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All Journal Teika INTI Nusa Mandiri Mosharafa: Jurnal Pendidikan Matematika Infomans: Jurnal Ilmu-ilmu Informatika dan Manajemen Jurnal Intelek Dan Cendikiawan Nusantara
Fidi Supriadi
Universitas Sebelas April
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Mathematics Other

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Perbandingan Model Regresi Nonlinear Polynomial, Ridge, dan Lasso untuk Prediksi Biaya Asuransi Kesehatan Berdasarkan Kerangka CRISP-DM Siti Rachmania Putri; Fidi Supriadi; David Setiadi
TeIKa Vol 15 No 2 (2025): Jurnal
Publisher : Fakultas Teknologi Informasi - Universitas Advent Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36342/3kxrvj44

Abstract

The escalating cost of healthcare necessitates accurate prediction methods for determining medical insurance premiums. This research compares the performance of three nonlinear regression models, namely Polynomial, Ridge, and Lasso, in estimating individual health insurance costs. The research process follows the CRISP-DM framework, which includes the stages of business understanding, data processing, modeling, and evaluation. The dataset used is the Medical Cost Personal Dataset from Kaggle, containing 1,338 individual data points with seven demographic and behavioral features. Six outliers in the BMI and charges features were removed using the IQR method, while categorical features were encoded with One Hot Encoding. Numerical features were transformed using second-degree Polynomial Features to capture nonlinear relationships, and then the data was split into 80% training and 20% testing. Evaluation used the Mean Squared Error (MSE) and R-squared (R²) metrics. The results indicate Ridge Regression yielded the best performance with an R² value of 0.857 and an MSE of 2.35×10⁷. This model is more stable and effective in handling multicollinearity compared to the other two models. Nevertheless, the average prediction error of approximately USD 4,800 suggests the need for increased accuracy through parameter tuning or data augmentation before being implemented in a real business environment.
Needs Analysis: Development of an LMS-Assisted DELPHI-STEAM Model to Improve Students' Computational Thinking and Character Yusfita Yusuf; Margaretha Madha Melissa; Tuti Yuliawati Wachyar; Fidi Supriadi; Shofia Annisa Ratnasari; Ucu Kosmawa; Hadian Setya Ramdani; Anggia Gantira
Mosharafa: Jurnal Pendidikan Matematika Vol. 15 No. 1 (2026): January
Publisher : Department of Mathematics Education Program IPI Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31980/mosharafa.v15i1.3541

Abstract

Kemajuan teknologi menuntut siswa memiliki keterampilan berpikir komputasional sekaligus karakter yang kuat. Namun, belum tersedia model pembelajaran yang mengintegrasikan kedua aspek tersebut secara simultan. Penelitian ini bertujuan melakukan analisis kebutuhan untuk mengembangkan model pembelajaran DELPHI-STEAM (Deep Learning Project Hypnoteaching-STEAM) berbasis Learning Management System (LMS). Menggunakan model pengembangan ADDIE, penelitian saat ini berada pada fase analisis. Data dikumpulkan melalui instrumen penilaian berpikir komputasional, survei karakter, protokol observasi, dan wawancara terhadap guru serta siswa di 15 sekolah negeri dan swasta di Kabupaten Sumedang. Hasil penelitian menunjukkan bahwa pengembangan model DELPHI-STEAM berbasis LMS beserta perangkat pendukungnya sangat esensial dan layak diimplementasikan. Model ini terbukti dapat meningkatkan kemampuan berpikir komputasional dan pengembangan karakter secara bersamaan. Selain itu, model ini mampu mentransformasi matematika dalam proyek STEAM menjadi pengalaman belajar yang lebih bermakna dan menyenangkan bagi siswa. Technological advancements demand that students possess both computational thinking skills and strong character development. Currently, pedagogical models that simultaneously integrate these two aspects remain scarce. This study aims to conduct a needs analysis for developing the LMS-supported DELPHI-STEAM (Deep Learning Project Hypnoteaching-STEAM) model. Adopting the ADDIE development framework, the research is currently in the analysis phase. Data were collected through computational thinking assessments, character surveys, observation protocols, and interviews involving teachers and students across 15 public and private schools in Sumedang Regency. The findings indicate that the development of the LMS-based DELPHI-STEAM model and its supporting tools is both essential and feasible. This model is designed to concurrently enhance computational thinking and character growth. Furthermore, it transforms mathematics, traditionally utilized as a mere computational tool in STEAM projects, into a more meaningful and engaging learning experience for students.
Perbandingan Kinerja Algoritma Linear Search dan Binary Search dalam Pencarian Data Revaliana Indriyani Surachman; Fidi Supriadi; Asep Saeppani; Fathoni Mahardika
Infoman's : Jurnal Ilmu-ilmu Informatika dan Manajemen Vol. 19 No. 2 (2025): Infoman's
Publisher : LPPM & Fakultas Teknologi Informasi UNSAP

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Abstract

Data searching is a fundamental aspect of computer science that affects application performance. This study aims to analyze and compare the efficiency of two basic searching algorithms, namely Linear Search and Binary Search. The research method was conducted by testing both algorithms using datasets with a varying number of elements to measure execution time and algorithm complexity. The results showed that Linear Search is more efficient for small or unsorted data, while Binary Search shows much superior performance on large sorted datasets with a time complexity of O(log n). The conclusion of this study provides guidance in choosing the right searching algorithm based on data characteristics and system requirements.
ANALISIS DISTRIBUSI MINAT MAHASISWA PADA KONSENTRASI INFORMATIKA MENGGUNAKAN PENDEKATAN DATA-DRIVEN DECISION MAKING Fathoni Mahardika; Fidi Supriadi; Agun Guntara
INTI Nusa Mandiri Vol. 19 No. 2 (2025): INTI Periode Februari 2025
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v19i2.6347

Abstract

In the digital era, higher education institutions face the challenge of aligning the curriculum with the dynamic demands of the industry. This research aims to identify patterns of student interest in choosing specialization concentrations in the Informatics Study Program (S1), Universitas Sebelas April, using a data-driven decision-making approach. The study involved 133 5th semester students out of a total population of 500 students in the Computer Science program at Sebelas April University. The respondents were selected because they were at the relevant stage of study to determine the specialization concentration, the results of which provide important recommendations for curriculum optimization and resource allocation.Student specialization survey data were analyzed using descriptive statistics, data visualization, and trend analysis to provide data-driven insights to support more efficient academic planning. The results showed that the concentration of "Computer Science, Software, and Intelligent Systems" was more desirable than "System Security and Computer Networks".
Rancang Bangun Sistem Informasi Sekolah Luar Biasa Bina Bhakti Mandiri Berbasis Web Raka Rey Ferdian; Fidi Supriadi; David Setiadi
Jurnal Intelek Dan Cendikiawan Nusantara Vol. 3 No. 04 (2026): AGUSTUS - SEPTEMBER 2026
Publisher : PT. Intelek Cendikiawan Nusantara

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Abstract

SLB Bina Bhakti Mandiri belum memiliki website sebagai media penyampaian informasi dan promosi sekolah, sehingga informasi mengenai profil, kegiatan, prestasi, fasilitas, serta Penerimaan Peserta Didik Baru (PPDB) belum dapat disampaikan secara optimal kepada masyarakat. Penelitian ini bertujuan untuk menghasilkan Sistem Informasi Sekolah Luar Biasa Bina Bhakti Mandiri berbasis web yang dapat digunakan sebagai media informasi, media promosi, dan layanan PPDB secara online. Pengembangan sistem menggunakan metode Agile Software Development dengan tahapan Requirement, Design, Development, Testing, Deployment, dan Review. Pengujian sistem dilakukan menggunakan Black Box Testing untuk menguji fungsi sistem dan User Acceptance Testing (UAT) untuk mengetahui tingkat penerimaan pengguna. UAT dilakukan terhadap 26 responden yang terdiri atas 1 admin dan 25 pengunjung menggunakan kuesioner dengan skala Likert. Hasil pengujian UAT menunjukkan persentase sebesar 90,86% pada aspek kemudahan pengguna, 90,93% pada aspek kepuasan pengguna, 90,73% pada aspek fungsionalitas sistem, dan 89,13% pada aspek kinerja sistem. Seluruh hasil tersebut berada pada kategori sangat baik. Berdasarkan hasil pengujian, sistem yang dikembangkan telah memenuhi kebutuhan fungsional dan memperoleh penerimaan yang baik dari pengguna. Sistem berhasil diimplementasikan secara online menggunakan domain slbbinabhaktimandiri.sch.id dan dapat digunakan sebagai media informasi dan promosi SLB Bina Bhakti Mandiri.
Co-Authors Agun Guntara Anggia Gantira Asep Saeppani David Setiadi David Setiadi Fathoni Mahardika Hadian Setya Ramdani Margaretha Madha Melissa Raka Rey Ferdian Revaliana Indriyani Surachman Shofia Annisa Ratnasari Siti Rachmania Putri Tuti Yuliawati Wachyar Ucu Kosmawa Yusfita Yusuf