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Penerapan Metode Regresi Linear Sederhana Untuk Prediksi Harga Beras di Kota Padang Hasibuan, Lilis Harianti; Musthofa, Syarto
JOSTECH: Journal of Science and Technology Vol 2, No 1: Maret 2022
Publisher : UIN Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/jostech.v2i1.3802

Abstract

The purpose of this research is to get predictions of rice prices. Linear regression is used  as a method of predicting rice prices in the next X(t) period. In this study, the actual rice price Y(t) is the effect variable and the time period is the causal variable. The linear regression equation obtained is Y'=13562.561+9.041958X. Testing the accuracy of the prediction results was carried out using RMSE with a value of 0.126. The prediction of rice prices using the linear regression method can be said to be in the very good category, it can be seen that the RMSE value is very small in the test and meets the standard.
Barisan Cauchy pada Ruang Semimetrik Terbatas Rianjaya, Ilham Dangu; Putri, Amelia; Musthofa, Syarto
JOSTECH Journal of Science and Technology Vol 4, No 1: Maret 2024
Publisher : UIN Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/jostech.v4i1.8234

Abstract

Semimetric spaces with bounded property means that it is bounded below and bounded above by constant multiples of a metric space. Moreover, in semimetric spaces, every convergent sequence is not necessarily to be a Cauchy sequence. This study aims to examine the property of sequences of semimetric spaces with boundary property. In this work, analytical method of proof is used. The results obtained are the equivalence of the convergence of the sequence, and the fulfillment of the Cauchy criterion in the finite semimetric space and the metric space that bounds it. In addition, the completeness property in one space also causes the other space to fulfill the completeness property.
ANALISIS DATA LONGITUDINAL DENGAN RESPON BINER MENGGUNAKAN GENERALIZED ESTIMATING EQUATION (GEE) Musthofa, Syarto; Hasibuan, Lilis Harianti; Putri, Darvi Mailisa; Jannah, Miftahul; Rianjaya, Ilham Dangu
MAp (Mathematics and Applications) Journal Vol 5, No 2 (2023)
Publisher : Universitas Islam Negeri Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/map.v5i2.7416

Abstract

Data longitudinal adalah data yang diperoleh dari hasil pengukuran sejumlah individu secara berulang dalam beberapa waktu yang berbeda. Data longitudinal menunjukkan bagaimana perubahan nilai pada individu yang diamati relatif terhadap waktu dan beberapa kovariat yang menjadi perhatian. Variabel respon pada data longitudinal dimungkinkan dalam bentuk biner. Data dengan respon biner pada dasarnya bisa dianalisis dengan regresi logistik. Namun, regresi logistik tidak mempertimbangkan korelasi antar pengamatan yang mungkin terjadi pada satu individu. Dalam penelitian ini Generalized Estimating Equation (GEE) digunakan dalam melakukan estimasi parameter pada model data longitudinal. GEE memberi ruang pembahasan pada adanya kemungkinan korelasi antar pengamatan pada satu individu untuk data longitudinal yang memiliki variabel respon biner. Studi kasus dalam penelitian ini menganalisis probabilitas terjadinya kondisi suhu di atas normal berdasarkan lamanya penyinaran matahari (X_1). Estimasi parameter yang dilakukan menghasilkan model π_i=1/(1+e^(-(-2.427+0.553x_1i)) ) dengan struktur korelasi exchangeable (α=0,607) yang menunjukkan bahwa semakin lama penyinaran matahari akan semakin memperbesar probabilitas kondisi suhu di atas normal. Kata Kunci: Data Longitudinal, Regresi Logistik, Generalized Estimating Equation (GEE)
Mathematics Games Creation by Using Block-Based Programming (Scratch) to Enhance Students Learning Experiences Fauzi, Ahmad; Syafi’i, Mohamad; Musthofa, Syarto; Wandira, Raju; Azmi, Zain; Zikri, Muhamad
Engagement: Jurnal Pengabdian Kepada Masyarakat Vol 8 No 1 (2024): May 2024
Publisher : Asosiasi Dosen Pengembang Masyarajat (ADPEMAS) Forum Komunikasi Dosen Peneliti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29062/engagement.v8i1.1633

Abstract

The use of information technology in making teaching materials by teachers can improve students' learning experiences. One of learning methods that can be adopted with technology integration is game-based learning design. The problem is that teachers generally lack the ability to utilize technology in learning process. Through this service activity, the team provides assistance to teachers at MTsN 5 and MTsN 6 Padang in designing interesting learning process using game-based learning design. This approach produces active involvement of students in the learning process while increasing students' creativity and understanding.
PERBANDINGAN PRINCIPAL COMPONENT REGRESSION DAN REGRESI RIDGE PADA ANALISIS FAKTOR-FAKTOR INDEKS PEMBANGUNAN MANUSIA DI PROVINSI SUMATERA BARAT Khoiro, Ismi; Asfa'ani, Ezhari; Musthofa, Syarto
MAp (Mathematics and Applications) Journal Vol 6, No 2 (2024)
Publisher : Universitas Islam Negeri Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/map.v6i2.10168

Abstract

Penelitian ini membahas tentang perbandingan metode principal component regression dan regresi ridge dalam mengatasi masalah multikolinearitas pada data Indeks Pembangunan Manusia (IPM) di Provinsi Sumatera Barat. Penelitian menggunakan data yang diambil dari Badan Pusat Statistika Sumatera Barat pada tahun 2023. Kedua metode tersebut akan dibandingkan berdasarkan nilai  dan RSE. Nilai  yang dihasilkan principal component regression  (93,2%)  regresi ridge (84,89%), begitu juga dengan nilai  principal component regression (92,8%)  regresi ridge (84,89%). Sedangkan nilai RSE principal component regression (0,2683)   RSE regresi ridge (0,4). Dapat disimpulkan bahwa model terbaik yang diperoleh untuk mengatasi masalah multikolinearitas pada data IPM Provinsi Sumatera Barat adalah principal component regression.
COMPARISON OF SEASONAL TIME SERIES FORECASTING USING SARIMA AND HOLT WINTER’S EXPONENTIAL SMOOTHING (CASE STUDY: WEST SUMATRA EXPORT DATA) Hasibuan, Lilis Harianti; Musthofa, Syarto; Putri, Darvi Mailisa; Jannah, Miftahul
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1773-1784

Abstract

Export is the activity of selling goods or services from one country to another. This activity usually occurs in a specific region or country. Export data is a type of data that has a seasonal pattern. This study aims to compare SARIMA and Holt Winter’s methods in forecasting export data. In this study, the SARIMA model ((1,1,1) (0,1,1))12 and Holt Winter's simulation were obtained. The data used is the export data of West Sumatra from 2016 to 2022. The best model is the one with the smallest MAPE or MAD. The SARIMA model yielded a MAPE of 0,437% and MAD of 78,821. Meanwhile, the Holt Winter's method yielded a MAPE of 0,894% and MAD of 163,320 with α=0,2, β=0,5, γ=0,1. Therefore, the SARIMA outperformed the Holt Winter’s method due to its higher accuracy. It can be concluded that the SARIMA is suitable to use as the forecasting model in this case. In this study, forecast have been made for the next 24 periods, from January 2023 to December 2024.