SISTEM PENDUKUNG KEPUTUSAN PENANGANAN GIZI BALITA DENGAN METODE FUZZY MAMDANI

Decision Support System is a branch of artificial intelligence used to help make decisions in semi-structured cases, where it is not known exactly how decisions should be made. In this research, the design and making of decision support system that is used to help determine the nutritional status of children with weight input, age, height, head circumference, nutrition value of toddlers and the output of nutritional status of children under five and their handling. The problem of data uncertainty in decision support system is solved by using fuzzy mamdani method. The existence of data uncertainty in the process can occur because of the differences in existing calculations on the system. The process of determining the nutritional status of this decision support system is begun by entering the input data of toddlers, where the system will display some variables that have been made then start the calculation with the application. The end result of this research is decision support system to do nutritional handling in toddler along with their nutrition result. The calculations show the level of confidence in the system of nutritional status of the toddler and from the results of this study obtained the system accuracy of 83.33% of the 18 test data that has been tested is obtained. Therefore, it can be concluded that decision support system produces a good examination. Keywords: Decision Support System, Fuzzy Mamdani, Underfive Nutrition

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Sistem Penunjang Keputusan Untuk Menentukan Status Gizi Balita Menggunakan Metode Fuzzy Tsukamoto

Jurnal Informatika ◽

10.31311/ji.v5i1.2440 ◽

2018 ◽

Vol 5 (1) ◽

pp. 22-33

Author(s):

Dewi Ayu Nur Wulandari ◽

Arfhan Prasetyo

Keyword(s):

Decision Support ◽

Nutritional Status ◽

Decision Support System ◽

Support System ◽

Nutrition Status ◽

Interactive System ◽

Healthy Children ◽

Children Under Five ◽

Under Five ◽

Nutritional Status Of Children

Abstrak Masalah gizi anak masih menjadi masalah nasional. Ciri khas anak yang sehat harus dilihat dari tumbuh dan berkembang. Untuk memastikan bahwa perkembangan anak balita optimal dan untuk mengantisipasi malnutrisi yang dapat mempengaruhi balita, diperlukan teknik untuk menilai status gizi anak. Status gizi anak balita perlu dipantau terus menerus, karena status gizi balita dapat dijadikan ilustrasi kesehatan, pertumbuhan dan perkembangan anak. Untuk membantu dalam menentukan status gizi anak, diperlukan bantuan teknologi informasi. Sistem Pendukung Keputusan adalah sistem interaktif berbasis komputer yang dapat membantu pengambil keputusan dalam menggunakan data dan model untuk memecahkan masalah terstruktur dan tidak terstruktur. Fuzzy Tsukamoto adalah salah satu metode yang paling fleksibel dan toleran yang tersedia, dengan keuntungan yang lebih intuitif, diterima oleh banyak pihak, lebih sesuai untuk input yang diterima dari manusia daripada mesin, ia akan memfasilitasi pihak-pihak yang terlibat dalam memantau perkembangan dan perkembangan balita. Hasil penelitian ini berupa Sistem Pendukung Keputusan untuk mengetahui Status Gizi metode Fuzzy Tsukamoto berbasis Balita yang diharapkan dapat digunakan di posyandu untuk memantau pertumbuhan bayi balita sehingga anak-anak dengan status gizi kurang mendapatkan penanganan yang lebih baik dan lebih cepat. Hasil Penelitian menunjukkan akurasi metode tsukamote di bandingkan dengan metode antropometri dalam menentukan status gizi balita adalah sebesar 82,75%. Kata kunci: inferensi fuzzy, fuzzy tsukamoto, Status Gizi Balita Abstract Children's nutritional problems are still a national problem. Characteristic of healthy children should be seen from growing and developing. To ensure optimal development of children under five and to anticipate malnutrition that may affect children under five, a technique to assess the nutritional status of children is required. Nutrition status of toddlers needs to be monitored continuously because the nutritional status of children can be illustrated health, growth, and development of children. To assist in determining the nutritional status of children, information technology assistance is required. Decision Support System is a computer-based interactive system that can assist decision makers in using data and models to solve structured and unstructured problems. Fuzzy Tsukamoto is one of the most flexible and tolerant methods available, with more intuitive advantages, accepted by many, more suited to inputs received from humans rather than machines, it will facilitate the parties involved in monitoring the development and development of toddlers. The results of this research are Decision Support System to know the Nutritional Status of Fuzzy Tsukamoto-based Toddler method which is expected to be used in posyandu to monitor the growth of infants so that children with less nutritional status get better and faster handling. The result of the research shows the accuracy of tsukamoto method in comparison with anthropometry method in determining the nutritional status of children under five is 82,75% Keywords: fuzzy inference, fuzzy tsukamoto, the Nutritional Status of Toddler

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Sardanashvili S.A., Shvechkov V.A. Artificial intelligence technologies application in the development of innovative domestic dispatching decision support system in the field of modeling, planning and management of inter-regional gas flows in the unified gas supply system (UGSS)

Automation Telemechanization and Communication in Oil Industry ◽

10.33285/0132-2222-2019-8(553)-31-37 ◽

2019 ◽

pp. 31-37

Author(s):

S.A. Sardanashvili ◽

◽

V.A. Shvechkov ◽

Keyword(s):

Artificial Intelligence ◽

Decision Support ◽

Decision Support System ◽

Support System ◽

Supply System ◽

Gas Flows ◽

Planning And Management ◽

Gas Supply

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IMPLEMENTASI METODE VIKOR DALAM PENERIMAAN JURNALIS PADA KORAN WASPADA MEDAN

KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) ◽

10.30865/komik.v2i1.905 ◽

2018 ◽

Vol 2 (1) ◽

Author(s):

Soraya Rahma Hayati ◽

Mesran Mesran ◽

Taronisokhi Zebua ◽

Heri Nurdiyanto ◽

Khasanah Khasanah

Keyword(s):

Decision Making ◽

Decision Support ◽

Decision Support System ◽

Decision Support Systems ◽

Support System ◽

Support Systems ◽

Knowledge Based ◽

Computer Based ◽

Support Decision Making ◽

Made In

The reception of journalists at the Waspada Daily Medan always went through several rigorous selections before being determined to be accepted as journalists at the Waspada Medan Daily. There are several criteria that must be possessed by each participant as a condition for becoming a journalist in the Daily Alert Medan. To get the best participants, the Waspada Medan Daily needed a decision support system. Decision Support Systems (SPK) are part of computer-based information systems (including knowledge-based systems (knowledge management)) that are used to support decision making within an organization or company. Decision support systems provide a semitructured decision, where no one knows exactly how the decision should be made. In this study the authors applied the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) as the method to be applied in the decision support system application. The VIKOR method is part of the Multi-Attibut Decision Making (MADM) Concept, which requires normalization in its calculations. The expected results in this study can obtain maximum decisions.Keywords: Journalist Acceptance, Decision Support System, VIKOR

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Perceived Effectiveness of Artificial Intelligence based Decision Support System in a Clinical Setting: A Systematic Literature Review (Preprint)

10.2196/preprints.19282 ◽

2020 ◽

Author(s):

Avishek Choudhury

Keyword(s):

Artificial Intelligence ◽

Decision Making ◽

Decision Support ◽

Literature Review ◽

Decision Support System ◽

Support System ◽

Clinical Setting ◽

Clinical Decision Making ◽

Theoretical Perspective ◽

Care Providers

UNSTRUCTURED Objective: The potential benefits of artificial intelligence based decision support system (AI-DSS) from a theoretical perspective are well documented and perceived by researchers but there is a lack of evidence showing its influence on routine clinical practice and how its perceived by care providers. Since the effectiveness of AI systems depends on data quality, implementation, and interpretation. The purpose of this literature review is to analyze the effectiveness of AI-DSS in clinical setting and understand its influence on clinician’s decision making outcome. Materials and Methods: This review protocol follows the Preferred Reporting Items for Systematic Reviews and Meta- Analyses reporting guidelines. Literature will be identified using a multi-database search strategy developed in consultation with a librarian. The proposed screening process consists of a title and abstract scan, followed by a full-text review by two reviewers to determine the eligibility of articles. Studies outlining application of AI based decision support system in a clinical setting and its impact on clinician’s decision making, will be included. A tabular synthesis of the general study details will be provided, as well as a narrative synthesis of the extracted data, organised into themes. Studies solely reporting AI accuracy an but not implemented in a clinical setting to measure its influence on clinical decision making were excluded from further review. Results: We identified 8 eligible studies that implemented AI-DSS in a clinical setting to facilitate decisions concerning prostate cancer, post traumatic stress disorder, cardiac ailment, back pain, and others. Five (62.50%) out of 8 studies reported positive outcome of AI-DSS. Conclusion: The systematic review indicated that AI-enabled decision support systems, when implemented in a clinical setting and used by clinicians might not ensure enhanced decision making. However, there are very limited studies to confirm the claim that AI based decision support system can uplift clinicians decision making abilities.

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