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All Journal Natural Science: Journal of Science and Technology Electronic Journal of Graph Theory and Applications (EJGTA) JURNAL ILMIAH MATEMATIKA DAN TERAPAN BAREKENG: Jurnal Ilmu Matematika dan Terapan Mathvision : Jurnal Matematika Riemann : Research of Mathematics and Mathematics Education Jurnal Pengabdian Farmasi dan Sains
Selvy Musdalifah
Algebra And Combinatorics Research Group, Department Of Mathematics, Faculty Of Mathematics And Natural Sciences, Universitas Tadulako
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Immunology & microbiology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Transportation

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PENENTUAN TINGKAT RESIKO PENYAKIT DIABETES MELLITUS DENGAN METODE SUGENO DI RSUD UNDATA PROVINSI SULAWESI TENGAH Huzaimah, Huzaimah; Musdalifah, Selvy; Hendra, A; Sudarsana, I Wayan
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 9 No. 1 (2012)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (509.106 KB) | DOI: 10.22487/2540766X.2012.v9.i1.7458

Abstract

PENENTUAN TINGKAT RESIKO PENYAKIT DIABETES MELLITUS DENGAN METODE SUGENO DI RSUD UNDATA PROVINSI SULAWESI TENGAH
MENENTUKAN NILAI PRODUKSI INDUSTRI ROTAN CV. BUDI MULYA DENGAN MENGGUNAKAN METODE DEKOMPOSISI LU PADA MODEL EKONOMI LEONTIEF Werokati, I; Musdalifah, Selvy; Hendra, A
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 9 No. 1 (2012)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (349.941 KB) | DOI: 10.22487/2540766X.2012.v9.i1.7460

Abstract

MENENTUKAN NILAI PRODUKSI INDUSTRI ROTAN CV. BUDI MULYA DENGAN MENGGUNAKAN METODE DEKOMPOSISI LU PADA MODEL EKONOMI LEONTIEF
ENKRIPSI AFFINE CIPHER UNTUK STEGANOGRAFI PADA ANIMASI CITRA GIF Musdalifah, Selvy; Hendra, A
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 9 No. 1 (2012)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (580.13 KB) | DOI: 10.22487/2540766X.2012.v9.i1.7462

Abstract

ENKRIPSI AFFINE CIPHER UNTUK STEGANOGRAFI PADA ANIMASI CITRA GIF
IMPLEMENTASI ALGORITMA K-MEANS UNTUK DIAGNOSA PENYAKIT GAGAL GINJAL KRONIS Hervisari, Hervisari; Musdalifah, Selvy; Sudarsana, I Wayan
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 11 No. 1 (2014)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (373.718 KB) | DOI: 10.22487/2540766X.2014.v11.i1.7468

Abstract

IMPLEMENTASI ALGORITMA K-MEANS UNTUK DIAGNOSA PENYAKIT GAGAL GINJAL KRONIS
PELABELAN SUPER MEAN PADA GRAF 𝑫𝒏(𝑪𝟑) DAN 𝑫𝒏(𝑪𝟑) v 𝑷𝒕 Wahyuningsi, Sri; Sudarsana, I Wayan; Musdalifah, Selvy
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 12 No. 1 (2015)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (520.978 KB) | DOI: 10.22487/2540766X.2015.v12.i1.7490

Abstract

PELABELAN SUPER MEAN PADA GRAF 𝑫𝒏(𝑪𝟑) DAN 𝑫𝒏(𝑪𝟑) v 𝑷𝒕
PELABELAN SUPER MEAN PADA GENERALISASI GRAF TUNAS KELAPA Merdekawati, Dian Ayu; Sudarsana, I Wayan; Musdalifah, Selvy
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 13 No. 1 (2016)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (633.365 KB) | DOI: 10.22487/2540766X.2016.v13.i1.7498

Abstract

PELABELAN SUPER MEAN PADA GENERALISASI GRAF TUNAS KELAPA
Penyelesaian Persamaan Diferensial Menggunakan Metode Runge Kutta Orde Keenam Dengan Algoritma Paralel Al Fajri, Iman; Hendra; Kusuma, Jeffry; Musdalifah, Selvy; Nacong, Nasria; Sain, Hartayuni; Arsal, Armayani
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 20 No. 2 (2023)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/2540766X.2023.v20.i2.16354

Abstract

Penelitian tentang paralelisasi terus mengalami perkembangan saat ini, termasuk dalam perhitungan numerik. Pada tulisan ini akan dibahas penyelesaian persamaan diferensial menggunakan metode Runge-Kutta orde keenam dengan algoritma paralel. Makalah ini menyajikan penurunan dari metode Runge-Kutta orde keenam yang cocok untuk implementasi secara paralel. Pengembangan model paralel didasarkan pada struktur ketersebaran. Hasil perhitungan dengan model paralel kemudian akan dibandingkan dengan model sekuensial dari sisi akurasi dan waktu eksekusi. Pehitungan numerik menunjukkan bahwa metode paralel lebih mendekati solusi analitik, artinya akurasinya lebih baik. Ditinjau dari sisi waktu eksekusi, metode paralel juga memiliki keunggulan dibandingakan dengan metode sekuensial, yaitu lebih cepat.
Application Of Max-Plus Algebra In Determining The Shortest Route Of Goods Distribution On Jalur Nugraha Ekakurir (JNE) In Palu City Tandi, Andri; Lusiyanti, Desy; Musdalifah, Selvy
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 21 No. 1 (2024)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/2540766X.2024.v21.i1.17082

Abstract

Determining the shortest route is a solution that is needed for companies engaged in the distribution of goods, because the shortest route can help companies optimize the distance traveled and streamline the time needed. Therefore, this study aims to apply max-plus algebra to determine the shortest route for the distribution of goods on the Jalur Nugraha Ekakurir (JNE) in Palu City. This method was chosen because Max-Plus Algebra can find more optimal results from the matrix exponentiation operation of a weighted graph. The data used were obtained from previous research which consisted of 13 JNE warehouse points along with the distance between these points. The results to be obtained are in the form of the shortest route between one point and another which is represented in a graph path with each path length and weight obtained based on the results of max-plus algebraic calculations. Of all the possible route, obtained the route with the minimum weight for distribution of goods from JNE main warehouse dewi sartika (v_1) to JNE tondo mantikulore (v_13), that is JNE main warehouse dewi sartika (v_1) → to JNE basuki rahmat (v_4) → JNE Sisingamangaraja palu (v_8) → JNE tondo mantikulore (v_13) with a total distance of 13.3 km.
PELATIHAN PENGGUNAAN APLIKASI GEOGEBRA DALAM MENYELESAIKAN TURUNAN FUNGSI REAL BAGI SISWA SMA 4 SIGI Lusiyanti, Desy; Selvy Musdalifah; Iman Al Fajri; Andri
JURNAL PENGABDIAN FARMASI DAN SAINS Vol. 3 No. 1 (2024): Oktober 2024
Publisher : Jurusan Farmasi FMIPA Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/jpsf.2024.v3.i1.17365

Abstract

The training on the use of the GeoGebra™ application at SMA 4 Sigi aimed to enhance students' understanding of the concept of derivatives of real functions through an interactive and technology-based learning approach. GeoGebra™ was chosen as a tool due to its capability to visualize function graphs and their derivatives, thus facilitating students' comprehension of complex mathematical concepts. This training involved 40 students, beginning with basic GeoGebra™ introductions and concluding with practical applications in solving derivative problems. The results of the training showed a significant improvement in students' understanding and skills, as evidenced by an average increase of 25 points in post-test scores compared to pre-test scores. Additionally, feedback from students indicated that 90% felt more confident and found GeoGebra™ easy to use, and were satisfied with the learning method implemented. The use of GeoGebra™ also successfully fostered students' interest in exploring more mathematical topics through visualization approaches. The success of this training highlights the importance of integrating technology into education to enhance learning quality and students' skills in solving mathematical problems. It is recommended that this training becomes a regular program with a broader scope of topics to support the continuous development of students' technological and academic abilities.
Evaluasi Kinerja Algoritma Machine learning pada Dataset Skala Besar Lusiyanti, Desy; Musdalifah, Selvy; Sahari, Agusman; Fajri, Iman Al
MathVisioN Vol 7 No 1 (2025): Maret 2025
Publisher : Prodi Matematika FMIPA Unirow Tuban

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55719/mv.v7i1.1661

Abstract

Di era digital, volume data yang dihasilkan terus meningkat secara eksponensial, menuntut pengembangan metode analisis yang lebih efisien dan akurat. Machine Learning (ML) telah menjadi pendekatan utama dalam pengolahan dataset skala besar, termasuk dalam analisis kualitas air. Penelitian ini bertujuan untuk mengevaluasi performa beberapa algoritma ML dalam mengklasifikasikan kualitas air berdasarkan dataset berskala besar yang diperoleh dari sumber daring. Model yang diuji mencakup Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), XGBoost (XGB), K-Nearest Neighbors (KNN), dan Support Vector Machine (SVM). Metodologi yang diterapkan mencakup preprocessing data dengan imputasi median untuk menangani missing values serta K-Fold Cross Validation (k=10) untuk memastikan hasil yang lebih generalizable. Evaluasi model dilakukan berdasarkan metrik akurasi, precision, recall, F1-score, dan waktu komputasi. Hasil penelitian menunjukkan bahwa XGBoost memiliki performa terbaik dengan akurasi 67%, diikuti oleh Decision Tree, KNN, dan SVM dengan akurasi 65%, sedangkan Logistic Regression dan Random Forest memiliki akurasi 63%. Temuan ini mengonfirmasi bahwa model berbasis gradient boosting seperti XGBoost lebih unggul dalam menangani kompleksitas dataset skala besar dibandingkan model berbasis regresi atau pohon keputusan tunggal. Penelitian ini berkontribusi dalam memberikan rekomendasi bagi akademisi dan praktisi dalam memilih algoritma ML yang paling efisien dan optimal untuk analisis kualitas air. Rekomendasi untuk penelitian selanjutnya mencakup eksplorasi optimasi hyperparameter, balancing dataset, serta pengujian dengan dataset real-time untuk validasi lebih lanjut.
Co-Authors Afni, N Agusman Sahari Al Fajri, Iman Andi Hendra Andri Anita Ahmad Kasim Armayani Arsal Desy Lusiyanti Faisal Susanto Fitria Fitria Hartayuni Sain Hervisari, Hervisari Huzaimah Huzaimah I W. Sudarsa I Wayan Sudarsana Iman Al Fajri Iman Al Fajri Ismiyanti, Ismiyanti Jeffry Kusuma Merdekawati, Dian Ayu Nasria Nacong Nikita Nikita, Nikita Noviana Noviana Nurainun Nurainun Nurwijayanti Rizki Amalia S Fatimah, S Sri Nurhayati Tandi, Andri Trisha Magdalena A. Jauvani Wahyuningsi, Sri Werokati, I Yesi, Indah