cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Muhammad Yunus
Contact Email
m.yunus@polije.ac.id
Phone
-
Journal Mail Official
jtim.sekawan@gmail.com
Editorial Address
Jl. Bandeng No.25, Bintaro, Kec. Ampenan, Kota Mataram, Nusa Tenggara Bar. 83511
Location
Kota mataram,
Nusa tenggara barat
INDONESIA
JTIM : 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.
Arjuna Subject : -
Articles 152 Documents
 12   13   14   15   16 
Implementasi Agile Scrum Pembuatan Game Visual Novel Cerita Asal Usul Kota Surabaya Artiarini Kusuma Nurindiyani; Ashafidz Fauzan Dianta; Halimatus Sa’dyah; Ilham Agung Riyadi
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol 4 No 4 (2023): February
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v4i4.277

Abstract

Surabaya is the second largest city in Indonesia after Jakarta. The city of Surabaya has a distinctive designation, namely "the city of heroes" because of the great support from the people of Surabaya in fighting for Indonesian independence. The lack of interest of Indonesia's younger generation in Indonesian folklore and their preference for video games and other advanced technology, does not rule out the possibility that history will be forgotten and slowly extinct because it is only passed down orally. The purpose of this research is to implement the agile-scrum method in making visual novel games as an effort to attract the interest of the younger generation to know and preserve the history of the origins of the city of Surabaya with a modern approach and according to the target audience. The visual elements used in this game are costume details, props, poses and various expressions according to modified references. In addition, the narration/storyline used has also been developed with a story style and choice of words that are relevant to the target user. The method used in this final project is agile-scrum which has 8 stages of development, starting from the stage of exploring problems that can become product ideas to the final testing stage. From the results of the final test, the creation of a visual novel game based on the story of the origins of the city of Surabaya can be used properly by users.
Klasterisasi Pelanggan Tenant Inkubator Bisnis STIKOM Bali Untuk Strategi Manajemen Relasi Dengan Menggunakan Fuzzy C-Means I Gede Harsemadi; Dedy Panji Agustino; I Gede Bintang Arya Budaya
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol 4 No 4 (2023): February
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v4i4.293

Abstract

Business Incubator is an institution that assists start-up businesses as their tenants that are still newly established or are growing. The main goal of a business incubator is to explore the most appropriate ways of assistance for tenants, from the process of starting a business, developing a business, and scaling up a business so that tenants can succeed in their business. Based on existing assistance data and the results of interviews with managers of the STIKOM Bali business incubator, one of the challenges for tenants is the ineffectiveness of the marketing process and strategic schemes in terms of maintaining customer loyalty. Ineffective and efficient plans can result in wasted use of resources. The customer relationship management (CRM) strategy can be applied by tenants as the solution, but the basis is that tenants need to know how to find out the right treatment for customers. So a strategy is needed to find out the characteristics of customers. In this case, it is done by using a business intelligence approach through customer clustering using fuzzy c-means. The dataset comes from the transaction of one of the tenants who is engaged in education technology. Based on values of the fuzzy partition coefficient (FCP) for the scenarios from clusters 2 to 10, it was found that 7 is the most optimal number of clusters (customer category) with the highest FCP value = 0.793. The main strategy that can be implemented based on tenant business for CRM is the pricing of subscription and engagement packages to customers regarding the information on both recently released and upcoming learning content.
Analisis Pengaruh Komposisi Data Training dan Data Testing pada Penggunaan PCA dan Algoritma Decision Tree untuk Klasifikasi Penderita Penyakit Liver Baiq Nurul Azmi; Arief Hermawan; Donny Avianto
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol 4 No 4 (2023): February
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v4i4.298

Abstract

Liver disease is one of the diseases that is difficult to detect and becomes the largest contributor to deaths because it is considered a silent killer without symptoms. Liver disease can be detected based on abnormalities in the number of contents in the human body. The Indian Liver Patient Dataset (ILPD) dataset has many variables related to content in the body of liver patient data which are used as parameters in the classification of liver disease patients. Previous studies have shown that only two variables influence the ILPD dataset. The purpose of this study is to examine the use of the Principal Component Analysis (PCA) method to determine the optimal number of features in the context of classification of liver disease and examine the percentage distribution of data training and data testing which produces the best accuracy. The ILPD dataset was obtained from the UCI Machine Learning website with a total of 583 rows of data and 11 features. The percentage of training data and testing data used is 50%:50%, 60%:40%, 70%:30%, 73%:27%, 75%:25%, 80%:20%, 83%:17%, 85%:15% and 90%:10%. The use of different training and testing data percentages serves to find the best accuracy. The PCA result feature is used as input for the Decision Tree C4.5 classification algorithm. The experimental results show that using the training and testing data distribution percentage of 90%:10% and after the application of PCA produces the highest accuracy, namely 78.40% which is obtained for the number of PCA components n = 8.
Best Machine Learning Model For Face Recognition in Home Security Application Istiqomah; Faqih Alam; Achmad Rizal
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol 4 No 4 (2023): February
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v4i4.306

Abstract

Particularly since the COVID-19 outbreak, Indonesia has seen an annual surge in criminal prosecutions. To increase home security, many technological advances have been made. Face recognition served as the main form of security for almost all of them. Face detection, face segmentation, and face recognition are the three steps in the face recognition process. To avoid misclassification and increase system dependability, accurate recognition of faces becomes crucial in security systems. The optimization tool Grid Search CV produces using a number of machine learning methods that are proposed. Each machine learning has been created using its best model and has attained accuracy levels of at least 90%. The most effective strategy is SVM, which has 100% accuracy rates. A technique for choosing the best model is an alternative. The computation time will be compared to that of more complex systems before these results are eventually communicated to the real system
Prediksi Persentase Body Fat Menggunakan Algoritma CART dan M5’ Uswatun Hasanah; Ade Nurhopipah
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol 4 No 4 (2023): February
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v4i4.316

Abstract

Body Fat Percentage (BFP) is a measurement of total body fat that is used as an accurate measurement for the diagnosis of obesity. BFP measurement is sometimes difficult and inconvenient to perform, even though the picture of BFP’s value is very important for someone to find out the chances of being obese. To overcome this, data mining techniques can be used to measure the predictions of BFP values in a more practical way. This study implements data mining techniques, namely the CART and M5’ algorithm to predict a person's BFP value based on his/her body measurement. The CART algorithm uses the sample average values at leaf nodes to make numerical predictions, while the M5' algorithm builds a regression model for each leaf node with a hybrid approach. Regression trees provide a simple way of explaining the relationship between features and numerical results, but more complex model trees also provide more accurate results. In this study, the results show that the M5' algorithm is superior to the BFP dataset with a correlation value of 0.86 and an MAE value of 3.86.
Load and Stability Optimization Based Carbon Arm with Split Tank on Unmanned Aerial Vehicle for Foliar Fertilizer Faisal Lutfi Afriansyah; Fendik Eko Purnomo; Ahmad Rofi'i; Nurul Zainal Fanani
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol 4 No 4 (2023): February
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v4i4.318

Abstract

This research focuses on the load and stability of unmanned aerial vehicles that are as light as possible but with optimal stability functions and increasing the capacity of liquid fertilizer lifted by unmanned aerial vehicles. The increase in lift is related to the payload and stability to be carried by the unmanned aerial vehicle. By optimizing the arm using the arm carbon method, so without reducing the strength and function of the drone, the gross weight of the components becomes much lighter, so that the weight can be focused on increasing the capacity of liquid fertilizer. With the increase in liquid fertilizer capacity, of course, the weight also increases, this raises a new problem, which is to make the balance value when the drone take-off has a large magnitude, thus affecting stability which causes the potential to fail to fly, therefore this research was carried out so that the drone has stability. maximum and can minimize the effects of shocks from increasing capacity after using arm-carbon. The measurements taken were the success rate of the system in flying over agricultural land, power testing and current measurements. After testing, it was found that by using a split tank and carbon arm system, current and power tend to be more stable, so that battery life is longer, liquid fertilizer capacity can be increased and the potential for flight failure can be minimized with a split tank system with 90% accuracy, carried out optimizing weight with carbon arms and increasing the capacity of liquid fertilizer by 30%, using a split tank system increases the stability of the drone at take-off by up to 80%.
Sipekernik: Sistem Pemantau Kekeruhan Air dan Pengairan pada Akuaponik Menggunakan Sensor Turbidity, LDR dan Water Level Nur Aziezah; Walidatush Sholihah; Inna Novianty; Mega Romadhona; Anggi Mardiyono
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol 4 No 4 (2023): February
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v4i4.324

Abstract

Aquaponics is an alternative to cultivating plants and fish in one place. This technique integrates fish farming with plants. In this case, aquaponic plants utilize nutrients from fish waste. Plants in aquaponics function as a biofilter, which will reduce these toxic substances into substances that are not harmful to fish and supply oxygen to fish-keeping ponds. With this technique, there will be a symbiosis of mutualism or a mutually beneficial cycle. The advantages obtained are the efficiency of water use and the reduction of waste contamination resulting from disposal into public waters. The water recirculation period affects the quality and quantity of fish and plants produced. Turbidity for cultivation should be no more than 25 NTU. Therefore, this tool is designed to detect the turbidity value of fish pond water in order to know the time to drain the pond using a turbidity sensor and regulate water irrigation in aquaponic installations based on light intensity values so that water does not stagnate in the installation pipe. The manufacture of this tool uses several components, such as an Arduino as a microcontroller, LDR (Light Dependent Resistor) sensor functions to turn on and off the pump, turbidity sensor functions to determine the turbidity value of pool water, and water level sensor functions to adjust the water level when draining and filling. pond water. At pump 1, the water will turn on if the intensity value of the LDR sensor is 650. If the turbidity sensor value is 25 NTU, then pump 2 will turn on and dump pool water into the shelter. After the pond water is drained to the specified height level, pump 3 will turn on to fill the fish pond with water. Pump 3 will stop when the water level is > 665.
Prediksi Status Gizi Balita Dengan Algoritma K-Nearest Neighbor (KNN) di Puskemas Cakranegara Muhammad Yunus; Ni Kadek Ari Pratiwi
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol 4 No 4 (2023): February
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v4i4.328

Abstract

Nutritional status is a picture of a person's physical condition as a reflection of the balance of incoming and outgoing energy by the body. Determining the nutritional status of toddlers is useful for knowing the nutritional status of toddlers based on weight/age (weight for age). The system designed is a system for determining the nutritional status of toddlers using the K-Nearest Neighbor (KNN) method, where the KNN method is a method of classifying or grouping test data whose class is unknown to the nearest neighbors using the distance calculation formula. The variables used in this system are based on anthropometric data or measurements of the human body, namely gender, age and weight. This system is designed and built using the PHP programming language and MySQL database. The results of this system are nutritional status based on body weight for age (weight for age), namely malnutrition, undernutrition, good nutrition, over nutrition. Based on the test results, the accuracy of the success rate for determining the nutritional status of toddlers using the KNN method produced by this system reaches 88.06%.
Feasibility Evaluation of an Android-based Nutrition App (Dietducate) Among Nutritionists Using the User Version of The Mobile Apps Rating Scale (uMARS) Muhammad Iqbal; Elita Dwi Nurrahmawati; Husin Husin
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol 5 No 1 (2023): May
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v5i1.330

Abstract

Online nutrition consultations are one of the strategic measures utilized to address complex nutritional issues. The use of smartphones in Indonesia is on the rise, particularly smartphones with the Android operating system. Indonesia has entered the 4.0 Industrial Revolution, which involves the application of technology in a variety of fields, including the healthcare industry. One application of this technology is the creation of the android application "dietducate." Using the uMARS (End-User Version of The Mobile Apps Rating Scale) method, this study aims to assess the feasibility of the android-based health application "dietducate" for nutritionists. Utilizing the uMARS research method and a 5-point scale, the research design is quantitative. Using a technique of purposive sampling, up to 35 nutritionists were gathered as subjects. The application evaluation was conducted using the uMARS questionnaire. The results indicated that the application quality score was within the acceptable range (4.05 out of 5). The component outcomes are determined by four supporting factors: involvement, functionality, aesthetics, and information. The results of each score are 3.97, 4.03, 4.02, and 4.23, respectively. It can be concluded that nutritionists can utilize the dietducate application. This app is also regarded as user-friendly and efficient for completing nutritionists' work. However, there are too many advertisements and minor bugs that need fixing to optimize app performance.
Penentuan Rute Optimal Untuk Jasa Pengiriman Barang Menggunakan Algoritma Genetika Gatra Cahya Ramadhan; Pratama Bagus W; Yesy Diah Rosita
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol 5 No 1 (2023): May
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v5i1.322

Abstract

In the delivery process there is a problem commonly known as the Travelling Salesman Problem (TSP), therefore a program is needed that can minimize shipping costs and find a quick route to maximize the profits obtained. Then, set up alternative routes and optimum routes so that the problem can be solved. The purpose of this research is to determine the route or route and the minimum distance search results in goods delivery services using the method of genetic algorithms. Using 27 randomly selected data points from four sub-districts in the Mojokerto district, Clustering data is divided into three clusters and tested using MATLAB software. Using a crossover probability of 0.6, the probability of mutation is 0.4, and the total population is 27. The results of the test in finding the optimal route and the fast track are in the second cluster with a distance of 20 km and the optimal route of 5-8-7-1-9-4 -10-3-6-2-5, i.e., Dsn. Mojoroto, Banjartanggul, Dsn. Sumber Bendo, Perum Mojo Asri, Wonokoyo, Dsn. Trawas, Wonokusumo, Dsn. Pecuk, Dsn. Resik Bulu, Damarsi, Etc. Mojoroto From the optimal route generated in this study, it is expected that the shipping service can get the optimal route to speed up the delivery of goods.

Page 14 of 16 | Total Record : 152

 12   13   14   15   16 

Filter by Year

2019 2023


Reset
Filter By Issues
All Issue Vol 5 No 2 (2023): August Vol 5 No 1 (2023): May Vol 4 No 4 (2023): February Vol 4 No 3 (2022): November Vol 4 No 2 (2022): Agustus Vol 4 No 1 (2022): May Vol 3 No 4 (2022): February Vol 3 No 3 (2021): November Vol 3 No 2 (2021): August Vol 3 No 1 (2021): May Vol 2 No 4 (2021): February Vol 2 No 3 (2020): November Vol 2 No 2 (2020): August Vol 2 No 1 (2020): May Vol 1 No 4 (2020): February Vol 1 No 3 (2019): November Vol 1 No 2 (2019): August Vol 1 No 1 (2019): May More Issue