Article Per Year (5 Year)
p-Index From 2021 - 2026
4.617
P-Index
This Author published in this journals
All Journal JURNAL INSTEK (Informatika Sains dan Teknologi) Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Jurnal Teknologi Informasi dan Multimedia bit-Tech G-Tech : Jurnal Teknologi Terapan Idealis : Indonesia Journal Information System Jurnal Sisfotek Global Academic Journal of Computer Science Research (AJCSR) Indonesian Community Journal Jurnal Tren Bisnis Global Information Technology Education Journal JPEG Jurnal Topik Global Jurnal Pendidikan MIPA
DETIN SOFIA
Institut Teknologi Dan Bisnis Bina Sarana Global
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Public Health Social Sciences Other

Published : 34 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 34 Documents
Search

 1   2   3   4 
Sistem Pakar Diagnosa Penyakit TBC Menggunakan Algoritma Forward Chaining dan Certainty Factor Berbasis Android di Puskesmas Kedaung Barat Ujang Sutisna; Argin Fiorenza; Detin Sofia; Shafirah Fitri
Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Vol 8, No 2 (2025): Juli
Publisher : Akademi Ilmu Komputer Ternate

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47324/ilkominfo.v8i2.357

Abstract

Abstrak: Tuberkulosis (TBC) termasuk dalam kategori penyakit menular dan hingga sekarang masih menjadi tantangan besar dalam sektor kesehatan di Indonesia. Proses diagnosa dini sangat penting untuk mencegah penyebaran dan mempercepat penanganannya. Tujuan dari penelitian ini adalah membuat sistem pakar berbasis Android, yang dapat digunakan oleh pengguna untuk mendiagnosis penyakit TBC secara mandiri. Aplikasi dibuat menggunakan Flutter, sebuah framework UI lintas platform yang dikembangkan oleh Google dan bahasa pemrograman Dart untuk mendukung pengembangan aplikasi Android. Sistem ini menerapkan metode Forward Chaining untuk menelusuri gejala yang dimasukkan oleh pengguna, serta Certainty Factor untuk menghitung tingkat kepastian hasil diagnosis berdasarkan gejala yang dialami. Pengujian dilakukan terhadap 25 responden dengan membandingkan hasil sistem dan diagnosis tenaga medis. Tingkat akurasi yang diperoleh melalui pengujian menggunakan metode Confusion Matrix mencapai 84% dengan tampilan antarmuka yang memudahkan pengguna untuk mendapatkan indikasi awal TBC serta solusi tindak lanjut, sehingga mendorong pengguna untuk segera melakukan pemeriksaan ke fasilitas kesehatan.Kata kunci: Sistem Pakar, Tuberkulosis, Forward Chaining, Certainty Factor, AndroidAbstract: Tuberculosis (TB) is classified as a contagious disease and remains a significant challenge in the health sector in Indonesia to this day. Early diagnosis is crucial to prevent its spread and accelerate treatment. This study aims to develop an Android-based expert system that allows users to diagnose TB independently. The application was developed using Flutter, a cross-platform UI framework developed by Google, and the Dart programming language to support Android application development. The system employs the Forward Chaining method to trace symptoms input by users and the Certainty Factor method to calculate the confidence level of the diagnosis based on the experienced symptoms. Testing was conducted on 25 respondents by comparing the system’s results with diagnoses made by medical professionals. The accuracy rate obtained from testing using the Confusion Matrix method reached 84%, with a user-friendly interface designed to provide initial indications of TB and recommended follow-up actions, encouraging users to seek medical examinations promptly..Keywords: Expert System, Tuberculosis, Forward Chaining, Certainty Factor, Android 
Bahasa Inggris Bahasa Inggris Maulana Bhakti Handoko; Zidan Wahyu Fauzi; Halim Agung; Detin Sofia
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2577

Abstract

Selecting a major in Senior High School significantly shapes students’ academic paths and future careers. However, the current process often lacks objectivity, relying on subjective teacher consultations and academic data without standardized analysis. This study addresses this gap by developing a decision support system using the Decision Tree algorithm to assist students at Al-Istiqomah High School in choosing between science and social science majors, based on academic performance and non-academic factors like attitudes and attendance. The study follows the CRISP-DM methodology, which includes six stages: business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Academic records from 123 students were used to build the model. The Decision Tree algorithm identified mathematics, biology, and physics scores as key predictors for major classification. The model demonstrated high predictive performance, with 96% accuracy, 100% precision, and 95% recall. Additionally, an Area Under the Curve (AUC) of 97% confirmed the model’s robust ability to distinguish between science and social science tracks. This system was implemented as a user-friendly web application using Streamlit, enabling students and educators to input data and receive immediate major predictions. By offering objective, data-driven recommendations, the system helps students make more informed decisions about their academic futures and provides educators with targeted, evidence-based advice. These results highlight the Decision Tree algorithm as an effective, efficient, and practical tool for enhancing the academic advising process and supporting students in selecting the major that best fits their strengths and interests.
The Role of Learning Website Integration, Teacher Support, and Student Independence in Enhancing Mathematics Competence at Vocational Schools Lilis Stianingsih; Ferawati; Fiqih Hana Saputri; Detin Sofia
Information Technology Education Journal Vol. 4, No. 4, November (2025)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v4i4.9909

Abstract

Mathematics competence is essential for developing students’ analytical and problem-solving abilities in vocational education. However, many students still face challenges in mastering mathematical concepts effectively. This study aims to examine the influence of Learning Website Integration, Teacher Support, and Student Independence on students’ mathematics competence using a quantitative ex post facto design. The research involved 100 respondents from SMK Bina Mandiri. Data were collected through questionnaires and mathematics competency tests, then analyzed using descriptive statistics and multiple linear regression. The results show that the regression model meets all classical assumption tests and is statistically appropriate for explaining the relationships among variables. Simultaneous testing indicates that all three independent variables significantly influence students’ mathematics competence. Partial testing reveals that each variable has a significant positive effect, with Teacher Support identified as the most dominant factor. The coefficient of determination (R²) is 0.572, meaning that 57.2% of the variation in mathematics competence can be explained by the three variables, while the remaining 42.8% is influenced by other factors outside the model. These findings highlight the importance of integrating technology, strengthening teacher support, and fostering student independence to improve mathematics learning outcomes in vocational education. The results of this study provide guidance for implementing technology-based pedagogy in vocational education.
PENERAPAN METODE STACKING ENSEMBLE UNTUK ANALISIS SENTIMEN PADA ULASAN APLIKASI RUANG GURU Detin Sofia; Pina Sekarpuji
IDEALIS : InDonEsiA journaL Information System Vol. 8 No. 2 (2025): Jurnal IDEALIS Juli 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v8i2.3559

Abstract

Penelitian ini bertujuan untuk menganalisis sentimen pengguna terhadap aplikasi Ruangguru berdasarkan ulasan di Google Play Store. Studi ini berupaya untuk menggambarkan persepsi masyarakat terhadap layanan pembelajaran digital tersebut. Data berupa 99.000 ulasan pengguna dalam bahasa Indonesia dikumpulkan melalui teknik web scraping. Analisis sentiment dilakukan menggunakan pendekatan klasifikasi sentimen berbasis pembelajaran mesin. Penelitian mengikuti tahapan metodologi Cross Industry Standard Process for Data Mining (CRISP-DM), yang terdiri dari Business Understanding, Data Understanding, Data Preparation, Modelling, Evaluation dan Deployment. Sentimen dikategorikan menjadi tiga kelas: positif, negatif dan netral. Proses pra-pemrosesan data melibatkan tahapan seperti pembersihan, tokenisasi, normalisasi. Ekstraksi fitur menggunakan Term Frequency–Inverse Document Frequency (TF-IDF), serta pelabelan data yang dilakukan dengan pendekatan lexicon-based menggunakan kamus kata positif dan negatif yang diunduh dari sumber terbuka. Model klasifikasi yang digunakan dalam penelitian ini adalah Stacking Ensemble dengan Random Forest, Support Vector Machine (SVM), dan Extreme Gradient Boosting (XGBoost) sebagai base learner, serta Logistic Regression sebagai meta learner. Evaluasi performa model menggunakan confusion matrix dan Area Under the Curve (AUC). Model ini menghasilkan Akurasi 88%, Precision 87%, Recall 88% dan F1-Score 87% serta AUC 0,945. Hasil penelitian menunjukkan bahwa mayoritas ulasan memiliki sentimen positif terhadap aplikasi Ruangguru. Temuan ini dapat menjadi masukan strategis bagi pengembang dalam meningkatkan kualitas layanan dan kepuasan pengguna.
Co-Authors Abdillah, Refa Maulana Abdul Latif Achmad Sidik Agustina Mardeka Raya Aldian Ridho Kusuma Alfarizi, Abi Alfrian Ernande Annida Rosna Fadhilah Ardiansyah Jamil Ardie Pratama Argin Fiorenza Azi Abdul Fauzi Bara, Muhamad Aldi Mudin Batu Beny Priambudi Cathy Lintang Prameswary Dedi Dedi Fauzan Dimas Adi Pratama FAUZIAH, FAHMI Ferawati Ferawati Fiqih Hana Saputri, Fiqih Hana Fredy Susanto Frihatini, Farida Habinata Habinata Hafidin, Alfa Halim Agung Hamzah, Muhamad Riski Hanafri, Muhammad Iqbal Herman Santoso Imammul Mutaqin Indri Sela Purwanti Julianti, M. Ramaddan Khoirul Anwar Lilis Stianingsih M. Iqbal Dzulhaq Maulana Bhakti Handoko Mila Amri Misbahul Zannah Mochammad Ramdi Ramadhan Moh Sofjan Moh. Sofjan Mu'ammar Ryadli Muhammad Haromaen Nova Dwi Yulianti Nova Teguh Sunggono Nurahman, Adhi NURBAITI, FITRI Nurmaesah, Nunung Petty Aprilia Sari Pina Sekarpuji Pramana Anwas Panchadria Pratama, Alfian Eka Putri, Eka Uliyanti Rachmat Agusli Rahmat Tullah Ramdhan, Syaipul Rizki Ekadani Rizki Maldini Saepudin, Muhamad Safitri, Nur Hafidzah Santoso, Yuli Savitri Octavia SEKARPUJI, PINA Shafirah Fitri Siti Maisaroh Suladi, Ronal Yulianto Surya Pratama Suryaningtiyas, Galih Alifah Suryantiko, Sandy Susilawati, Novri Sutarman Sutarman Titis Fatmah Sukamto Trian Afiansyah Tullah, Rahmat Ujang Sutisna William Chicho Ferdinan Zainul Hakim Zainul Hakim Zidan Wahyu Fauzi