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All Journal Jurnal Ilmu Dasar Jurnal Sains Dasar Journal of Mathematics Education and Application (JMEA) Journal of Natural Sciences and Mathematics Research Edu Sains: Jurnal Pendidikan Sains dan Matematika JMPM: Jurnal Matematika dan Pendidikan Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Matematika UNAND Dinasti International Journal of Economics, Finance & Accounting (DIJEFA) Jambura Journal of Biomathematics (JJBM) Indonesian Journal of Applied Research (IJAR) Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi JES-MAT (Jurnal Edukasi dan Sains Matematika) Pakem : Jurnal Pengabdian Kepada Masyarakat Journal of Educational Sciences Pattimura International Journal of Mathematics (PIJMath) Jurnal Riset Mahasiswa Matematika Innovative: Journal Of Social Science Research Hexagon: Jurnal Ilmu dan Pendidikan Matematika Journal of Mathematics, Computation and Statistics (JMATHCOS) Indonesian Journal of Computational and Applied Mathematics
Nurwan, Nurwan
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Comparison of Feature Selection Based on Computation Time and Classification Accuracy Using Support Vector Machine Salmun K Nasib; Fadilah Istiqomah Pammus; Nurwan; La Ode Nashar
Indonesian Journal of Applied Research (IJAR) Vol. 4 No. 1 (2023): Indonesian Journal of Applied Research (IJAR)
Publisher : Universitas Djuanda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30997/ijar.v4i1.252

Abstract

The goal of this research to compare Chi-Square feature selection with Mutual Information feature selection based on computation time and classification accuracy. In this research, people's comments on Twitter are classified based on positive, negative, and neutral sentiments using the Support Vector Machine method. Sentiment classification has the disadvantage that it has many features that are used, therefore feature selection is needed to optimize a sentiment classification performance. Chi-square feature selection and mutual information feature selection are feature selections that both can improve the accuracy of sentiment classification. How to collect the data on twitter taken using the IDE application from python. The results of this study indicate that sentiment classification using Chi-Square feature selection produces a computation time of 0.4375 seconds with an accuracy of 78% while sentiment classification using Mutual Information feature selection produces an accuracy of 80% with a required computation time of 252.75 seconds. So that the conclusion are obtained based on the computational time aspect, the Chi-Square feature selection is superior to the Mutual Information feature selection, while based on the classification accuracy aspect, the Mutual Information feature selection is more accurate than the Chi-Square feature selection. The recommendations for further research can use mutual information feature selection to get high accuracy results on sentiment classification
Improving students' problem-solving abilities by using geogebra learning media on three-dimensional material Ramadiana, Anastasya; Takaendengan, Bertu Rianto; Nurwan, Nurwan; Zakaria, Perry; Usman, Kartin; Yahya, Lailany
Edu Sains: Jurnal Pendidikan Sains & Matematika Vol 12 No 1 (2024): VOLUME 12 NOMOR 1 JUNI 2024
Publisher : IAIN Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23971/eds.v12i1.5802

Abstract

The COVID-19 pandemic has had an impact on the learning process in schools. For this reason, researchers observed learning at SMA Negeri 1 Gorontalo, it was found that students were still not optimal in solving mathematical problems, especially in formulating steps to solve problems. This research aims to improve students' problem-solving abilities by using GeoGebra on three-dimensional material. The research was carried out at SMA Negeri 1 Gorontalo in class XII IPA 5 from September to October of the 2022/2023 academic year with research subjects totaling 30 students. The research is Classroom Action Research (CAR) using the Kemmis and McTaggart model, which involves the stages of planning, action, observation, and reflection. Data was obtained from observation and written tests. Analysis of observation results was obtained by calculating scores for each aspect criterion observed both on the teacher observation sheet and the student observation sheet, while the written test was analyzed by referring to the minimum completeness criteria. The results of the research show that there is an increase in students' problem-solving abilities in three-dimensional material after taking action using the GeoGebra learning media.
Nonpreemptive Goal Programing Method in Optimization Nurse Scheduling by Considering Education Level Utina, Fitriani; Yahya, Lailany; Nurwan, Nurwan
Jurnal ILMU DASAR Vol 22 No 2 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/jid.v22i2.16939

Abstract

Nurse scheduling is one of the problems that often arise in hospital management systems. Head of ICU room and nurse to cooperate in making good nurse scheduling for the creation of optimal service. In this paper, we study a hospital nurse schedule design by considering the level of nurse education and the provision of holidays. Nurses with undergraduate education (S1) Nurses become leaders on every shift and are accompanied by nurses with diploma education (D3). The scheduling model in this study using the nonpreemptive goal programming method and LINGO 11.0 software. The preparation of the schedule of nurses assigned to this method can optimize the need for efficient nurses per shift based on education level. The data in the research was obtained by collecting administrative data at Aloei Saboe Gorontalo hospital. The data used are the published schedule by the head of the ICU room. In making a nurse schedule, there are limitations to consider such ashospital regulation. The results of the study obtained an optimal solution in the form of meeting all the desired obstacles. Computational results shows that nurse scheduling using the nonpreemptive goal programming method and LINGO 11.0 software better than the schedule created manually. Every shift is a maximum of one leader with an undergraduate education (S1) background and accompanied by a nurse with a diploma education (D3) background. Keywords: scheduling, goal programming, nonpreemptive goal programming.
ANALISIS WAKTU PELAYANAN TEKNIK GANGGUAN LISTRIK OLEH PERUSAHAAN LISTRIK NEGARA (PLN) DENGAN METODE ALJABAR MAX PLUS DAN PETRI NET Yahya, Lailany; Nuha, Agusyarif Rezka; Sari, Lia Nanda; Nurwan, Nurwan
Jurnal Sains Dasar Vol 13, No 2 (2024): Oktober 2024
Publisher : Faculty of Mathematics and Natural Science, Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jsd.v13i2.74503

Abstract

Penelitian ini menggabungkan konsep Aljabar Max Plus dan jaringan Petri Net untuk mengetahui waktu optimal dalam sistem pelayanan teknik gangguan listrik. Aljabar Max Plus digunakan untuk menganalisis dengan memperhitungkan waktu proses pelayanan teknik gangguan listrik dan untuk alur Petri Net digunakan untuk menggambarkan struktur sistem pelayanan teknik gangguan listrik. Dengan menggunakan kedua metode ini, dapat mengoptimalkan alur kerja dan meningkatkan efisiensi pelayanan. Dari hasil analisis alur Petri Net pelayanan teknik gangguan listrik yang telah dibuat diperoleh bahwa Petri Netselalu Liveness dan tidak pernah deadlocks. Hasil analisis dan simulasi model Aljabar Max Plus diperoleh lamanya waktu proses pelayanan teknik gangguan listrik melalui contact center 123 sampai selesai membutuhkan waktu 40 menit 59 detik. Untuk Pelayanan teknik gangguan listrik dengan datang langsung ke kantor sampai selesai membutuhkan waktu 44 menit 26 detik dan untuk  Pelayanan teknik gangguan listrik melalui PLN mobile sampai selesai membutuhkan waktu 39 menit 30 detik.
Penerapan Hybrid Metode ARFIMA-ANN Menggunakan Algoritma Backpropagation pada Peramalan Indeks Harga Saham Gabungan Buhungo, Rayhanul Jannah; Hasan, Isran K; Nurwan, Nurwan
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 12 Issue 2 December 2024
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v12i2.28474

Abstract

The Composite Stock Price Index (IHSG) is a of the key indicator a country uses to assess its economic condition. The fluctuating movements of stock prices create uncertainly in the stock market, complicating decision-making for investors and government entities. Therefore, there is a need for a method that can forecast the Composite Stock Price Index to monitor such fluctuations. The objective of this study is to model the Composite Stock Price Index Utilizing a hybrid method and to assess the accuracy of this hybrid approach. The hybrid method employed is the Autoregressive Fractionally Integrated Moving Average (ARFIMA)-Artificial Neural Network (ANN). The results of this study show that the best ARFIMA model is ARFIMA (1,d,1) with a differencing parameter of dR/S = 0,362. The ANN model's optimal architecture obtained through the backpropagation algorithm is ANN (3,2,1). The accuracy of the hybrid ARFIMA-ANN model, measured by the Mean Absolute Percentange Error (MAPE), yielded of 1,0164%, lower than the MAPE value of 1,7326% for the standalone ARFIMA model. This suggests that the hybrid model improves forecasting accuracy and is the most efferctive model for predicting the IHSG. 
On The Rainbow Connection Of Middle Graph Of Firecracker Graphs (F_(n,4)) Rahim, Delvira Masita; Nurwan, Nurwan; Yahya, Nisky Imansyah; Wungguli, Djihad; Arsal, Armayani
JMEA : Journal of Mathematics Education and Application Vol 4, No 1 (2025): Februari
Publisher : JMEA : Journal of Mathematics Education and Application

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jmea.v4i1.22686

Abstract

Coloring in graph theory includes various approaches, one of which is rainbow coloring which is closely related to the concept of rainbow connected numbers which refers to the least number of colors needed to color the edges in a graph so that every two vertices connected in a rainbow path have the same color and is denoted by rc(G). Rainbow coloring can be studied in several forms of graph development, one of which is the middle graph. All types of graphs, both simple and complex, can be represented as a middle graph. A middle graph is a graph whose vertices are obtained from the vertices and edges of graph G and is denoted by V (M(G)) = V (G)∪(G). Two points in a middle graph are considered adjacent if and only if they are adjacent edges in G or one of the points is adjacent to an edge of G. In this research, we discuss the number rc(G) on the middle graph of firecracker graph (F_(n,4))  with n ≥ 2. Based on the research results, we obtain the rainbow connected number theorem on the middle graph of firecrackers graph rc(M(F_(n,4))) = 3n + 2 for n ≥ 2.
Bilangan Terhubung Pelangi pada Graf Ferris Wheel (Fw_n) Lakisa, Narti; Nurwan, Nurwan; Nasib, Salmun K.; Yahya, Nisky Imansyah
JMPM: Jurnal Matematika dan Pendidikan Matematika Vol 7 No 1 (2022): March - August 2022
Publisher : Prodi Pendidikan Matematika Universitas Pesantren Tinggi Darul Ulum Jombang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/jmpm.v7i1.2337

Abstract

Pada penelitian ini didefinisikan graf baru yang dinamakan graf ferris wheel yang dinotasikan dengan Fw_n. Graf ferris wheel dengan 2n+1 titik dan 5n sisi dihasilkan dengan menggabungkan dua buah graf yaitu graf lingkaran dan graf roda dengan menambahkan sisi sebanyak 2n. Tujuan dari penelitian ini adalah menentukan bilangan terhubung pelangi pada graf ferris wheel dengan bilangan bulat positif n>=3 dengan langkah-langkah; menggambar graf ferris wheel, menentukan bilangan terhubung pelangi dan membuktikan teorema bilangan terhubung pelangi pada graf ferris wheel. Metode dalam penelitian ini adalah studi literatur. Hasilnya diperoleh bilangan terhubung pelangi pada graf ferris wheel yaitu rc(Fw_3 atau Fw_4)=2, rc(Fw_5 atau Fw_6)=3, rc(Fw_7 atau Fw_8)=4, rc(Fw_9 atau Fw_10)=5, dan rc(Fw_n)=j+6 jika n=3j+11, 3j+12, dan 3j+13 untuk j>=0
Karakteristik Rantai Markov pada Data Curah Hujan Bulanan Stasiun Djalaluddin Nasib, Salmun K; Nurwan, Nurwan; Yanuari, Eka Dicky D; Macmud, Tedy
JMPM: Jurnal Matematika dan Pendidikan Matematika Vol 7 No 2 (2022): September 2022 - February 2023
Publisher : Prodi Pendidikan Matematika Universitas Pesantren Tinggi Darul Ulum Jombang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/jmpm.v7i2.2654

Abstract

Penelitian ini bertujuan untuk menganalisis karakteristik model rantai Markov pada data curah hujan bulanan. Data curah hujan bulanan dibagi dalam tiga state yaitu kering, lembab, dan basah. Sebagian besar data terkategorikan pada state 3 yaitu kondisi basah sebesar 54,41%. Berdasarkan hasil evaluasi data curah hujan di Stasiun Djalaluddin, memiliki curah hujan yang cukup tinggi dengan presentase diatas 50%. Peluang transisi tertinggi adalah  sebesar 61,9% dimana peluang transisi dari kondisi basah kembali ke kondisi basah lebih besar daripada peluang menuju kondisi kering atau lembab. Karakteristik rantai Markov data curah hujan bulanan menunjukkan kondisi yang tidak stabil dan kecilnya peluang transisi untuk berpindah ke kondisi lainnya.
PENERAPAN MODEL INTEGER LINEAR PROGRAMMING DALAM OPTIMASI PENJADWALAN PERKULIAHAN SECARA OTOMATIS Wungguli, Djihad; Nurwan, Nurwan
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 14 No 3 (2020): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1001.471 KB) | DOI: 10.30598/barekengvol14iss3pp411-422

Abstract

Lectures scheduling is a difficult administrative task for universities. This happens because in lectures scheduling must combine the number of courses, approve the room, day and period, as well as teaching lecturers. The purpose of this article is to create an optimization model for courses scheduling using integer linear programming to minimize the level of dissatisfaction between lecturers and students. This model is applied to making a schedule in the Mathematics Study Program at Gorontalo State University. In this research, data and information collected about the scheduling of lectures as a basis for making models. There are 55 study groups scheduled in 4 rooms, 5 days and 12 time periods. Furthermore, the scheduling optimization model is made in the form of integer linear programming and is solved by LINGO 18.0 software. The result obtained from this study is a lecture schedule that is free of conflict. Lectures scheduling produced meets the requirements and requests for lecturers and students in the Mathematics Study Program. In addition, the resulting model can help the time needed to do the scheduling.
ANALISIS PERPINDAHAN PENGGUNAAN APLIKASI TRANSPORTASI ONLINE MENGGUNAKAN RANTAI MARKOV K. Nasib, Salmun; Nurwan, Nurwan; Aryasandi, I Wayan Can; K. Hasan, Isran; Asriadi, Asriadi
Jurnal Matematika UNAND Vol. 13 No. 1 (2024)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.13.1.26-40.2024

Abstract

The purpose of this study is to find out the opportunities for switching to the use of online transportation applications and predict the future use of online transportation applications by Gorontalo State University students using the Markov chain. The data used in this study are primary data obtained through questionnaires. The results of the prediction of the proportion for future market share show that the proportion of users of the Maxim transportation application is 82.89%, Grab is 7.75%, Gojek is 5.06% and InDriver is 4.48%.
Co-Authors Abdul Wahab Abdulah, Siska Agusyarif Rezka Nuha Ahaya, Sitty Oriza Sativa Putri Aini Fitriyah Armayani Arsal Artes Jr., Rosalio Aryasandi, I Wayan Can Asriadi Asriadi Asriadi Asriadi Aznaim, Aznaim Bertu Rianto Takaendengan Bilondatu, Rosna Ningsih Buhungo, Rayhanul Jannah Dewi Rahmawaty Isa Djihad Wungguli Evi Hulukati Fadilah Istiqomah Pammus Fatmawati, Ainun Franky Alfrits Oroh Hamid Habbe, Abdul Hasan S. Panigoro Hubu, Anisa Fitra Dila Husain, Moh Rizal Isa, Jefri N. Ismail, Sri Rahmawati Isnawati, Ayus Riana Isran K Hasan Jusuf, Anryan K. Hasan, Isran K. Nasib, Salmun Kartin Usman Kobandaha, Putri Ekawaty La Ode Nashar Lailany Yahya Laiya, Gusti Hari Fajar Lakisa, Narti Macmud, Tedy Majid, Majid Muanalifah, Any Muhammad Rezky F. Payu Nadhilah, Farhah NISKY IMANSYAH YAHYA Nisky Imansyah Yahya Nteseo, Sutriany Paudi, Rivka Perry Zakaria Rahim, Delvira Masita Rahmi, Emli Ramadiana, Anastasya Rauf, Dewi Nur Angriani Rauf, Moh Dody Afandi Resmawan Resmawan Rosalio Artes Jr Saiful Pomahiya Salmun K. Nasib Sari, Lia Nanda Sembiring, Rinawati Siti Zakiyah Stella Junus Sumarno Ismail Syamsu Qomar Badu Usali, Rahmayunda Utina, Fitriani Yamin Ismail Yanuari, Eka Dicky D Yuli Sagita