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All Journal HAYATI Journal of Biosciences Media Statistika 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 Natural Jurnal Hasil Pengabdian Kepada Masyarakat Universitas Jember Indonesian Journal of Statistics and Its Applications DIGIMAS: Jurnal Transformasi Digital Masyarakat
Alfian Futuhul Hadi
Departement Of Mathematics, Faculty Of Mathematics And Natural Science, University Of Jember, Jember, 68121, Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy 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 Energy Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Neuroscience Physics Social Sciences Other

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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.
Analysis of Drought Stress Effect on Inpari Germination: Survival Method Rusdiana, Riza Yuli; Sa'diyah, Halimatus; Hadi, Alfian Futuhul
HAYATI Journal of Biosciences Vol. 32 No. 1 (2025): January 2025
Publisher : Bogor Agricultural University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.4308/hjb.32.1.223-232

Abstract

Drought stress using mannitol can inhibit the germination of rice variety seeds. These studies typically produce time-to-event data and censored observation. Survival analysis techniques are valuable for accounting for these non-germination events, as they describe how germination probability changes over time based on the likelihood of seed development. Until now, there have not been survival studies regarding rice germination affected by drought stress in Indonesia. Thus, we investigated the germination probability of three rice varieties (Inpari 19, Inpari 32, and Inpari 49) under drought stress using survival analysis. The seeds were germinated in 0%, 2%, 4%, 6%, and 8% concentrations of mannitol and evaluated daily over 14 days. Our results demonstrated that higher mannitol concentrations significantly decreased the germination percentage and delayed germination time. The survival rates varied significantly between different mannitol concentrations, highlighting the adverse effects of drought stress. However, there was no significant difference in the probability of seed germination among the varieties treated with 2% mannitol. Among the varieties studied, Inpari 19 is more likely to be drought-resistant compared to Inpari 32 and Inpari 49. It is based on the highest germination percentage, shortest germination time, and highest probability of germination compared.
Penentuan Arsitektur Terbaik Model NAR-NN untuk Peramalan Kasus Covid-19 Awalin, Qonita Ilmi; Anggraeni, Dian; Hadi, Alfian Futuhul
ESTIMASI: Journal of Statistics and Its Application Vol. 6, No. 1, Januari, 2025 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v6i1.21365

Abstract

The NAR-NN model will be applied in time series forecasting, namely data on confirmed cases of Covid- 19 in East Kalimantan Province. The use of time series data as the basis for forecasting so that it can recognize patterns that occur which can then be used as a reference to predict the number of cases that will occur. This research data is 300 daily data for the time period from October 23, 2020 to August 18, 2021, which follows a nonlinear pattern and experiences an upward trend. In this study, the best architecture was determined for the NAR-NN model using the sigmoid activation function and the Levenberg-Marquadt Backpropagation training algorithm. The NAR-NN architecture consists of three layers, namely the input layer, the hidden layer, and the output layer. The evaluation model used is the Mean Absolute Percentage Error (MAPE). The results of this study by experimenting with the number of hidden neurons showed that the model with the best architecture at the time of delay was 4 and the number of hidden neurons was 8 with the MAPE value forecast with actual data of 7.5083%.
Peningkatan Literasi Statistik dan Pemanfaatan Data Kriminalitas melalui Model GWR di Jawa Tengah dan D.I. Yogyakarta Paramitha, Luckyta Citra Ayu; Dewi, Yuliani Setia; Tirta, I Made; Hadi, Alfian Futuhul
Jurnal Hasil Pengabdian kepada Masyarakat Universitas Jember Vol 4 No 1 (2025): Jurnal Hasil Pengabdian Kepada Masyarakat Universitas Jember
Publisher : LP2M Universitas Jember

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

Abstract

Crime is a complex problem influenced by various structural and cultural factors, such as economic, social, and demographic conditions. Based on the 2019 Crime Statistics data published by BPS, Central Java and D.I. Yogyakarta Provinces are among the 15 provinces with the highest crime rates in Indonesia in 2018. This community service activity aims to convey the results of spatial crime analysis to local governments and the community through an applied statistical approach, especially using the Geographically Weighted Regression (GWR) method. The analysis was carried out to identify factors that locally influence crime rates, as well as to provide information that can be used as a basis for formulating data-based policies. The GWR model applied shows spatial variation in the influence of variables on crime rates. This model is better than the ordinary linear regression (OLS) model. The results show that the population density variable (X2) has a significant effect on crime rates in all districts/cities. Based on the similarity of variables that significantly affect crime, six groups of districts/cities were formed. This activity is expected to encourage wider use of open government data and increase the capacity of local policy makers in using statistical approaches for more responsive and targeted development planning.  
Optimizing Data Classification in Support Vector Machines Using Metaheuristic Algorithms Awalin, Qonita Ilmi; Agustin, Ika Hesti; Hadi, Alfian Futuhul; Dafik, Dafik; Sunder, R.
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 9, No 2 (2024): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v9i2.29320

Abstract

To categorize patient diagnosis data related to Chronic Kidney Disease (CKD), this study compares the classification performance of Support Vector Machines (SVM) enhanced by Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). CKD is a severe illness in which the kidneys fail to adequately filter blood and perform their normal functions. This study utilized secondary data consisting of patient conditions and health information. Based on references from CKD-related journals, 15 independent variables and one dependent variable were selected from an initial set of 54 variables. To address the issue of unbalanced data, an oversampling technique was applied, and the data was subsequently split into 80% for training and 20% for testing. During the training phase, SVM-PSO and SVM-GA models were developed, and the gamma value was optimized using the RBF kernel function of SVM. The results indicated that in classifying CKD patient diagnosis data, the SVM-PSO model (97.54% accuracy) outperformed the SVM-GA model (97.37% accuracy). This finding suggests that PSO-based hyperparameter optimization yields a superior model for data classification
Designing Hybrid Learning Tools Based on Lesson Study for Learning Community against Metacognition Ability Madinda, Diah Putri; Hobri, Hobri; Hadi, Alfian Futuhul; Fauziyah, Mailulah Ely
Kreano, Jurnal Matematika Kreatif-Inovatif Vol 13, No 1 (2022): Kreano, Jurnal Matematika Kreatif-Inovatif
Publisher : Mathematics Dept, Math. and Science Faculty, Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/kreano.v13i1.34857

Abstract

This study aims to analyse the outcomes of establishing valid, practical, effective Hybrid Learning tools based on Lesson Study for Learning Community (LSLC) and their impact on students' metacognitive abilities. Research and Development (R D) and experimental research are used to conduct the study. The research subjects are consisted of three classes of 7th grade students. Collaborative Learning and Learning Community are implemented which are the components of LSLC. The 4-D model, which includes define, design, develop, and disseminate, is used to develop learning tools. Lesson plans, worksheets, and a metacognition ability test were created as a result of the research and met the criteria of being of valid, practical, and effective. Based on experimental research, there is a significant effect of Hybrid Learning tools based on Lesson Study for Learning Community on students' metacognitive abilities with p-value of 0.001 (sig 0.05).Penelitian ini bertujuan untuk menganalisis hasil pengembangan perangkat pembelajaran Hybrid Learning berbasis Lesson Study for Learning Community yang valid, praktis, efektif dan menganlisis pengaruhnya terhadap kemampuan metakognisi siswa. Metode penelitian yang digunakan dalam penelitian ini yaitu metode penelitian kombinasi atau mix method. Penelitian ini menggabungkan dua bentuk penelitian yaitu penelitian pengembangan (research and development) dan penelitian eksperimen. Subjek penelitian dalam penelitian ini terdiri dari tiga kelas siswa VII yang terdiri dari kelas uji coba, kelas eksperimen dan kelas kontrol. Komponen Lesson Study for Learning Community yang diterapkan yaitu Collaborative Learning dan Learning Community. Proses pengembangan perangkat pembelajaran dilaksanakan melalui 4-D yaitu pendefinisian, perancangan, pengembangan dan penyebaran. Hasil pengembangan perangkat pembelajaran Hybrid Learning berbasis Lesson Study for Learning Community berupa RPP, LKS dan tes kemampuan metakognisi siswa yang valid, praktis dan efektif. Berdasarkan penelitian eksperimen dan observasi, terdapat pengaruh yang signifikan perangkat pembelajaran Hybrid Learning berbasis Lesson Study for Learning Community terhadap kemampuan metakognisis siswa dengan nilai signifikasi 0.001 .
DIVERSIFIKASI USAHA KELOMPOK PENJUAL DURIAN MELALUI OLAHAN LIMBAH BUAH DURIAN Sa'diyah, Halimatus; Hadi, Alfian Futuhul; Ilminnafik, Nasrul
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.
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): International Journal of Quantitative Research and Modeling
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.
Projection Pursuit Regression (PPR) on Statistical Downscaling Modeling for Daily Rainfall Forecasting Putra, Rio Pradani; Anggraeni, Dian; Hadi, Alfian Futuhul
Indonesian Journal of Statistics and Applications Vol 5 No 2 (2021)
Publisher : Statistics and Data Science Program Study, SSMI, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v5i2p326-332

Abstract

Rainfall forecasting has an important role in people's lives. Rainfall forecasting in Indonesia has complex problems because it is located in a tropical climate. Rainfall prediction in Indonesia is difficult due to the complex topography and interactions between the oceans, land and atmosphere. With these conditions, an accurate rainfall forecasting model on a local scale is needed, of course taking into account the information about the global atmospheric circulation obtained from the General Circulation Model (GCM) output. GCM may still be used to provide local or regional scale information by adding Statistical Downscaling (SD) techniques. SD is a regression-based model in determining the functional relationship between the response variable and the predictor variable. Rainfall observations obtained from the Meteorology Climatology and Geophysics Council (BMKG) are a response variable in this study. The predictor variable used in this study is the global climate output from GCM. This research was conducted in a place, namely Kupang City, East Nusa Tenggara because it has low rainfall. The Projection Pursuit Regression (PPR) will be used in this SD method for this study. In PPR modeling, optimization needs to be done and model validation is carried out with the smallest Root Mean Square Error (RMSE) criteria. The expected results must have a pattern between the results of forecasts and observations showing or approaching the observational data. The PPR model is a good model for predicting rainfall because The results of the forecast and observation show that the results of the rainfall forecast are observational data.
Co-Authors A. A. Mattjik Abduh Riski Achmad Budi Susetyo Anak Agung Gede Sugianthara Awalin, Qonita Ilmi Bagus Sartono Budi Lestari D. Dafik Dian Anggraeni Dian Anggraeni Dian Anggraeni Dian Anggraeni Dian Anggraeni Dian Anggraeni Dimas Bagus Cahyaningrat Wicaksono EVI RAMADHANI 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 I Made Tirta Ika Hesti Agustin, Ika Hesti INA YATUL ULYA Ira Yudistira Kosala Dwidja Purnomo Kurnia Ahadiyah Luckyta Citra Ayu Paramitha M Dika saputra Madinda, Diah Putri Miftahul Ulum Mohamad Fatekurohman Muhammad Iqbal Yunan Helmi Muhammad Subianto Muharom, Lutfi Ali Nasrul Ilminnafik Nurul Fittriyah, Nurul Paramitha, Luckyta Citra Ayu Prayogo, Rizky Putra, Rio Pradani Rio Pradani Putra Rory Ronella Agustin Rusdiana, Riza Yuli Sa'diyah, Halimatus Sa’diyah, Halimatus Sudarko Sudarko Sunder, R. Syamsul Arifin Tresnawanti, Dini Wibisono, Dwi Anugrah Yuliani Setia Dewi