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All Journal Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Majalah Ilmiah Matematika dan Statistika (MIMS) Prosiding Seminar Nasional Official Statistics
Ulya, Fadilla Zundina
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Humanities Computer Science & IT Economics, Econometrics & Finance Mathematics Social Sciences

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Peramalan Harga Cabai dan Bawang di Pasar Tradisional Purwokerto dengan Model Autoregressive Integrated Moving Average (ARIMA) Ulya, Fadilla Zundina; Wijaya, Andreas Rony; Puspita, Popy Laras
Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2023i1.1794

Abstract

Chilies and onions are the agricultural commodities that are commonly used in daily life. However, fluctuating chili and onion prices can cause market instability and harm farmers when prices drop sharply. Therefore, it is necessary to conduct forecasting to predict the future price of both commodities. This research aims to find the best model for predicting chili and onion prices using the Autoregressive Integrated Moving Average (ARIMA) method which is determined based on minimum AIC and BIC values. The data used in this research includes the price of large red chilies, bird's eye chilies, shallots and garlic at the Purwokerto Traditional Market from January 2022 to April 2023. The selected models are ARIMA (0,1,0), ARIMA (1,1,0 ), ARIMA (0,1,0), and ARIMA (3,1,0) respectively for large red chilies, bird's eye chilies, shallots, and garlic. The forecasting model evaluation metrics used are RMSE and MAPE. The value is small enough to indicate that the model is appropriate. Based on the forecasting results, the price of chilies and onions in the next month will tend to be constant at IDR 55,000 for large red chilies, IDR 55,086 for bird's eye chilies, IDR 45,000 for shallots, and IDR 40,000. - for the garlic.
Analisis efektivitas vaksin booster pada kasus terkonfirmasi positif Covid-19 menggunakan uji Mann-Whitney Ulya, Fadilla Zundina; Dewi, Atika Ratna; Winesti, Alifia Zahra; Nurlita, Laksmi Dyah
Majalah Ilmiah Matematika dan Statistika Vol. 23 No. 2 (2023): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v23i2.38190

Abstract

Covid cases in Indonesia have started to decline since the vaccination program was carried out in January 2021. Until now the vaccination program in Indonesia has reached the third vaccination stage or booster vaccine. The booster vaccine aims to strengthen the vaccine dose that has been given previously, with the hope of reducing the number of confirmed patients with the Covid-19 virus. To determine the effectiveness of the booster vaccine in reducing the number of Covid-19 in Indonesia, it is necessary to conduct research using the Mann-Whitney non-parametric trial method. This journal will discuss the analysis of the effectiveness of the third dose (booster) vaccine using the Mann-Whitney test. The data collection used is data on the number of patients confirmed positive for Covid before the booster vaccine, namely from July to December 2021 and the number of patients confirmed positive after the booster vaccine from February to July 2022. Whitney manually is 15 while the p-value value in the calculation of Mann Whitney with SPSS is 0.631. The results of calculations provide a conclusion that the third dose vaccination (booster) is not effective in the reducing the number of patients of covid-19 confirmed for the Covid-19.Keywords: Covid-19, Vaccines, Mann Whitney testMSC2020: 62G05, 62G10
Analisis Efisiensi Metode K-Nearest Neighbor dan Forward Chaining Untuk Prediksi Stunting Pada Balita Pangestu, Happy Gery; Sinaga, Rifaldo Yohannes; Ulya, Fadilla Zundina; Athiyah, Ummi; Muhammad, Arif Wirawan; Alameka, Faza
Informatika Mulawarman : Jurnal Ilmiah Ilmu Komputer Vol 18, No 2 (2023): Informatika Mulawarman : Jurnal Ilmiah Ilmu Komputer
Publisher : Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/jim.v18i2.10169

Abstract

Permasalahan gizi buruk yang terjadi di Indonesia menjadi sebuah tantangan yang nyata bagi pemerintah maupun masyarakat. Salah satu gizi buruk kronis yang menyerang balita di Indonesia yaitu stunting (tubuh pendek). Masalah stunting sering dialami oleh anak-anak di Indonesia. Dalam satu dekade terakhir, balita yang terindikasi stunting cenderung tidak mengalami perbaikan. Jika terus dibiarkan stunting akan mengakibatkan masalah serius yang dapat mengganggu pertumbuhan dari anak. Oleh karena itu, diperlukan pencegahan sejak dini terkait masalah stunting pada anak. Pada penelitian kali ini akan dibuat sebuah website untuk melakukan deteksi stuntung pada balita. Penelitian dilakukan dengan membandingkan metode sistem pakar forward chaining yang menggunakan pengkondisian manual pada bahasa pemrograman python dan machine learning menggunakan K-Nearest Neighbor. Hasil dari sistem pakar forward chaining memiliki akurasi prediksi yang lebih baik karena dapat memprediksi dengan benar 10/10 pengujijan yang diberikan, sedangkan dengan menggunakan machine learning K-Nearest Neighbour hanya dapat memprediksi benar 8/10 pengujian yang telah diberikan. Kemudian metode yang terpilih akan dilakukan deploying kedalam website. Pada tahap deploying, metode yang digunakan adalah forward chaining.
Co-Authors Alameka, Faza Andreas Rony Wijaya Arif Wirawan Muhammad Atika Ratna Dewi Nurlita, Laksmi Dyah Pangestu, Happy Gery Puspita, Popy Laras Sinaga, Rifaldo Yohannes Ummi Athiyah Winesti, Alifia Zahra