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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 30 Documents
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Search results for , issue "Vol 4, No 1 (2022): September 2022" : 30 Documents clear
Development of Desktop Application with Three Dimensional (3D) Pageflip Professional Based on Network Design and Construction Class XI TKJ Ayu Hidayati; Dedy Irfan; Asrul Huda
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 1 (2022): September 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4396

Abstract

This research and development aims to produce products in the form of E-Modules or electronic modules based on three dimensions (3d) Pageflip Professional in NETWORK DESIGN AND BUILDING Subjects (RBJ) Class XI Computer and Network Engineering (TKJ) at SMK Negeri 2 Padang. After the validity test has been carried out by the experts, the overall assessment of the validator test on the E-Modul or electronic applicationbased on three dimensions (3d) Pageflip Professional in the NETWORK DESIGN AND BUILDING (RBJ) Subject is 89.94%, so that the level of validity can be interpreted as valid. . The results of the overall practicality test assessment of the E-applicationbased on 3d Pageflip Professional in the NETWORK DESIGN AND BUILDING (RBJ) Eye is 89.50%, so that the practicality level can be interpreted as very practical to use. The results of the overall effectiveness test assessment of the effectiveness of the 3d Pageflip Professional-based E-Modul in NETWORK DESIGN AND BUILDING (RBJ) subjects are 90.63%, so that the level of effectiveness can be interpreted as very effective to use.
Analisis Sentimen Customer Feedback Tokopedia Menggunakan Algoritma Naïve Bayes Aldian Umbu Tamu Ama; Deva Nita Mulya; Yashinta Putri D Astuti; Ignatius Bias Galih Prasadhya
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 1 (2022): September 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4783

Abstract

Products and customers have a close relationship, therefore UMKM need to build good relationships with customers. The most common way that companies or UMKM do is to look at the reviews given, this is called customer feedback. The results of customer feedback to companies or UMKM can improve service and product quality. The problem that arises is how to process the many reviews given, especially reviews from marketplaces like Tokopedia. Therefore, a method is needed to see user reviews of the products being sold, whether positive or negative. The method that will be used is sentiment analysis. Sentiment analysis is the process of understanding and extracting and automatically processing text data and can produce sentiments that are displayed in a sentence. The steps taken were taking House of Smith customer review data at Tokopedia, manual labeling to get positive and negative data reviews, data preprocessing, TF-IDF weighting and classification using the Naïve Bayes algorithm. The results of sentiment testing using the Naïve Bayes algorithm with TF-IDF weighting quality accuracy of 83% with visualization of the distribution of words that appear the most are the words 'good', 'comfortable' and 'use' for positive reviews. The most frequent negative reviews were 'material' and 'thin' which indicated that some buyers felt that the product had a thin material.
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 : STMIK 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.
Deteksi Dini Anak Disleksia dengan metode Support Vector Machine Ardhian Ekawijana; Akhmad Bakhrun; Zulkifli Arsyad
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 1 (2022): September 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4776

Abstract

Dyslexia is a brain disorder caused by genetics. People with dyslexia can live a normal life and even have certain advantages if they get the correct education. People with dyslexia often get the predicate stupid because teachers do not know the case of their students. Early detection of dyslexic children can be done with a series of tests so that the system can conclude that the data is dyslexic or not. Support Vector Machine is a data classification method to share dyslexia test results or not. This system is trained with test results data that are already available using the SVM method. This study uses gamification data to detect dyslexic children or not. SVM proves a good level of accuracy in predictions up to 94%.
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 : STMIK 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.
Analisis Sentimen Vaksinasi Booster Berdasarkan Twitter Menggunakan Algoritma Naïve Bayes dan K-NN Afid Rozaqi; Agung Triayudi; Rima Tamara Aldisa
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 1 (2022): September 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4907

Abstract

Covid-19 or the corona virus has spread throughout the world, one of which is Indonesia. There have been many problems due to this virus for 2 years in Indonesia, and various efforts and policies have been made by the government to control the impact that does not become worse by this corona virus, these efforts are vaccination actions against the Indonesian people, and in early 2022 the government started a new program, namely booster vaccination. Many people are pro and contra to the program on social media Twitter. This study was conducted with the aim of knowing the sentiment of Indonesians towards booster vaccination in Indonesia.The data obtained as many as 2000 tweets obtained from the keyword "booster vaccine" on Twitter. Then the data is divided into training data and test data (training) then made into three different portions, namely 60/40, 70/30, and 80/20. The test results are that the best performance is found in testing a portion of 80% of the training data 20% of the test data using the K-NN algorithm, the test produced the highest value results, namely 78.62% accuracy and AUC 0.845 and categorized as good classification. The results show that the K-NN algorithm model with an 80% portion of training data is the best in the classification of booster vaccination sentiment analysis. The sentiment results in the test data were positive with 303 tweet data and negative sentiment totaled 93 tweet data. The results of more positive sentiments show that booster vaccinations in Indonesia are acceptable and get a lot of support from the Indonesian people on social media Twitter.
Analisis Sentimen Produk Kecantikan Jenis Serum Menggunakan Algoritma Naïve Bayes Classifier Muhammad Hamka; Naila Alfatari; Dhani Ratna Sari
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 1 (2022): September 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4740

Abstract

The increased consumption of beauty products as a lifestyle has increased public opinion on the beauty products used. Generally, reviews are given through posts on social media. This study discusses the classification of sentiment analysis on the use of serum beauty products on Twitter using the Naïve Bayes Multinomial algorithm. Sentiment analysis of serum beauty products is carried out to provide information and preferences to the public regarding the quality of a product. The results of the information and preferences become a reference for consideration in choosing the appropriate serum beauty product. The data used in this study were 27,587 tweets using three keywords, namely "serum," "face serum", and "beauty serum". Tweet data is divided into training data and test data with the number of training data as much as 22,070 tweets and test data as much as 5,518 tweets. The data is categorized using the lexicon senticnet 7 dictionary based on polarity values. The results of the analysis of positive sentiment are 35%, negative sentiment is 63.8%, and neutral sentiment is 1.2%. The classification results using Naïve Bayes Multinomial obtain the highest accuracy value of 80%. The Confusion Matrix results get the highest precision value of 88%, the highest recall of 81%, and the highest f1-Score of 86%.
Analisis Perbandingan Sistem Pendukung Keputusan Menggunakan Metode SAW dan WP Dalam Penilaian Kinerja Tenaga Kontrak Yusril Yusuf; Lukman Bachtiar
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 1 (2022): September 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4421

Abstract

Employees at the Regional Secretariat office of East Kotawaringin Regency are divided into 2, namely Permanent Employees (Civil Employees) and Contract Employees (Contract Workers). Contract workers are employees who have non-permanent employment status, so it is necessary to evaluate the quality of their performance to determine the sustainability of the contract extension. There are 6 assessment criteria that are used as a reference for assessing the performance of contract workers, namely Individual Performance Targets, Service Orientation, Integrity, Commitment, Discipline, and Cooperation. The performance appraisal of contract workers at SETDA Kotim has been computerized, but there is still no method applied to the performance appraisal of contract workers, causing the performance appraisal of contract workers to be unstructured. From these problems, a decision support system is needed to be able to assist the process of assessing the performance of contract workers. The researcher conducted a comparative analysis between the SAW method and the WP method, which is expected to determine the right method to be applied in the performance appraisal of contract workers, and can assist the personnel department in processing the performance appraisal of contract workers. Based on the final calculation results, the SAW method and the WP method can be applied in assessing the performance of contract workers and produce the same ranking order, namely the alternative contract worker named A2 = Akmad Rosidi as the best alternative, followed by the other best alternatives A5, A1, A3, and A4. From the comparison results using the MSE (Mean Squared Error) method, the Weighted Product (WP) method produces a higher deviation value than the Simple Addative Weighting (SAW) method, with a comparison of the deviation values, namely the WP method = 228679.4811, while the SAW method = 227926, 7694. So, the Weighted Product (WP) method can be recommended in assessing the performance of contract workers at the Regional Secretariat of East Kotawaringin Regency.
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 : STMIK 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.
Perancangan dan Implementasi Sistem Pemantauan Suhu dan Ketinggian Air pada Akuarium Ikan Hias berbasis IoT Piter Wijaya; Theophilus Wellem
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 1 (2022): September 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4539

Abstract

Environmental monitoring and control systems of various electronic equipment such as sensors, actuators, televisions, lights, and surveillance cameras are one of the essential applications of Internet-of-Things (IoT). The utilization of IoT has also given birth to the smart home concept, which is realized in the form of home automation, where various equipment at home is equipped with a microcontroller and WiFi module such that they can connect to the Internet and interact with each other. One of the equipment at home that can be monitored and controlled using IoT technology is a fish aquarium which is commonly owned by ornamental fish cultivators or people who have a hobby of taking care of ornamental fish. Taking care of ornamental fish requires special attention to the parameters of temperature and water quality such that the fish can grow well. This study aims to design and implement an IoT-based temperature and water level monitoring system in an aquarium. The hardware in this system is implemented using NodeMCU ESP8266 as the central controller and the WiFi module that connects the system to the Internet, temperature sensor DS18B20, ultrasonic sensor HC-SR04, and relays to turn on and off equipment controlled by the system. In addition, Telegram bots are used to give commands to control equipment and receive notifications from the system. The testing results show that the designed system can work according to predetermined specifications. If the water temperature in the aquarium is outside of a specified range (24°C to 32°C), the system will activate a fan or a heater to adjust the water temperature.

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