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All Journal BERKALA SAINSTEK Jurnal Basicedu Parameter: Journal of Statistics Jurnal Basicedu
Fadri, Firda
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Education Mathematics Physics Social Sciences

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Analisis Self Regulated Learning Mata Pelajaran IPA pada Siswa Madrasah Tsanawiyah Fadilah, Rizka Elan; Fadri, Firda; Nurisya, Khofifatu
Jurnal Basicedu Vol. 7 No. 5 (2023)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/basicedu.v7i5.5185

Abstract

Self-Regulated Learning penting untuk dimiliki siswa sebagai upaya dalam menjaga motivasi belajar. Penelitian ini bertujuan untuk menganalisis kemampuan Self-Regulated Learning pada pembelajaran IPA siswa Madrasah Tsanawiyah kelas IX. Metode pengumpulan data menggunakan kuesioner yang berisi tiga aspek Self-Regulated Learning, yaitu aspek perencanaan, pelaksanaan, dan evaluasi. Analisis data dalam penelitian ini menggunakan pendekatan statistik deskriptif. Hasil analisis diperoleh persentase sebesar 60,61% untuk aspek perencanaan belajar, 69,7% untuk aspek pelaksanaan, dan 63,64% untuk aspek evaluasi. Berdasarkan hasil analisis data, secara keseluruhan, kemampuan self-regulated learning siswa pada pembelajaran IPA di salah satu Madrasah Tsanawiyah kelas IX di Kabupaten Kediri masuk dalam kategori sedang.
Implementation of the Fuzzy Time Series Singh Method for Forecasting Non-Oil and Gas Export Values in Indonesia Borahima, Maharani Safira B.; Sain, Hartayuni; Setiawan, Iman; Fadri, Firda
BERKALA SAINSTEK Vol 12 No 3 (2024)
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/bst.v12i3.52663

Abstract

Export activities drive a country's economic growth by increasing revenue and strengthening trade relations between countries. In Indonesia, non-oil and gas products are the primary contributors of export performance. In 2022, non-oil and gas exports values reached 275.96 million USD, marking an increase of 25.80% compared to the previous year's export value. This growth in export value was influenced by various external factors, leading to substantial changes. The government requires further analysis to forecast future trends in non-oil and gas export values due to the uncertain and fluctuating patterns. The Singh Fuzzy Time Series method, an advancement of FST, utilizes fuzzy sets to forecast volatile economic data, yielding more accurate predictions. This research used the Singh FST method and achieved a low MAPE value of 1.31%, indicating a high level of accuracy. Forecasts for Indonesia's non-oil and gas export value over the next three months are projected to reach USD 22,263.02 million in January 2023, followed by USD 22,217.21 million in February 2023, and USD 22,243.68 million in March 2023. These export value forecasts can aid the government in policy-making related to exports and sustain the stability of the country’s economic growth rate.
Analisis Self Regulated Learning Mata Pelajaran IPA pada Siswa Madrasah Tsanawiyah Fadilah, Rizka Elan; Fadri, Firda; Nurisya, Khofifatu
Jurnal Basicedu Vol. 7 No. 5 (2023)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/basicedu.v7i5.5185

Abstract

Self-Regulated Learning penting untuk dimiliki siswa sebagai upaya dalam menjaga motivasi belajar. Penelitian ini bertujuan untuk menganalisis kemampuan Self-Regulated Learning pada pembelajaran IPA siswa Madrasah Tsanawiyah kelas IX. Metode pengumpulan data menggunakan kuesioner yang berisi tiga aspek Self-Regulated Learning, yaitu aspek perencanaan, pelaksanaan, dan evaluasi. Analisis data dalam penelitian ini menggunakan pendekatan statistik deskriptif. Hasil analisis diperoleh persentase sebesar 60,61% untuk aspek perencanaan belajar, 69,7% untuk aspek pelaksanaan, dan 63,64% untuk aspek evaluasi. Berdasarkan hasil analisis data, secara keseluruhan, kemampuan self-regulated learning siswa pada pembelajaran IPA di salah satu Madrasah Tsanawiyah kelas IX di Kabupaten Kediri masuk dalam kategori sedang.
Negative Binomial Regression Modeling to Analyze the Determinants of Infant Mortality in West Java Province Fadri, Firda; Firmansyah, Ari; Erlanda, Victor Alesyus
BERKALA SAINSTEK Vol. 13 No. 1 (2025)
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/bst.v13i1.53686

Abstract

The Infant Mortality Rate (IMR) is an important indicator in assessing the quality of public health and the success of health programs in a region. Proper handling of factors that determine IMR is essential to reduce this number. The data used were 27 districts/cities in West Java in 2022 with predictor variables including the number of health workers, percentage of poor population, percentage of iron tablet consumption, percentage of clean and healthy living behavior, percentage of exclusive breastfeeding, and percentage of low birth weight babies. The results of the analysis with Poisson Regression showed overdispersion so that IMR modeling was carried out using Negative Binomial Regression. The AIC value for the Negative Binomial Regression model was 305.630 and the BIC value was 315.997. The deviance ratio and Pearson's Chi-square approached one, indicating effective handling of overdispersion. The only significant variable affecting IMR was the percentage of clean and healthy living behavior. This shows the importance of increasing clean and healthy living behavior as the main strategy for reducing IMR in West Java Province.
Predicting Drought in East Nusa Tenggara: A Novel Approach Using Wavelet Fuzzy Logic and Support Vector Machines Sain, Hartayuni; Fadri, Firda
Parameter: Journal of Statistics Vol. 4 No. 1 (2024)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2024.v4.i1.17142

Abstract

The water crisis, or what is hereinafter referred to as drought, has become a systemic and crucial problem in several regions in Indonesia. Indonesia is an agricultural country, where the presence of water is very influential so that drought can become a natural disaster if it starts to cause an area to lose its source of income due to disturbances in agriculture and the ecosystem it causes. Drought forecasting can provide support solutions in preventing the impact of drought. In this paper, we compare the performance of wavelet fuzzy logic and the support vector machine (SVM) as a supervised learning method for drought forecasting in East Nusa Tenggara. This study examines the monthly rainfall data for 1999-2015 which is the basis for calculating the drought index based on the Standardized Precipitation Index (SPI). The SPI value used is SPI-3 at a station in East Nusa Tenggara. The performance of models is compareded on R2. The results showed that R2 of wavelet fuzzy logic is smaller than one of SVMVM is better than the wavelet fuzzy logic for forecasting SPI value of drought in East Nusa Tenggara.
Co-Authors Ari Firmansyah, Ari Borahima, Maharani Safira B. Erlanda, Victor Alesyus Hartayuni Sain Iman Setiawan Nurisya, Khofifatu Rizka Elan Fadilah, Rizka Elan