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All Journal PROSIDING SEMINAR NASIONAL Media Statistika Jurnal Ilmu Dasar Jurnal Statistika Universitas Muhammadiyah Semarang Jurnal Edukasi dan Penelitian Informatika (JEPIN) Proceeding SENDI_U Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Variance : Journal of Statistics and Its Applications LOSARI: Jurnal Pengabdian Kepada Masyarakat Jurnal Litbang Edusaintech Journal of Data Insights Jurnal Pengabdian Masyarakat dan Riset Pendidikan Prosiding Seminar Nasional Unimus Jurnal Meteorologi dan Geofisika
Tiani Wahyu Utami
Program Studi Statistika, Universitas Muhammadiyah Semarang
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Nursing Physics Public Health Social Sciences Transportation Other

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Analysis of DHF Patients Based on Laboratory Examination Results with Nonparametric Approach Utami, Tiani Wahyu; Haris, M. Al; Salma, Nadia Khoirunnafisa
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 1 (2026): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i1.33609

Abstract

The dengue virus, which is spread by the Aedes aegypti mosquito, is the cause of Dengue Hemorrhagic Fever (DHF). In the city of Semarang, there was a threefold increase in cases of DHF compared to previous years. This type of research is quantitative research because it produces function that describes the relationship to what extent changes in predictor variable are related to changes in response variable to understand the level of association. Modelling the link between response and predictor factors is the aim of this study. Platelet as the response variable and hemoglobin and leukocyte as the predictor variables, so that the obtained model can be used as a prediction, especially regarding the dynamics of platelet changes influenced by hemoglobin and leukocytes. The pattern of the relationship between platelets and the suspected influencing factors does not form specific pattern, so the Nonparametric Spline method is used in this study. The Spline method is chosen for its flexibility; this model tends to independently seek data estimates, the completion of this study using R software. In the Spline method, there are knot points indicating data changes. The selection of optimum knot points is done by choosing the minimum GCV value The secondary data used came from Roemani Muhammadiyah Hospital's 2023 medical records. The data include platelet count, hemoglobin, and leukocyte. Based on the modeling conducted using truncated spline, the optimum knot points on the linier spline are determined to be 3 knot points with a coefficient determination of 83.58%. The coefficient of determination of 83.58% indicating that 83.58% of the variation in response variable can be explained by predictor variables studied in the regression model. This value indicates that predictor variables have a strong ability to explain changes in response variable.
Literasi Data Kependudukan melalui Infografis dan Monografi Desa Bagi Kader Posyandu : Pengabdian Utami, Tiani Wahyu; Ningrum, Ariska Fitriyana; Imron, Ali; Nurhidayah, Sri; Yunanita, Novia
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 3 (2026): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 3 (Januari 202
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i3.5483

Abstract

Literasi data kependudukan menjadi sangat penting karena menyangkut kemampuan individu, organisasi, maupun pemerintah dalam memahami, menggunakan, dan mengelola informasi mengenai jumlah, karakteristik, serta dinamika penduduk. Bagi kader Posyandu, data kependudukan memiliki arti strategis karena mereka adalah ujung tombak layanan kesehatan dasar di tingkat masyarakat. Tanpa pencatatan yang baik, intervensi menjadi tidak terarah dan evaluasi program menjadi sulit dilakukan. Kelurahan Pedurungan Lor, khususnya RW 1, Kecamatan Pedurungan, Kota Semarang, dipilih sebagai lokasi kegiatan pengabdian masyarakat. Urgensi kegiatan pengabdian ini adalah mengingat pentingnya data sebagai dasar dalam pengambilan keputusan dan perencanaan kesehatan masyarakat, juga peningkatan kompetensi kader Posyandu dalam pengelolaan dan visualisasi data menjadi sangat mendesak. Oleh karena itu diperlukan kegiatan yang meningkatkan pengetahuan literasi data kependudukan dan melatih pembuatan infografis dan monografi desa. Evaluasi dilakukan dengan pre-post test terkait pemahaman literasi data dan pembuatan infografis. Berdasarkan kegiatan yang dilakukan menunjukkan hasil adanya peningkatan pemahaman literasi data dan pembuatan infografis melalui Canva, hal ini tercermin pada nilai rata-rata skor post test yang mengalami peningkatan yang signifikan.
Clustering Untuk Menentukan Indeks Kesejahteraan Rakyat di Provinsi Jawa Tengah 2022 Menggunakan Metode Fuzzy C-Means: Clustering to Determine the People's Welfare Index in Central Java Province 2022 Using the Fuzzy C-Means Method Indra Firmansyah; Salmaa Fauziah; Hanif Nur Ibrahim; Fatkhurokhman Fauzi; Tiani Wahyu Utami
Journal of Data Insights Vol 1 No 2 (2023): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v1i2.149

Abstract

Kesejahtraan rakyat merupakan salah satu tujuan negara yang tercantum pada Undang-undang Dasar 1945. Dalam meningkatakan kesejahtraan rakyat, tentunya perlu adanya pembangunan yang merata. Untuk menjalankan program pembangunan yang merata, harus dilakukan identifikasi berdsarkan karaktaeristik tingkat kesejahtraan rakyat berdasarkan variabel-variabel yang telah ditentukan agar dalam membuat strategi dan mengambil kebijakan untuk meningkatkan kesejahtraan rakyat dapat tepat sasaran dan optimal. Tujuan dari penelitian ini adalah untuk mengetahui pengelompokkan 35 Kabupatan/Kota di Provinsi Jawa Tengah dan k arakteristik dari setiap kelompok berdasarkan indeks kesejahtraan rakyat. Berdasarkan hasil analisis yang dilakukan, bahwa terdapat 35 Kabupaten/Kota di Provinsi Jawa Tengah dapat membentuk 4 kelompok (cluster), dimana pada cluster 0 beranggotakan 8 Kabupaten/Kota dengan karakteristik Jumlah peduduk miskin tinggi, Daya beli cenderung rendah, rata-rata lama sekolah rendah, angka harapan hidup sangat rendah. Pada cluster 1 terdapat 12 Kabupaten/Kota dengan karakteristik Nilai PDRB sangat tinggi, angka pengangguran relatif rendah, angka lama sekolah relatif tinggi. Pada cluster 2 terdapat 5 Kabupaten/Kota dengan karakteristik Nilai PDRB sangat rendah, jumlah penduduk miskin sangat rendah, daya beli sangat tinggi, kepemilikan rumah rendah, kepadatan penduduk tinggi, daya beli tinggi, angka melek huruf tinggi, rata-rata lama sekolah tinggi, dan yang terakhir cluster 3 terdapat 10 Kabupaten/Kota dengan karakteristik PDRB rendah, kepadatan penduduk sangat rendah, kepemilikan rumah sangat tinggi, daya beli cenderung rendah.
Implementation of K-Means Algorithm to Group Age of Cardiovascular Disease Patients: Impelementasi Algoritma K-means untuk Mengelompokkan Usia Penderita Penyakit Kardiovaskular Mulya Asy-syifa Rahmi; Prizka Rismawati Arum; Tiani Wahyu Utami
Journal of Data Insights Vol 3 No 1 (2025): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v3i1.216

Abstract

Cardiovascular disease, including coronary heart disease, peripheral arteries and heart failure, is a serious disease that is the leading cause of death globally. Risk factors such as high blood pressure, dyslipidemia, smoking, diabetes, and obesity contribute to the development of this disease. This study aims to group cardiovascular disease sufferers based on age using the k-means clustering method with optimization of the k value using the elbow method. The data used comes from more than 35,000 preprocessed observations. The analysis results show that the optimal number of clusters is five. Data preprocessing succeeded in cleaning the data from missing values, and the elbow method helped determine the number of clusters that were relevant for age grouping of cardiovascular disease sufferers. The results of this grouping can be used for further analysis in efforts to prevent and manage cardiovascular disease.
Comparison of Holt-Winters Exponential Smoothing (HWES) and Singular Spectrum Analysis (SSA) Methods in Forecasting the Number of Passengers at PT KAI in Indonesia: Perbandingan Metode Holt-Winters Exponential Smoothing (HWES) Dan Singular Spectrum Analysis (SSA) Pada Peramalan Jumlah Penumpang PT KAI di Indonesia Samikoh Ulinuha; Tiani Wahyu Utami; Prizka Rismawati Arum; Dannu Purwanto
Journal of Data Insights Vol 2 No 2 (2024): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v2i2.654

Abstract

Penelitian ini mengkaji penerapan dua metode peramalan, yaitu Holt Winters Exponential Smoothing (HWES) dan Singular Spectrum Analysis (SSA), dalam meramalkan jumlah penumpang di PT Kereta Api Indonesia. Hasil penelitian menunjukkan bahwa penerapan metode HWES dengan model additive menghasilkan nilai parameter pemulusan optimal dengan alpha , beta dan gamma model ini memiliki nilai MAPE sebesar 10.75%. Sementara itu, pada HWES model multiplicative menghasilkan nilai parameter pemulusan alpha , beta dan gamma , menghasilkan nilai MAPE 14.50%. Metode SSA dengan window length menghasilkan nilai MAPE 13.33%. Perbandingan nilai MAPE anatara metode HWES additive, HWES multiplicative dan SSA menunjukkan bahwa HWES additive lebih unggul dengan MAPE sebesar 10.75%. Peramalan jumlah penumpang Kereta Api Indonesia menggunakan metode terbaik Holt Winters Exponential Smoothing Additive untuk periode Januari hingga Desember 2024 memperlihatkan variasi jumlah penumpang terendah pada bulan Agustus dan tertinggi pada bulan Januari.
ADASYN-Based Multiclass Support Vector Machine for Village Development Index Classification in North Maluku Province: Support Vector Machine Multikelas Berbasis ADASYN untuk Klasifikasi Indeks Pembangunan Desa di Provinsi Maluku Utara Tiani Wahyu Utami; Lea Angelina; Saeful Amri
Journal of Data Insights Vol 4 No 1 (2026): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v4i1.1154

Abstract

Class imbalance is a significant constraint that can diminish the performance of classification models. This study implements the integration of Adaptive Synthetic Sampling (ADASYN) and Multiclass Support Vector Machine (SVM) to classify the 2024 Village Development Index (IDM) in North Maluku Province. The dataset comprises 684 villages, utilizing the Social Resilience Index (IKS), Economic Resilience Index (IKE), and Environmental Resilience Index (IKL) as predictor variables. The data was partitioned using a ratio of 80% for training and 20% for testing. An extreme imbalance was identified in the "independent village" category (0.88%); therefore, ADASYN was applied to the training data to generate 862 synthetic samples to balance the class distribution. The optimal model yielded by the process was a linear kernel SVM with a Cost value of 100, yielding an accuracy of 98.54%, precision of 98.26%, recall of 99.4%, and an F1-score of 98.83%. Of the total 137 villages evaluated, only two villages were misclassified: Salimuli Village and Dowongimaiti Village. These findings demonstrate the effectiveness of the ADASYN-SVM combination in producing accurate classifications to support village development policies in island regions.
Co-Authors Abdul Rohman Agus Rusgiyono Aisyah Lahdji, Aisyah Alan Prahutama Alan Prahutama Ali Imron Alwan Fadlurohman Amri, Saeful Amrullah, Setiawan Anissatush Sholiha Arianti, Irma Arini Rizky Wahyuningtyas Ariska Fitriyana Ningrum Aulia, Syifa Aura Hisani, Zahra Ayu Wulandari Azqia Fajriyani Biru, Pelangi Langit Dannu Purwanto Devi Nurlita Dewi Ratnasari Wijaya Dhani, Oktaviana Rahma Dheanyta Alif Shafira Diana Wahyu Safitri Dwi Ispriyanti Eko Yuliyanto, Eko Elvia Nanda Sofiyanti Endah Suryaningsih Endang Tri Wahyuni Maharani Fathikatul Arnanda Fatimahthus Zahra, Diandra Fatmawati Nurjanah Fauzi, Fatkhurokhman Hanif Nur Ibrahim Hasbi Yasin Hikmah Nur Rohim, Febrian Iffah Norma Hidayati Ihsan Fathoni Amri Iis Widya Harmoko Iis Widya Harmoko, Iis Widya Imaroh Izzatun Indah Manfaati Nur Indah Sulistiya Indra Firmansyah Iqbal Kharisudin Ismawati - Juwita Rahayu Laila Khoirun Nisa Lea Angelina Lia Miftakhul Janah M. Al Haris M. Saifudin Nur Martyana Prihaswati Maulana Afham Mifta Luthfin Alfiani Moh Yamin Darsyah Moh Yamin Darsyah Moh. Yamin Darsyah Mulya Asy-syifa Rahmi Nila Amelinda Putri Nur Chamidah Nurhidayah, Sri Nursamsiah Nursamsiah Pranandira Rilvandri, Quinsy Prizka Rismawati Arum Rahma Dhani, Oktaviana Rahman, Budiono Rizma Novinda Puteri Rochdi Wasono Rochdi Wasono Roosyidah, Nila Ayu Nur Salma, Nadia Khoirunnafisa Salmaa Fauziah Samikoh Ulinuha Septi Winda Utami Setiayani, Wiwik Silvia Tri Wahyuni Sri Kustiara Sudarno Sudarno Sugito Sugito Suherdi, Andri Suparti Suparti Suparti Suparti Suparti, S. Syaifullah, Ahmad Reyhan Toha Saifudin Ujang Maulana Ujiati Suci Rahayu Vega Zayu Varima Velia Arni Widyasari Wahyu Putri Pratiwii Wisudawati, Dinda Tri Yulianita, Tanti Yuliardi, Fahrul Raditiar Yunanita, Novia Yusnia Kriswanto