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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 6 Documents
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Search results for , issue "Vol 2 No 3 (2021): Mei 2021" : 6 Documents clear
Sistem Pendukung Keputusan Untuk Menentukan Tempat Gymnastic Terbaik di Kota Medan Mengunakan Metode TOPSIS Amin Rahman
Journal of Computer System and Informatics (JoSYC) Vol 2 No 3 (2021): Mei 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

Decision support system as a computer-based system consisting of components between system components (language). Knowledge system components and problem processing system components that interact with one another. Decision support system is a approach or methodology to support decisions, CBIS (computer based information system) that is flexible, interactive and adaptable, which was developed to support solutions for specific management problems that are not structured. To help the problems faced by the decision support system in determining / placement of the best Gym, where the selection is seen from the symptoms and strengths of each place. Using the Topsis method (Technique for Order Preference by similarity to Ideal Solution) is expected in the decision support system to calculate the results from the best value of the Gym
Sistem Pendukung Keputusan Pemilihan Konten Lokal Terbaik Menerapkan Metode Moosra (Studi Kasus: Komisi Penyiaran Indonesia) Divya Febrina; Imam Saputra
Journal of Computer System and Informatics (JoSYC) Vol 2 No 3 (2021): Mei 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

Decision support system as a computer-based system consisting of components including language system components, knowledge system components and problem processing system components that interact with one another, which helps decision making through the use of data and decision models to solve semi-structured and unstructured problems. This study uses the Moosra Method in Selecting the Best Local Content based on criteria by using a formula which results are more accurate and right on target. In it also all data are combined into one with the weight of the assessment that has been obtained through an assessment of the test results. The research conducted is to create a system that can provide consideration in making decisions for the selection of the best local content.
Penerapan Metode Extended Promethee II (EXPROM II) Dalam Penyeleksian Siswa Pada Jurusan Ground Support Equipment (GSE) Operator Nadarya Aviation Center Medan Eka Murlisah; Mesran Mesran
Journal of Computer System and Informatics (JoSYC) Vol 2 No 3 (2021): Mei 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

The Nadarya Aviation Center (NAC) Aviation Training Institute is a private training institution that aims to prepare skilled, work-ready, mentally strong, responsible human resources, have faith and piety, have quality and are able to compete independently and professionally. Ground Support Equipment (GSE) Operator is an aircraft ground service equipment personnel who has a license and rating to carry out the operation of aircraft ground service equipment while the aircraft is on the ground (apron / aircraft parking at the airport). It is hoped that an effective selection process will be able to screen training students in the GSE Operators department who really fit the target desired by the Director of the flight training institute. One of the right solutions for these problems is to use a Decision Support System (DSS). Decision Support Systems (DSS) can assist aviation training institutions in making student selection decisions for the right operator ground support equipment (GSE) majors and will increase the efficiency of these decisions. Extended Promethee II (EXPROM II) is a method of decision making on preference functions with problems through the outranking approach or is a multicriteria analysis, comparing one alternative with another and calculating the difference between the alternative pairs to produce an output that is an alternative ranking based on value. highest
Sistem Pakar Deteksi Minat Untuk Pemilihan Jenjang Karir Menggunakan Metode Certainty Factor M. Tsana'uddin Farid; Hanung Adi Nugroho; Indriana Hidayah
Journal of Computer System and Informatics (JoSYC) Vol 2 No 3 (2021): Mei 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

Interests have an important role in the career path because interests will affect a person's performance, passion and abilities during their educational studies. The problem that occurs is that based on a survey conducted by the Indonesian Career Center Network, it was found that 87% of students in Indonesia felt that they were wrong in deciding which major they were taking. This problem is because the majors they take do not match their interests. This problem can be prevented by detecting interest early on so that career paths can be planned appropriately. This study aims to provide a solution to this problem by building an interest detection expert system to support career path selection. Certainty Factor methods are used in determining the output of the expert system to be built with the adaptation of the interest test tool, called RIASEC. Testing is done by comparing the system output results with expert consultation. The test results showed that the expert detection system was able to answer the interest with an accuracy of 93%. Based on the test results, the solution in interest detection expert system could be used as a reference assessment in planning career path choices
Prediksi Hasil Produksi Kelapa Sawit PTPN IV Bahjambi Menggunakan Algoritma Backpropagation Venny Vidya utari; Anjar Wanto; Indra Gunawan; Sumarno Sumarno; Zulaini Masruro Nasution
Journal of Computer System and Informatics (JoSYC) Vol 2 No 3 (2021): Mei 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

Oil palm is a tropical plant of the Indonesian natural palmae group which has a tropical climate. The growth and harvest of oil palm also depends on fertilizers and the rainfall that falls every day. To get good production results it requires high ability and a lot of labor. Each production result certainly does not always increase, there must be a time when the production will decrease, therefore an algorithm is needed to predict it so that companies can find out the development of palm oil production in the future. In this study, researchers used the Backpropagation Algorithm. The Backpropagation Algorithm is an algorithm that functions to reduce the error rate by adjusting the weight based on the desired output and target, there are 5 training and data testing architectural models, namely 2-21-1, 2-22-1, 2-24-1, 2-26 -1 and 2-28-1. From the results of testing data on oil palm production, the best architectural model is obtained, namely 2-22-1 which shows that the target is reduced by the output that SSE is 0.35206024, from the data obtained, the performance of the calculation of artificial neural networks with the Backpropagation Algorithm gets an accuracy of 83.3%. . So that it can be used as a benchmark in predicting palm oil production, seen from the comparison of the desired target with the predicted target
Analisa Datamining dengan Metode Klasifikasi C4.5 Sebagai Faktor Penyebab Tanah Longsor Afrialita Widiastari; Solikhun Solikhun; Irawan Irawan
Journal of Computer System and Informatics (JoSYC) Vol 2 No 3 (2021): Mei 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

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Abstract

Landslides are geological events where soil movement occurs such as falling rocks or large lumps on the ground. Landslides often occur when it rains, although not always. In addition, landslides generally occur in areas with steep slopes. With the C4.5 method it can be used to classify data that has numeric and categorical attributes. The results of the classification process in the form of rules can be used to predict the value of the discrete type attribute from a new record. Data obtained from the National Disaster Management Agency regarding the factors causing landslides can produce an accuracy value of 77.78%, meaning that the resulting rules or rules are close to 100%, it can be concluded that to classify the factors causing landslides using C4.5 by looking at the node the highest is slope. To find out these factors can provide input to the Disaster Management Agency to be more concerned with the factors that caused the landslides

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