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All Journal Seminar Nasional Teknologi Informasi Komunikasi dan Industri
Elvia Budianita
Teknik Informatika UIN Suska Riau
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mathematics

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Membangun Sistem Penjadwalan Ruang Laboratorium dengan Algoritma Modified BiDirectional A M ridwan; Elvia Budianita
Seminar Nasional Teknologi Informasi Komunikasi dan Industri 2014: SNTIKI 6
Publisher : UIN Sultan Syarif Kasim Riau

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Abstract

Sistem penjadwalan ruang laboratorium merupakan sistem terkomputerisasi yang berfungsi untukmenyusun jadwal kelas-kelas praktikum yang akan menggunakan laboratorium. Pada saat ini, penyusunanjadwal laboratorium jurusan Teknik Informatika UIN Suska masih dilakukan secara manual sehingga kepalalaboratorium harus mengumpulkan sendiri data yang dibutuhkan dalam penyusunan jadwal. Teknik analisis datapada sistem ini menggunakan metode pembangunan perangkat lunak secara waterfall. Proses penyusunanjadwal dilakukan dengan metode MBDA (Modified Bidirectional A*) dengan penentuan bobot berdasarkankategori sisa waktu terbuang, kelas yang berulang, dan status dosen yang telah terjadwal. Pada MBDA* metodepencarian heuristik dilakukan dan setiap kandidat solusi akan disimpan kedalam struktur data graph yangmemiliki bobot. Algoritma MBDA akan menelusuri simpul tersebut dan mencari solusi terbaik berdasarkan totalbobot terendah. Berdasarkan pengujian terhadap 10 kasus secara acak, seluruh kasus menghasilkan jadwalyang bebas bentrokan waktu pengajar ataupun mahasiswa dan sesuai dengan waktu kosong yangdiajukan(100%).Kata kunci: Penjadwalan, pencarian heuristic, euclidean distance, MBDA.
Klasifikasi Status Gizi Balita Berdasarkan Indikator Antropometri Berat Badan Menurut Umur Menggunakan Learning Vector Quantization Elvia Budianita; Novriyanto Novriyanto
Seminar Nasional Teknologi Informasi Komunikasi dan Industri 2015: SNTIKI 7
Publisher : UIN Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (512.681 KB)

Abstract

Determination of nutritional status is an effort made in order to improve the health of children. Common method used for the assessment of nutritional status is anthropometry. To classify the nutritional status of children into malnutrition, malnutrition, good nutrition and nutrition then used anthropometric indices weight for age (W / A). In Rimbo data Puskesmas, calculation of anthropometric indices for the assessment of nutritional status of children is done manually using z-scores table lists or standard deviation (SD) WHO NCHS. In this research, the authors tried to establish a classification system based nutritional anthropometric indices weight for age (W / A) by applying the Learning Vector Quantization algorithm uses two functions, namely euclidean and manhattan distance. The variables used were gender, age, weight, family economic status, mother's education, father's occupation. From the results of research and discussion conducted, Learning Vector Quantization algorithm using euclidean distance function can recognize the pattern with the best accuracy percentage of 80% whereas the manhattan distance function only 20% of 110 training data and test data amounted to 10. The amount of training data and the diversity of patterns that exist in the class used nutritional status affects learning outcomes and the accuracy of the systemsKeywords: Antropometri, Euclidean, Learning Vektor Quantization, Manhattan, Z-skor
Co-Authors M ridwan Novriyanto Novriyanto