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Journal of Computer System and Informatics (JoSYC)
Published by Forum Kerjasama Pendidikan TInggi
ISSN : 27147150     EISSN : 27148912     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Industrial & Manufacturing Engineering
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
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 443 Documents
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Rancang dan Bangun Sistem Pembersih Permukaan Panel Surya Otomatis dengan Sistem Elektromekanis Cerdas Aripin Triyanto; Heri Kusnadi
Journal of Computer System and Informatics (JoSYC) Vol 4 No 3 (2023): May 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i3.3287

Abstract

The influence of weather changes on the cleanliness of solar panel surfaces is a problem that must be faced at this time. One of the factors that can affect the output value of roof photovoltaic efficiency is the level of dust density found on the photovoltaic surface. Solutions that can be used as a panel surface cleaner can use an automatic cleaning system to overcome the amount of dust on the photovoltaic surface. The method used in this study uses the Arduino Amega328p component, GP2Y1010AU0F sensor, Arduino drive, and real-time testing. There is a dust sensor and a voltage sensor to determine the amount of dust density on the photovoltaic surface, while the voltage sensor can be used as a reader of the voltage output on the photovoltaic. This research aims to help humans work in cleaning rooftop solar panels and create a system for detecting the thickness of dust and dust cleaners to increase the efficiency value of solar panels from solar radiation absorbed on the surface. The results of the PWM research with a duty cycle of 100% Vout 11.72 Volts, Dust Density of 0.54 mg/m3 produce analog data of 3.75 Volts and an ADC value of 767. Meanwhile, an analog sensor value is obtained for a dust density of 0.41 mg/m3d. of 3.02 Volts, logic 1 and the cleaning actuator ON position. Surface conditions and abnormal conditions are dusty at 0.54 mg/m3 for photovoltaic sensors at 9.13. The resulting efficiency when the photovoltaic surface is clean is 55%-80%.
Implementasi Algoritma Brute Force Pada Sistem Pertanahan di Balai Desa Ajeng Tri Rahayu; Mukhtar Hanafi; Maimunah Maimunah
Journal of Computer System and Informatics (JoSYC) Vol 4 No 3 (2023): May 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i3.3361

Abstract

Development epoch in era globalization like current information systems utilizing computer technology which is very sophisticated and modern will facilitate data processing which can save time and cost. Result information obtained will facilitate data processing which can save or agencies that utilize artificial intelligence humans or is often called artificial intelligence (AI). Processing data and information fast and efficiently are important things which are needed by an agency, one is office hall village. Processing or archiving books C or Letter C this village still uses manual methods with recording or writing data at books archives villages and views reworked sequence number parcel book C or Letter C previous: to record numbers on owners of old land and owner new land. The way is certainly not efficient because it will require a lot of books and take a lot of time to record data on ownership of land. Objective of this study i.e. implement algorithm brute force to facilitate the search owners land previous on archive electronic. Method development on a system which is used in research is a brute force algorithm in searching for land data, string matching is a part of the string search process. The resulting land data is very dependent on the technique or algorithm carried out in matching the string. In this study, the algorithm used in string matching is brute force. This algorithm performs matching strings with shifts one by one patterns and adjusts them to text so that between Pattern and Text have patterns which are equal. Results analysis of studies This is in the form of trials trial matching strings-with algorithms brute force with studies case using search or search engine with programming language PHP to matching strings.
Expert System Hama dan Penyakit Tanaman Bawang Merah dengan Certainty Factor Debi Gusmaliza; Alfis Arif
Journal of Computer System and Informatics (JoSYC) Vol 4 No 3 (2023): May 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i3.3423

Abstract

This study aims to produce an expert system using the Certainty Factor (CF) Method for Diagnosing Pests and Diseases on Shallot Plants. The background of this research is to obtain information about pests and diseases. Expert System or expert system of Shallot Pests and Diseases with Certainty Factor is an expert system developed to identify pests and diseases in shallot plants. The development method used in the development of this system is the waterfall method. In the early stages of development, a needs analysis is carried out with the aim of understanding the requirements of the expert system, including the types of pests and diseases that must be identified, the associated symptoms, and the required expert knowledge. Furthermore, system design is carried out to design the system architecture and rule structure as well as the Certainty Factor weights that will be used in the diagnosis. In applying the certainty factor method, it gets a value of 46% for armyworm pests. After the design is complete, the implementation phase begins. At this stage, the expert system is designed and coded based on the designs that have been made before. The required modules, such as the inference module and the knowledge base module, are developed according to predetermined specifications. After the implementation is complete, the testing phase is carried out. using the black-box testing technique, with a score of 4.0 from the expert and 3.7 from the implementation of the beta user graph with a valid category. This test aims to ensure that the system provides an accurate diagnosis according to the symptoms observed in shallot plants.
Komparasi Metode Weighted Product (WP) Dan Simple Additive Weighting (SAW) Pada Sistem Pendukung Keputusan Dalam Menentukan Pembangunan Infrastruktur Kelurahan Flipo Hariski; Agung Triayudi; Gatot Soepriyono
Journal of Computer System and Informatics (JoSYC) Vol 4 No 3 (2023): May 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i3.3520

Abstract

The goverment gives urban villages more power includes urban village development. In accordance with local village goverment policies, there are specific criteria for allocating funds for village infrastructure development. The aim is to make the development of urban village infrastructure more equitable and targeted. Priorities for urban village infrastructure development must be decided. Decisions on urban infrastructure development are still made by voting and voting and often more significant developments have to be postponed due to losing votes. To prioritizes urban infrastructure development, urban village officials can use decision support system. Prioritization of urban village infrastructure development is determined using Simple Additive Weight (SAW) and Product weightn(WP) methodologies. Each proposal will be assessed according to the criteria chosen by the Kelurahan to determine development priorities. It is expected that the decision support system will be easier, more accurate, and faster in determining development priorities in Rangkapan jaya urban village. Comparison of SAW and WP methods using 10 alternative data, shows that both methods get accurate data and are suitable when applied as ranking of infrastructure development.
Face Mask Recognition Menggunakan Model CNN (Convolutional Neural Network) Berbasis Python dan OpenCV Chuy Mandala Putra; Agung Triayudi; Sari Ningsih
Journal of Computer System and Informatics (JoSYC) Vol 4 No 3 (2023): May 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i3.3532

Abstract

During the COVID-19 pandemic, masks are one of the main measuring tools in carrying out health protocols, masks are also a top priority when carrying out activities outside the home or office. Because masks are quite effective in filtering out disease particles that allow users not to get infected. Therefore, many places have made masks an important requirement in maintaining health protocols during the COVID-19 pandemic. Previously there was a system that had been created to assist the government in implementing the mandatory wearing of masks, but there were still deficiencies. Therefore the authors created a system to detect mask wearing by updating previous researchers using the convolutional neural network (CNN) algorithm. For making this system the author uses the PYTHON and OPENCV programming languages. which will produce four parts in this detection, namely Mask, No Mask, Covered Mouth Chin and Covered Nose Mouth.
Penerapan Sistem Pendukung Keputusan dalam Penentuan Alat Bantu Media Pembelajaran Fisika Terbaik Menggunakan Metode PSI Dwina Pri Indini; Mesran Mesran; Agung Triayudi
Journal of Computer System and Informatics (JoSYC) Vol 4 No 4 (2023): August 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i4.3466

Abstract

Technology in the Revolutionary Era 4.0 and Society 5.0 made changes in the manual learning system to digital. Along with the development of technology that makes technology and humans very difficult to separate. There are many ways to acquire learning knowledge, one of which is to use learning media tools that are already available on mobile phones. There are so many physics learning media tools available that make students confused in determining the best media to use. In determining physics learning media tools when learning online there are several criteria for Storage Capacity, Application Features, Number of Materials, Number of Language Choices, Number of Users and Rating Reviews. Based on these problems, a decision support system is needed as a problem solving technique and is assisted by a method that can produce an accurate final value. The method is the Preference Selection Index (PSI) method which is very helpful in generating the best weight and preference values ​​from alternative data and criteria so that the final result is that the best physics learning media tool is in Alternative F4 with a value of 0.79563, namely the PhyWiz application.
Sistem Pendukung Keputusan Menentukan Aplikasi Chat Terbaik Menggunakan Metode OCRA Dengan Pembobotan ROC Ardinsah Ardinsah; Mesran Mesran; Agung Triayudi
Journal of Computer System and Informatics (JoSYC) Vol 4 No 4 (2023): August 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i4.3467

Abstract

In this study, a study was conducted to determine the Best Chat Application, the more we enter the digital era, the more applications and communication media or sending messages that appear. So researchers want to do research to determine which chat application is the best that people can use and unfortunately it is suitable for use today, then a system is applied that can help to decide, namely a Decision Support System (DSS) which can simplify the process of selecting the Best Chat Application by implementing 5 criteria i.e. Security, Number of Downloads, Reviews, Features, Storage. So we need a system that can make decisions by using SPK that applies the ROC and Operational Comprtitiveness Rating Analysis(OCRA) methods in getting the weighting value for each criterion and preference value from the best alternative, namely alternative A¬1 with the name Whatsapp Application with a preference value of 128,3123
Clustering Content Types and User Motivation Using DBSCAN on Twitter Made Mita Wikantari; Yuliant Sibaroni; Aditya Firman Ihsan
Journal of Computer System and Informatics (JoSYC) Vol 4 No 4 (2023): August 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i4.3750

Abstract

We are currently in an era full of information and communication technology. One of the communication media used is Twitter. Twitter is a microblogging service that is used by its users to express their thoughts on a topic called a tweet. Tweets that are posted can be either positive tweets or negative tweets. One of the topics that is currently being discussed by Twitter users is Anies Baswedan as a 2024 Indonesian Presidential Candidate. Many people have tweeted this but it is not known how many users support or reject Anies Baswedan to run as a 2024 Indonesian presidential candidate. To assist the analysis, use the method clustering namely algorithm (Density-Based Spatial Clustering of Application with Noise). DBSCAN has the advantage of being able to detect data that is not included in a cluster and will be considered noise. This can improve the accuracy of the grouping because the data in the cluster will be cleaner. The TF-IDF Vectorizer is used to make it easier for programs to manage data because it can turn sentences into vectors that can be processed by the algorithm. To determine the evaluation of the program, the silhouette score method will be used. The results of calculating the silhouette score show a value of 0.29 with the formation of 3 clusters. Then an analysis is carried out based on the top words from each cluster and it can be identified that cluster 0 has a positive category supporting Anies Baswedan to run for the 2024 Presidential Candidate and cluster 1 has a negative category that does not support Anies Baswedan not advancing for the 2024 Presidential Candidate.
Clustering Content Types and User Roles Based on Tweet Text Using K-Medoids Partitioning Based Raisa Benaya; Yuliant Sibaroni; Aditya Firman Ihsan
Journal of Computer System and Informatics (JoSYC) Vol 4 No 4 (2023): August 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i4.3751

Abstract

In this modern era, the spread of information occurs rapidly through social media. One of the channels for disseminating information is through the Twitter platform. Many Twitter users respond to existing content with positive, negative and neutral responses. One of the hot content to respond to is political content. This content is currently being discussed considering the approaching election of the 2024 Presidential Candidate of the Republic of Indonesia. One of the candidate pairs discussed was Anies Baswedan. With so many responses from Twitter users, it will be difficult to track whether users support Anies Baswedan to run as a presidential candidate due to the large number of responses. This study aims to determine the response of twitter users to the advancement of Anies Baswedan as a presidential candidate. The method used in this study is the K-Medoids Partitioning-Based algorithm based on twitter user text. This algorithm was chosen because it is easy to implement considering the basis of K-Medoids development is the K-Means algorithm but the K-Medoids algorithm can overcome the shortcomings of the K-Means algorithm which is sensitive to outliners. The evaluation will be done using Silhouette Score which produces a value of 0.35 with the number of clusters is 2. Then an analysis of each cluster is carried out by looking at the words in the cluster. As a result, from the two clusters formed, both clusters contain positive content and show that Twitter users support Anies Baswedan to run as a 2024 presidential candidate.
Analisis Kepuasan Pengguna Menggunakan Metode EUCS Pada Sistem Computer Based Test di Institusi Pendidikan I Putu Yesha Agus Ariwanta; I Gede Tiar Eka Saputra; Ni Putu Eka Apriyanthi; I Made Agus Oka Gunawan; Gede Indrawan
Journal of Computer System and Informatics (JoSYC) Vol 4 No 4 (2023): August 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i4.3752

Abstract

Penerapan sistem ujian online, atau Computer Based Test (CBT), telah menjadi bagian penting dari pendidikan tinggi di bidang kesehatan, termasuk di Poltekkes Kartini Bali, salah satu perguruan tinggi di Bali. Poltekkes Kartini Bali berkomitmen untuk mengikuti perkembangan teknologi dengan menyediakan sistem ujian online yang dapat diakses oleh para mahasiswa melalui laman web web www.cbt.politeknikkesehatankartinibali.ac.id. Situs ini menyediakan bank soal untuk mahasiswa serta informasi mengenai pencapaian nilai ujian akhir setiap matakuliah. Evaluasi kepuasan pengguna terhadap sistem ini menjadi hal yang penting untuk memastikan efektivitas dan kualitas layanan yang diberikan. Penelitian ini bertujuan untuk menganalisis kepuasan pengguna terhadap sistem ujian online dengan menggunakan metode End User Computing Satisfaction (EUCS) di Poltekkes Kartini Bali. Penelitian ini menggunakan pendekatan kuantitatif dan melibatkan partisipasi mahasiswa dari berbagai program studi di Poltekkes Kartini Bali. Penelitian ini difokuskan pada variabel konten, variabel ketepatan, variabel bentuk, variabel kemudahan penggunaan, dan variabel ketepatan waktu. Setelah pengumpulan data dan analisis dilakukan, diperoleh hasil perhitungan rata-rata tingkat kepuasan. Hasilnya menunjukkan bahwa nilai rata-rata kepuasan pengguna adalah 4.22 untuk variabel content, 4.17 untuk variabel accuracy, 4.29 untuk variabel format, 4.22 untuk variabel timeliness, dan 4.23 untuk variabel ease of use. Mengacu pada teori Kaplan dan Norton, semua variabel menunjukkan bahwa tingkat kepuasan pengguna terhadap Computer Based Test (CBT) di Poltekkes Kartini Bali termasuk dalam kategori "puas".

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