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All Journal HAYATI Journal of Biosciences Jurnal Ilmu Dasar Statistika BERKALA SAINSTEK CAUCHY: Jurnal Matematika Murni dan Aplikasi Kreano, Jurnal Matematika Kreatif-Inovatif Prosiding Seminar Matematika dan Pendidikan Matematik AJIE (Asian Journal of Innovation and Entrepreneurship) UNEJ e-Proceeding Martabe : Jurnal Pengabdian Kepada Masyarakat Mathvision : Jurnal Matematika Abdimas Universal JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) ESTIMASI: Journal of Statistics and Its Application Majalah Ilmiah Matematika dan Statistika (MIMS) International Journal of Quantitative Research and Modeling Jurnal Hasil Pengabdian Kepada Masyarakat Universitas Jember Indonesian Journal of Statistics and Its Applications
Alfian Futuhul Hadi
Departement Of Mathematics, Faculty Of Mathematics And Natural Science, University Of Jember, Jember, 68121, Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Physics Social Sciences Other

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DIAGNOSIS PENDERITA PENYAKIT KANKER PARU MENGGUNAKAN SUPPORT VECTOR MACHINE DAN NAÏVE BAYES Muhammad Iqbal Yunan Helmi; Dian Anggraeni; Alfian Futuhul Hadi
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 21, No 1 (2021)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v21i1.7566

Abstract

Menurut data jenis kanker yang menjadi penyebab kematian terbanyak adalah kanker paru, mencapai 1,7 juta kematian pertahun. Penyakit ini disebabkan oleh banyak faktor salah satunya genetika. Dalam penelitian ini akan dilakukan diagnosis kanker paru menggunakan metode Support Vector Machine (SVM) dan Naïve Bayes. Naïve Bayes merupakan teknik prediksi berbasis probabilitas sederhana yang berdasarkan pada model fitur independent, sedangkan klasifikasi menggunakan SVM dapat dijelaskan secara sederhana yaitu usaha untuk mendapatkan hyperplane sebagai fungsi pemisah terbaik yang dapat memisahkan dua kelas yang berbeda pada ruang input. Pada penelitian ini akan dibandingkan metode SVM dan Naive Bayes untuk didapatkan mana metode yang mempunyai akurasi terbaik. Data microarray yang digunakan pada penelitian ini  berupa 80 individu dengan masing-masing jumlah ekspresi genetiknya 2408. Sebanyak 60 individu tergolong ke dalam kelas kanker, dan 20 individu termasuk ke dalam kelas normal. Hasil dari penelitian ini adalah SVM mempunyai nilai akurasi sebesar 90% dan Naïve Bayes mempunyai nilai akurasi sebesar 75%.
Principal Component Regression in Statistical Downscaling with Missing Value for Daily Rainfall Forecasting M Dika saputra; Alfian Futuhul Hadi; Abduh Riski; Dian Anggraeni
International Journal of Quantitative Research and Modeling Vol 2, No 3 (2021)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v2i3.151

Abstract

Drought is a serious problem that often arises during the dry season. Hydrometeorologically, drought is caused by reduced rainfall in a certain period. Therefore, it is necessary to take the latest actions that can overcome this problem. This research aims to predict the potential for a drought to occur again in the Kupang City, Indonesia by developing a rainfall forecasting model. Incomplete daily local climate data for Kupang City is an obstacle in this analysis of rainfall forecasting. Data correction was then carried out through imputed missing values using the Kalman Filter method with Arima State-Space model. The Kalman Filter and Arima State-Space model (2,1,1) produces the best missing data imputation with a Root Mean Square Error (RMSE) of 0.930. The rainfall forecasting process is carried out using Statistical Downscaling with the Principal Component Regression (PCR) model that considers global atmospheric circulation from the Global Circular Model (GCM). The results showed that the PCR model obtained was quite good with a Mean Absolute Percent Error (MAPE) value of 2.81%. This model is used to predict the daily rainfall of Kupang City by utilizing GCM data.
PENERAPAN METODE EXTENDED KALMAN FILTER PADA KASUS PERTUMBUHAN PENDUDUK KABUPATEN JEMBER Rory Ronella Agustin; Kosala Dwidja Purnomo; Alfian Futuhul Hadi
MathVisioN Vol 1 No 02 (2019): September 2019
Publisher : Prodi Matematika FMIPA Unirow Tuban

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (182.416 KB)

Abstract

This study discusses the estimated number of people using the methods of Jember Regency Extended Kalman Filter (EKF) and determine the appropriate logistic growth model for predicting the next populations in Jember. There are two assumptions logistic growth model will be compared, first is logistic growth model assuming a linear populations function and the second is logistic growth model assuming parabolic populatins function. To determine efficiency of Extended Kalman Filter conducted trial process, using 6, 14, 28 measurements data. Each data taken from Central Statistic Agency of East Java Province during 1990-2017. Finally, this study indicate that the logistic growth model assuming parabolic populations function is an appropiate better than logistic growth model assuming a linear populations for populations in Jember during 1990-2017. The Extended Kalman Filter method is able to increase the confidence level of the estimation results indicated by getting smaller of average norm covariance error. More data used, the estimation results using Extended Kalman Filter method are getting better and closer to the real data.
DIVERSIFIKASI USAHA KELOMPOK PENJUAL DURIAN MELALUI OLAHAN LIMBAH BUAH DURIAN Halimatus Sa'diyah; Alfian Futuhul Hadi; Nasrul Ilminnafik
Martabe : Jurnal Pengabdian Kepada Masyarakat Vol 5, No 2 (2022): Martabe : Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jpm.v5i2.550-558

Abstract

Desa Pakusari Krajan di Kabupaten Jember memiliki pusat penjualan durian berupa deretan kios-kios penjual buah durian segar yang menetap. Saat ini, banyak pembeli durian yang menikmati buah durian di kios penjual, mengakibatkan banyak limbah durian menumpuk berupa biji dan kulit, sehingga lingkungan menjadi kotor. Para penjual durian, sebagi mitra dalam kegiatan ini, hanya menjual satu macam produk saja, belum memiliki pengetahuan untuk meningkatkan usaha dagangnya, serta belum ada managemen usaha. Kegiatan pengabdian masyarakat ini bertujuan menyelesaikan permasalahn tersebut melalui pemanfaatan limbah durian menjadi olahan produk makanan dan minuman, serta pengaplikasian mesin teknologi tepat guna untuk membantu proses pengolahan tersebut. Adanya produk olahan limbah durian tersebut dapat menganekaragamkan produk yang dijual para penjual durian. Tujuan lain yang ingin dicapai adalah memberi pengetahuan mitra tentang managemen usaha. Metode yang digunakan adalah penyuluhan dan pelatihan, praktek pengolahan maupun praktek penggunaan teknologi tepat guna dalam proses produksi. Mitra mengikuti kegiatan dengan penuh antusias. Semua program yang telah dilaksanakan diiukuti dengan baik oleh mitra, diharapkan memberikan pengaruh positif bagi mitra baik dalam, aspek pengembangan ipteks, ekonomi maupun lingkungan. Kegiatan ini mendorong adanya diversifikasi produk, dimana mitra menjual olahan limbah durian selain durian segar yang biasa mereka jual. Lingkungan juga menjadi lebih bersih bebas limbah durian. Mitra juga leebih memahami pentingnya managemen usaha, antara lain melalui pembukuan kas sederhana.
Rancang Bangun Data Warehouse dan R Studio Serta Pemanfaatanya dalam Peramalan Pola Konsumsi Masyarakat di Kabupaten Jember Lutfi Ali Muharom; Alfian Futuhul Hadi; Dian Anggraeni
JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Vol 1, No 1 (2016): JUSTINDO
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/justindo.v1i01.244

Abstract

As we know that we have to process and store the data recording well. Data warehouse is one of data processing method that use to support the decission-making process. The data warehouse process started from colecting, selecting, designing and uploading data in to data warehouse. In this research, we use the data of SUSENAS from year of 1997 until 2012. We took the daily consumption data (household expendature) to be proceed in data warehouse. The implementation of web based R studio program can facilitate the users to acces R . R can be accessed by any kind of devices which have browser and internet acces by any kind of devices which have browse and internet acces. The connectivity of R studio to data warehouse can be simplify the users to access and process the data. As the result of consumption patterns (staple food) forecasting in jember, we conclude that the best forecasting method for forecasting method for forecasting using AR(1) model. The limited data collections caused the ensemble wouldn’t become the best method , whereas, it should be the best method.
Keterampilan Statistika dan Data Science: Manfaatnya di Berbagai Bidang pada Era Digital Alfian Futuhul Hadi; Halimatus Sa'diyah
Abdimas Universal Vol. 4 No. 2 (2022): Oktober
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Balikpapan (LPPM UNIBA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36277/abdimasuniversal.v4i2.245

Abstract

Data Scientist is a trending career in recent years. The survey results show that the need for a data scientist is high, but the availability is very low with limited capabilities. A data scientist needs statistics and programming skills. But, from a student's point of view, statistics is considered the same as mathematics, so it is less desirable because it is mathematical and is considered difficult. Students as prospective workers need to have insight into how to work and skills in the era of the industrial revolution 4.0. Failure to adapt to this new era will lead to increased unemployment of working age in the future. It is important to make the younger generation understand about statistics and data science skills, including the opportunities and job that exist, so efforts are needed to disseminate them. It is hoped that after understanding it, the younger generation will be interested in choosing a profession related to digital. The target audience is students of SMAN 3 Jember. The method used is presentation, then evaluation using a questionnaire. More than 79% of students rated the material presented as important, interesting and up to date. Students can also understand most of the material given, and the level of student interest in both fields is very high. This activity was generally successful.
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
Simple House Needs in Jember with Robust Small Area Estimation Murtinasari, Frida; Hadi, Alfian Futuhul; Anggraeni, Dian
Jurnal ILMU DASAR Vol 18 No 1 (2017)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (694.747 KB) | DOI: 10.19184/jid.v18i1.3159

Abstract

SAE (Small Area Estimation) is often used by researchers, especially statisticians to estimate parameters of a subpopulation which has a small sample size. Empirical Best Linear Unbiased Prediction (EBLUP) is one of the indirect estimation methods in Small Area Estimation. The presence of outliers in the data can not guarantee that these methods yield precise predictions . Robust regression is one approach that is used in the model Small Area Estimation. Robust approach in estimating such a small area known as the Robust Small Area Estimation. Robust Small Area Estimation divided into several approaches. It calls Maximum Likelihood and M- Estimation. From the result, Robust Small Area Estimation with M-Estimation has the smallest RMSE than others. The value is 1473.7 (with outliers) and 1279.6 (without outlier). In addition the research also indicated that REBLUP with M-Estimation more robust to outliers. It causes the RMSE value with EBLUP has five times to be large with only one outlier are included in the data analysis. As for the REBLUP method is relatively more stable RMSE results.
Classification of Cardiovascular Disease Gene Data Using Discriminant Analysis and Support Vector Machine (SVM) Prayogo, Rizky; Anggraeni, Dian; Hadi, Alfian Futuhul
BERKALA SAINSTEK Vol 10 No 3 (2022)
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/bst.v10i3.22259

Abstract

Cardiovascular disease is a disease caused by impaired function of the heart and blood vessels. This disease is caused by many factors, one of which is genetics, while the causes are age, gender, and family history. In this study, classification of 62 individuals with normal response and cardiovascular disease was carried out. Discriminant Analysis (AD) is a method that classifies data into two or more groups based on several variables where data that has been entered into one group will not be included in another group. The Support Vector Machine (SVM) performs classification by building an N-dimensional hyperplane that optimally separates data into two categories in the input space. Furthermore, AD and SVM will be compared to get which method has the best accuracy, after that it will be added to clustering using k-means and k-means kernels to improve the accuracy of each method. The results of this study are AD and SVM have accuracy values of 83.33% and 91.66%, for AD and SVM which are subjected to k-means have accuracy values of 91.66 % and 91.66 %, and for AD and SVM subjected to k-means kernel has an accuracy value of 100 % and 100 %.
Fungsi Likehood Pada Data Tersensor Interval Univariat Tresnawanti, Dini; Fatekurohman, Mohamad; Hadi, Alfian Futuhul
BERKALA SAINSTEK Vol 6 No 2 (2018)
Publisher : Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/bst.v6i2.9227

Abstract

Analisis survival adalah metode statistika yang digunakan dalam mempelajari ketahanan hidup yang berhubungan dengan waktu, mulai waktu awal yang sudah ditentukan dalam penelitian sampai waktu akhir penelitian, namun ada beberapa kendala untuk mengestimasi fungsi tersebut yakni adanya data tersensor. Untuk mengestimasi fungsi dengan masalah demikian digunakan metode nonparametrik maksimum likelihood estimator dengan data tersensor interval univariat yakni data pasien kanker payudara di Rumah Sakit Baladhika Husada (DKT) berupa data interval l i =( Li , Ri ) dengan i adalah banyaknya pasien kanker Payudara serta. Pada metode NPMLE sesuai dengan usulan Turnbull perlu dicari terlebih dahulu bagaimana bentuk fungsi likelihood. Dalam mencari fungsi likelihood dengan data univariat, dilakukan pendekatan representasi petrie untuk menghasilkan matriks Clique sebagai matriks indikator (αij ) . Hasil dari penelitian ini berupa fungsi non linear dengan derajat paling besar yaitu berderajat 5. Kata Kunci: survival, nonparametrik, likelihood, matriks Clique,Turnbull.
Co-Authors A. A. Mattjik Abduh Riski Achmad Budi Susetyo Anak Agung Gede Sugianthara Awalin, Qonita Ilmi Budi Lestari D. Dafik Dian Anggraeni Dian Anggraeni Dian Anggraeni Dian Anggraeni Dian Anggraeni Dian Anggraeni Fatmala, Siti Febriana Fauziyah, Mailulah Ely Forestryani, Veniola Frida Murtinasari, Frida Halimatus Sa'diyah Halimatus Sa'diyah Halimatus Sa’diyah Herry Purnomo, Bambang Hidayat, Muhammad Jamil Hobri I Made Sumertajaya I Made Tirta Ika Hesti Agustin, Ika Hesti Ira Yudistira Kosala Dwidja Purnomo Kurnia Ahadiyah M Dika saputra Madinda, Diah Putri Miftahul Ulum Mohamad Fatekurohman Muhammad Iqbal Yunan Helmi Muharom, Lutfi Ali Nasrul Ilminnafik Nurul Fittriyah, Nurul Paramitha, Luckyta Citra Ayu Prayogo, Rizky Rio Pradani Putra Rory Ronella Agustin Rusdiana, Riza Yuli Sa’diyah, Halimatus Sudarko Sudarko Sunder, R. Syamsul Arifin Tresnawanti, Dini Wibisono, Dwi Anugrah Yuliani Setia Dewi