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Statistical Perspective of Dengue Hemorrhagic Fever in West Java: Insights from Two-Way RE Model Danarwindu, Ghiffari Ahnaf; Fadhlurrahman, Muhammad Ghani
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 4 Issue 2, October 2024
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol4.iss2.art4

The Indonesian Ministry of Health has reported an alarming increase in Dengue Hemorrhagic Fever (DHF) cases, particularly in West Java Province. Given this trend, collaborative research and surveillance efforts are crucial to understanding and managing DHF cases in Indonesia. The panel data regression model in dengue fever cases will provide new insights into modeling. This research aimed to identify the most appropriate random effects model for estimating a dataset with four different variables. This study involved panel data variables on the effect of population density, percentage of poor people, percentage of households with access to clean water, and proper sanitation on DHF cases in West Java Province. This method emphasized selecting the best model from one-way and two-way Random Effects (RE) models and identifying what factors influenced the increase of DHF cases in West Java province. The best model obtained was a two-way RE Model with three significant variables. Based on the selected variables in the model, West Java Province needs to pay attention to the distribution of housing and economic activity in each district because population density is a crucial concern for the local government.

Perbandingan Metode Peramalan Volume Transaksi Sistem Resi Gudang: Prophet, Exponential Smoothing dan Sarima: Perbandingan Metode Peramalan Volume Transaksi Sistem Resi Gudang: Prophet, Exponential Smoothing dan Sarima Noviani Sugianto, Vickie Ashri; Danarwindu, Ghiffari Ahnaf; Prihatmoko, Harry
Emerging Statistics and Data Science Journal Vol. 3 No. 2 (2025): Emerging Statistics and Data Science Journal
Publisher : Statistics Department, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/esds.vol3.iss.2.art8

Fluktuasi harga komoditas saat panen raya sering menyebabkan rendahnya pendapatan petani dan kesulitan akses pembiayaan. Sistem Resi Gudang (SRG) dirancang sebagai solusi untuk menstabilkan harga dan memberi akses pembiayaan tanpa agunan tambahan, serta mendukung ketahanan pangan nasional. Meskipun SRG terus berkembang, implementasinya masih menghadapi tantangan seperti keterbatasan kapasitas gudang, infrastruktur yang belum merata, dan perbedaan karakteristik komoditas. Peramalan volume komoditas yang masuk diperlukan untuk mengoptimalkan penggunaan gudang dan mendukung kebijakan logistik serta penyimpanan. Penelitian ini membandingkan tiga metode peramalan deret waktu yaitu Prophet, Exponential Smoothing (Holt-Winters), dan SARIMA. Menggunakan data bulanan volume Resi Gudang dari Januari 2022 hingga Desember 2024. Evaluasi akurasi model dilakukan dengan Mean Absolute Scaled Error (MASE). Prophet dengan konfigurasi multiplicative memberikan akurasi tertinggi dengan MASE 0,4134, namun menghasilkan prediksi negatif pada awal 2025. Holt-Winters menghasilkan prediksi yang lebih stabil dan realistis meski nilai MASE-nya lebih tinggi (0,7875). SARIMA memiliki performa terendah dengan MASE 0,9097. Hasil ini menunjukan bahwa pemilihan model tidak hanya bergantung pada nilai error, tetapi juga pada hasil yang diperoleh. Peramalan volume SRG yang akurat dapat meningkatkan efisiensi operasional gudang, mencegah kekurangan kapasitas, serta mendukung stabilitas harga dan pengambilan kebijakan strategis.

Pipeline on microarray data analysis: Pre-processing Fajriyah, Rohmatul; Kongchouy, Noodchanath; Ayudhaya, Wanvisa Saisanan Na; Yotenka, Rahmadi; Danarwindu, Ghiffari Ahnaf
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.v5i1.12539

Bioinformatics is blooming and its data are store in some repository offline and or online. Yet some basic concepts are not fully disseminated. The paper intends to provide the reader with a review of one important concept in the pipeline bioinformatics data analysis of microarray, pre-processing. In pre-processing, there are four steps, background correction, normalization, probe correction and summarization. Each step consists of several methods, and we describe each method to give a better understanding on how it works theoretically. We focused on microarray data from Affymetrix platform with single-color chip.

Optimization of Oral Disentegrating Film (ODF) Matrix from Alginate and Pectin/Gum Acacia/Carrageenan Polymer Using PEG/Glycerol as Plasticizer: Matrix Film From Alginate and Pectin/Acacia Gum/Caragenan Viviane Annisa; Fajar Aji Lumakso; Ghiffari Ahnaf Danarwindu; Khasbi Andi Irawan
Journal of Food and Pharmaceutical Sciences Vol 14, No 3 (2026): J.Food.Pharm.Sci
Publisher : Integrated Research and Testing Laboratory (LPPT) Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jfps.27153

Oral dispersible film (ODF) is an innovative oral drug dosage form that is easy to consume, especially by pediatric, geriatric, and low-compliance patients. This preparation quickly disintegrates in the mouth without the need for water, providing a rapid onset of action, high bioavailability, and comfort of use. Hydrophilic polymers such as alginate are often used because they form strong films and dissolve readily in saliva. One important component in ODF formulations is a plasticizer, which increases flexibility and reduces film fragility. Two common plasticizers used are polyethylene glycol (PEG) and glycerol, each with different characteristics. This research method uses solvent casting. The polymers used are combinations of alginate:pectin, alginate:gum acacia, and alginate: carrageenan, with ratios of 3:0, 3:1, 3:2, 2:2, 2:1, and 0:3. Each polymer formulation was given additional PEG400 or glycerol at three concentration levels: 1%, 2.5%, and 5%. All formulas were tested for organoleptic, physical characteristics, disintegration time, strength, elongation, Scanning Electron Microscopy (SEM), and FTIR. The selection of glycerol and PEG400 plasticizers can affect disintegration time, tensile strength, elongation percentage, and SEM. Polymers also affect film characteristics, including the type of polymer and the concentration of the combined polymers.

Optimization of Oral Disentegrating Film (ODF) Matrix from Alginate and Pectin/Gum Acacia/Carrageenan Polymer Using PEG/Glycerol as Plasticizer: Matrix Film From Alginate and Pectin/Acacia Gum/Caragenan Viviane Annisa; Fajar Aji Lumakso; Ghiffari Ahnaf Danarwindu; Khasbi Andi Irawan
Journal of Food and Pharmaceutical Sciences Vol 14, No 3 (2026): J.Food.Pharm.Sci
Publisher : Integrated Research and Testing Laboratory (LPPT) Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jfps.27153

Oral dispersible film (ODF) is an innovative oral drug dosage form that is easy to consume, especially by pediatric, geriatric, and low-compliance patients. This preparation quickly disintegrates in the mouth without the need for water, providing a rapid onset of action, high bioavailability, and comfort of use. Hydrophilic polymers such as alginate are often used because they form strong films and dissolve readily in saliva. One important component in ODF formulations is a plasticizer, which increases flexibility and reduces film fragility. Two common plasticizers used are polyethylene glycol (PEG) and glycerol, each with different characteristics. This research method uses solvent casting. The polymers used are combinations of alginate:pectin, alginate:gum acacia, and alginate: carrageenan, with ratios of 3:0, 3:1, 3:2, 2:2, 2:1, and 0:3. Each polymer formulation was given additional PEG400 or glycerol at three concentration levels: 1%, 2.5%, and 5%. All formulas were tested for organoleptic, physical characteristics, disintegration time, strength, elongation, Scanning Electron Microscopy (SEM), and FTIR. The selection of glycerol and PEG400 plasticizers can affect disintegration time, tensile strength, elongation percentage, and SEM. Polymers also affect film characteristics, including the type of polymer and the concentration of the combined polymers.

IMPLEMENTASI METODE HOLT-WINTERS ADDITIVE UNTUK MEMPREDIKSI PENUMPANG KERETA API TAKSAKA RELASI YOGYAKARTA-GAMBIR: IMPLEMENTASI METODE HOLT-WINTERS ADDITIVE UNTUK MEMPREDIKSI PENUMPANG KERETA API TAKSAKA RELASI YOGYAKARTA-GAMBIR Dewati, Nabila Ratna; Danarwindu , Ghiffari Ahnaf; Shinta
Emerging Statistics and Data Science Journal Vol. 4 No. 2 (2026): Emerging Statistics and Data Science Journal
Publisher : Statistics Department, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/esds.vol4.iss.2.art04

Kereta api merupakan salah satu moda transportasi yang sering digunakan oleh masyarakat di Indonesia. Kereta Api Taksaka menjadi salah satu layanan unggulan dari PT Kereta Api Indonesia (Persero) yang melayani rute Yogyakarta-Gambir. Seiring dengan meningkatnya kebutuhan layanan transportasi, perusahaan perlu memahami pola jumlah penumpang sebagai dasar perencanaan operasional. Penelitian ini menggunakan metode Holt-Winters Additive karena data yang dianalisis menunjukkan adanya pola musiman dan trend. Tahapan penelitian meliputi analisis deskriptif, identifikasi pola data runtun waktu, penerapan metode Holt-Winters Additive, serta evaluasi model menggunakan nilai Mean Absolute Percentage Error (MAPE). Data yang digunakan adalah jumlah penumpang harian dari bulan Januari 2022 hingga Januari 2025 yang diperoleh dari PT Kereta Api Indonesia (Persero) Daop VI Yogyakarta. Penelitian ini bertujuan untuk menghasilkan model prediksi yang dapat memperkirakan jumlah penumpang harian Kereta Api Taksaka dan diharapkan dapat menjadi pertimbangan dalam pengambilan keputusan terkait perencanaan operasional, pengelolaan kapasitas, serta strategi pelayanan Kereta Api Taksaka. Hasil penelitian menunjukkan model Holt-Winters Additive mampu memprediksi jumlah penumpang berdasarkan pada nilai MAPE yang dihasilkan. Diperoleh tingkat akurasi sangat baik untuk Kereta Api Taksaka Pagi dengan nilai MAPE sebesar 9.71% dan akurasi memadai untuk Kereta Api Taksaka Malam dengan nilai MAPE sebesar 25.67%. Selain itu, hasil peramalan menunjukkan pola mingguan. Jumlah penumpang Kereta Api Taksaka Pagi diprediksi meningkat pada 10 Februari 2025 menjadi 495 penumpang dan menurun pada 5 Februari 2025 menjadi 371 penumpang. Sedangkan, jumlah penumpang Kereta Api Taksaka Malam pada 1 Februari 2025 diprediksi mengalami kenaikan menjadi 477 penumpang dan diprediksi menurun pada 7 Februari 2025 menjadi 261 penumpang.

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