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PENDEKATAN GEOGRAPHICALLY WEIGHTED ZERO INFLATED POISSON REGRESSION (GWZIPR) DENGAN PEMBOBOT FIXED BISQUARE KERNEL PADA KASUS DIFTERI DI INDONESIA Ismah, Ismah; Sumertajaya, I Made; Djuraidah, Anik; Fitrianto, Anwar
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 14 No 1 (2020): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : MATHEMATIC DEPARTMENT, FACULTY OF MATHEMATICS AND NATURAL SCIENCES, UNIVERSITY OF PATTIMURA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (679.128 KB) | DOI: 10.30598/barekengvol14iss1pp039-046

Abstract

The number of deaths due to diphtheria is counts data and there is a considerable presence of zeros (excess zeros). Besides, data on the spread of disease are generally geographically oriented or observed in each particular region, which is a type of spatial data. Geographically Weighted Zero Inflated Poisson Regression (GWZIPR), as the development of Geographically Weighted Regression (GWR) and Zero Inflated Poisson (ZIP) models will be used as a model in processing provincial diphtheria data in Indonesia in 2018, with the independent variable percentage of diphtheria cases (X1), percentage of vaccinated numbers (X2) and percentage of the population (X3) in each province in Indonesia. Estimating model parameters uses the method of maximum likelihood estimation. While the weighting function used is fixed bisquare kernel. Data is processed using software R packages lctools. The results were obtained if the model involved all three independent variables, the effect of the three independent variables on the number of deaths due to diphtheria was not significant. This is because there is a strong and significant relationship between independent variables, so that if the model does not involve a variable percentage of the population (population density), the percentage of vaccinated people affects the number of deaths caused by diphtheria significantly in an area. So that the provision of immunization vaccines can reduce the number of deaths caused by diphtheria
A Study of Count Regression Models for Mortality Rate Fitrianto, Anwar
CAUCHY Vol 7, No 1 (2021): CAUCHY: Jurnal Matematika Murni dan Aplikasi
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v7i1.13642

Abstract

This paper discusses how overdispersed count data to be fit. Poisson regression model, Negative Binomial 1 regression model (NEGBIN 1) and Negative Binomial regression 2 (NEGBIN 2) model were proposed to fit mortality rate data. The method used is comparing the values of Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) to find out which method suits the data the most. The results show that the data indeed display higher variability. Among the three models, the model preferred is NEGBIN 1 model.
PENENTUAN LAMA WAKTU OPTIMAL PADA PENGUKURAN GLUKOSA DARAH NON-INVASIF Fitrianto, Anwar; Erfiani, Erfiani; Nisa, Rahmatun
JST (Jurnal Sains dan Teknologi) Vol 11, No 1 (2022)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jst-undiksha.v11i1.43185

Abstract

Pengukuran kadar glukosa darah menggunakan metode invasif, yaitu melukai bagian tubuh, seperti jari, merupakan metode yang kurang disukai oleh sebagian besar masyarakat. Untuk itu, diperlukan pengembangan teknologi berupa alat pengukur kadar glukosa darah non-invasif. Alat ini menggunakan prinsip kerja spektroskopi inframerah. Oleh karena itu, lama waktu pengukuran menjadi hal yang harus dipertimbangkan. Keoptimalan lama waktu pengukuran diperlukan agar proses pemeriksaan kadar glukosa darah efisien dan bisa merekam seluruh informasi. Tujuan penelitian ini adalah menentukan lama waktu optimal pada alat pengukur kadar glukosa darah non-invasif. Data yang digunakan merupakan data primer hasil pengukuran kadar glukosa darah dari tiga responden. Data tersebut dianalisis menggunakan metode eksplorasi dan regresi linier. Hasil pemodelan dengan persamaan ,  lama waktu optimal tersebut berada pada waktu perlakuan sebesar 1700 ms dengan menggunakan metode gradien pada kurva.
Statistical model for IC50 determination of acetylcholinesterase enzyme for Alzheimer’s disease Anwar Fitrianto; Siau Man Mah; Siau Hui Mah
International Journal of Public Health Science (IJPHS) Vol 11, No 3: September 2022
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijphs.v11i3.21282

Abstract

This study aimed to formulate a suitable statistical model to determine acetylcholinesterase enzyme's half-maximal inhibitory (IC50) by a series of synthetic compounds. It was done with the same core structure for acetylcholinesterase inhibition for anti-Alzheimer’s disease (AD). The IC50 of eighteen synthesized compounds on anticholinesterase activities was obtained and statistical methods were applied. Regression models were fitted to the dose-response curve to look for their IC50. Simple linear regression is the simplest model for the dose-response curve. However, polynomial regression models or non-linear regression models fit the data more accurately. The adjusted coefficient of determination (????2????????????) was used to determine the best model among the linear models, while the root mean square error (RMSE) is more suitable in determining the goodness of fit between linear and non-linear model. Four-parameter logistic (4-PLR) regression often fits the dose-response data closely. Based on the RMSE value, a polynomial regression fitted better than 4-PLR with the IC50 of 245.52.
Rekayasa Model Kebijakan Manajemen Otoritas Lokal dalam Eksploitasi Air Bersih Menggunakan Powersim Contructor lmam Hanafi; Anwar Fitrianto
Jurnal Aplikasi Manajemen Vol 8, No 1 (2010)
Publisher : Jurusan Manajemen Fakultas Ekonomi dan Bisnis Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1530.459 KB)

Abstract

Stale authority intervention through public policies played an important role to fairly distributed and optimally utilized water resource. However. the local government as state representations could be fallen down on the execution. This research constructed by local authority policies model in exploiting clean water in Batu, East Java. This research model follows the quantitative paradigm. The created methodology model's foundations were based on systemic thinking methods and cognitive policies mapping by using Powerism Control Software. Constructed policies model was clean water exploitation. The model shows the common difficulties typology model. This model able to guide limitation, exploitation, and consumption of water resource management policies in order to create fairness, better service, competition, and give priority to public interest and hamper private dominations. Local government controls regarding to managing allocation (quantity, quality, duration), pricing, and water retributions were the prerequisite to ensure sufficient original district revenue while private companies acquire profit. Control and regulation by the government in term of clean water privatization were as a purpose to ascertain the long term benefits and eliminate any disadvantages. 
Skenario Kebijakan Tentang Ruang Terbuka Hijau Di Kota Batu: Suatu Pendekatan Simulasi Imam Hanafi; Anwar Fitrianto
Kolaborasi : Jurnal Administrasi Publik Vol 8, No 1 (2022): April 2022
Publisher : Department of Public Administration, Muhammadiyah University of Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/kjap.v8i1.6998

Abstract

Steps to create environmental comfort in Batu City, East Java, need to support sustainable development. This research aims to develop policy scenarios related to simulation-based Green Open Space (RTH) planning to realize Batu City's environmental sustainability. The study of stakeholder preferences for the function of green space is carried out by digging primary data from the relevant parties (stakeholders) using interviews and observations. The green open space in Batu City is decreasing due to the conversion of the RTHK function into a built area. The change in RTHK was caused by the implementation of Batu City development activities which were more inclined to infrastructure development as well as physical facilities and infrastructure. Policy analysis is carried out by conducting simulations (changes to model parameters) and then observing their behavior. Several green open space planning scenarios were carried out using the Powersim constructor software. Several scenarios are related to green open space planning in Batu City, including free scenario, moderate scenario, and sustainable scenario. Of the three scenarios, the sustainable scenario is more suitable because the increase in land ares used in the sustainable scenario is relatively controlled. There are efforts to allocate green open space on residential land, industrial land, social and social facilities land, trade and service land every year to reduce the decrease in green open space.
Sentiment Analysis on Covid-19 Vaccination in Indonesia Using Support Vector Machine and Random Forest I Made Sumertajaya; Yenni Angraini; Jamaluddin Rabbani Harahap; Anwar Fitrianto
JUITA : Jurnal Informatika JUITA Vol. 10 No. 1, May 2022
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1277.257 KB) | DOI: 10.30595/juita.v10i1.12394

Abstract

World Health Organization (WHO) stated Covid-19 as a global pandemic in March, 2020. This pandemic has influenced people’s life in many sectors such as the economy, health, tourism, and many more. One way to end this pandemic is to make herd immunity obtained through the vaccination program. This program still raises pros and cons at the beginning of its implementation in Indonesia. Many people doubt the safety and side effects of the vaccine. There are also pros and cons to vaccination programs in social media such as Twitter. This platform generates a huge amount of text data containing people's perceptions about vaccines. This research aims to predict sentiment using supervised learning such as support vector machine (SVM) and random forest and capture sentiment about vaccines in Indonesia in the first two weeks of the program. The result shows SVM was a better model than random forest based on the precision and F1-score metrics. The SVM approach produces a precision value of 0.50, a recall of 0.64, and an F1-score of 0.52. In the study, it was also found that tweets with neutral sentiment dominated the twitter user sentiment in the study period. Tweets with negative sentiment decreased after the first week of the COVID-19 vaccination program.
Development of direct marketing strategy for banking industry: The use of a Chi-squared Automatic Interaction Detector (CHAID) in deposit subscription classification Anwar Fitrianto; Wan Zuki Azman Wan Muhamad; Budi Susetyo
JOURNAL OF SOCIOECONOMICS AND DEVELOPMENT Vol 5, No 1 (2022): April
Publisher : Publisher of Widyagama University of Malang (UWG Press)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31328/jsed.v5i1.3420

Abstract

A comparison between Chi-squared Automatic Interaction Detector (CHAID) and logistic regression analysis was performed for classification problems on bank direct marketing data. CHAID Performance Comparison and comparison with Logistic Regression (LR) performance were also conducted. Priority performance with two statistical measures was evaluated: classification accuracy and sensitivity in the presence of data containing categorical imbalances. Random over sampling (ROS) was then applied to deal with class balance problems to get better performance of CHAID analysis. Segmentation analysis was also performed using the CHAID approach to improve the performance of the analysis results. CHAID outperforms LR because of its advantages that it can be used to perform segmentation modeling. Direct marketers should pay attention to traits are Duration, Month, Contact, and Housing. To get a higher subscription, the bank must extend the call duration. Based on these results, the banking industry needs to prepare regulations related to human resources, infrastructure, costs, and government support to achieve higher subscriptions.JEL Classification  A10; C10; G21
PENINGKATAN AKURASI KLASIFIKASI INTERAKSI FARMAKODINAMIK OBAT BERBASIS SELEKSI PASANGAN OBAT TAKBERINTERAKSI Hilma Mutiara Winata; Farit Mochamad Afendi; Anwar Fitrianto
Indonesian Journal of Statistics and Applications Vol 3 No 3 (2019)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1006.047 KB) | DOI: 10.29244/ijsa.v3i3.327

Abstract

Identifying the pharmacodynamics drug-drug interaction (PD DDI) is needed since it can cause side effects to patients. There are two measurements of drug interaction performance, namely the golden standard positive (GSP) which is the drug pairs that interact pharmacodynamics and golden standard negative (GSN), which is a drug pairs that do not interact. The selection of GSN in the previous which studies were only selected randomly from a list of drug pairs that do not interact. The random selection is feared to contain drug pairs that actually interact but have not been recorded. Therefore, in this study the determination of GSN was carried out by, first, grouping drug pairs included in the GSP using the DP-Clus algorithm with certain values of density and cluster properties. Then the drugs in different group would be paired and only the drug pairs in the GSN list are selected. It was found that our new proposed classification method increases the AUC value compared to the results obtained by random selection of GSN.
PERBANDINGAN BEBERAPA METODE KLASIFIKASI DALAM MEMPREDIKSI INTERAKSI FARMAKODINAMIK Hasnita Hasnita; Farit Mochamad Afendi; Anwar Fitrianto
Indonesian Journal of Statistics and Applications Vol 4 No 1 (2020)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (305.755 KB) | DOI: 10.29244/ijsa.v4i1.328

Abstract

One mechanism for Drug-Drug Interaction (DDI) is pharmacodynamic (PD) interactions. They are interactions by which the effects of a drug are changed by other drugs at the site of receptor. The interactions can be predicted based on Side Effects Similarity (SES), Chemical Similarity (CS) and Target Protein Connectedness (TPC). This study aims to find the best classification technique by first applying the scaling process, variable interaction, discretization and resampling technique. We used Random Forest, Support Vector Machines (SVM) and Binary Logistic Regression for the classification. Out the three classification methods, we found the SVM classification method produces the highest Area Under Cover (AUC) value compared to the other, which is 67.91%.