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INDONESIA
Journal of Computer System and Informatics (JoSYC)
ISSN : 27147150     EISSN : 27148912     DOI : -
Journal of Computer System and Informatics (JoSYC) covers the whole spectrum of Artificial Inteligent, Computer System, Informatics Technique which includes, but is not limited to: Soft Computing, Distributed Intelligent Systems, Database Management and Information Retrieval, Evolutionary computation and DNA/cellular/molecular computing, Fault detection, Green and Renewable Energy Systems, Human Interface, Human-Computer Interaction, Human Information Processing Hybrid and Distributed Algorithms, High Performance Computing, Information storage, Security, integrity, privacy and trust, Image and Speech Signal Processing, Knowledge Based Systems, Knowledge Networks, Multimedia and Applications, Networked Control Systems, Natural Language Processing Pattern Classification, Speech recognition and synthesis, Robotic Intelligence, Robustness Analysis, Social Intelligence, Ubiquitous, Grid and high performance computing, Virtual Reality in Engineering Applications Web and mobile Intelligence, Big Data
Articles 443 Documents
Penerapan Keran Wudu Otomatis pada Optimasi Penggunaan Air dengan Sensor Ultrasonic Berbasis Arduino dengan Sistem Back Up Daya Otomatis Nurhikmah Fajar; Nur Azhary Iriawan Eka Putra; Isminarti Isminarti; Mohamad Ilyas Abas
Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i1.4426

Abstract

A resource is a potential value possessed by a particular material or element in life. Water is a resource that is a basic human need for survival, both for living needs and spiritual needs, even up to the era of modern technology. The level of human well-being is measured by the fulfillment of social, economic, and spiritual needs, including the need for automated technology to make work easier and more efficient. The need for automatic equipment in every field is increasing due to considerations of its practical and efficient nature, including spiritual needs. Spiritual activities that can apply automatic technology include the ablution process. The ablution is a mandatory routine activity. Water users in the process of taking wudu water are not optimal because when they want to perform wudu the tap lever is immediately turned, while they still need time to prepare themselves, for example by removing the hijab or rolling up the sleeves of their clothes. The water will flow continuously until the ablution process is complete and the tap lever is turned to close the water flow. So, in this case, a lot of water is wasted. Applying automatic technology to the wudu faucet requires a continuous supply of electricity so that it always remains operational by providing a backup power supply that charges automatically so that the wudu process can be carried out at any time. The use of Arduino and the PING HC-SR04 ultrasonic sensor as an object distance detector can make the tap automatic and therefore practical. The working principle of this automatic faucet is that the solenoid will activate when the sensor detects an object under the faucet at a distance of 5 to 40 cm. The maximum detection angle is 10°. The average efficiency of automatic faucets compared to manual faucets is ±30.09%.
Sistem Pemilah Otomatis Tingkat Kematangan Buah Kelapa Sawit Menggunakan Metode Logika Fuzzy Mamdani Dan Sensor TCS3200 Salma Salsabilla; Irma Nirmala; Tedy Rismawan
Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i1.4449

Abstract

The palm oil sector has a strategic impact on the growth of Indonesia's economy, because the fruit of palm oil produces oil which can be used as alternative fuel, food oil and basic materials for various industries. Currently, oil palm fruit is sorted manually based on color, which takes much longer. As a result, a system was created to categorize oil palm fruit according to their state of maturity. This system uses the TCS3200 sensor as the main sensor to detect the color of oil palm fruit and implements the Mamdani fuzzy logic method to classify it. Arduino Uno can control the hardware components used in the system. Data obtained from RGB color values ​​(red, green, blue) obtained by the TCS3200 sensor is used as input in the system. Meanwhile, the outcomes this system produced are in the form of maturity levels of oil palm fruit which are classified into 3 categories, namely unripe, ripe and past ripe. Based on tests carried out with the confusion matrix, the accuracy value obtained was 95.6%.
Penerapan Metode Evaluation based on Distance from Average Solution (EDAS) dalam Optimalisasi Layanan dan Pemasaran Coffeeshop Yerik Afrianto Singgalen
Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i1.4460

Abstract

Business owners of coffee shops that fall under the Micro, Small, and Medium Enterprises (MSMEs) employ marketing methods to attract more clients to satisfy the demands and preferences of coffee enthusiasts. However, consumer purchasing behavior demonstrates the difficulty in evaluating marketing performance. In light of this, this study employs the Distance from Average Solution Evaluation Method (EDAS). Meanwhile, coffee shop business brands observed and used as alternatives in this study are Coffee Tanem, 1915 Koffie-Huis, Friends of Coffee Salatiga, Dusk Koffie Salatiga, and Street Side Coffee Salatiga. The results of this study show that the EDAS method can be used to optimize coffee shop business services and marketing as a strategic step in strengthening and improving the performance of the coffee shop business or business. In the context of testing the EDAS decision model, each alternative is assigned a random code (A1-A5). Coffee varieties (C1), aroma and roasted level (C2), serving technique variants (C3), beverage prices (C4), and coffeeshop locations (C5) are often employed as criteria, with categories C1–C3 representing advantages, and C4–C5 representing expenses. Based on the EDAS method's calculation results, it can be seen that the top-ranking coffee shops are those that offer a variety of coffee bean varieties (robusta and arabica), various aromas, and roasted levels (light, medium, dark), various serving methods using espresso machines and manual brew, affordable drink prices, and strategically located coffee shops with enough parking. Thus, it is advised that coffee shop business experts assist in improving capital capabilities and business performance and optimize marketing mix components in STP (Segmenting, Targeting, Positioning) marketing strategies to increase trust, sales volume, consumer satisfaction, and loyalty.
Kombinasi Metode Evaluation Based on Distance from Average Solution (EDAS) dan Rank Order Centroid (ROC) Dalam Pemilihan Konten Layak Tonton Untuk Anak Usia Dini Ben Rahman; Isfauzi Hadi Nugroho; Rima Ruktiari Ismail; Rito Cipta Sigitta Hariyono; Nurul Mega Saraswati
Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i1.4464

Abstract

YouTube accommodates videos on almost any topic, including entertainment, guides, music, personal vlogs, news, short films, documentaries, and other variations. This allows users to access content according to their interests and needs without significant restrictions. However, the issue of unsuitable content for children on YouTube has become an increasingly prevalent topic of discussion. The main issues related to unsuitable content for children on YouTube involve videos containing inappropriate material, violence, abusive language, and false or misleading information. While efforts have been made by YouTube to address this issue, it remains a concern given the large number of videos uploaded every day. In selecting YouTube content for early childhood, there are several criteria, including safety feasibility, interesting animation, interactivity, educational value, and positive value. Thus, this research emphasizes the importance of the existence of a decision support system in helping with the selection of YouTube content suitable for children. Decision Support Systems (DSS) use data analysis methods and various algorithms to process available information and data. The author applies a combination of EDAS (Evaluation Based on Distance From Average Solution) and ROC (Rank Order Centroid) methods to select the most appropriate and safe YouTube content for young children. This approach is used to rank each assessed piece of content. This resulted in the YouTube content "Lagu Anak Indonesia Balita" getting the top rank on alternative A8 with a maximum value of 1.00000, making it highly recommended for early childhood.
Implementasi AES ECB dan Hashing MD5/SHA-256 Pada Aplikasi Penyuratan Android Fajar Febriyadi; Fitra Kurnia; Nazruddin Safaat Harahap; Febi Yanto; Pizaini Pizaini
Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i1.4505

Abstract

The Riau Ministry of Religion Regional Office is still archiving assignment letters and official travel letters manually. The staff who take care of the correspondence section, namely personnel and legal unit staff, do not have an application that facilitates the activities of assignment letters and official travel letters to simplify filing and data containing certain information contained in letters which include assignment letters and official travel letters. Security is important because it relates to data. Therefore, a correspondence application was created to support the correspondence activities of the Riau Ministry of Religion Regional Office and make it easier for staff in the Civil Service and Legal unit to properly manage assignment letters and official travel letters as well as control books. Android application development uses the waterfall method and the ECB (Electronic Code Book) mode AES algorithm and MD5/SHA-256 hashing for security. By building this application, it will be easier for leaders and employees to exchange letters and confidential information, guaranteed security and the application built can be used by users easily. The results of the Black Box testing carried out on the application produced the expected output and the UAT test obtained a score of 89%. Application testing on sentences, Jpg, Png and PDF files has a fairly high level of security using statistical analysis methods, namely bit frequency testing, autocorrelation, 0/1 bit distribution, entropy.
Perbandingan Jarak Metrik pada Klasifikasi Jamur Beracun Menggunakan Algoritma K-Nearest Neighbor (K-NN) Andre Suarisman; Alwis Nazir; Fadhilah Syafria; Liza Afriyanti
Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i1.4511

Abstract

Mushrooms are organisms from the kingdom fungi that have a fleshy body structure and can be consumed, but there are some species of mushrooms that are not safe to eat and have specific characteristics, so distinguishing between edible and poisonous mushrooms can be tricky due to the almost identical appearance of various mushroom species. Errors in identifying edible mushrooms can impact the health of consumers who consume the mushrooms. Evaluating the performance of various methods on a dataset is a key step in determining the most suitable classification method. This research is about how to measure the performance of classification methods on toxic mushroom datasets using the K-Nearest Neighbor algorithm with several metrics such as euclidean, manhattan and minkowski, which is a method for classifying new data based on proximity to existing training data. The results obtained in this study with several distance metrics can be concluded that the accuracy value of the manhattan metric is better than the euclidean and minkowski metrics. Because the manhattan metric gets the highest accuracy result of 99% with K = 100 and the lowest 82% with K = 3000, while the euclidean metric gets accuracy results with a value of 98% with K = 100 and 72% with K = 3000, and the minkowski metric gets accuracy results with a value of 96% at K = 100 and 64% at K = 3000.
Implementasi Alat Pemantau Debit dan Ketinggian Air Sungai Berbasis Internet of Things Untuk Penanggulangan Banjir Cep Lukman Rohmat; Odi Nurdiawan; Irfan Ali; Arif Rinaldi Dikananda; Athhar Hafizha Luthfi; Eti Rohayati
Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i1.4518

Abstract

The increasing frequency and intensity of floods in Cirebon City demands innovative solutions to reduce the impact of damage and risks to society and infrastructure. requires the latest approaches to risk management and prevention. This research focuses on the implementation of an Internet of Things (IoT)-based river discharge and water level monitoring tool designed to improve flood detection and prevention capabilities in Cirebon City. The main problems faced include accurate measurements, real-time monitoring, and rapid response to river water fluctuations. By combining the latest sensors and IoT technology, this tool is able to provide accurate data about water discharge and river levels continuously. The first stage in developing the Internet of Things (IoT) is identification and study of flooding problems in Cirebon City and analysis of the need for a monitoring system for flood prevention. Second, design a monitoring tool concept that meets the needs and specifications and determine the type of sensors, hardware and IoT technology that will be used. Third, choose a sensor to measure river discharge and water level. Fourth, build a monitoring tool prototype based on conceptual design. Fifth, Testing and Validation. The results of this research are based on river tests in the city of Cirebon, there are 4 rivers that frequently flood and the results of the test are that the Kalijaga River has a height of 20cm in the Safe level category, the Kedung Pane River has a height of 15cm in the Safe Level Category, the Kesunean River has a height of 10cm in the Safe Level Category and the Sukalila River has a height of 17cm in the Safe level category this is influenced by dry weather. Then the data collected from monitoring tools can be used to analyze flood patterns, trigger factors and impacts. Then, from this data, a flood classification analysis can be carried out based on the level of river water discharge, so that it can be classified as light, medium or heavy floods based on the amount of water flowing.
Penerapan Metode Clustering Dengan K-Means Untuk Memetakan Potensi Tanaman Padi di Sumatera Irma Sanela; Alwis Nazir; Fadhilah Syafria; Elin Haerani; Lola Oktavia
Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i1.4523

Abstract

Rice plants are the primary source of rice, the staple food for the majority of the Indonesian population. Despite the presence of other food alternatives, rice remains irreplaceable for those accustomed to consuming rice. According to data from the Food and Agriculture Organization of the United Nations (FAO) in 2018, Indonesia is the third-largest rice producer in the world, with a total production of 59.2 million tons. However, urban and agricultural spatial planning is not yet fully integrated, resulting in often conflicting decisions in land use planning for agriculture and urban development. To meet the rice demand in Sumatra, efforts are needed to increase rice production in each province. Therefore, this research aims to map the potential for rice cultivation in Sumatra based on production and harvest results from 1993 to 2020. The method used in this study is K-Means, which allows the grouping of rice potential areas into three categories: high, medium, and low. The research results produced three clusters, evaluated using the Davies Bouldin Index (DBI) with a value of 0.3943. The clustering results indicate that Cluster 0 contains 92 areas with a high success rate, Cluster 2 comprises 84 areas with a medium success rate, and Cluster 1 consists of 48 areas with a low success rate. The category of low success rate is found in Cluster 1 with 48 areas. Cluster 0 includes Aceh, North Sumatra, West Sumatra, South Sumatra, and Lampung within certain time periods. Cluster 1 encompasses other areas with different characteristics. Cluster 2 includes the provinces of Riau, Jambi, and Bengkulu.
The Implementation of MOORA method in the Selection of Direct Cash Aid Recipients Tri Pratiwi Handayani; Irawan Ibrahim; Hilmansyah Gani; Moh. Nasrul Arief Setiawan Adam; Mohamad Ilyas Abas
Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i1.4527

Abstract

This research aims to implement the Multi-Objective Optimization on The Basis of Ratio Analysis (MOORA) algorithm as a Decision Support System for selecting recipients of Direct Cash Assistance in Cempaka Putih village, Gorontalo. With a dataset of 112 prospectus recipients, the study focuses on developing an efficient approach to assist the village head in the beneficiary selection process. By combining multi-objective optimization and ratio analysis, the MOORA algorithm objectively evaluates and ranks recipients based on eligibility and suitability. The findings demonstrate the effectiveness of MOORA in streamlining the selection process, ensuring transparency and optimizing resource allocation for those most in need. This research contributes to decision support systems by showcasing the practical application of MOORA, enhancing assistance distribution, and improving community welfare. The results show that Alternative A1 receives the highest ranking, which is 1, with a Yi value of 1.32. Therefore, Alternative A1 is recommended as the best candidate to receive direct cash assistance in the Cempaka Putih village. The method has the capability to rank the top 12 suitable candidates who are eligible to obtain direct cash aid. However, there are instances where certain Yi values match, resulting in the same ranking for those alternatives. This similarity necessitates further observation and analysis.
Penerapan Metode Support Vector Machine (SVM) Dalam Klasifikasi Produktivitas Padi Hamim Tohari; Sri Harini; Muhammad Ainul Yaqin; Irwan Budi Santoso; Cahyo Crysdian
Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i1.4538

Abstract

Indonesia is one of the largest rice producing countries in the world. Almost 95% of the Indonesian population consumes rice as a mandatory staple food, so that every year the demand for rice increases along with the increase in population. East Java is known as the largest rice producing province in Indonesia. To optimize rice production, Central Java province can group rice producing cities or districts. This aims to see and find out cities or districts that have the potential to produce rice as well as find out areas that have less than optimal rice production. To see whether the need for rice in East Java province is met, it is necessary to predict rice productivity in the East Java region so that it can be used as a basis for efforts to increase rice yields for the next period. In this research, the Support Vector Machine (SVM) method was used to classify data for predicting crop yields in East Java province. The advantage of the SVM algorithm is that it can be used for classification and regression problems with linear kernels or non-linear kernels. The data used is agricultural statistical data obtained from the website jatim.bps.go.id. The data is then analyzed using a data mining process. The results of this research are in the form of a prediction pattern with a decision tree which can be used as a basis for predictions in estimating harvest results in the next period. From dividing 80% training data and 20% testing data, results were obtained with 80% accuracy when predicting category '0' (not on target), and 100% accuracy when predicting category '1' (on target). And overall, the classification model has an accuracy of 88%. The contribution to be achieved in this research is to provide ideas for data processing in the agricultural sector.