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All Journal Jupiter Zero : Jurnal Sains, Matematika, dan Terapan Innovative: Journal Of Social Science Research Journal of Informatics and Data Science (J-IDS)
Refisis, Nice Rejoice
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Agriculture, Biological Sciences & Forestry Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Physics Public Health Other

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Development Of An Expert System For Identifying Dental Diseases Using Certainty Factor Method (Case Study : UPT Puskesmas Parmaksian) Sirait, Gian Patar P.; Refisis, Nice Rejoice
Journal of Informatics and Data Science Vol 3, No 1 (2024): JUNE 2024
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/j-ids.v3i1.51274

Abstract

Dental health is crucial for human well-being, yet awareness of its significance is often low. This study addresses the need for an expert system to identify dental diseases, employing the Certainty Factor method. This method allows the system to express the level of certainty in expert statements, facilitating personalized use. The developed expert system calculates Certainty Factor values for each symptom, resulting in an 83% accuracy rate in identifying dental diseases based on tests conducted with 47 out of 56 cases. This research contributes to the field by providing an effective tool for dental disease identification, enhancing both awareness and practical applications in oral health.
Pengembangan Website Dengan Algoritma K-Nearest Neighbor (KNN ) Dalam Klasifikasi Perkembangan Prestasi Siswa Terhadap Hasil Belajar (Studi Kasus SD Negeri 107396 Paluh Merbau) Siburian, Rulli Prasetio Bane; Refisis, Nice Rejoice; Rangkuti, Yulita Molliq; Napitupulu, Elvis; AI Idrus, Said Iskandar
Innovative: Journal Of Social Science Research Vol. 4 No. 5 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i5.12832

Abstract

Pemahaman perkembangan intelektual anak di SD sangat penting sebagai acuan pendidikan. SD Negeri 107396 Paluh Merbau, yang masih menggunakan metode manual untuk mengklasifikasikan nilai siswa, menjadi tempat ideal untuk penelitian ini. Tujuan penelitian adalah menganalisis efektivitas algoritma K-Nearest Neighbor (KNN) dalam klasifikasi perkembangan siswa berdasarkan hasil belajar dan membangun website sebagai platform pengumpulan data dan implementasi KNN. Prestasi siswa diukur melalui nilai ujian semester, ujian harian, tugas, sikap, dan absensi. Data dikumpulkan secara dokumenter dan dianalisis dengan mengurutkan jarak data uji ke data latih dari yang terkecil hingga terbesar, menggunakan k=1 hingga k=10. Hasil klasifikasi mayoritas menunjukkan prestasi Rafa Rifa'i berada di kategori kelas 0 (di bawah rata-rata). Penelitian ini menunjukkan bahwa algoritma KNN efektif dalam klasifikasi prestasi siswa, memberikan wawasan untuk meningkatkan strategi pembelajaran.
Comparison of OLS Regression and Robust Regression in Overcoming Outlier Problems (Case Study: Cost of Living Data for Urban Areas in Indonesia) Susiana, Susiana; Chairunisah, Chairunisah; Refisis, Nice Rejoice
ZERO: Jurnal Sains, Matematika dan Terapan Vol 8, No 2 (2024): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v8i2.21345

Abstract

Multiple regression analysis in quantitative statistical studies describes the relationship between independent and dependent variables. On the other hand, outliers in a set of data can have an unfavourable influence on data analysis, such as high residuals, significant variances, and bias, and can even cause errors in decision-making. It can be done in several ways to overcome the outlier problem in multiple linear regression analysis, including using robust regression or Ordinary Least Square (OLS) Regression by removing data indicated as an outlier first. The OLS Regression method forms a regression model by minimizing the sum of squared residuals from the estimator of the regression equation. Meanwhile, robust regression is closer to the average parameters and variance-covariance of a particular estimator, namely by standardizing the estimator for the average parameters and variance-covariance in such a way as to produce a consistent estimator for these parameters. This research aims to compare the OLS Regression and robust regression methods as alternatives for dealing with outlier problems in data. The data used in this research is secondary data (cost of living) from the Cost of Living Survey conducted by The Central Statistics Agency of the Republic of  Indonesia in 2018. The stages of this research method are literature study, data collection, descriptive analysis to see the characteristics of the data, forming a regression model using the OLS Regression method, testing classical assumptions, creating a new regression model OLS Regression, forming a regression model with Robust Regression, calculating the MSE (Mean Square Error) of each regression model formed, determining the best regression model, The results of the research show that for the cost of living data, the best regression model is obtained through the OLS Regression method with data without outliers, namely .  
Implementasi Algoritma Hill Cipher Untuk Keamanan Rekam Medis Di Puskesmas Pematang Raya Sinaga, Ronaldo Mardianson; Refisis, Nice Rejoice
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 15 No 2 (2023): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.10068238

Abstract

Kurangnya keamanan yang di terapkan pada data rekam medis, sehingga ada kemungkinan orang lain yang tidak berwenang mengakses data rekam medis. Tujuan penelitian ini untuk mengamankan data rekam medis dengan mengimplementasikanya pada algoritma Hill Cipher dan mempermudah dalam mencari data serta mentransimikan data dengan lebih efisien dan aman. Pengumpulan data dilakukan dengan menggunakan intrumen penelitian, yaitu wawancara dan studi dokumen. Pada penelitian ini kunci enkripsi dan dekripsinya berupa perkalian matriks dan untuk karakter yang digunakan sebanyak 93 karakter. Dalam penerapan terhadap sistem algoritma Hill Cipher di terapkan pada database, sehingga data tersimpan dengan aman. Hasil pengujian validasi enkripsi dan deskripsi diketahui bahwa sistem dapat mengenkripsi dan mendeskripsikan kembali data sesuai dengan ketentuan algoritma hill cipher. Dari pengujian fungsionalitas dan non fungsionalitas, sistem bekerja segabagaimana mestinya dan dapat menyesuaikan pada perangkat yang digunakan.
Development Of An Expert System For Identifying Dental Diseases Using Certainty Factor Method (Case Study : UPT Puskesmas Parmaksian) Sirait, Gian Patar P.; Refisis, Nice Rejoice
Journal of Informatics and Data Science Vol. 3 No. 1 (2024): JUNE 2024
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/j-ids.v3i1.51274

Abstract

Dental health is crucial for human well-being, yet awareness of its significance is often low. This study addresses the need for an expert system to identify dental diseases, employing the Certainty Factor method. This method allows the system to express the level of certainty in expert statements, facilitating personalized use. The developed expert system calculates Certainty Factor values for each symptom, resulting in an 83% accuracy rate in identifying dental diseases based on tests conducted with 47 out of 56 cases. This research contributes to the field by providing an effective tool for dental disease identification, enhancing both awareness and practical applications in oral health.
Co-Authors Elvis Napitupulu, Elvis Said . Iskandar Siburian, Rulli Prasetio Bane Sinaga, Ronaldo Mardianson Sirait, Gian Patar P. Susiana, Susiana Yulita Molliq Rangkuti