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All Journal Jurnal Ilmu Pertanian Indonesia FORUM STATISTIKA DAN KOMPUTASI Media Statistika Disease Prevention and Public Health Journal JURNAL PETERNAKAN Sosioinforma JUITA : Jurnal Informatika International Journal of Advances in Intelligent Informatics BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) JURNAL ILMIAH PETERNAKAN TERPADU J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Jambura Journal of Mathematics ComTech: Computer, Mathematics and Engineering Applications J-ADIMAS (Jurnal Pengabdian kepada Masyarakat) JURNAL AKUNTANSI KEUANGAN DAN MANAJEMEN Jurnal Pendidikan dan Kebudayaan Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika JURNAL ILMIAH GLOBAL EDUCATION Jurnal Indonesia Sosial Sains Jurnal Natural Journal of Economics Xplore: Journal of Statistics Jurnal Pengabdian Masyarakat dan Lingkungan Parameter: Jurnal Matematika, Statistika dan Terapannya PRAGMATIS Jurnal Manajemen dan Bisnis Jurnal Medika Veterinaria Scientific Journal of Informatics Indonesian Journal of Statistics and Its Applications Jurnal Info Kesehatan Limits: Journal of Mathematics and Its Applications
Indahwati
Department Of Statistics, Faculty Of Mathematics And Natural Science, IPB University, Bogor, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Physics Public Health Social Sciences Transportation Veterinary Other

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Performance Evaluation of ARIMA and LSTM Models to Handle Multi-Interventions in Automobile Production Forecasting Maghfiroh, Firda Aulia; Indahwati, Indahwati; Saefuddin, Asep
Jurnal Ilmiah Global Education Vol. 6 No. 4 (2025): JURNAL ILMIAH GLOBAL EDUCATION
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/jige.v6i4.4694

Abstract

Intervention refers to disturbances caused by internal or external variables, such as market changes, international events, or policy shifts. The dataset used in this study contains three intervention events, referred to as a multi-input intervention. The data consist of car production figures from PT Astra Daihatsu Motor obtained from the official GAIKINDO website. The forecasting task focuses on predicting PT Astra Daihatsu Motor’s production, which was influenced by three major interventions: policy changes in 2013, the impact of the COVID-19 pandemic in 2020, and the increase in SUV production in 2022. This study compares ARIMA and LSTM models for car production forecasting. The dataset covers monthly production data from January 2010 to June 2024, with a total of 174 observations. RMSE, MAPE, and SMAPE are employed as accuracy measures. Based on the testing data (May 2023–June 2024), the results show that the LSTM model outperforms ARIMA in capturing trend patterns, with lower error values of RMSE (4587.65), MAPE (10.37), and SMAPE (10.39), compared to ARIMA with RMSE (5059.48), MAPE (11.59), and SMAPE (10.50). Accordingly, LSTM represents a relevant and robust modeling alternative for production forecasting in operational decision-making, owing to its flexibility and strong capability in capturing complex data patterns.
Evaluating the Performance of Ordinal Logistic Regression and XGBoost on Ordinal Classification Datasets Hanifa, Jasmin Nur; Mingka, Rizka Annisa; Indahwati, Indahwati; Silvianti, Pika
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 4 No 3 (2025): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv4i3pp459-470

Abstract

Choosing the appropriate classification model is crucial, especially when dealing with data featuring an ordinal dependent variable. This study explores and compares the performance of Ordinal Logistic Regression (OLR) and Ordinal XGBoost in classifying ordinal data using ten datasets obtained from the UCI Machine Learning Repository and Kaggle, which vary in the number of observations and features. Each dataset undergoes multicollinearity detection, an 80% training and 20% testing data split, and class balancing using SMOTE. Model performance is evaluated using metrics such as accuracy, F1-score, AUC, MSE, precision, and recall. The results show that ordinal XGBoost outperforms on datasets with complex structures and a higher number of features, achieving a maximum accuracy of 0.953. In contrast, Ordinal Logistic Regression demonstrates more stable performance on datasets with fewer features or balanced class distributions.
Efisiensi Alokasi Sumber Daya Sektor Kesehatan di Provinsi Jawa Barat Tahun 2023 Fernando, Billy; Hakim, Arif Rachman; Indahwati, Indahwati
Jurnal Ekonomika : INDEPENDEN Vol 5 No 3 (2025): Desember 2025
Publisher : Universitas Negeri Surabaya

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Abstract

This empirical study aims to measure the level of technical efficiency in resource allocation within the health sector, including Health Expenditure, Health Personnel, and Hospitals, in converting this investment into human development outcomes, namely Life Expectancy (AHH) and the Human Development Index (IPM), across 27 Districts/Cities in West Java in 2023. The research evaluates fiscal decentralization policies and validates the Human Capital Theory. The methodology employed a quantitative, analytical descriptive approach, utilizing the non-parametric Data Envelopment Analysis (DEA), specifically the Input Oriented CRS Model, with all 27 Districts/Cities designated as Decision Making Units (DMU). DEA results indicate that the majority of DMUs in West Java operate at an inefficient level (theta < 1). Only Tasikmalaya and Pangandaran Districts were declared absolutely efficient, while Subang District, Tasikmalaya City, and Cimahi City were identified as the most technically inefficient units. Slack Analysis provided tangible evidence that the primary source of inefficiency is rooted in significant input overuse (Islack), especially in Health Expenditure. In conclusion, the technical inefficiency in West Java is a persistent and structural resource management problem, necessitating a necessary shift in managerial focus from absolute input fulfillment toward optimizing input conversion.
Evaluasi Kinerja Metode CLARA dan FCM dalam Analisis Gerombol untuk Data Berjumlah Besar dengan Pencilan Panjaitan, Intan Juliana; Indahwati, Indahwati; Afendi , Farit Mochamad
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 3 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 3 Edisi No
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i3.3118

Abstract

Analisis gerombol adalah suatu metode statistika yang mengidentifikasi gerombol objek berdasarkan karakteristik serupa. Masalah yang sering terjadi dalam analisis gerombol adalah keberadaan data pencilan. Keberadaan pencilan dapat mengakibatkan output yang tidak sesuai dengan gambaran yang sebenarnya, sehingga gerombol yang dihasilkan tidak merepresentasikan objek dengan tepat. Masalah lain yang dapat muncul dalam analisis gerombol adalah besarnya jumlah amatan, sehingga diperlukan metode analisis yang efisien dalam penggerombolan. Penelitian ini juga memperdalam tentang kinerja keduanya terhadap jarak antara pusat gerombol dan kondisi penggerombolan melalui kajian simulasi, dimana masing-masing faktor terdiri dari tiga level yang diobservasi.Metode Clustering Large Applications (CLARA) dan Fuzzy C-Means (FCM) adalah metode yang kekar terhadap pencilan dan mampu menganalisis dataset besar. Metode FCM menggunakan nilai pembobot (w) yang optimal untuk mencapai kekar terhadap pencilan. Metode CLARA memiliki sifat kekar dikarenakan menggunakan medoid sebagai pusat gerombol dan penggunaan jarak Manhattan dalam perhitungan jarak antara objek dan pusat gerombol. Metode tersebut akan dievaluasi menggunakan beberapa kriteria evaluasi kebaikan yaitu berdasarkan rasio simpangan baku dalam gerombol dan antar gerombol. Hasil analisis menunjukkan pengaruh signifikan pada masing-masing faktor dan interaksi antar faktor. Visualisasi menunjukkan bahwa peningkatan persentase pencilan mengurangi akurasi penggerombolan, sementara jumlah data yang lebih besar meningkatkan akurasi. Jarak yang lebih besar antara pusat gerombol dan kondisi gerombol yang terpisah menghasilkan rasio simpangan baku gerombol yang lebih kecil. Hasil penelitian menunjukkan bahwa metode FCM lebih efektif dalam menangani data dengan variasi yang signifikan.
Co-Authors A. A., Muftih Aditya Ramadhan Afendi , Farit Mochamad Agus Mohamad Soleh Agustini , Ni Ketut Yulia Agustini, Ni Ketut Yulia Aji Hamim Wigena Akbar Rizki Alahmad, Ali Omar Aliu, Mufthi Alwi ALIU, MUFTIH ALWI Amelia, Reni Amin, Yudi Fathul Anang Kurnia Anik Djuraidah Antonius Benny Setyawan Ari Handayani Arie Anggreyani Aristawidya, Rafika ASEP SAEFUDDIN Assyifa Lala Pratiwi Hamid Aunuddin . Bagus Sartono Budi Susetyo Cahya, Septa Dwi Cahyani Oktarina Chrisinta, Debora Daswati, Oktaviyani Dea Fisyahri Akhilah Putri Dian Kusumaningrum Erfiani Erfiani Erfiani Etis Sunandi Eva Wany, Eva Farit Mochamad Afendi Farit Mohamad Afendi Fatimah Fatimah Fernando, Billy Fira Nurahmah Al Aminy Fitrianto, Anwar Fulazzaky, Tahira Ghina Fauziah Hakim, Arif Rachman Hanifa Izzati Hanifa, Jasmin Nur Hari Wijayanto Harismahyanti A., Andi Hasanah, Lailatul I Gusti Putu Purnaba I Made Sumertajaya Iin Maena Indah, Yunna Mentari Irawan Irawan Jaya, Eddy Santosa Julianti, Elisa D Kamil, Farid Ikram Karunia, Nia Kefi Amtiran, Chandraone Putra Khairil Anwar Notodiputro Khikmah, Khusnia Nurul Kholidiah, Kholidiah Khusnia Nurul Khikmah Kristorio, Kevin Kusman Sadik Latifah, Leli Lestari, Nila Lili Puspita Rahayu Maghfiroh, Firda Aulia Mingka, Rizka Annisa Miranti, Ita Miranti, Ita Mohammad Masjkur Mualifah, Laily Nissa Mualifah, Laily Nissa Atul Muhammad Nur Aidi Naima Rakhsyanda Narindria, Yasmin Nadhiva Nurul Fadhilah Panjaitan, Intan Juliana Pika Silvianti Puput Cahya Ambarwati Purnaningrum, Evita Putra, Stefanus Morgan Setyadi Perdana Putri, Christiana Anggraeni Ramdani, Indri Rasyid, Baharun Ray Sastri Regan, Regan Reni Amelia Reni Amelia Reza, Charolina Therezia Rifki Hamdani Rindy Anggun Pertiwi Salvina Salvina Silmi Annisa Rizki Manaf Siti Hafsah Siwi Haryu Pramesti Tina Aris Perhati Titin Agustina Titin Suhartini Titin Suhartini, Titin Utami Dyah Syafitri Vera Maya Santi Vitona, Desi Wahyudi Setyo Yenni Angraini Yuniarty, Titin Zulkarnain, Rizky _ Aunuddin