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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Alamtana
Raja Ayu Mahessya
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering

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IMPLEMENTASI METODE ANFIS DATA MINING DALAM MENYELEKSI BEASISWA DI SMPN 7 SOROLANGUN Raja Ayu Mahessya; Sulvia Indrawati
Jurnal PROCESSOR Vol 12 No 1 (2017): Jurnal Processor
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The author discusses the use of Adaptive Neuro Fuzzy Interference System (ANFIS) in implementing the Scholarship Selection Acquisition using ANFIS (Adaptive Neuro Fuzzy Interface System) or Adaptive Network-based Fuzzy Interface System for the withdrawal of its conclusions. ANFIS is an architecture that is functionally similar to the fuzzy rule base Sugeno models. It could be said that ANFIS is a method by which in adjusting the rules used learning algorithms on a set of data. The hope is to get knowledge of such data, obtained from the knowlage ANFIS method is the rule on Fuzzy Interface System (FIS). This study aims to predict students who received scholarships, so the school did not have to bother anymore to manually select students. Data for the training system focuses on three pieces of input value, Number of Dependents Parents and Parents Income; and 1 pc output is Earned Scholarship. From the results obtained training, web-based application created to determine Acquisition Scholarship based on the available quota. Then students can register online for the scholarship application process so that students easily access the information about scholarships
Pemanfaatan Teknologi Digital dalam Pembelajaran Siswa SMP Sahara Padang Raja Ayu Mahessya; Larissa Naviarani; Devia Kartika
Alamtana: Jurnal Pengabdian Masyarakat UNW Mataram Vol 3 No 3 (2022): Edisi Desember 2022
Publisher : LPPM UNIVERSITAS NAHDLATUL WATHAN MATARAM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51673/jaltn.v3i3.1243

Abstract

Pemanfaatan teknologi informasi dan komunikasi menjadi salah satu prinsip pembelajaran di sekolah menengah pertama dalam rangka meningkatkan efisiensi dan efektifitas pembelajaran. Seorang guru perlu mengembangkan penerapan teknologi informasi dan komunikasi yang disesuaikan dengan situasi dan kondisi peserta didik secara terintegrasi, sistematis, efektif. Guru dapat melakukan penerapan teknologi informasi dan komunikasi pada pembelajaran dengan berbagai bentuk salah satunya adalah pembelajaran dengan menggunakan e-module interaktif menggunakan aplikasi canva. E-module merupakan salah satu bentuk media ajar yang memiliki konten dan lebih berfokus pada aktivitas belajar yang dikembangkan pada program pendidikan dan pelatihan. E-modul digital merupakan salah satu jenis yang dioperasikan pada berbagai peralatan digital seperti computer dan mobile.
Optimizing Sensitivity in Machine Learning Models for Pediatric Post-operative Kyphosis Prediction Raja Ayu Mahessya; Dian Eka Putra; Rostam Ahmad Efendi; Rayendra; Rozi Meri; Riyan Ikhbal Salam; Dedi Mardianto; Ikhsan; Ismael; Arif Rizki Marsa
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 3 (2025): June 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i3.6606

Abstract

Post-operative kyphosis represents a significant complication following pediatric spinal corrective surgery, necessitating sophisticated prediction methods to identify high-risk patients. This study developed and evaluated machine learning models for kyphosis prediction using a dataset of 81 pediatric patients by comparing the logistic regression and decision tree approaches. Despite achieving a higher overall accuracy (82%), the logistic regression model failed to identify any kyphosis cases, rendering it clinically ineffective. Conversely, the decision tree model demonstrated superior clinical utility by successfully identifying 33% of kyphosis cases while maintaining 71% accuracy. Feature importance analysis established starting vertebral position as the dominant predictor (importance=0.554), followed by patient age (0.416), with vertebrae count contributing minimally (0.030). The decision tree identified critical thresholds for risk stratification: operations beginning at or above T8-T9, particularly in children aged 5-9 years, carried a substantially elevated kyphosis risk. Our methodological approach emphasizes sensitivity over conventional accuracy metrics, recognizing that missing high-risk patients have greater clinical consequences than unnecessary monitoring. This study demonstrates the capacity of decision tree models to extract clinically meaningful patterns from small, imbalanced surgical datasets that elude conventional statistical approaches.
Co-Authors Arif Rizki Marsa Dedi Mardianto Devia Kartika Dian Eka Putra Ikhbal Salam, Riyan Ikhsan Ismael Larissa Naviarani Rayendra Rostam Ahmad Efendi Rozi Meri Sulvia Indrawati