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All Journal Jurnal Ilmu Dasar Jurnal Gaussian BERKALA SAINSTEK AKSIOMA: Jurnal Program Studi Pendidikan Matematika UNEJ e-Proceeding Indonesian Journal of Applied Statistics BAREKENG: Jurnal Ilmu Matematika dan Terapan Limits: Journal of Mathematics and Its Applications Edumaspul: Jurnal Pendidikan Vygotsky: Jurnal Pendidikan Matematika dan Matematika Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) ESTIMASI: Journal of Statistics and Its Application Majalah Ilmiah Matematika dan Statistika (MIMS) Jurnal Riset Statistika Jurnal Statistika dan Komputasi (STATKOM) Limits: Journal of Mathematics and Its Applications
Mohamad Fatekurohman
Fakultas Matematika Dan Ilmu Pengetahuan Alam (FMIPA),Universitas Jember
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Comparison of Arima Method and Artificial Neural Network Method to Predict Productivity Rice In Panti District Fendi Setiawan; Yuliani Setia Dewi; Mohamad Fatekurohman
Edumaspul: Jurnal Pendidikan Vol 6 No 2 (2022): Edumaspul: Jurnal Pendidikan
Publisher : Universitas Muhammadiyah Enrekang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (765.496 KB) | DOI: 10.33487/edumaspul.v6i2.4681

Abstract

Rice production is a community activity to produce rice, it is intended to maintain food security in the future. The aim of this research is to develop the best model for forecasting rice production based on ARIMA (Autoregressive Integrated Moving Averages) and ANN (Artificial Neural Network) approaches. The results will be compared with the error rate values of the ARIMA and ANN methods with the available data. The data used in this study is data on rice production in Panti District, Jember Regency. The level of forecasting accuracy produced by each forecasting method is measured by the criteria of MAPE (Mean Absolute Percentage Error), MSE (Mean Square Error) and RMSE (Root Mean Square Error). The results showed that from the forecasting method used in this study, the ARIMA (1,0,1) (1,0,2) method is the best forecasting method for the best rice harvest area in Panti District, Jember Regency with an average MAPE value is 0.05668374, MSE is 5.587553, and RMSE is 2.3638. Meanwhile, forecasting rice productivity using the ANN BP method (7,(7,3),1) is a fairly good forecasting method with an average MAPE value of 0.05703856 MSE of 4.828465, and RMSE of 2.197377. Therefore, the ARIMA model (1,0,1) (1,0,2)[12] is quite effective for predicting the amount of rice production in Panti District, Jember Regency, East Java Province for the next few years.
MODIFIKASI FLOWER POLLINATION ALGORITHM DENGAN REPLACEMENT BERBASIS ILS: PERMASALAHAN QUADRATIC BOUNDED KNAPSACK Yona Eka Pratiwi; Mohamat Fatekurohman; Firdaus Ubaidillah
UNEJ e-Proceeding 2022: E-Prosiding Seminar Nasional Matematika, Geometri, Statistika, dan Komputasi (SeNa-MaGeStiK)
Publisher : UPT Penerbitan Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Optimization problems are the most interesting problems to discuss in mathematics. Optimization is used to modeling problems in various field to achieve the effectiveness and efficiency of the desired target. One of the optimization problems that are often encountered in everyday life is the selection and packaging of items with limited media or knapsack to get maximum profit. This problem is well-known as knapsack problem. There are various types of knapsack problems, one of them is quadratic bounded knapsack problem. In this paper, the authors proposed a new modified algorithm, which is Flower Pollination Algorithm (FPA) added with Iterated Local Search (ILS)-based Replacement mechanism. Furthermore, the implementation of the proposed algorithm, MFPA, is compared to the original FPA. Based on the results of this study, the proposed MFPA performs better and produces the best solution than the original algorithm on all data used. The advantage obtained by the MFPA algorithm is better and in accordance with the knapsack capacity. In addition, although the computational of the MFPA takes longer time than FPA with the same number of iterations, MFPA is able to find better solutions faster and able to escape from the local optimum. Keywords: Flower Pollination Algorithm, Iterated Local Search, Knapsack, Optimization, Quadratic Bounded Knapsack.
PENINGKATAN KEMAMPUAN BERPIKIR KRITIS SISWA DENGAN PENDEKATAN RME BERBASIS LSLC Dian Atika Sofie; Didik Sugeng Pambudi; Mohamat Fatekurohman; Nurcholif Diah Sri Lestari; Dian Kurniati
AKSIOMA: Jurnal Program Studi Pendidikan Matematika Vol 12, No 3 (2023)
Publisher : UNIVERSITAS MUHAMMADIYAH METRO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/ajpm.v12i2.6432

Abstract

Rendahnya kemampuan berpikir kritis siswa merupakan salah satu masalah yang harus diatasi, khususnya menghadapi Era Revolusi Industri 4.0 dan pembelajaran abad 21. Salah satu cara meningkatkan kemampuan berpikir kritis siswa adalah melalui pembelajaran Realistic Mathematics Education (RME) berbasis Lesson Study for Learning Community (LSLC). Tujuan penelitian ini adalah untuk mendeskripsikan peningkatan kemampuan berpikir kritis siswa dalam pembelajaran materi SPLDV menggunakan pendekatan RME berbasis LSLC. Penelitian ini menggunakan jenis penelitian Quasi Eksperimen, dengan menggunakan satu kelas eksperimen dan satu kelas kontrol. Subjek dalam penelitian ini adalah 50 siswa kelas VIII SMP Al-Ikhlash Lumajang. Pembelajaran RME berbasis LSLC dikenakan pada 25 siswa kelas VIII A sebagai kelas eksperimen dan pembelajaran konvensional dikenakan pada 25 siswa kelas VIII B sebagai kelas kontrol. Hasil penelitian menunjukkan bahwa penerapan model RME berbasis LSLC mampu meningkatkan kemampuan berpikir kritis siswa pada materi SPLDV lebih baik dibandingkan dengan pembelajaran konvensional. Tingkat berpikir kritis siswa pada kelas eksperimen lebih besar dari kelas kontrol terjadi pada tingkat berpikir kritis level 3 (TBK 3) dan level 4 (TBK 4). Pada kedua level tersebut, kelas eksperimen mencapai 40% dan 24%, sedangkan kelas kontrol mencapai 32% dan 20%. Dari hasil ini disarankan kepada guru matematika hendaknya menerapkan pembelajaran RME berbasis LSLC dalam upaya meningkatkan kemampuan berpikir kritis siswa.
Analisis Faktor Risiko Kematian Ibu di Kabupaten Jember Menggunakan Cox Proportional Hazard Roydatul Jamila; Mohamat Fatekurohman; Dian Anggraeni
ESTIMASI: Journal of Statistics and Its Application Vol. 4, No. 2, Juli, 2023 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v4i2.26669

Abstract

Maternal mortality is the death of a woman who is pregnant, giving birth and childbirth to the pregnancy or its handler. Maternal mortality in East Java Province still quite high with the highest number of deaths in 2021 is Jember Regency. The purpose of this paper is to determine risk factors that cause death in an effort to reduce the number of maternal deaths. Method used for the analysis of risk factors for maternal mortality is survival analysis with the Cox Proportional Hazard model. Survival analysis purpose to assess the relationship of predictor variables to survival time to determine maternal survival. Cox Proportional Hazard model is one of the models in survival analysis that is often used. Selection of the best model for Cox Proportional Hazard is carried out to determine the factors that have a significant effect. The best model is done by selecting the smallest AIC value backwards. Parameter significance test on the best model was carried out simultaneously and partially. Results obtained for maternal mortality factors in Jember Regency are anemia status and parity.
Perbandingan Metode Naïve Bayes Classifier dengan Metode Random Forest pada Prediksi Rating Review Drama Korea Meisty, Ferisa Dwi Alfia; Anggraeni, Dian; Fatekurohman, Mohamat
ESTIMASI: Journal of Statistics and Its Application Vol. 5, No. 1, Januari, 2024 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v5i1.26942

Abstract

Korean dramas have very many fans and are spread in various countries. This study aims to determine whether the korean drama is classified as Bagus, Tidak Bagus, or Cukup Bagus and compares two methods, namely the naïve bayes classifier method and the random forest method in predicting korean drama review ratings. This study shows that the naïve bayes classifier and random forest methods are capable of predicting korean drama review ratings. In the prediction review, the random forest method obtained an accuracy value of 89%, while the naïve bayes classifier method obtained an accuracy value of 86%. In rating predictions, the random forest method obtains an accuracy value of 41%, while the naïve bayes classifier method obtains an accuracy value of 40%. The conclusion of this study is that the random forest method is superior and accurate in predicting Korean drama review ratings.
PENENTUAN LOKASI STRATEGIS AUTOMATIC TELLER MACHINE PT. BANK SYARIAH INDONESIA TBK MENGGUNAKAN METODE DECISION TREE Masruroh, Masruroh; Fatekurohman, Mohamat; Anggraeni, Dian
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 14 No 1 (2022): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2022.14.1.5653

Abstract

ABSTRACT. The problem of placing the location of the Automatic Teller Machine Bank Syariah Indonesia Tbk (ATM BSI) both already and to be installed can take into account various factors such as reach or distance from the center of the crowd to the location, population density, topography and security level. Decision Tree is one of the classification methods in data mining to solve the problem of various factors to determine the strategic location of BSI ATM. The results obtained from training data and testing data are 100% each and the AUC value is 1. The results show the best variables are the population variable and the distance from ATM to gas stations with very good accuracy, and able to predict strategic and non-strategic locations.Keywords: Strategic Location, Automatic Teller Machine (ATM), Decision Tree Method. ABSTRAK. Permasalahan penempatan lokasi Automatic Teller Machine Bank Syariah Indonesia Tbk (ATM BSI) baik yang sudah maupun yang akan dipasang dapat memperhatikan berbagai faktor seperti, jangkauan atau jarak dari pusat keramaian menuju lokasi, kepadatan penduduk, topografi dan tingkat keamanan. Decision Tree adalah salah satu metode klasifikasi pada data mining untuk menyelesaikan permasalahan berbagai faktor untuk menentukan lokasi strategis ATM BSI. Adapun hasil yang diperoleh dari data training dan data testing masing- masing 100% dan nilai AUC 1. Hasil menunjukkan variabel terbaik adalah variabel jumlah penduduk dan jarak ATM ke SPBU dengan akurasi sangat baik, dan mampu memprediksi lokasi strategis dan tidak strategis.Kata Kunci: Lokasi strategis, Automatic Teller Machine (ATM), Metode Decision Tree.
Analysis of the Death Risk of Covid-19 Patients Using Extended Cox model Romarizka, Cyndy; Fatekurohman, Mohamat; Tirta, I Made
Jurnal ILMU DASAR Vol 24 No 1 (2023)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/jid.v24i1.33074

Abstract

Globally, in 2021, there were 170,051,718 COVID-19 cases and 3,540,437 patients who died. The high mortality rate of patients infected with COVID-19 gives an idea to research the analysis of the factors that influence the death of Covid-19 patients. The data used in this study is data on Covid-19 patients obtained from the Mexican Government, with response variables namely time and status and predictor variables, namely patient laboratory results in the form of a history of illness that has been suffered by Covid-19 patients so that they adopt the extended model to evaluate the data. The data in this study are heterogeneous and large in number so that data clustering is carried out into 3 clusters, namely low emergency clusters, medium emergency clusters and high emergency clusters using K-means clustering. Because the study could not find the factors that influence the death of Covid-19 patients, two clusters were chosen, namely the medium emergency cluster and the high emergency cluster. So that the factors that influence the death of Covid-19 patients in the medium emergency cluster are sorted by the highest hazard ratio, namely pneumonia, old age, renal chronic, diabetes, Chronic Obstructive Pulmonary Disease (COPD), immune system, hypertension, cardiovascular, obesity, gender, and asthma. In the high emergency cluster, sorted by the highest hazard ratio is the immune system, renal chronic, cardiovascular, COPD, tobacco, hypertension, obesity, gender, and pneumonia.
Survival Analysis of Sea Turtles Eggs Hatching Success using Cox non Proportional Hazard Regression Forestryani, Veniola; Fatekurohman, Mohamad; Hadi, Alfian Futuhul
Jurnal ILMU DASAR Vol 20 No 1 (2019)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (343.428 KB) | DOI: 10.19184/jid.v20i1.6531

Abstract

The aims of this research is to know both the model and also the factors of incubation period and hatching success of eggs of sea turtles in Kuta, Legian and Seminyak Beach, Bali from January to September 2016. The reasearch was conducted by doing survival analysis by using Cox Non Proportional Hazard regression and then compare the model derived from it with log-logistic regression model. Precipitation, location, temperature, humidity, and hours of daylight are the factors which significantly influence incubation period and hatching success of eggs of sea turtles. According to the descriptive analysis, 12≤ precipitaion <18, Seminyak Beach, 28,5≤ temperature <29,5, 86≤ humidity ≤91, and 5,8≤ hours of daylight <8,3 are the factors which have highest percentage of hatching success. Meanwhile 12≤ precipitation <18, Seminyak Beach, 28,5≤ temperature <29,5, 86≤ humidity ≤91, and 0,8≤ hours of daylight <3,3 are the factors which have highest percentage of hatching success based on the hazard value. Although Seminyak Beach has the highest rate of hatching success, it’s not significantly different from Legian beach in respect to the location factor’s categories. Keywords: hatching success, cox non proportional hazard, log-logistic, survival analysis
Cox Proportional Hazard Model for Analysis of Farmers Insurance Premium Payment Period Rosida, Ayu; Fatekurohman, Mohamat; Dewi, Yuliani Setia; Arif, M. Ziaul
BERKALA SAINSTEK Vol 12 No 3 (2024)
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/bst.v12i3.47118

Abstract

The sub-sector of agriculture plays a significant role in the national economic order. The crop failure rate is one of the unexpected risks caused by natural disasters, including drought, pest attacks, and floods. Agricultural insurance has been used as a pilot project in several areas, such as Gresik and Palembang Regencies. This pilot project has not been carried out in many places and cannot be implemented optimally in Jember. Farmer insurance is a transfer of risk due to farming business losses so that the sustainability of the farming business can be guaranteed. Survival analysis is a statistical method for analyzing data with observed response variables in terms of the time until an event occurs. One survival analysis is to determine the factors that cause an event with a response variable, namely using the Cox Proportional Hazard Model. The results of the significance testing obtained the variable that had a significant influence on the model, namely the growing season variable (X4). Then, a hazard ratio comparison was made for the category of cultivation season variables, and the category with the lowest hazard value was selected, followed by the second category, the months of May until August. (X42), This significantly influenced the policyholder’s time spent paying farmer’s insurance premiums.
Application of Black Scholes Method in Determining Agricultural Insurance Premium Based On Climate Index Using Historical Burn Analysis Method Sholiha, Aminatus; Fatekurohman, Mohamat; Tirta, I Made
BERKALA SAINSTEK Vol 9 No 3 (2021)
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/bst.v9i3.22920

Abstract

Climate index insurance is an insurance that provides reimbursement for losses due to decreased harvest rates or crop failures caused by weather. The use of Historical Burn Analysis (HBA) method in determining climate index based on rainfall resulted in a concept of the agricultural insurance payment in Pasuruan Regency. The application of The Black Scholes method in determining agricultural insurance premiums is obtained when rainfall more than 17 mm the premium is Rp 221,234. If the rainfall are 13 mm ≥ RR < 17 mm, the nominal premium paid by farmers to the insurance party is Rp 147,489. Respondents in the study were farmers who owned rice fields. Instrument quality testing (questionnaire) using validity test and reliability test using the help of SPSS statistical software. It can be concluded that the questionnaire is valid and reliable. Based on the results of the questionnaire, farmers considered that the nominal agricultural insurance premiums are in accordance with farmers' income.
Co-Authors Abduh Riski Alfian Futuhul Hadi Anak Agung Gede Sugianthara Arif, M. Ziaul Arivatus Solehah Audina, Bella Aulia, Andini Cahya Bella Audina Dian Anggraeni Dian Anggraeni Dian Atika Sofie Dian Kurniati Didik Sugeng Pambudi Dwi Putra, Candra Yanuar Dwi Putri Antika Dwi Putri Antika Evi Takrimatul Ailiyyah Fatmala, Siti Febriana Fendi Setiawan Firda Anisa Fajarini Firdaus Ubaidillah Firdausiah, Lailatul Firdausiah Forestryani, Veniola Hanifia, Fidiatma Foristy I Made Tirta Khan, Akhmad Safrin Sadad Khoirunnisa, Wilda Masruroh Masruroh Masruroh MASRUROH Maulidani, Noor Dyah Meisty, Ferisa Dwi Alfia Nurcholif Diah Sri Lestari Rizal, Navioer Romarizka, Cyndy Rosida, Ayu Roydatul Jamila Sholiha, Aminatus Solly Aryza Tresnawanti, Dini Tutik Qomaria Yona Eka Pratiwi Yuliani Setia Dewi Yusrillah Ihza Zianita Afni