldin Index at 0.76. The first customer segment exhibits the highest shopping frequency and monetary value, categorizing them as active and profitable customers. Special loyalty services are recommended for this segment. The second segment, despite having the largest number of customers, exhibits a shopping frequency of only 1-2 times, with an average recency of approximately the last 2 months. These customers require effective after-sales service. The third segment consists of customers who last shopped more than 6 months ago, making them a low-priority segment. Re-engagement strategies, such as email marketing, are suggested for this segment. Support institutions can focus on CRM assistance targeting these three identified segments.
Pengembangan Laboratorium Multimedia Virtual sebagai Media Pembelajaran Audio Digital menggunakan Model Game First Person Shooter Iwan Sonjaya; Noorlela Marcheta; Prayoga Bayu Lail Segara
Jurnal Teknologi Informasi dan Multimedia Vol. 5 No. 4 (2024): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v5i4.435

Abstract

The laboratories at PNJ cannot be operated optimally because the available equipment does not yet have equipment with the latest technology. Whereas students should be able to practice theories related to the latest technology so that equipment is needed that continues to change in line with current technological developments. However, the situation in changing the existing technology requires a bureaucracy that is quite complicated and long. Virtual laboratories are media used to help understand a subject matter and can be a solution to the limitations or absence of laboratory equipment that can be upgraded more easily. Acceleration in the world of education is also re-sponded to by shifting the function of the laboratory. In addition, this virtual laboratory can also be utilized as a distance learning tool. This application is made using the MDLC (Multimedia De-velopment Life Cycle) method which has 6 stages, namely, concept, design, material collecting, assembly, testing, and distribution. The virtual laboratory in audio multimedia learning has been successfully created using the First Person View model. This success is based on the results of testing from 37 responders through 11 questions posed to users who have tried the application found that the respondent's interpretation of the ease of use of the application in learning is 85.40%. While 81.62% stated that the Digital Audio Laboratory already had a feel like a real lab and 85.94% stated that participants were interested in learning through a virtual digital audio laboratory.
Aplikasi Virtual Reality untuk Media Terapi Phobia Ketinggian Muhamad Akbar Triadi Fadillah; Aldy Putra Aldya; Eka Wahyu Hidayat
Jurnal Teknologi Informasi dan Multimedia Vol. 5 No. 4 (2024): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v5i4.438

Abstract

This research aims to develop a therapy application using Virtual Reality technology and a smartwatch to view heart rate data as an assessment in dealing with and assessing how bad Arcophobia (phobia of heights) is in users. The application built is a Virtual Reality (VR) application on the Android platform and applies the Exposure-Based Therapy (EBT) method, the Exposure-Based Theraphy (EBT) method is a method that applies an introduction to phobias suffered gradually according to the ability of the sufferer, in this case the EBT method is proven effective in reducing phobias including Arcophobia. The use of multimedia elements is given gradually to individuals who have phobia. The results show that the development of Android-based Virtual Reality applications is able to help individuals efficiently and effectively overcome Arcophobia by using simulated altitude situations. This application has 3 stages of desensitization (exposure) in a Virtual Reality environment that is made in such a way that individuals can slowly get used to their phobia. In addition, this application collects heart rate data to assess how severe the phobia experienced by the individual there are 3 objective assessments to determine how bad the phobia suffered by the user is if the user's heart rate ranges from 60bpm - 100bpm (normal) while 105bpm - 115bpm is included in the category (quite normal) and 120bpm-200bpm is categorized (bad), from these 3 assessment categories provide additional information that is useful for objectively evaluating the progress of therapy.
Implementasi Internet of Things pada Otomasi Pemberian Pakan Ayam Ras Petelur Lukie Perdanasari; Bety Etikasari; Trismayanti Dwi Puspitasari; Ratih Ayuninghemi
Jurnal Teknologi Informasi dan Multimedia Vol. 6 No. 3 (2024): November
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v6i3.452

Abstract

Adequate nutrition affects the quality and quantity of egg production which has an impact on the profitability of laying hen breeders. Rizqie Farms experienced problems with the management of feeding laying hens, when the rainy season and open cage conditions made feeding irregular. It is important to be disciplined in feeding layer chickens on time at the same time as a research ur-gency, so that the chickens do not become stressed so that discipline in feeding management increases the quality and quantity of egg production. The design thinking method as a meth-od-ology for completing the creation of Android smartphone tools and applications. The com-pletion stages start with empathize, define, ideate, prototype and test. The materials used to make the tool are ESP32 DEVKIT V1 S2, Ultrasonic Sensor, Servo driving droplet feed, Power Source/Supply 12v 1A, Stepper Motor Driver l928n, Stepper Motor Nema 17 20nm, DS3231 RTC Module (timer), Arduino Uno R3, Buzzer / Speaker, LCD 1062 16x2 with I2c port. Sensor data connected to the ESP32 DEVKIT V1 S2, Ultrasonic Sensor, Servo drive is converted to an Android smartphone as a monitoring medium. Monitoring is carried out via a mobile application, with the Internet of Things connected to the device as an internet-based communication medium. Feeding equipment testing had an average delay of 40.2 seconds and MSE 0,0514. Black box testing was carried out to test the functionality of the monitoring application on 5 users with a percentage of 100%.
Deteksi Nodul Paru pada Citra CT dengan Klasifikasi Pseudo Nearest Neigbour Rule Jaya, I Nyoman Surya; Aryanto, Kadek Yota Ernanda; Divayana, Dewa Gede Hendra
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol 5 No 4 (2024): February
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v5i4.463

Abstract

This research aims to obtain the classification performance of the Pseudo Nearest Neighbor Rule (PNNR) algorithm in detecting lung nodules in CT scan images. The PNNR classification algorithm is used to reduce the influence of noise or outliers in the classification process so that false positives (prediction of an object that is not a nodule as a nodule) can be reduced. The data set used is 200 patient data obtained from the public data of The Lung Image Database Consortium and Infectious Disease Research Institute (LIDC/IDRI) where 4 fold Cross Validation will be carried out. The preprocessing stage is carried out by segmenting the otsu image, where from the segmentation results the two largest blobs are then searched for to determine the area of ​​the lung to be analyzed. Next, the feature extraction process from the candidate nodules (white pixels / foreground) is obtained from the Otsu segmentation process again. The results of this second segmentation contain information from the candidate nodules to then calculate the value of the shape features of the candidate nodules such as area, eccentricity, equivalent diameter, major axis length, minor axis length and perimeter which produces feature set values ​​as the basis for training data and data test for the classification process in PNNR The results of the classification proposed in this research, namely using the PNNR classification method, obtained an Accuracy value of , which is included in the excellent classification level or the Accuracy level is very good but with a lower level of sensitivity or recognition of true positives, namely . In further research, classification optimization can be carried out by selecting the feature set usedThis research aims to obtain the classification performance of the Pseudo Nearest Neighbor Rule (PNNR) algorithm in detecting lung nodules in CT scan images. The PNNR classification algorithm is used to reduce the influence of noise or outliers in the classification process so that false positives (prediction of an object that is not a nodule as a nodule) can be reduced. The data set used is 200 patient data obtained from the public data of The Lung Image Database Consortium and Infectious Disease Research Institute (LIDC/IDRI) where 4 fold Cross Validation will be carried out. The preprocessing stage is carried out by segmenting the otsu image, where from the segmentation results the two largest blobs are then searched for to determine the area of ​​the lung to be analyzed. Next, the feature extraction process from the candidate nodules (white pixels / foreground) is obtained from the Otsu segmentation process again. The results of this second segmentation contain information from the candidate nodules to then calculate the value of the shape features of the candidate nodules such as area, eccentricity, equivalent diameter, major axis length, minor axis length and perimeter which produces feature set values ​​as the basis for training data and data test for the classification process in PNNR The results of the classification proposed in this research, namely using the PNNR classification method, obtained an Accuracy value of , which is included in the excellent classification level or the Accuracy level is very good but with a lower level of sensitivity or recognition of true positives, namely . In further research, classification optimization can be carried out by selecting the feature set used

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