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All Journal TEKNIK INFORMATIKA Journal of Computer System and Informatics (JoSYC)
Elin Haerani
UIN Suska Riau
Computer Science & IT Decision Sciences, Operations Research & Management Industrial & Manufacturing Engineering

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PENGEMBANGAN SISTEM PENDUKUNG KEPUTUSAN PENENTUAN KONSENTRASI BIDANG KEAHLIAN MAHASISWA DENGAN INTEREST INVENTORY Haerani, Elin; Rukun, Kasman; Rizal, Fahmi
JURNAL TEKNIK INFORMATIKA Vol 13, No 1 (2020): JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (553.916 KB) | DOI: 10.15408/jti.v13i1.15710

Abstract

Universities are designed to prepare graduates who are ready to enter the workforce and are able to develop a professional attitude. Educational institutions such as the University need a form of decisions in determining the right concentration for students, so that the learning process can be achieved well. The decision is very influential on the process of handling the choice of alternative concentration, choosing an appropriate concentration of interest will also have an impact on the research focus for the final assignment of students. This research develops student concentration selection system in Electrical. Currently the concentration determination system is based only on academic assessment alone, regardless of student interest, so that it can impact on student learning outcomes. The system was developed by combining academic judgment and interest inventory with three criteria, ie, interest tests using interest inventory, prerequisite concentration course grades, and GPA. The system is built using an intelligent system model that is Fuzzy Multiple Attribute Decision Making (FMADM), which helps the Department in the selection process and helps the process of career guidance on students. With this selection system, the Department can be provide the most suitable concentration decisions with interest in student.
Penerapan Algoritma Naïve Bayes Classifier Dalam Klasifikasi Status Gizi Balita dengan Pengujian K-Fold Cross Validation Nurainun, Nurainun; Haerani, Elin; Syafria, Fadhilah; Oktavia, Lola
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.v4i3.3414

Abstract

Nutritional status is a condition related to nutrition that can be measured and is the result of a balance between nutritional needs in the body and nutritional intake from food. In Indonesia, there are still many nutritional problems such as malnutrition and other nutritional problems. This research will use the Naïve Bayes Classifier algorithm with K-Fold Cross Validation testing. The data used is data on the nutritional status of toddlers in August 2022 at the Rambah Samo I Health Center. Attributes in this study include Gender, Birth Weight, Birth Height, Age at Measurement, Weight, Height, ZS BB/U, BB/U, ZS TB/U, and TB/U. Determination of the nutritional status of toddlers in this study was based on the BB/TB index which consisted of 6 classes, namely severely wasted, wasted, normal, possible risk of overweight, overweight, and obese. From the research conducted, it was found that the Naïve Bayes Classifier algorithm with K-Fold Cross Validation can correctly classify the nutritional status of toddlers. From data processing using 10-Fold Cross Validation on the Naïve Bayes Classifier algorithm, it is known that the highest accuracy value is 82.94% in the 5th iteration, while the lowest accuracy value is 65.88% in 6th iteration. With an average overall accuracy value of 75.47%. Meanwhile, the average precision value obtained is 81.36% and the average recall value is 75.47%.
Penerapan Algoritma Mean-Shift Pada Clustering Penerimaan Bantuan Pangan Non Tunai Rizuan, Rizuan; Haerani, Elin; Jasril, Jasril; Oktavia, Lola
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.v4i4.3876

Abstract

Kemiskinan merupakan kondisi individu atau sekumpulan individu yang tidak memiliki akses ke sumber daya yang memadai untuk memenuhi kebutuhan dasar serta menjalani kehidupan yang baik. Tujuan bantuan pangan non tunai adalah untuk memberikan bantuan pangan kepada yang membutuhkannya melalui metode non tunai, seperti kartu debit atau kartu elektronik. Penelitian ini bertujuan menemukan pola karakteristik calon penerima Bantuan Pangan Non Tunai (BPNT) berdasarkan kriteria dari Dinas Sosial Kota Pekanbaru. Berdasarkan hasil pengujian menggunakan Silhouette Score didapatkan kluster terbaik adalah 2 kluster dengan bandwidth 285 dan Silhouette Score 0.95 klaster 1 memiliki 680 data, dan klaster 2 memiliki 2 data. Hasil claster 1 memiliki pola status penguasaan tempat tinggal berstatus bebas sewa dan kontrak/sewa, untuk jenis lantai terluas adalah batu merah/ sementara, jenis adalah dinding plasteran dan jenis air konsumsi dari leding meteran. Sedangkan hasil cluster 2 memiliki pola penguasaan tempat tinggal berstatus milik sendiri, untuk jenis lantai adalah keramik, jenis dinding adalah tembok dan konsumsi air dari sumur bor pompa.
Co-Authors Fadhilah Syafria Fahmi Rizal Jasril Jasril Kasman Rukun Nurainun Nurainun Oktavia, Lola Rizuan, Rizuan