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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 755 Documents
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Seleksi Fitur untuk Prediksi Hasil Produksi Agrikultur pada Algoritma K-Nearest Neighbor (KNN) Delvi Nur Aini; Bella Oktavianti; Muhammad Jalal Husain; Dian Ayu Sabillah; Said Thaufik Rizaldi; Mustakim Mustakim
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 4 No. 1 (2022): September 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4813

Abstract

Agriculture is one of the largest economic driving sectors in Indonesia. The Central Statistics Agency (BPS) in 2021 recorded that 37.02% of Indonesia's population worked in the agricultural sector. The problem faced by farmers today is the decline in yields, both in quantity and quality due to unpredictable weather, making it difficult for farmers to choose the types of plants that are suitable for planting. The application of data mining techniques has problems related to the complexity of weather parameters and natural conditions that support agricultural production, so it is very important to do feature selection, namely to form the most relevant features. This study conducted an experiment to determine the effect of implementing the Principal Component Analysis (PCA) selection feature on the performance of the K-Nearest Neighbor (KNN) algorithm which produces the highest accuracy of 99.64% in this study.
Monitoring dan Kontrol Pemberian Pakan Air Tawar Menggunakan Internet Messaging Secara Real time Yakobus Dapi; Ikhwan Ruslianto; Suhardi Suhardi
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 4 No. 1 (2022): September 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4821

Abstract

One important aspect that must be considered in freshwater aquaculture is the feeding of the fish. However, in its implementation, fish feeding is generally still done conventionally, farmers must sprinkle feed every day with an irregular amount of feed and time. The next problem is the limitations of humans as fish farmers to carry out several activities at the same time and in separate places. Therefore, a system was created that can monitor and control the feeding of fish in real time using Internet Messaging based on the Internet of Things via Telegram. NodeMCU ESP32 is used as overall system control. The hardware used to open and close the fish feed gap is a Tower Pro Micro Servo 9g SG90 360 Continuous type servo motor. The HC-SR04 Ultrasonic Sensor Device is used to determine the remaining feed in the storage container when the feed execution is complete. The test results showed that fish feeding was successfully carried out with the average weight of automatic feeding scheduled every 07.01 WIB and 16.01 WIB was 4 grams, and 6.17 grams for manual feeding. Detection of residual fish feed was also successfully carried out with an average error value of 27.74%. Then, the average response time during execution of opening the feed gap is 3.36 seconds and 3.46 seconds to close the feed gap.
Penerapan Metode Multi-Objective Optimization On The Basis Of Ratio Analysis (MOORA) Dalam Menentukan Bintara Polri Di Sumatera Utara Soeb Aripin; Ria Zulkarnaen Harahap
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 4 No. 1 (2022): September 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4822

Abstract

Selection of candidates for police officers is carried out by police institutions throughout Indonesia, with the aim of improving the quality of personnel. In this recruitment, the North Sumatran National Police prepare a large quota for the National Police NCO. The criteria sought in this recruitment are to meet the aspects of capability, potential ability, creativity, basic character and sincerity in carrying out their duties. The North Sumatra Regional Police is one of the government institutions that utilizes the development of technology and information, namely the creation of a system for the selection of non-commissioned officers. The problem that is often found in the North Sumatra Regional Police is that the selection of BINTARA so far is still considered less than optimal. The problem was because the examiners at the time of selection were still using the manual system. The manual system in question is that an examiner must first go to the office to take a list of the scores of the selection participants and then take it to the test location which is quite far from the SUMUT POLDA office. After that, the examiner must fill in the list of participants' scores at the test location and return it to the SUMUT POLDA office. The list of values will then be processed by the admin on duty in the office, then after processing, the results of the exam will be obtained. To determine how to select candidates for the National Police, the Decision Support System can be used. The research method used is the Multi-Objective Optimization On The Basis Of Ratio Analysis (MOORA) method. The result of this study is to find out that Academic, Psychology, Health and Equality (Physical) have a very large influence in determining the selection of the National Police officer candidate in North Sumatra.
Penerapan Framework Bootstrap Dalam Sistem Informasi Rekam Medis Data Posyandu dengan Metode Waterfall Yunus Anis; Purwatiningtyas Purwatiningtyas; Retnowati Retnowati; Elsa Awalin Nur Fajrina
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 4 No. 2 (2022): Desember 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i2.4833

Abstract

Bootstrap is a combined framework of CSS and JavaScript that is offered as an alternative among other frameworks with the intention of providing consistency to the interface development stage in building a website, one of which is the website at the Posyandu Kemuning Gajah Village. The problems that arise are related to recording visitor data manually in the register book, which is often done because there are so many things that must be recorded such as weight, developmental data for mothers, children under five, maternal development data, other personality data related to pregnant women and toddlers visiting posyandu. . For this reason, it is necessary to support an information system for recording participant activities so that the number of participants does not need to be developed in data processing and re-accessing so that data redundancy does not arise. The system that will be created using the bootstrap framework includes the participant registration process and data processing for posyandu participants, so that they are able to manage data and generate data reports in a valid and correct manner. Testing with the blackbox method shows that the entire system built from the implementation of the login form to the print report shows that everything has been successfully implemented in the system.
Analisis Data Mining Klasifikasi Berita Hoax COVID 19 Menggunakan Algoritma Naive Bayes Fani Prasetya; Ferdiansyah Ferdiansyah
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 4 No. 1 (2022): September 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4852

Abstract

The rapid dissemination of information along with the rapid development of technology along with the massive speed of electronic media and the internet. But the rapid spread of news cannot guarantee that the information and news that we get can be validated from valid sources. Based on data released by Kominfo at the end of 2021, there were 1773 hoax news that were successfully clarified from the hoax news. Then during the Covid-19 pandemic itself, there were various hoaxes circulating in the community. Throughout 2021, the Ministry of Communications and Informatics discovered as many as 723 hoaxes about Covid-19. Based on the background above, the researchers and previous studies have discussed hoax detection in various fields. Such as, fraud detection in online writing style [1], classification of hoax news based on machine learning [3] and the application of nave Bayes and PSO algorithms for classification of hoax news on social media [4]. From here the researchers tried to carry out experiments on the nave Bayes classification algorithm to classify hoax covid 19 news. Based on the results of research that has been done, the nave Bayes model and cross validation can classify hoax news well, the resulting accuracy is 86.3% where 80-90% included in the good classification criteria. The data that is predicted to be incorrect is also not too much from a total of 300 datasets, only 41 are declared incorrect in labeling less than 2% of the total dataset, so it can be concluded that this model can be used as a reference if you want to proceed to a more complex prediction model, for example the model prediction using web-based machine learning.
Sistem Pendeteksi Keamanan Ruangan “Smart Security” Dengan Metode Fuzzy Logic Menggunakan Sensor PIR Berbasis Internet of Things (IoT) Rima Tamara Aldisa; Sechan Alfarisi
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 4 No. 1 (2022): September 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4862

Abstract

The system is an attempt to assist in detection using sensors, an effort made for a room or house if people come or enter. A tool is designed that can be easy, affordable and can be used to prevent the danger of unknown people from entering the room or even into our homes. The author designed a "Smart Security" Room Security Detection System Using the Fuzzy Logic Method Using Internet of Things (IoT)-Based PIR Sensors. sending messages if someone enters the room or house so that the owner knows if someone is unknown. The author wants to design and make this tool that can be very helpful for use inside or at home in order to minimize the danger of people who cannot be recognized entering, room security detectors here with a distance of 1 cm to 2 meters the sensor can still be detected, if it exceeds 2 meter then the sensor will not read if anyone comes.
Implementasi Metode Perbandingan Eksponensial (MPE) Pada Sistem Pendukung Keputusuan Pemilihan Internet Protocol Camera Umbar Riyanto; Nurdiana Handayani; Mohammad Imam Shalahudin
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 4 No. 1 (2022): September 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4875

Abstract

The development of video surveillance has given rise to various types of surveillance cameras, one of which is the Internet Protocol Camera (IP Camera). The number of IP Camera brands in the market, makes people who want to buy IP Cameras have to find their own information about the specifications and capabilities of the IP Camera to be purchased. It takes time and effort to choose an IP Camera, because you have to learn one by one which IP Camera to buy. This study aims to build a decision support system for choosing an IP Camera with a website-based Exponential Comparison Method (MPE) to make it easier to determine the right IP Camera. MPE can sort the priority of decision alternatives on existing criteria and is able to distinguish the value of each alternative in contrast. Based on the case study, the best alternative is Xiaomi Mi 360 with a value of 386, followed by Yi Home Camera 3 getting a value of 369, Ezviz C6N getting a value of 350, Imilab EC4 getting a value of 343 and Cleverdog Egg Cam getting a value of 110. The results of the MPE calculation generated by the system shows the same value as the manual calculation, then the MPE calculation on the system is declared valid. In addition, the test results with black-box testing show that the system can run well.
Implementasi Algoritma Frequent Growth (FP-Growth) Menentukan Asosiasi Antar Produk Rangga Yogasuwara; Ferdiansyah Ferdiansyah
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 4 No. 1 (2022): September 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4894

Abstract

Data accumulation is caused by the amount of transaction data stored. By utilizing the sales transaction data in the database, the data can be further processed into useful information for managers to make decisions. With the existence of data mining, it is hoped that it can help the Leaning Shop to find the information contained in the transaction data into new knowledge. Association Rule, which is a procedure in Market Basket Analysis to find relationships between items in a data set or it can be said that this association rule aims to find a collection of items that often appear at the same time and display them in the form of consumer habits in shopping. The FP-Growth algorithm is an algorithm that can be used to determine the data set that appears most often (frequent itemset) in a data, in the search for frequent itemset in a data set by generating a prefix-tree structure or often called the FP-Tree. From the test results it can be concluded that the application of data mining using the FP-Growth Algorithm can be used to analyze consumer spending patterns.
Implementasi Logika Fuzzy Untuk Pendukung Keputusan Sistem Penyiraman Otomatis Tanaman Anthurium Dina Meliana Saragi; Faqih Hamami; Tatang Mulyana
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 4 No. 1 (2022): September 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4895

Abstract

Anthurium is a class of ornamental plants that are admired by many lovers of ornamental plants, this plant is cultivated on a wide scale in the floriculture industry. There are factors that support the current high price of anthurium plants, first, a unique species with a ratio of 10% of anthurium seeds that grow exactly the same as the parent. In addition, anthurium growth is very slow and difficult to care for. Other factors must be considered in the cultivation of anthurium plants, namely air temperature, humidity, sunlight, acidity (pH) and water requirements. This anthurium plant is a plant that is sensitive to water so it requires supervision of regular watering so that the plant does not die. Farmers need advanced expert knowledge in making different decisions related to agriculture, especially in dosing and timing of crop watering. Therefore, in this study, researchers designed fuzzy logic according to the needs of anthurium plants with a rule base that can change IoT sensor data in the form of DHT11 sensors and Soil Moisture Sensors FC-28 into the output of a decision on the duration of plant watering. In this stage, the process of fuzzification, inference and defuzzification. The results obtained during this research are comparative testing of 15 values from the output devices that are taken at random approximately closer to the values from the simulation with MATLAB with a total difference of 8.61% due to the difference in calculations between IoT devices and simulations with MATLAB, but this can still be categorized accurately because the output results of the MATLAB tool and simulation are still within the range of membership function values.
Implementasi Moving Average dan Kalman Filter pada Wireless Odometer untuk Informasi Service Kendaraan Bermotor Fajar Alif Chalifatullah; Wahyu Setyo Pambudi; Ilmiatul Masfufiah
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 4 No. 1 (2022): September 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4899

Abstract

Regular maintenance is one step to keep your car looking good, but many people still underestimate the importance of regular maintenance. A tool called Wireless Odometer has been created which can notify vehicle owners through the application if the vehicle mileage has entered the recommended criteria for periodic servicing. Based on previous research, Wireless Odometer still has weaknesses. sensor readings on this tool still have an error of 13.2% so it is still less accurate if applied to measure mileage on vehicles. It is necessary to have a digital filter that must be added to the sensor readings so that the sensor is resistant to noise that occurs due to mechanical or electrical. In this research, we implement the Moving Average Filter and Kalman Filter methods for sensor readings on the Wireless Odometer. After several tests were carried out, it was found that the percentage of reading errors when filtered reached 0.80% using the Kalman filter method and 1.81% using the Moving Average Filter method. It can be concluded that the filter that is suitable for use on this Wireless Odometer is the kalman filter.

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