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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Statistika Jurnal Pendidikan Matematika RAFA Science and Technology Indonesia Jurnal Penelitian Sains Jurnal Pengabdian Pada Masyarakat Seminar Nasional Lahan Suboptimal M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Journal of Engineering and Scientific Research (JESR) Indonesian Journal of Engineering and Science (IJES) Inovasi Matematika (Inomatika) Bulletin of Applied Mathematics and Mathematics Education Jurnal Pelita Sriwijaya Prosiding Seminar Nasional Unimus Mathematics Education Journal Journal on Mathematics Education
Yulia Resti
Jurusan Matematika Fakultas MIPA Universitas Sriwijaya,Jl. Raya Palembang-Prabumulih Km.32 Inderalaya 30662, Ogan Ilir, SumateraSelatan
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Physics Public Health Social Sciences Other

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Designing a Financial Mathematical Task for Vocational High School Using Saving and Stock Context Ramadhan, M. Hasbi; Zulkardi; Putri, Ratu Ilma Indra; Resti, Yulia
Mathematics Education Journal Vol. 18 No. 2 (2024): Jurnal Pendidikan Matematika
Publisher : Universitas Sriwijaya in collaboration with Indonesian Mathematical Society (IndoMS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22342/jpm.v18i2.pp149-162

Abstract

In daily life, banks usually not only offer their saving programs but also their stocks. This research focuses on designing a financial mathematical task for vocational high school (VHS) which is valid, practical, and has potential effects using saving and stock context. Pendidikan Matematika Realistik Indonesia (PMRI) is the approach used in this research. For the method, we used design research with a type of development studies. This research was conducted at VHS 1 at Jambi City with research subjects were the eleventh-grade students of accounting major. This research produces three financial mathematical tasks with the context of saving and stock. The results of research also found that by using saving and stock context, students became more understanding of real-world problems and wise in making decisions regarding financial problems. This research can also be used as a reference for financial mathematics teaching materials, especially for vocational high school teachers.
Ensemble Method of Multiple Decision Trees with Crisp and Fuzzy Discretization for Axial Surface Roughness Prediction Resti, Yulia; Yani, Irsyadi; Puspitasari, Dewi; Thamrin, Ismail; Saputra, M.A. Ade
Science and Technology Indonesia Vol. 10 No. 3 (2025): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2025.10.3.678-689

Abstract

AISI 1045 is a steel used to make engine components for motor vehicles and aircraft. The quality of AISI 1045 is influenced by its surface roughness, both axial and tangential. The prediction of AISI 1045 surface roughness aims to produce quality products in a shorter time and at a lower cost. The axial surface roughness is in the form of certain grades according to ISO. This method is a prediction technique that combines several single prediction models to obtain better prediction results. In this work, the ensemble method is built using a voting system from an odd number of single prediction models of the decision trees. The proposed Single Model consists of one decision tree model with crisp discretization (DT1) and three models with fuzzy discretization (DT2, DT3, and DT4). The research data were obtained through experiments measuring the axial surface roughness of AISI 1045 steel using a wet machining system by considering cutting speed, feed motion, axial depth of cut, and tangential surface roughness. The study’s results indicate that not all proposed ensemble models are built to have better performance than single prediction models. Of the four proposed single prediction models, only one model has an accuracy above 80%, namely the decision tree model with fuzzy discretization using a combination of linear-trapezoidal fuzzy membership functions (DT4 model). The model performance based on accuracy, recall, precision, F1-score, and AUC is 80.73%, 48.53%, 73.47%, 58.44%, and 67.72%, respectively. For the four ensemble models formed from the combination of three Single decision tree models, only the combination of DT1, DT2, and DT3 does not perform better than the Single model. The other three ensemble methods have better accuracy, recall, and AUC than the performance of all proposed Single models with values of 81.33 - 82.67%, 51.62 - 55.19%, and 69.04 - 71.02%, respectively.
The Symmetric Pattern Fuzzy Discretizationin Predicting Plastic Type for a Sorting System Using Decision Tree Methods Yani, Irsyadi; Marwani; Puspitasari, Dewi; Resti, Yulia
Science and Technology Indonesia Vol. 10 No. 3 (2025): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2025.10.3.789-801

Abstract

Plastics made from petroleum as the main ingredient cannot decompose quickly like organic materials, but rather take 500 years to 1000 years. Recycling plastic waste can significantly reduce the negative impacts that damage the environment. In addition, it can also reduce the use of natural resources as raw materials and energy use in the extraction process from mining to ready-for-use. In the process of recycling plastic bottle waste in industry, a sorting system is needed to sort the types of plastic bottle waste automatically, effectively, and efficiently. The system needs a prediction model with satisfactory performance. This research aims to build the prediction models of a plastic bottle waste sorting system with a fuzzy approach using the Decision Tree method. The main focus is fuzzy discretization with asymmetric pattern where the membership functions for the first and the last categories are balanced. Seven Decision Tree models are proposed in this study, six models with symmetric fuzzy discretization and one model with crisp discretization as a comparison. Three types of plastics are the objects of the study, namely Polyethylene Terephthalate (PET/PETE), High-Density Polyethylene (HDPE), and Polypropylene (PP). All three are types of plastics that are widely found in household waste. The unique contribution of this paper is that the symmetric pattern fuzzy discretization in the decision tree method can improve the performance of the decision tree model, but the combination of fuzzy membership functions used also contributes. Not all combinations used can improve the performance of the prediction model. Four of six models of symmetric fuzzy discretization have better performance than the decision tree model with crisp discretization. The combination of fuzzy membership functions consisting of linear and triangular functions provides the highest performance. Two models that do not perform better than crisp discretization are the linear-trapezoidal combination and the linear-Gaussian combination.
Comparing the performance of DTID3 and DTID3-Smote methods in predicting the rain events with unbalanced classes Zayanti, Des A.; Eliyati, Ning; Resti, Yulia; Hoiri, Sajiril; Kresnawati, Endang S.; Dewi, Novi R.; Amran, Ali; Yani, Irsyadi
Bulletin of Applied Mathematics and Mathematics Education Vol. 5 No. 1 (2025)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/bamme.v5i1.13122

Abstract

Prediction of rainfall events in a region is important for many aspects of life. However, the majority of datasets that predict rainfall events have an unbalanced distribution of observations in their classes, including the Prabumulih city dataset, South Sumatra. DTID3 provides very satisfactory performance in many cases of prediction, while the Smote technique is useful for balancing the distribution of data classes.  This study aims to compare the performance of the DTID3 and DTID3-Smote methods in predicting rainfall events in Prabumulih City.  The main contribution of this study compared to previous studies is that the DTID3 and Smote methods are used together to predict rainfall events, especially in Prabumulih City. Using training data from 2017-2022 and test data from 2023, the results show that the DTID3-Smote method has a better performance measure than the decision tree method in predicting rainfall events in Prabumulih City. In the decision tree method, the accuracy, precision, recall, specificity, and f1-score metrics are 73.56%, 81.91%, 50.94%, 91.22%, and 62.81%, respectively. In the decision tree-SMOTE method, the values ​​are respectively 74.66%, 82.61%, 53.44%, 91.22%, and 64.9%.
SOSIALISASI PENTINGNYA PENERAPAN KESELAMATAN, KESEHATAN KERJA DAN LINGKUNGAN (K3L) DI INDUSTRI KECIL MESIN PERKAKAS Yanis, Muhammad; Mohruni, Amrifan Saladin; Basri, Hasan; Firdaus, Aneka; Yani, Irsyadi; Saputra, M. A. Ade; Adanta, Dendy; Resti, Yulia; Yuliasari, Nova; Sari, Dewi Puspita; Teguh Prakoso, Akbar
Jurnal Lentera Nusantara Vol 4 No 1 (2025): Jurnal Pelita Sriwijaya
Publisher : Asosiasi Peneliti Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51630/jps.v4i1.179

Abstract

Keselamatan, Kesehatan Kerja dan Lingkungan (K3L) merupakan faktor penting dalam menciptakan tempat kerja yang aman, produktif, dan ramah lingkungan. Penerapan K3L di industri kecil mesin perkakas masih sering terabaikan karena kurangnya pemahaman terhadap risiko akibat kerja dan dampak lingkungan. Kegiatan pengabdian ini melakukan sosialisasi pentingnya penerapan K3L bagi pelaku usaha kecil mesin perkakas. Metode kegiatan meliputi pemaparan materi, diskusi-tanya jawab dan evaluasi serta hibah APD. Tempat kegiatan di bengkel las dan bubut Tris yang berada di Kelurahan Kebun Bunga Palembang. Kegiatan sosialisasi menunjukkan peningkatan pemahaman dan kesadaran bahaya di tempat kerja, pentingnya penggunaan APD, dan pengelolaan limbah yang bertanggung jawab. Dari semua materi yang disampaikan, terjadi peningkatan pemahaman rata-rata sebesar 33.3%. Sosialisasi dapat meningkatkan kesadaran K3L secara signifikan, namun agar penerapan secara konsisten maka perlu program lebih berdampak seperti pendampingan dan dukungan berkelanjutan.
PENGENALAN KONSEP HIMPUNAN FUZZY DALAM MENDUKUNG LITERASI SAINS DAN NUMERASI Resti, Yulia; Zayanti, Des A.; Kresnawati, Endang S.; Eliyati, Ning; Yani, Irsyadi
Jurnal Lentera Nusantara Vol 4 No 1 (2025): Jurnal Pelita Sriwijaya
Publisher : Asosiasi Peneliti Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51630/jps.v4i1.180

Abstract

Literasi sains dan numerasi diperlukan masyarakat modern untuk menghadapi berbagai permasalahan ilmu pengetahuan dan teknologi. Sayangnya berdasarkan tes PISA, literasi sains dan numerasi anak-anak Indonesia tergolong sangat rendah. Guna mendukung literasi sains dan numerasi, pada kegiatan ini, konsep himpunan fuzzy dikenalkan kepada siswa-siswa SMA-SMK Kartini Palembang. Penguasaan tentang konsep keanggotaan himpunan secara umum (himpunan crisp) dan keanggotaan himpunan fuzzy beserta contoh nyata dalam kehidupan sehari-hari diberikan kepada siswa untuk memberikan kemudahan dalam memahami materi. Penilaian kemampuan diberikan dalam bentuk pra-test dan post test. Hasil kegiatan menunjukkan bahwa literasi sains dan numerasi khalayak sasaran meningkat signifikan. Uji beda rata-rata kedua kelompok nilai pra-test dan post-test dengan tingkat signifikansi 5 % untuk khalayak sasaran menunjukkan bahwa kedua kelompok memiliki perbedaan yang signifikan, Hasil ini juga menginfomasikan bahwa rata-rata nilai post-test secara signifikan mengalami peningkatan. Artinya kegiatan kegiatan pengabdian kepada masyarakat ini memberikan implikasi yang signifikan terhadap peningkatan kemampuan literasi dan numerasi mereka.
PENGUATAN LITERASI SAINS MELALUI PENGENALAN METODE STATISTIKA UNTUK DATA HILANG Kresnawati, Endang S.; Resti, Yulia; Dewi, Novi R.; Yani, Irsyadi; Marwani, Marwani
Jurnal Lentera Nusantara Vol 4 No 1 (2025): Jurnal Pelita Sriwijaya
Publisher : Asosiasi Peneliti Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51630/jps.v4i1.181

Abstract

Kemampuan literasi sains yang baik berkontribusi secara signifikan terhadap kemajuan bangsa. Sebagai generasi penerus, sepatutnya siswa Sekolah Mengengah Atas (SMA) dibekali banyak pengetahuan guna meningkatkan literasi sains yang mereka miliki termasuk dalam menangani data atau pengamatan yang hilang, mengingat saat ini merupakan era big data. Kegiatan pengabdian yang dilaksanakan ini bertujuan mengenalkan metode-metode statistika dalam mengatasi data hilang. Pengetahuan ini diharapkan dapat menguatkan literasi sains siswa SMA Kartini Palembang, yang merupakan sekolah swasta yang berada sekitar 1 km di belakang kampus Universitas Sriwijaya. Sekolah ini memiliki akreditasi B dan fokus untuk peminatan IPA. Berdasarkan pra-test dan post-test terkait pengetahuan dasar tentang metode statistika dalan menangani daa hikang, hasil kegiatan menunjukkan bahwa literasi sains dan numerasi khalayak sasaran meningkat signifikan. Uji beda rata-rata kedua kelompok nilai pra-test dan post-test dengan tingkat signifikansi 5 % untuk khalayak sasarn menunjukkan bahwa kedua kelompok memiliki perbedaan yang signifikan, Hasil ini juga menginfomasikan bahwa rata-rata nilai post-test secara signifikan mengalami peningkatan. Artinya kegiatan kegiatan pengabdian kepada masyarakat ini memberikan implikasi yang signifikan terhadap peningkatan kemampuan literasi dan numerasi mereka.
Coronary Artery Disease Prediction Using Decision Trees and Multinomial Naïve Bayes with k-Fold Cross Validation Endang S Kresnawati; Yulia Resti; Bambang Suprihatin; M. Rendy Kurniawan; Widya Ayu Amanda
Jurnal Inovasi Matematika Vol 3 No 2 (2021): Inovasi Matematika (Inomatika)
Publisher : Pendidikan Matematika Universitas Muhammadiyah Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1226.478 KB) | DOI: 10.35438/inomatika.v3i2.266

Abstract

Coronary artery disease has been the leading cause of death in the world population for at least two decades (2000-2019) and has experienced the largest increase in mortality in that time span compared to other causes of death. The success of predicting coronary artery disease early based on medical data is not only beneficial for patients, but also beneficial for the stability of the country's economy. This paper discusses the prediction of coronary artery disease risk by implementing two statistical learning methods, namely Multinomial Naïve Bayes and Decision Tree with 10-fold cross validation, where numerical variables are discretized to obtain categorical variables. The results showed that the Decision Tree method has better performance than the Multinomial Naïve Bayes method in predicting coronary artery disease. The performance measure of the Decision Tree method obtained an accuracy rate of 99.63%, 100% sensitivity, 99.33% specificity, 99.23% precision, and 100% Negative Prediction Value. These measures indicate that the Decision Tree method is appropriate for predicting coronary artery disease, including independent data (other coronary artery disease data with the same predictor variables). The results of this study also show that the different references to previous studies in discretizing numerical variables can improve the performance of the method in predicting coronary artery disease.
Implementation of a Breakpoint Halfway Discretization to Predict Jakarta's Air Quality Winoto Chandra; Resti, Yulia; Bambang Suprihatin
Jurnal Inovasi Matematika Vol 4 No 1 (2022): Inovasi Matematika (Inomatika)
Publisher : Pendidikan Matematika Universitas Muhammadiyah Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (696.13 KB) | DOI: 10.35438/inomatika.v4i1.310

Abstract

Despite the pandemic, Jakarta is one of the most polluted cities in the world. Knowing the daily air quality forecast aids the community, particularly Jakarta residents. Among these is the ability to protect oneself from dangerous air. The multinomial naive Bayes and the decision tree-ID3 methods are popular and perform well. Both of these strategies, however, require categorical variables. This need necessitates the implementation of a discretization technique for numerical variables. The purpose of this study is to predict Jakarta's air quality using the multinomial naive Bayes and decision tree method based on Particulate Matter 10 µg (PM10), Sulfur Dioxide (SO2), Nitrogen Dioxide (NO2), Ozone (O3), and Carbon Monoxide (CO). These continuous variables are discretized in two ways: using all midway breakpoints or halfway mixture breakpoints. The results indicated that the decision tree method with the mixture breakpoints halfway approach performed better than the multinomial nave Bayes method, with an accuracy of 98.90%, a specificity of 98.92%, a sensitivity of 75.00%, a precision of 75.00%, and an F1 score of 97.81%.
Co-Authors A. S. Mohruni Akbar Teguh Prakoso Ali Amran Ali Syahbana Alwine Zayanti, Des Amrifan Saladin Mohruni Andi Eka Putra Aneka Firdaus Anita Desiani Ansyori Ansyori Ansyori Ansyori Ansyori Yani Anthony Costa Arhami, Muhammad Astuti Astuti Bambang Suprihatin Bambang Suprihatin Bambang Suprihatin Burlian, F. Chandra Irsan Chandra Irsan Chandra Irsan Dendy Adanta Des A. Zayanti Des Alwine Zayanti Des Alwine Zayanti Des Alwine Zayanti Des Alwine Zayanti Des Alwine Zayanti, Des Alwine Des Alwine Zayantii Desi Herlina Saraswati Dewi Puspita Sari Dewi Puspitasari Dewi Puspitasari Dewi, Novi R. Endang S Kresnawati Endang S. Kresnawati Endang Sri Kresnawati Endang Sri Kresnawati Endang Sri Kresnawati Endang Sri Kresnawati Endang Sri Kresnawati F Nasution F. A. Alhamdini Firmansyah Burlian Firmansyah Burlian Firmansyah Burlian Fitri Puspasari Fusito Fusito Hasan Basri Hoiri, Sajiril I Yani Indah Meiliana Sari Irsyadi Yani Ismail Thamrin Jeremy Firdaus Latif Kresnawati, Endang S. M. Hasbi Ramadhan, M. Hasbi M. Rendy Kurniawan MARWANI Marwani Marwani, Marwani Mauizzatil Rahmayani Mega Tiara Putri Muflika Amini Muhammad Nawawi Muhammad Yanis Ning Eliyati Ning Eliyati Ning Eliyati Ning Eliyati Ning Eliyati Ning Elyati Noriszura Ismail Nova Yuliasari Novi R. Dewi Novi Rustiana Dewi Novi Rustiana Dewi Novi Rustiana Dewi Rahmayani, Mau’izatil Ratu Ilma Indra Putri Resnawati Rossi Passarella Saiful Hafizah Jaaman Saputra, M. A. Ade Saputra, M.A. Ade Setyo Cahyono, Endro Shohif Wijaya Sri Kresnawati, Endang Sugandi Yahdin Teguh Prakoso, Akbar Titania Jeanni Charissa Widya Ayu Amanda Winoto Chandra Yani, I. Yuli Andriani Zayanti, Des A. Zulkardi Zulkardi Zulkardi Zulkarnain Zulkarnain