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J-Icon : Jurnal Komputer dan Informatika
Published by Universitas Nusa Cendana
ISSN : 23377631     EISSN : 26544091     DOI : -
Core Subject : Science,
Computer Science & IT
J-ICON : Jurnal Komputer dan Informatika focuses on the areas of computer sciences, artificial intelligence and expert systems, machine learning, information technology and computation, internet of things, mobile e-business, e-commerce, business intelligence, intelligent decision support systems, information systems, enterprise systems, management information systems and strategic information systems.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 205 Documents
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PERANCANGAN DAN PEMBANGUNAN SISTEM INFORMASI PENGELOLAAN JEMAAT GBKP BERBASIS WEB Jean Sontri Ananta; Ramos Somya
J-ICON : Jurnal Komputer dan Informatika Vol 11 No 1 (2023): Maret 2023
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v11i1.10101

Abstract

A web-based information system is a technology that can be utilized for data archiving. Archiving data such as church congregations is crucial for the development of the church. However, one of the churches, the Batak Karo Protestant Church (GBKP), still archives data using books and Microsoft Excel. GBKP's data archiving using books and Microsoft Excel is still not efficient and effective when moving congregations, where a letter of request is submitted in writing by the church of origin to the church of destination. This research aims to implement a web-based information system that can provide congregational data management and transfer features to assist churches in conducting data processing more effectively and efficiently. The method applied in the design process to system implementation is the waterfall method and the development of information systems using the PHP, HTML, CSS and JavaScript programming languages. Testing in this study was carried out using the User Acceptance Test (UAT) method, namely the alpha and beta testing. In alpha testing, information is obtained that 100% of the functions are compliant or running well. In beta testing, it was concluded that this information system could provide convenience for churches in managing data, especially when moving congregations between churches, because the beta testing results reached a value of 95%. This web-based information system is proven to have a function that can provide convenience to churches in managing data and assist churches and congregations in moving because sending data and creating documents can be done quickly.
PENERAPAN METODE FUZZY TSUKAMOTO PADA PEREKRUTAN KARYAWAN Clarissa Elfira Amos Pah; Juan Rizky Mannuel Ledoh
J-ICON : Jurnal Komputer dan Informatika Vol 11 No 1 (2023): Maret 2023
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v11i1.10113

Abstract

A qualified workforce in a company is an essential asset to support the company's business goals. As a company grows, companies begin to understand patterns of qualified employees to be recruited and retained. This pattern is then used as employee recruitment criteria. However, as the number of applicants increases, companies become overwhelmed in assessing and comparing one prospective employee with another, as a result, the employee recruitment process becomes longer. One of the companies experiencing this problem is a Konsultan Teknik Informasi (KTI) Company which is the object of this research. The company, founded in 2008, has experienced an average increase in employee recruitment of 48% annually and a moderate increase in employee turnover of 11% annually. Of course, the number of applicants evaluated for acceptance will be more significant than those accepted for work. Therefore, this KTI company needs a decision support method that can quickly help select employees based on predetermined criteria and rank prospective employees who best meet the criteria. The decision support method proposed by the researcher is the Fuzzy Tsukamoto method. Fuzzy Tsukamoto is used because it can accommodate experts' opinions by making membership functions and rule base matrix. Each input value obtained from the prospective employee data is mapped in the membership functions and rule base matrix through a fuzzification process. This is then defuzzification to produce an output value that can be used to rank prospective employees. Tests carried out on three prospective employee data obtained crisp output values of 6.70, 6.58, and 6.42, respectively, with the largest value being the highest rank.
PENGUKURAN KUALITAS DATA UNTUK MENINGKATKAN APLIKASI SQA DI PT XYZ Ratna Yulika Go; Rahmi Julianasari; Ahmad Syaifulloh Imron; Yova Ruldeviyani
J-ICON : Jurnal Komputer dan Informatika Vol 11 No 1 (2023): Maret 2023
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v11i1.10138

Abstract

Service Quality Assurance (SQA) is one of a unit in PT XYZ an Indonesian e-commerce company. SQA is responsible for ensuring and maintaining services given to customers by Customer Service agents to meet the company's quality standard. However, the application was built without integration with the Customer Relationship Management (CRM) system, the main customer service application at PT XYZ. The problem is that if companies need SQA data, they must manually input data from SQA to CRM. This can cause vulnerabilities in the data input process. As a result, it impacts the company's business processes, which are inefficient and can be detrimental both materially and immaterially. This research aims to provide recommendations to improve the quality of SQA data so that companies can use the data to be integrated into the CRM system. The Total Data Quality Management (TDQM) method was used for this study with three dimensions: completeness, validity and accuracy. The results of each dimension are 99.64% for completeness, 84.75% for validity, and 100% for accuracy. Business rules on the validity dimension that have the lowest data quality are V1 28.57% and V6 65.11%. The problem factors were identified as an incomplete data dictionary, incomplete and obsolete SOP documents, and no business processes and data control on the application. Recommendations to improve the data quality of the application are PT XYZ can conduct an in-depth study of business roles so that all business processes can be clearly defined and regulations can be set forth in SOP documents. The use of specific reference data for each domain can be used to increase data legitimacy and the level of data suitability.
REAL-TIME STRUCTURAL ANALYSIS BASED ON MACHINE LEARNING FOR CUSTOM PRODUCT DESIGN: A CASE STUDY OF ORTHOPEDIC FIXATOR PRODUCT Aji Digdoyo; Adhitio Satyo Bayangkari Karno; Widi Hastomo; Agita Tunjungsari; Nada Kamilia; Indra Sari Kusuma Wardhana; Nia Yuningsih
J-ICON : Jurnal Komputer dan Informatika Vol 11 No 1 (2023): Maret 2023
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v11i1.9919

Abstract

Mass customization is related to increasing the balance between the needs of companies that are focused on customers on conditions of production flexibility and efficiency. Product adjustment according to customer needs can increase the company's competitiveness. However, special production processes and adjustments are time consuming and cost inefficient. Parametric product modeling is a fairly popular technique for dealing with this problem. However, it still has challenges related to the high cost of software and a workforce that has special expertise in the field of quality control. In addition, product-specific designs cannot be tested quickly, resulting in a long production time. This study proposes a machine learning (ML) method that aims to obtain a fast time structure to analyze the production of orthopedic fixators. This research process requires a collection of training data with product attributes, physical characteristics, quality, selected ML techniques, and determination of the appropriate set of hyperparameters. Optimization results were obtained using the gradient boosting method with a value of . With these results, the orthopedic fixation device can be used in the case study of developing this machine learning model.
SISTEM INFORMASI GEOGRAFIS PERSEBARAN SEKOLAH DI KOTA TASIKMALAYA BERBASIS WEB Adiwisastra, Miftah Farid; Rahmani, Alfia; Purnia, Dini Silvi; Mulyani, Yani Sri
J-Icon : Jurnal Komputer dan Informatika Vol 11 No 2 (2023): Oktober 2023
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v1i2.9808

Abstract

Tasikmalaya City is one of the cities in the West Java which has an area of around 184.2 km². According to data from the Ministry of Education and Culture, in Tasikmalaya City there are at least 543 schools consisting of 284 Elementary School, 142 Junior High School, 66 Senior High School and 51 Vocational High School. The purpose of this research was to create a web-based system or application that made it easier for visitors to find the distribution and location of schools in Tasikmalaya City more accurately. The method in this research used the Waterfall in software development because it was very suitable for building web-based geographic information system software. Geographic Information System is a computer system that has the abilities to write, record, store, analyse, and display geographic data. This ability can provide benefits in presenting very accurate location information with the help of the Google Map API owned by Google Map, making it easier for programmers to develop a Map on the Website. Web-based Geographic Information System for the distribution of schools in Tasikmalaya City can give information the location of school accurately and make easier to find it.
RESIDUAL NETWORK LAYER COMPARISON FOR SEAT BELT DETECTION Dewi, Irma Amelia; Nasrulloh, Nur Zam Zam
J-Icon : Jurnal Komputer dan Informatika Vol 11 No 2 (2023): Oktober 2023
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v11i2.9903

Abstract

Most of the monitoring of traffic violations on Indonesian roads is currently done manually by monitoring through CCTV cameras, so drivers still have the possibility of violating the use of seat belts. Residual Network (ResNet) as one of the architectures with an accuracy rate of up to 96.4% in 2015, which is intended to overcome the vanishing gradient problem that commonly occurs in networks with many layers. Therefore, in this study, a system was developed using the RetinaNet architecture to detect drivers who use seat belts and drivers who do not use seat belts with the ResNet backbone. In addition, this study compares the performance of ResNet-101 and ResNet-152. The hyperparameters used include a dataset of 10,623 images in the training process, and the batch size parameter is 1, with a total of 10,623 steps, and the number of epochs is 16. Based on 60 tests conducted in this study, the RetinaNet model with the ResNet-152 architecture performed better than the ResNet-101 architecture. The ResNet-152 architecture resulted in a system performance with an accuracy of 98%, precision value of 99%, recall value of 99%, and an f1 score of 99%.
KLASTERISASI DATA HASIL STUDI PELACAKAN TENTANG KARIR DAN PEKERJAAN LULUSAN PERGURUAN TINGGI MENGGUNAKAN ALGORITMA K-MEANS Sutrisno, Joko; Wibowo, Arief; Pratama, Bayu Satria
J-Icon : Jurnal Komputer dan Informatika Vol 11 No 2 (2023): Oktober 2023
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v11i2.12031

Abstract

Higher education has a responsibility to produce quality graduates. One indicator of the quality of graduates is the status of getting a job, the condition of the suitability of the field of work with the educational program pursued, and the waiting period to get the job. What is being done to find out these conditions is to conduct a tracer study for graduates. This study analyzes data from a college graduate tracking study about careers and jobs using a data mining clustering algorithm, namely K-Means. The results showed that the analysis of the tracking study data formed several graduate clusters with an evaluation value of the Davies-Bouldin Index (DBI) reaching 0.287 in the first trial and 0.291 in the second trial. The clusters formed consist of groups of graduates with status still needing to be working or currently working. The profile of graduates from each cluster can be identified in the form of a relatively short waiting period of less than six months to get a first job or a relatively slow waiting period of more than one year. Another cluster specification that is formed is about the profile of graduates with the level of compatibility between the education attained and the field of work carried out. The results of this study serve as feedback for study program managers to measure the quality of graduates and the improvements in the educational process that need to be made.
SISTEM PENDUKUNG KEPUTUSAN PENERIMA BANTUAN BENCANA ALAM MENGGUNAKAN METODE TOPSIS J.A, Yunita Hadrianti; Musyirifah, Musyirifah; Wajidi, Farid
J-Icon : Jurnal Komputer dan Informatika Vol 11 No 2 (2023): Oktober 2023
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v11i2.11178

Abstract

This research aims to produce a website-based system by implementing the TOPSIS method into the system to solve the problem of determining prospective recipients of natural disaster assistance. The type of research used is the type of development using the Waterfall model. The test subjects in this study were the Majene Regency Regional Disaster Management Agency staff. Data on the response of the staff of the Regional Disaster Management Agency Office regarding the implementation of the TOPSIS method in the decision support system for recipients of natural disaster assistance was collected through a questionnaire. The data collected in the trial was then analyzed using quantitative analysis techniques. The results of the research data show that (i) The results of the application of the TOPSIS method have succeeded in providing recommendations for determining prospective recipients of natural disaster assistance, (i) The results of testing with blackbox test show that this decision support system has no defects or errors, which means that the system created already meets the functional requirements, (ii) The User Acceptance Test (UAT) test produced 82% of users who stated that they strongly agreed with the existence of this decision support system which could assist in determining potential recipients of natural disaster assistance according to the criteria used.
ALT+F: PENGEMBANGAN FITUR REKOMENDASI LAPANGAN FUTSAL TERDEKAT DIANTARA DUA TIM BERBASIS ANDROID MENGGUNAKAN ALGORITMA DIJKSTRA Muhaqiqin, Muhaqiqin; Rikendry, Rikendry
J-Icon : Jurnal Komputer dan Informatika Vol 11 No 2 (2023): Oktober 2023
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v11i2.11478

Abstract

The development of futsal is rapid and is the fastest-growing sport in indoor sports worldwide. Playing futsal has become a lifestyle, especially for people in large cities. Futsal not only has become a lifestyle but also has different levels of play, ranging from amateur to semi-professional and professional. The level of play can be seen through competitions organized by Fédération Internationale de Football Association (FIFA) and futsal organizations in each country. Futsal competitions require thorough preparation, even at the amateur level. The playing experience of futsal players needs to be enhanced, so teams need different opponents. There are challenges in finding other teams to play against, such as teams not being familiar with each other, which means teams have to wait for competitions or futsal tournaments. In addition, the lack of information about the nearest futsal court location between teams that want to compete is also a challenge, making it difficult for teams to invite opponents for practice matches. Therefore, a platform is needed to find practice match opponents that includes a feature recommending the nearest futsal court between the two teams. In this research, a feature recommending the nearest futsal court between two teams is developed by implementing the Dijkstra algorithm. The development of this feature in the application uses the software development method called design sprint, which focuses on user needs, ensuring that the application's features align with user expectations. As a result, the application can display recommendations for the nearest futsal court between two teams that want to practice matches. This makes it easier for teams to determine the closest venue that is easily accessible for both teams and their opponents.
Penerapan Metode Gray Level Co-Occurrence Matrix dalam Mengklasifikasi Tingkat Kematangan Buah Naga Berbasis Citra Folla, Marni Monika; Bulan, Semlinda Juszandri
J-Icon : Jurnal Komputer dan Informatika Vol 11 No 2 (2023): Oktober 2023
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v11i2.11847

Abstract

Dragon fruit, also known as pitaya, is a fruit that originates from cactus plants belonging to the genus Hylocereus and Selenicereus, in the Cactaceae family, Cactaes order, and Dicotyledonae class. Dragon fruit is highly popular among people due to its various health benefits. The maturation process of dragon fruit begins approximately 11 months after planting, and it takes about 50 to 55 days from the formation of the flower bud to the fruit being ready for harvest. The maturation process of dragon fruit starts approximately 11 months after planting. From the moment the flower bud is formed until the fruit is ready to be harvested, it takes about 50 to 55 days. Dragon fruit has different levels of maturity, namely raw, half-ripe, ripe, and overripe. These maturity levels can be identified through changes in the fruit skin color. Currently, farmers still manually sort dragon fruit by directly observing the fruit's surface, but this method often leads to inaccurate and inconsistent classifications due to human error. Therefore, researchers are striving to develop a system that can classify the maturity levels of dragon fruit by utilizing Hue Saturation Value (HSV) color characteristics and implementing the Gray Level Co-Occurrence Matrix (GLCM) method. In the classification system developed using Matlab software, there are four maturity categories for dragon fruit, including raw, half-ripe, ripe, and overripe. This research achieved the highest accuracy of 90%. A total of 100 datasets were used, by using 5-fold-cross validation. Data analysis was performed using the GLCM method by calculating the nearest distance between each training and testing data using the Euclidean distance formula.

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