PERANCANGAN KNOWLEDGE MANAGEMENT BERBASIS ONTOLOGI UNTUK DIAGNOSIS STATUS GIZI PADA BALITA BESERTA REKOMENDASI MENU MAKANAN

LOGI NURSULTAN MUHAMMAD, Dr. Sri Suning Kusumawardani, S.T., M.T.; Warsun Najib, S.T., M.Sc.

2015 | Skripsi | S1 TEKNOLOGI INFORMASI

Pengukuran secara antropometri berdasarakan indeks BB/U, TB/U, dan BB/TB menghasilkan status gizi terhadap balita. Indeks BB/U dapat mengklasifikasi status gizi balita dalam status gizi buruk, gizi kurang, gizi baik dan gizi lebih dengan menggunakan standar ambang batas atau z-scores yang dikeluarkan oleh WHO maupun Kementerian Kesehatan RI. Status gizi buruk, gizi kurang dan gizi lebih bisa berdampak bahaya bagi balita. Untuk menangani masalah tersebut perlu proses pendeteksian atau diagnosis secara dini. Selain itu, apabila sudah terdiagnosis gizi buruk, gizi kurang dan lebih salah satu pendekatannya yaitu dengan memberikan rekomendasi menu makanan sesuai usia dengan jumlah kalori dan protein yang cukup. Pengembangan knowledge management status gizi pada balita beserta rekomendasi menu makanan pada penelitian ini untuk meningkatkan pengetahuan sekaligus solusi teknologi untuk membantu khususnya masyarakat dan para orang tua tentang penentuan gizi dan makanan pada balita. Sehingga dengan knowledge management berbasis ontologi dapat mempermudah masyarakat dalam penentuan gizi maupun makanan diharapkan mampu menggantikan peran dokter atau bidang medis lainnya. Perancangan knowledge management berbasis ontologi diagnosis status gizi balita beserta rekomendasi menu makanan menggunakan Protege 4.3 menghasilkan 43 class, 27 attribute, 9 relation, dan 41 rules yang didefinisikan dalam ontologi untuk merepresentasikan konsep tersebut. Pengujian rules menggunakan Pellet reasoner telah berhasil menghasilkan inferensi rules relasi dan atribut untuk mengetahui status gizi balita dan pemberian menu makanan serta menghitung kebutuhan spesifik kalori dan protein. Kemudian pengujian SPARQL berhasil menjawab 6 kompetensi pertanyaan sesuai perancangan.

Anthropometry measurements on the terms of the weight for age, height for age and weight for age index produce the nutritional status of the children. Weight for age index can classify the nutritional status of children in severely underweight, underweight, normal and overweight nutritional status using a standard threshold or z-scores issued by the WHO and the Ministry of Health Republic of Indonesia. Severely underweight, underweight, and overweight nutritional status can lead to a serious impact for children. How to deal with this problem is by doing the early detection or diagnosis. Moreover, when they are already diagnosed with severely underweight, underweight and overweight, one of the methods to overcome is to provide age-appropriate diet recommendations by the number of calories and protein needed. The development of knowledge management nutritional status of children and their recommendations on this research aims to increase the knowledge as well as technological solutions to help particular communities and parents about nutrition and food determination in children. By using ontology-based knowledge management to facilitate the public in the determination of nutrition and food is expected to replace the role of a doctor or other medical fields. The design of the ontology-based knowledge management diagnosis of nutritional status and food menu recommendations using Protege 4.3 resulted in 43 classes, 27 attributes, 9 relations, and 41 rules that are defined in the ontology to represent the concept. Testing rules using Pellet Reasoner has managed to generate relationships and attributes of inference rules to determine the nutritional status of children and the provision of food menu and calculate the specific needs of calories and protein. Then SPARQL testing managed to answer 6 competence questions in the design.

Kata Kunci : ontologi, protege, knowledge management, status gizi balita, menu makanan, Pellet, Simple Protocol and RDF Query Language.