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Mesran
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mesran.skom.mkom@gmail.com
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+6282161108110
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jurnal.json@gmail.com
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STMIK Budi Darma Jln. Sisingamangaraja No. 338 Telp 061-7875998
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Kota medan,
Sumatera utara
INDONESIA
Jurnal Sistem Komputer dan Informatika (JSON)
ISSN : -     EISSN : 2685998X     DOI : https://dx.doi.org/10.30865/json.v1i3.2092
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)
Articles 18 Documents
Search results for , issue "Vol 5, No 1 (2023): September 2023" : 18 Documents clear
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.
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%.
Penerapan Algoritma C4.5 Mengklarifikasi Penerimaan Bantuan Sosial Menggunakan Feature Selection M Wandi Dwi Wirawan; 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.v5i1.6653

Abstract

The Indonesian government's efforts to overcome poverty in Indonesia are through the Smart Indonesia Card (KIP) program which is carried out by the government in the form of providing assistance to underprivileged families. The main aim of distributing KIP assistance is to help send underprivileged children to continue their education, the difficulties found in receiving KIP are due to the large number of residents registering, as well as the data having several conditions, the limited time available in providing KIP by sub-district parties, the completion base is relatively low, therefore the provision of assistance must be right on target. Therefore, the aim of this research is to look for the most influential attributes in receiving KIP assistance in order to improve the results of the data verification process. After carrying out Feature Selection using Information Gain, the most influential attributes can be obtained. The influences are Number of Art, Number of Rooms, Cooking Room, Refrigerator, Motorbike. Therefore, we need to know some of the attributes that most influence the selection of KIP assistance so that we can get accuracy values from decision tree modeling using the C4.5 algorithm or decision tree. Test This experiment can produce a decision tree in which the Number of Art attribute is the most influential attribute with the success rate of KIP acceptance. This evaluation uses a confusion matrix to obtain an accuracy value of 98.21%, precision of 98.21%, recall of 99.48%.
Analisis Sentimen Ulasan Pelanggan Online Ubi Madu Cilembu Abah Nana Menggunakan Algoritma Naïve Bayes Muhammad Rafly Al Fattah Zain; Mia Kamayani
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.v5i1.6646

Abstract

This research aims to analyze the sentiment of online customer reviews for Ubi Madu Cilembu Abah Nana using the Naïve Bayes algorithm. The study has two main objectives: to classify the sentiment analysis of reviews into positive and negative categories regarding the service and products of Ubi Madu Cilembu Abah Nana, as well as to evaluate the accuracy level of the final classification results. The data was collected from online food delivery applications such as Gofood, Grabfood, and Shopeefood. The data used in this study amounts to 259 entries, with 310 positive and 49 negative data points. After conducting experiments, an accuracy result of 86.29% was obtained in Experiment 1 using the Split Data operator, and an accuracy of 86.12% was achieved in Experiment 2 utilizing Cross Validation with the assistance of language experts. The findings of this research indicate that the Naïve Bayes algorithm can be employed to classify customer sentiment towards the service and products of Ubi Madu Cilembu Abah Nana with a significantly high accuracy rate. These results can be valuable for Ubi Madu Cilembu Abah Nana in enhancing their service and product quality based on customer feedback. Additionally, this study also contributes to the field of sentiment analysis and natural language processing by applying classification algorithms to customer review data.
Implementasi Algoritma Knuth Morris Pratt Dalam Pencocokan String Pada Kamus Indonesia–Korea Rakhmat Kurniawan R; Aidil Halim Lubis; Siti Ayu Hadisa
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.v5i1.6149

Abstract

Currently, South Korean culture is very popular with many Indonesians, and the rapid development of Korean culture in Indonesia is currently very widespread and very popular. Many Indonesians even learn Korean to keep up with current trends, but due to the different structure of the language, learning Korean becomes more difficult for most people. The dictionary is an effective guide for translating foreign languages/terms. Conceptually, dictionaries are arranged alphabetically, along with explanations of definitions, uses or translations. This is also required for Indonesian to Hangul Korean translation. Many Indonesian-Korean dictionaries are currently published in printed form, but it is still difficult to use because users have to look up the meanings manually. We need practical and effective new media such as smartphone media. There are many algorithmic methods that can be used to create dictionary applications, one of which is using the Knuth Morris Pratt (KMP) algorithm. With this algorithm, every text to be translated is checked for word search and then a match is found with the appropriate word from the desired word. In this study, the final results of the study found differences in the use of the word hangul in formal and informal forms. In this study, the authors tested the application of the algorithm on an Android-based Indonesian-Korean dictionary application.
Sistem Antrian Pelanggan Menggunakan Metode Jackson Network Queue Mukhamad Niamaskur; Andi Widiyanto; Agus Setiawan
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.v5i1.6741

Abstract

Information systems can be applied in various fields either as the main means or to increase productivity or service quality. One of the uses of technology is that it is used as a means to make it easier for customers to place orders which aims to avoid queues that are too long. Setia Car Spare Parts Store is a provider of car spare parts that has many customers which sometimes makes the customer queue too much. This sometimes makes customers, especially new customers, impatient to queue. To make the queue more orderly, a queuing system will be built to maximize service and increase customer satisfaction which is calculated using the Jackson method. This method was chosen to calculate the time that is considered in accordance with what the customer expects. The queuing system applied to the system built is a single channel FIFO. From the results of system testing carried out, the application of a queuing system with online ordering by applying the Jackson method can enable employees to serve 48 customers in a day with an average of 15 minutes of service time. These results are more when compared to offline services where each employee can only serve 41 customers with an average service time of 17.56 minutes.
Metode TOPSIS Untuk Penerima Bantuan Pendidikan Bagi Mustahik Fakir Devit Satria; Desyanti Desyanti; John Suarlin
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.v5i1.6734

Abstract

Education is mandatory for all levels of society, every parent wants their children to be able to go to school properly, but the roots of education problems generally lie in financing for parents who have relatively low incomes. If conditions like this continue, Indonesia will lose the best generation if there are still many children who do not go to school due to the cost factor. The Dumai City National Amil Zakat Agency (BAZNAS) is one of the Amil Zakat Agencies in Riau Province. The Dumai City Baznas created an educational assistance program for poor families in the form of money to buy school supplies. Mustahik who wish to receive educational assistance must fill out a form and other predetermined conditions. After that, Baznas will select the incoming proposals and carry out the selection process. The large number of proposals caused Baznas to take a long time to make a decision because they had to check the submitted documents one by one, because it took a long time, the proposal for submitting assistance was approved based on the results of the meeting and agreement with the chairman of BAZNAS. So that the results decided are not as optimal as the actual conditions. For this reason, a system is needed that can assist BAZNAS in carrying out the document selection process in accordance with the requirements so that the assistance provided is right on target and can determine priorities for recipients of educational assistance for mustahik. The TOPSIS method is able to provide solutions to problems that occur, from the results of research conducted by Sutjiati Gita Lestari, it is ranked 1st with a value of 0.8041
Prediksi Harga Tandan Buah Segar dengan Algoritma K-Nearest Neighbor Silvi Joya Arditna Br Bukit; Rakhmat Kurniawan R.
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.v5i1.6818

Abstract

Palm oil and its derivative products are a source of foreign exchange for this country, because efforts are needed to maintain and develop the sustainability of palm oil as a potential natural resource. The company carries out statistical analysis on the factors inhibiting the previous month's harvest with a correction value of 5% – 12%. However, this kind of analysis still produces inaccurate prediction results, this is because the calculation process still involves estimation techniques from personal experience, looking at previous production patterns and other determining factors such as land area, principal amount and planting age. As a result, prediction targets often experience errors and production results are excessive or less than the target. Therefore, better predictive calculations are needed in determining palm oil production targets. Accurate predictions can help companies make decisions to increase production output. To carry out forecasting, it is necessary to apply the K-Nearest Neighbor Algorithm which can be used to predict palm oil prices in the future. Based on the results of data mining calculations using palm oil FFB prices from 2018 to 2023 (May 2023), it was concluded that the prediction of palm oil FFB prices in the 67th month (July 2023) had an accuracy level of 10,667 with k=3 and 19,200 with k=5.

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