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All Journal Desimal: Jurnal Matematika Abdimas Talenta : Jurnal Pengabdian Kepada Masyarakat BAREKENG: Jurnal Ilmu Matematika dan Terapan Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Saintek Lahan Kering Jurnal Varian JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Bakti Cendana: Jurnal Pengabdian Masyarakat Jurnal Pasopati : Pengabdian Masyarakat dan Inovasi Pengembangan Teknologi Jurnal Diferensial Enthusiastic : International Journal of Applied Statistics and Data Science Prosiding Konferensi Nasional PKM-CSR VARIANSI: Journal of Statistics and Its Application on Teaching and Research Journal of Mathematics Theory and Applications
Mada, Grandianus Seda
Program Studi Matematika, Fakultas Pertanian, Universitas Timor
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PENENTUAN METODE DEFUZZIFIKASI TERBAIK FUZZY INFERENCE SYSTEM MAMDANI DALAM DIAGNOSA PRE-EKLAMPSIA PADA IBU HAMIL Teti, Desriyani Yulianita Br. Kolo; Mada, Grandianus Seda; Dethan, Nugraha K. F.; Obe, Leonardus Frengky
JURNAL DIFERENSIAL Vol 6 No 1 (2024): April 2024
Publisher : Program Studi Matematika, Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jd.v6i1.12680

Abstract

Pre-eclampsia is the second of the three major causes of death in pregnant women after bleeding followed by infection. Pre-eclampsia is a disorder of unknown etiology specifically in pregnant women. To prevent pre-eclampsia from becoming increasingly severely diagnosed systems that can be used for pre-eclampsia premises syconome. One method that can be used to determine the pre-eclampsia diagnosis is the Fuzzy Inference System (FIS) Mamdani this method is based on the concept of fuzzy logic. The process of determining the final decision by this method has several stages, the application of implications, rules, and defuzzification composition. For defuzzification stages, there are four methods that can be used the method Centroid, Bisector, Mean of Maximum (MOM), Smallest of Maximum (SOM), and Largest of Maximum (LOM). This study aims to determine the diagnosis of pre-eclampsia (pregnancy poisoning) in pregnant women based on FIS Mamdani by previously determining the best FIS Mamdani defuzzification method. In determining the best defuzzification method, the measures Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), Mean Square Error (MSE), and Sum Square Error (SSE) are used. Based on the results of the prediction error comparison, the best defuzzification method to diagnose the pre-eclampsia status in Atambua Hospital is a bisector method with an accuracy of 95,48%.
Enhancing public service quality in border regions through fuzzy time series forecasting: A case study of the Timor Tengah Utara regional library Humoen, Oktovianus; Binsasi, Eva; Mada, Grandianus Seda; Blegur, Fried Markus Allung; Bano, Elinora Naikteas
Desimal: Jurnal Matematika Vol. 8 No. 3 (2025): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v8i3.202528958

Abstract

Forecasting the demand for public services is often overlooked in border regions, where data-driven management remains limited. However, accurate forecasts are essential for improving service quality and optimizing the use of public facilities. This study aims to predict the number of university student visits to the Regional Library of Timor Tengah Utara (TTU) Regency, an Indonesian border area, using Chen’s fuzzy time series (FTS) model. The dataset consists of monthly records of university student visits from April 2022 to September 2025. The forecasting process involves fuzzification, the establishment of fuzzy logical relationships, and defuzzification to obtain predicted values. The results show that the number of student visits decreased from 240 in April 2022 to 213 in October 2025. The model achieved a Mean Absolute Percentage Error (MAPE) of 35.15%, indicating a fairly good forecasting accuracy. This study extends the application of Chen’s FTS model to library management forecasting in developing and border regions. In the long term, improved forecasting and service planning are expected to enhance library management efficiency and encourage greater student interest in visiting and reading at regional libraries.
Comparative Machine Learning Methods for ICD-10 Diagnosis Classification Rahmadi, Deddy; Solihin, Muhammad; Mada, Grandianus Seda; Albar, Wakhid Fitri; Sani, Sophia Carolina
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 6 Issue 1, April 2026
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol6.iss1.art4

Abstract

The classification of disease diagnoses using the International Classification of Diseases (ICD-10) standard is essential for supporting clinical decision-making and administrative processes in healthcare systems. This study evaluated the performance of three machine learning algorithms, namely decision tree, random forest, and support vector machine (SVM), for ICD-10 diagnosis classification using 3,730 textual medical record entries collected from the Klinik Pratama UIN Sunan Kalijaga, Yogyakarta, Indonesia. The dataset exhibited significant class imbalance, which was addressed using the synthetic minority oversampling technique (SMOTE). The preprocessing procedures included text normalization and Term frequency-inverse document frequency (TF-IDF) vectorization, followed by model development with hyperparameter tuning through grid search cross validation. Model performance was assessed using accuracy, precision, recall, F1-score, confusion matrix, and five-fold cross validation. Random forest achieved the highest mean accuracy at 93.65%, followed by decision tree at 92.25% and SVM at 87.91%. These results indicate that ensemble-based approaches provide more reliable classification outcomes for imbalanced textual medical data. The findings are expected to support the development of semi-automated ICD-10 coding systems and improve the efficiency and accuracy of medical coding workflows.
Penerapan Teorema Titik Tetap Banach pada Ruang Metrik: bahasa indonesia Maria makulata Fernandes; Nugraha K. F. Dethan; Grandianus Seda Mada
Journal of Mathematics Theory and Applications Vol. 4 No. 2 (2026): Edisi April 2026
Publisher : Program Studi Matematika, Universitas Timor

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Abstract

ABSTRAK Ruang metrik merupakan suatu himpunan tak kosong X yang dilengkapi dengan sebuah fungsi yang disebut metrik pada X. Penerapan dari ruang metrik semakin hari semakin berkembang. Salah satunya dengan menggunakan Teorema Titik Tetap Banach. Teorema Titik Tetap Banach (teorema kontraksi) merupakan teorema ketunggalan dari suatu titik tetap pada suatu pemetaan yang disebut kontraksi dari ruang metrik kedalam dirinya sendiri. Selain diterapkan pada ruang metrik, teorema ini juga dapat digunakan untuk mencari solusi dari persamaan diferensial. Penelitian ini dilakukan untuk mengetahui perumusan dan pembuktian Teorema Titik Tetap Banach pada ruang metrik dan penerapannya dalam mencari solusi dari persamaan diferensial. Penelitian ini merupakan penelitian studi pustaka. Penelitian ini dilakukan melalui kajian pustaka terhadap buku-buku dan literatur lainnya. Dari kajian pustaka tersebut, kemudian dibahas materi-materinya secara mendalam. Hasil studi pustaka menunjukan bahwa Teorema Titik Tetap Banach berperan penting dalam penentuan soalusi Persamaan Diferensial. Dalam menentukan solusi Persamaan Diferensial dengan menggunakan metode Picard, Teorema titik tetap menjamin ketunggalan solusi dari Persamaan Diferensial yang diberikan. Kata Kunci: Ruang Metrik, Titik Tetap, Teorema Titik Tetap Banach, Teorema Picard, Persamaan Diferensial.
Co-Authors Albar, Wakhid Fitri Alfonsus Liquria Loin Aloisius Loka Son Andika Ellena Saufika Hakim Maharani Arkianti, Maria Maxmilla Yoche Azor Yulianus Tefa Bano, Elinora Naikteas Benu, Didi Prasetyo Binsasi, Eva Dethan, Nugraha K. F. Dira Asri Pramita Ernestina Lalian Estevania Daonce Mau Eva Binsasi Faustianus Luan Fried Markus Allung Blegur Hanas, Dicky Frengky Hendrika Yeni Meti Humoen, Oktovianus Kristina Sri Ayu Bere Lidya, Christie Lukas Pardosi Maria Julieta Esperanca Naibili Maria makulata Fernandes Matius Stefanus Batu Muhammad Solihin, Muhammad Nabu, Andreas Giovani Nugraha K. F. Dethan Nugraha K. F. Dethan Obe, Leonardus Frengky Oktovianus R. Sikas Pramita, Dira Asri Pramusita, Santa Maya Rahmadi, Deddy Sani, Sophia Carolina Sansela Neonbeni Santos, Adriano Dos Siahaan, Desta Gloria Sikas, Oktovianus R. Siprianus Septian Manek SITUMORANG, KOMILIE Tahulending, Peggy Tea, Marselina Theresia Djue Teti, Desriyani Yulianita Br. Kolo Wasim Raza Welsiliana Welsiliana Yakoba Yusina Muanley Yohana Noviayanti Da Silva Toti Yoseph Pius Kurniawan Kelen