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Rancang Bangun Data Warehouse dan R Studio Serta Pemanfaatanya dalam Peramalan Pola Konsumsi Masyarakat di Kabupaten Jember Muharom, Lutfi Ali; Hadi, Alfian Futuhul; Anggraeni, Dian
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 | Full PDF (619.418 KB) | 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.
Motivasi Petani Dalam Menggunakan Benih Padi Varietas Lokal Rollinda Mustikaning Cahyo; Mustapit Mustapit; Dian Anggraeni
JURNAL AGRIBISNIS TERPADU Vol 12, No 2 (2019)
Publisher : Jurusan Agribisnis Fakultas Pertanian Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (486.939 KB) | DOI: 10.33512/jat.v12i2.6778

Abstract

The existence of local varieties of rice in Indonesia is now declining, and is on the verge of extinction. The farmers' paradigm changed to seeing the economic value of rice and made the orientation of farmers shift to the market, slowly leaving local rice seeds. However, in the village of Cimandiri there are still farmers who survive and prefer to use local rice paddy seeds for farming activities. The purpose of the study was to describe motivation and explain the reasons (explanation) of farmers in choosing the local paddy rice seeds. This research is a qualitative research with the determination of the informant purposive sampling. Data analysis was used using Miles and Huberman's analysis.The results of the study show that the motivation of farmers to choose to use local varieties of paddy seeds is to fulfill the needs of existence or existence and relatedness. Satisfactory indicators of the need for existence are easy to obtain paddy seeds, farmers do not need to buy seeds, and consumption. Indicator of fulfilling the need for linkages, namely social activities. The results of the study also indicate that there is a need for existence and linkages that are fulfilled at the same time. The reason farmers use the local paddy rice seeds is based on farmers' economic moral actions and farmer's rationality at one time. Indicators of farmer's moral economic actions are culture and norms. Whereas farmer rationality acts because farmers dare to take cultivation risks and post-harvest risks. this study also shows the farmers' moral theory of economics and the theory of farmer rationality can be done at one time to make a decision.
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.
Analisis Hubungan Antara Financial Distress dan Keputusan Kebijakan Dividen Omisi Perusahaan Manufaktur Dwi Putri Antika; Mohamat Fatekurohman; Dian Anggraeni
Limits: Journal of Mathematics and Its Applications Vol 15, No 1 (2018)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (376.282 KB) | DOI: 10.12962/limits.v15i1.3390

Abstract

Financial distress adalah kondisi dimana perusahaan mengalami kerugian atau kehilangan, namun belum sampai dikatakan bangkrut. Kondisi yang paling mudah dilihat dari perusahaan yang mengalami financial distress adalah dari keputusan dividen omisi perusahaan. Tujuan dari penelitian ini adalah untuk mengetahui pengaruh dari rasio keuangan seperti likuiditas, leverage, profitabilitas, free cash flow, dan size terhadap durasi waktu antara perusahaan mengalami financial distress dan kemunculan dividen omisi dengan model Cox extended yang diinteraksikan dengan fungsi waktu dan dungsi Heaviside dan untuk mengetahui keberlangsungan perusahaan untuk membagikan dividen. Pada penelitian ini data yang digunakan adalah data rasio keuangan perusahaan manufaktur periode 2016 yang terdaftar di BEI yang telah membagikan dividen selama minimal tiga tahun berturut-turut. Data yang diperoleh dianalisis dengan mendeskripsikan karakteristik setiap variabel, estimasi fungsi survival menggunakan plot Kaplan-Meier, uji perbedaan kurva survival dengan uji Log-Rank, pembentukan model Cox extended dengan fungsi waktu dan fungsi heaviside dan dipilih model terbaik dengan melihat nilai AIC. Hasil dari penelitian ini adalah diperoleh model terbaik Cox extended dengan fungsi heaviside. Variabel yang signifikan adalah profitabilitas (Return on Asset), dan perusahaan yang memiliki profitabilitas yang lebih besar dari 5,98% memiliki risiko mengalami omitted dividend 21% kali lebih kecil daripada perusahaan dengan profitabilitas rendah
Aplikasi Model Cox Proportional Hazard pada Pasien Stroke RSD Balung Kabupaten Jember Tutik Qomaria; Mohamad Fatekurohman; Dian Anggraeni
Indonesian Journal of Applied Statistics Vol 2, No 2 (2019)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v2i2.34907

Abstract

According to the World Health Organization (WHO) cardiovascular disease is a disease caused by impaired heart and blood vessel function. There are many types of cardiovascular disease, but the most common and most well-known are coronary heart disease and stroke. Stroke is a syndrome characterized by symptoms and / or rapidly developing clinical signs in the form of focal and global brain functional disorders lasting more than 24 hours (unless there are surgical interventions or bringing death), which are not caused by other causes besides vascular causes. The number of stroke patients in Indonesia in 2013 based on the diagnosis of health personnel (Nakes) was 1.236.825 (7,0%), while based on the diagnosis of symptoms was 2.137.941 (12,1%). In this study the factors that can affect the survival of stroke sufferers were analyzed using the Cox proportional hazard regression model, the dependent variable was the length of time the patient was treated and the independent variables were gender, age, hypertension status, cholesterol status, Diabetes Militus (DM) status, stroke type, and Body Mass Index (BMI). The result showed that age, DM status, and type of stroke were the most influential factors on the survival of stroke patients at Balung Regional Hospital.Keywords : stroke disease, survival analysis, Cox proportional hazard model
Perbandingan Model Cox Proportional Hazard dan Regresi Weibull untuk Menganalisis Ketahanan Bank Syariah Yusrillah Ihza Zianita Afni; Mohamad Fatekurohman; Dian Anggraeni
Indonesian Journal of Applied Statistics Vol 2, No 2 (2019)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v2i2.33082

Abstract

On July 1, 2014 Financial Services Authority (OJK) issued a new regulation number 8/PJOK.13/2014 concerning the health of general sharia banks that can be valued from several aspects including credit risk, liquidity risk, Return on Asset (ROA), Net of Margin (NOM) and Capital Adequacy Ratio (CAR). The purpose of this study is to compare the models of Cox proportional hazard and Weibull regression for the resistance of sharia bank in 2017-2018 for 24 data. The data were analyzed by describing each variable and modeling in each method. Comparison result shows that Weibull regression model is better than the Cox proportional hazard model because it has smaller AIC and MSE.Keywords : Sharia Bank, Survival Analysis, AIC, MSE
PENENTUAN LOKASI STRATEGIS AUTOMATIC TELLER MACHINE PT. BANK SYARIAH INDONESIA TBK MENGGUNAKAN METODE DECISION TREE Masruroh Masruroh; Mohamat Fatekurohman; Dian Anggraeni
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 14 No 1 (2022): Jurnal Ilmiah Matematika dan Pendidikan Matematika
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

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

Abstract

ABSTRAK. Lokasi Automatic Teller Machine Bank Syariah Indonesia Tbk (ATM BSI) dapat dianalisis dengan mengambil beberapa data sesuai dengan faktor pendukung yang akan digunakan. Faktor pendukung yang sesuai dianalisis dengan salah satu metode klasifikasi data mining yaitu Desicion Tree untuk menentukan lokasi strategis ATM BSI yang sudah didirikan. Desicion Tree adalah salah satu metode klasifikasi pada data mining berupa pohon keputusan untuk menyelesaikan permasalahan yang diperoleh dan menghasilkan aturan-aturan yang dapat dijadikan sebuah kesimpulan. Hasil perhitungan dengan metode Desicion Tree diperoleh akurasi sesuai dengan tabel confusion matrix untuk data training 100% dengan nilai AUC 1 dan data testing 100% dengan nilai AUC 1 dengan aturan pohon keputusan berdasarkan variabel jumlah penduduk dan jarak ATM ke SPBU. Hasil akurasi menunjukkan sangat baik dan akurat serta model Desicion Tree mampu memprediksi lokasi strategis dan tidak strategis berdasarkan data lokasi yang digunakan. Kata Kunci: Lokasi strategis, Automatic Teller Machine (ATM), Metode Desicion Tree.
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.
PENENTUAN LOKASI ATM BANK SYARIAH INDONESIA DI WILAYAH JEMBER KOTA MENGGUNAKAN K-MEANS CLUSTERING Nila Al Indiani; Kiswara Agung Santoso; Dian Anggraeni
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

All transactions are inseparable from the role of the ATM as a supporter the business entity financial improvement. Therefore, the existence of an ATM has now become a general need of modern society. Currently, the population of Jember Regency is 2,568.88 people, and 10 ATM have been established, which means the population ratio and the number of ATM are not balanced, so it is necessary to make a data grouping in order to obtain the location of the ATM establishment that can reach the surrounding villages. This research examined the K-Means Clustering method in the case of determining the location of an ATM based on the distance from the center of the crowd. Calculation of distance using Google Maps K-Means Clustering algorithm was used to group 40 data points for the center of each village into 6 clusters. This research assumed that the centroid is the location of the ATM establishment and the cluster members were the village that can be reached by the centroid. The results of C1-C6 grouping were Tanjung Market, Pakusari Market, MTSN 2 Jember, KUA Arjasa, SMPN 3 Arjasa, and SMAN 4 Jember, sequentially. Keywords: ATM Location, Euclid Distance, K-Means Clustering