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Jurnal Sistem Komputer dan Informatika (JSON)
Published by Sekolah Tinggi Manajemen Informatika dan Komputer Budi Darma
ISSN : -     EISSN : 2685998X     DOI : https://dx.doi.org/10.30865/json.v1i3.2092
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering
The Jurnal Sistem Komputer dan Informatika (JSON) is a journal to managed of STMIK Budi Darma, for aims to serve as a medium of information and exchange of scientific articles between practitioners and observers of science in computer. Focus and Scope Jurnal Sistem Komputer dan Informatika (JSON) journal: Embedded System Microcontroller Artificial Neural Networks Decision Support System Computer System Informatics Computer Science Artificial Intelligence Expert System Information System, Management Informatics Data Mining Cryptography Model and Simulation Computer Network Computation Image Processing etc (related to informatics and computer science)
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 492 Documents
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Penerapan Metode Weighted Product Berbasis Visualisasi Graph Database dalam Merekomendasikan Parfum Isi Ulang Defy Lukbatul Qolbiah; Abd. Charis Fauzan; Tito Prabowo
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 4 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i4.6181

Abstract

Perfume is useful for increasing self-confidence, creating satisfaction, eliminating bad odors, and making self-assessment more attractive. Refill perfumes are made from certain perfume seeds dissolved in a suitable solvent. Perfume has many types and strengths of aroma, but there are obstacles when people want to choose the desired perfume scent. This problem becomes research material because it is expected that this problem can be solved. To determine perfume recommendations, it is calculated using the Weighted Product method and visualized using a graph database. In the Neo4j Graph Database visualization, the perfume category and perfume name are used as nodes and the ranking results are used as edges. From the ranking results using the Weighted Product method, 21 perfumes for each category are entered into the Graph Database visualization and a total of 63 perfumes will appear in the perfume recommendation system.Refill perfume is a perfume made from certain perfume seeds dissolved in the appropriate solvent.
Penerapan Metode Simple Multi Attribute Rating Technique (SMART) Untuk Seleksi Penerimaan Bantuan Usaha Produktif Raihan Mahdy; Fitra Kurnia; Iwan Iskandar; Eka Pandu Cynthia
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 4 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i4.6370

Abstract

Productive business assistance is assistance provided to improve business capabilities, depending on the type of business being running. The goal is to develop work productivity and also increase income. As for the distribution of productive business assistance at BAZNAS Pekanbaru City, it still uses an old system and is not yet effective, so the process takes quite a long process. In order for the selection process to be effective, a decision system was created for the alternative of recipients of productive business assistance. The method in this research using the simple multi attribute rating technique (SMART) method. This research uses 6 criteria and 22 sub-criteria. The application is build with using PHP and MySQL programming languages. The results of the application of the SMART method which has been tested on 10 sample recipients obtained the order of the highest value to the smallest. With the highest value is 0.75. This system has been tested using the Blackbox testing method and the user acceptance test (UAT) with an assessment final value is 94.4%.
Sistem Pakar Diagnosa Gizi Buruk Pada Balita Berbasis Mobile Menggunakan Metode Certainty Factor Afdal Muhammad Efendi; Tengku Khairil Ahsyar; M Afdal; Febi Nur Salisah; Syaifullah Syaifullah
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 4 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i4.6307

Abstract

Maltnutrition has a significant impact on children’s development and is a common problem in developing countries, including Indonesia. There are many factors that contribute to malnutrition, one of which is the lack of understanding and knowledge among parents regarding childcare and proper nutrition. This has motivated the author to develop an expert system application for diagnosing malnutrition in toddlers, aiming to facilitate the community, especially mothers with toddlers, in early diagnosis of malnutrition symptoms and diseases through mobile devices. This expert system application is built using Java Programming language with the assistance of Android studio as the development tool. The system analysis employed is the Unified Modeling Language (UML) to provide an overview of the application to be created. Testing is conducted using the Black Box method and data validation yields nearly 100% accuracy. The calculation for diagnosing symptoms and diseases utilizes the Certainty Factor methode, which serves as the calculation of value within the expert system application. The testing results based on symptoms and diseases through the applied calculation method achieve a 92% accuracy rate. The development of this application is expected to assist the community, especially mothers with toddlers, in identifying early symptoms and diseases of malnutrition in children, as well as obtaining solutions for the experienced illnesses.
Sistem Pendukung Keputusan Menentukan Siswa Berprestasi dengan Metode SAW (Simple Addtive Weighting) Isnia Anjar Setyani; Yoannes Romando Sipayung
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 4 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i4.6179

Abstract

MI Kalirejo is an Islamic Madrasah located in Kalirejo Village, East Ungaran District, Semarang Regency. Based on the number of students who have achievement in academic and non-academic fields, a process is needed to determine student achievement. Currently MI Kalirejo still uses the manual method in the assessment process and only through the results of report cards in determining outstanding students. The author is interested in building a website-based decision support system in determining outstanding students based on predetermined criteria, so that it can help make it easier for school institutions to process and determine appropriate, fast and accurate assessments there are several criteria such as the average value of report cards, attitude scores. This system designs and creates and implements a website-based decision support system using the Simple Additive Weighting method. In this study, researchers collected data throught observation and interviews. Then the researchers used the waterfall method in system development. In testing the system using a black box to obtain accuracy results. The conclusions obtained in making a decision support system in determining outstanding students using simple additive weighting based on a website are obtained alternative values from the result of calculations that have been carried out. The author shows accuracy of 100% using the sample and population of Sugiono’s theory. From the result of calculations using the SAW method, it shows that alternative A2 is obtained by a student named Faeza with a value of 1 in the first rank. Thus alternative A2 students on behalf of Faeza were chosen as the best alternative to achieve achievements as outstanding students at MI Kalirejo. Based on the trials and the resulting values have the same result so that the purpose of making this website has been achieved
Klasifikasi Citra Daging Sapi dan Daging Babi Menggunakan CNN Arsitektur EfficientNet-B6 dan Augmentasi Data M. Fadil Martias; Jasril Jasril; Suwanto Sanjaya; Lestari Handayani; Febi Yanto
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 4 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i4.6195

Abstract

In daily life, beef often serves as a staple food for humans. However, the high and expensive price of beef has prompted traders to adulterate it with pork for the sake of profit. Such adulteration has serious implications in the Islamic religion, where not all types of meat are considered halal (permissible for consumption), such as pork. As a result, consumers often remain unaware that the beef they purchase has been adulterated with pork. At a glance, both types of meat exhibit similar appearance and texture, making them difficult to differentiate. This research aims to classify beef and pork using a deep learning model with the Convolutional Neural Network (CNN) method, combined with data augmentation. The model used is EfficientNet-B6 with variations in the testing scenario. The variations include the ratio of training and testing data, learning rates, and optimizer for EfficientNet-B6. Data augmentation is performed using techniques such as random rotation, shifting, image scaling, vertical and horizontal flipping, and nearest pixel filling. Evaluation results using the confusion matrix show that the model with data augmentation achieves the highest accuracy for the classes of beef, pork, and adulterated samples at 92.00%, while the model without augmentation achieves an accuracy of 91.67%. However, from this experiment, the best scenario to avoid misclassifying pork and adulterated samples as beef can be obtained. This scenario involves a model with data augmentation, a 90:10 data split, SGD optimizer, and a learning rate of 0.01, which achieves the highest precision for the beef class at 96.05%. The research findings demonstrate that the use of data augmentation on images can improve the model's performance, and the model with data augmentation, a 90:10 data split, SGD optimizer, and a learning rate of 0.01 exhibits the best performance in classifying beef images.
Sistem Pendukung Keputusan Dalam Pemilihan Buah Semangka yang Layak Dijual Menggunakan Metode AHP dan PROMETHEE Agil Indriyani; Raissa Amanda Putri
Jurnal Sistem Komputer dan Informatika (JSON) Vol 5, No 1 (2023): September 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i1.6743

Abstract

Watermelon and Melon Buying and Selling Twins is a business that exports watermelons and melons to various cities owned by Mr. Kliwon whose address is at Pulau Gambar Village. In the Watermelon and Melon Buying and Selling Twins, in selecting the best quality watermelons suitable for sale, problems were found, namely that usually because they were affected by high prices, farmers did not prioritize the best quality watermelons and only focused on the number of fruits to be sold and agents had difficulty selecting watermelons. The best quality is suitable for sale, especially for export outside the city. So, with this problem, the author took the initiative to solve the problem correctly and maximize the determination of watermelons that are suitable for sale by designing and building a web-based decision support system by applying the AHP and PROMETHEE methods to help agents determine the best quality of watermelon. The design of this web-based application was carried out by conducting research at the Watermelon and Melon Buying and Selling Twins by collecting data on watermelon fruit and criteria data on watermelon fruit. After the data was collected, each fruit was weighted and ranked and then entered into the application that had been built. Based on the calculation results in this research, alternative weighting using the AHP method helps weighting with a weight scale of 1 - 9 according to AHP provisions. After carrying out alternative weighting, the next ranking is using the PROMETHEE method to get the netflow value, ranking 1 is obtained by 15 with a netflow value of 3,583 and Rank 15 is obtained by fruit 5 with a netflow value of -1.833.
Sistem Pendukung Keputusan Dalam Menentukan Calon Nasabah Penerima Pinjaman Dana Menerapkan Metode TOPSIS dan AHP Sri Yuslina Siregar; Raissa Amanda Putri
Jurnal Sistem Komputer dan Informatika (JSON) Vol 5, No 1 (2023): September 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i1.6744

Abstract

PT. FIFGroup is a company that has obtained permission from the Minister of Finance, where this company carries out business in the field of providing loans in the form of funds. PT. FIFGroup Cikampak is one of several branches in other cities, as a prospective customer there are 5 criteria that must be considered and have been determined, namely according to the prospective customer's income, collateral for the prospective customer, employment, needs and term of borrowing funds. However, when determining potential customers who will receive loan funds, PT.FIFGroup Cikampak still uses manual methods, such as analyzing the conditions attached when applying for funds. In order to avoid errors in customer decision making, a web-based decision support system is needed to provide information quickly and precisely regarding the criteria for prospective customers. This decision support system uses a combination method, namely Topsis (Technique for orders preference by siilatyt ideal solution) and AHP (Analytical hierarchy process), this system can automatically recommend potential loan recipient customers who comply with predetermined criteria. Prospective customers who receive loan funds in this system will produce a ranking based on Topsis and AHP calculations. Based on calculations using the AHP method from the five criteria elements, the alternative weightings use a satty scale weighting of 1-9 according to the provisions of the AHP method. Then the ranking was carried out using the topsis method, resulting in the first rank being the name of the Misno customer with a manual priority of 0.729 and a system of 0.729, the lowest value or lowest ranking of the 15 alternatives, namely Sri Irma Naibaho manual priority of 0.204 and system of 0.204. The design of the decision support system has been successfully built using the Topsis and AHP methods, based on the results of Black Box testing, the system runs very well as desired.
Implementasi Teorema Bayes Pada Sistem Informasi Posyandu Dalam Mendeteksi Stunting Pada Balita Dedi Gunawan; Verania Nur Andika
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 4 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i4.6146

Abstract

Abstract–The management of posyandu data in Majegan Village is still carried out manually. This causes health monitoring to be not optimal, especially in detecting stunting in toddlers. One of the efforts to overcome this problem is to provide a posyandu information system that can make it easier for posyandu officers to record and analyze fetal growth until toddlerhood and can detect symptoms of stunting. Through the implementation of Bayes' theorem in a web-based application, stunting symptoms can be observed earlier. Bayes' theorem calculates the values of the symptoms experienced by toddlers so as to obtain the results of probability numbers that can be used to predict stunting in toddlers. System design uses the waterfall method which goes through the stages of SDLC (System Development Life Cycle). After the system was developed, to test the quality of the application and the accuracy of naïve bayes in predicting stunting, two types of testing were carried out, namely black box testing and system usability testing (SUS). The black box test results show that the application functionality runs well with an error percentage of 0%, while the SUS test results show that the application has a usability level at Level B which means the application can be used and help users. Meanwhile, the results of the prediction of naïve bayes produced the model with the highest prediction of 60%.
Sistem Pemantauan Suhu, Kelembapan Udara dan pH Air pada Rumah Anggur berbasis Internet of Things Menggunakan Aplikasi Website Mislaini Mislaini; Ikhwan Ruslianto; Kasliono Kasliono
Jurnal Sistem Komputer dan Informatika (JSON) Vol 5, No 1 (2023): September 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i1.6675

Abstract

Grapes are plants that are difficult to grow in tropical climates. It requires specific enviromental conditions as well as special care, with optimal growth of grapes occuring in lowlands (0-300 masl) with a humidity score ranging from 75% - 80% humidity and temperatures between 23°C - 31°C, and a water pH level from 5.5 pH - 7.3 pH. To achieve these ideal conditions, technology in the form of an Internet of Things (IoT) system and a greenhouse is used in order to monitor and control the grapes' growing environment. The use of this technology aims to improve efficiency and productivity by taking into account the temperature, humidity and water pH level as factors which affect the growth, quality, and yield of grapes. Research result shows that the use of IoT technology in controlling temperature and humidity air effectively increases the productivity of grapes. This can be seen from the increase in the number of leaves, stem length, and number of shoots on grapes that were monitored and controlled by the IoT system. The results of testing the accuracy of each sensor by conducting 15 experiments show that the average water pH measurement accuracy is 0.1%, while temperature measurements and air humidity has an average accuracy of 0.1% and 0.3% respectively. In addition, the average response time of the system in controlling mist makers, fans and pumps alkaline is 3 seconds based on 15 tries.
Penerapan Seleksi Fitur Untuk Klasifikasi Penerima Bantuan Sosial Pangkalan Sesai Menggunakan Metode K-Nearest Neighbor Muhammad Fauzan; Siska Kurnia Gusti; Jasril Jasril; Pizaini Pizaini
Jurnal Sistem Komputer dan Informatika (JSON) Vol 5, No 1 (2023): September 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i1.6654

Abstract

The inability to fulfill basic human needs is how poverty is defined. To address this issue, the indonesian goverment implements various social assistance programs, one of which is Kartu Indonesia Pintar (KIP), aimed at providing free education to children aged 7-18 who are economically disadvantaged. However, in the distribution of aid in the Pangkalan sesai sub-district, distributing officers often face challenges due to the high number of eligible recipients applying, complex data requierements, and limited time for the officers. Distributing this social assistance accurately is crusial. Therefore, this research aims to determine the accuracy value for the data of potential recipients of the Kartu Indonesia Pintar (KIP to enhance the data verification process’s outcomes. To tackle this issue, the research employs the K-Nearest Neighbor (K-NN) algoritm and also employs feature selection using Information Gain to reduce less influential attributes. The data used consists of 1998 records of KIP beneficiaries from the 2023 in excel format, with 33 attributes. After performing data cleaning an Information Gain-based feature selection, the dataset is reduced to 1675 records, with 5 selected attributes. The best classification result in this study is achieved with ratios of 7:3 and 8:2, and a value of k = 5, yielding the highest accuracy of 98,21%. The lowest accuracy is obtained using a ratio of 9:1 with the same k value when not using Information Gain, resulting in an accuracy of 89,82%.

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