Article Per Year (5 Year)
p-Index From 2020 - 2025
13.096
P-Index
This Author published in this journals
All Journal International Journal of Public Health Science (IJPHS) Jurnal Ilmu Pertanian Indonesia Jurnal Ekonomi Pembangunan JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Sains dan Teknologi Techno.Com: Jurnal Teknologi Informasi CAUCHY: Jurnal Matematika Murni dan Aplikasi JAM : Jurnal Aplikasi Manajemen Jurnal TIMES Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUITA : Jurnal Informatika Kubik Journal of Accounting and Investment JURNAL KOLABORASI JIMKesmas (Jurnal Ilmiah Mahasiswa Kesehatan Masyarakat) Al-Jabar : Jurnal Pendidikan Matematika Desimal: Jurnal Matematika Indonesian Journal of Artificial Intelligence and Data Mining BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING Journal of Socioeconomics and Development Jurnal Informatika Universitas Pamulang J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Teorema: Teori dan Riset Matematika Sainmatika: Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam Jambura Journal of Mathematics ComTech: Computer, Mathematics and Engineering Applications Ecces: Economics, Social, and Development Studies Inferensi Journal of Data Science and Its Applications International Journal of Science, Engineering and Information Technology Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Jurnal Statistika dan Aplikasinya KUBIK: Jurnal Publikasi Ilmiah Matematika Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi MATH LOCUS: Jurnal Riset dan Inovasi Pendidikan Matematika PROFETIK: Jurnal Mahasiswa Pendidikan Agama Islam SRIWIJAYA JOURNAL OF ENVIRONMENT MATHunesa: Jurnal Ilmiah Matematika VARIANSI: Journal of Statistics and Its Application on Teaching and Research Aceh International Journal of Science and Technology Jurnal Sains dan Informatika : Research of Science and Informatic STATISTIKA Scientific Journal of Informatics Jurnal Pendidikan Progresif Indonesian Journal of Statistics and Its Applications Jurnal Info Kesehatan
Fitrianto, Anwar
Departemen Statistika, Fakultas MIPA, IPB University, Bogor 16680
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

Published : 104 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 104 Documents
Search

 1   2   3   4   5 
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
Backwards Stepwise Binary Logistic Regression for Determination Population Growth Rate Factor in Java Island Khusnia Nurul Khikmah; Indahwati Indahwati; Anwar Fitrianto; Erfiani Erfiani; Reni Amelia
Jambura Journal of Mathematics Vol 4, No 2: July 2022
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1332.021 KB) | DOI: 10.34312/jjom.v4i2.13529

Abstract

The high population growth rate can impact various fields due to several factors. Some of the impacts of this high rate are high poverty rates, unemployment, consumption levels, inequality in education figures, gender empowerment index, and increasingly narrow land or area. Therefore, research on the rate of population growth using data on poverty, unemployment, consumption levels, education rates, gender empowerment index, and area makes sense. This data was taken from the official website of the Central Statistics Agency for six provinces on the island of Java, Indonesia. The data used contains missing data so that the missing data is presumed by using the k-nearest neighbour method. The estimated missing data values were modelled using binary logistic regression. Variables that significantly affect the rate of population growth, namely the level of consumption, gender empowerment index, and area, are obtained using the backward stepwise method and are selected based on the smallest Aikakes criterion information value or the one with the most excellent accuracy rate. 
Geo-additive Models in Small Area Estimation of Poverty Novi Hidayat Pusponegoro; Anik Djuraidah; Anwar Fitrianto; I Made Sumertajaya
Journal of Data Science and Its Applications Vol 2 No 1 (2019): Journal of Data Science and Its Applications
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/jdsa.2019.2.15

Abstract

Spatial data contains of observation and region information, it can describe spatial patterns such as disease distribution, reproductive outcome and poverty. The main flaw in direct estimation especially in poverty research is the sample adequacy fulfilment otherwise it will produce large estimate parameter variant. The Small Area Estimation (SAE) developed to handle that flaw. Since, the small area estimation techniques require “borrow strength” across the neighbor areas thus SAE was developed by integrating spatial information into the model, named as Spatial SAE. SAE and spatial SAE model require the fulfilment of covariate linearity assumption as well as the normality of the response distribution that is sometimes violated, and the geo-additive model offers to handle that violation using the smoothing function. Therefore, the purpose of this paper is to compare the SAE, Spatial SAE and Geo-additive model in order to estimate at sub-district level mean of per capita income of each area using the poverty survey data in Bangka Belitung province at 2017 by Polytechnic of Statistics STIS. The findings of the paper are the Geo-additive is the best fit model based on AIC, and spatial information don't influence the estimation in SAE and spatial SAE model since they have the similar estimation performance.
Image Classification of Beef and Pork Using Convolutional Neural Network in Keras Framework salsa bila; Anwar Fitrianto; Bagus Sartono
International Journal of Science, Engineering, and Information Technology Vol 5, No 02 (2021): IJSEIT Volume. 05 Issue 02. JULY 2021
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/ijseit.v5i02.9864

Abstract

Beef is a food ingredient that has a high selling value. Such high prices make some people manipulate sales in markets or other shopping venues, such as mixing beef and pork. The difference between pork and beef is actually from the color and texture of the meat. However, many people do not understand these differences yet. In addition to socialization related to understanding the differences between the two types of meat, another solution is to create a technology that can recognize and differentiate pork and beef. That is what underlies this research to build a system that can classify the two types of meat. Convolutional Neural Network (CNN) is one of the Deep Learning methods and the development of Artificial Intelligence science that can be applied to classify images. Several regularization techniques include Dropout, L2, and Max-Norm were applied to the model and compared to obtain the best classification results and may predict new data accurately. It has known that the highest accuracy of 97.56% obtained from the CNN model by applying the Dropout technique using 0.7 supported by hyperparameters such as Adam's optimizer, 128 neurons in the fully connected layer, ReLu activation function, and 3 fully connected layers. The reason that also underlies the selection of the model is the low error rate of the model, which is only 0.111.Keywords: Beef and Pork, Model, Classification, CNN
Co-Authors A. A., Muftih Aam Alamudi Abd. Rahman Adeline Vinda Septiani Agung Tri Utomo Agus M Soleh Agus Mohamad Soleh Ahmad Syauqi Alfa Nugraha Alfa Nugraha Pradana Alfa Nugraha Pradana Alfa Nugraha Pradana Alfa Nugraha Pradana Alfi Indah Nurrizqi Aliu, Mufthi Alwi ALIU, MUFTIH ALWI Amalia Kholifatunnisa Amanda, Nabila Amatullah, Fida Fariha Amelia, Reni Amir Abduljabbar Dalimunthe Anadra, Rahmi Anang Kurnia Anang Kurnia Anik Djuraidah Anisa Nurizki Annisa Putri Utami Annissa Nur Fitria Fathina Ardhani, Rizky Aristawidya, Rafika Asri Pratiwi, Asri Assyifa Lala Pratiwi Hamid Azis, Tukhfatur Rizmah Aziza, Vivin Nur Bagus Sartono Budi Susetyo Budi Susetyo Budi Susetyo Budi Susetyo Bukhari, Ari Shobri Cahya Alkahfi Daswati, Oktaviyani Defri Ramadhan Ismana Deri Siswara Dessy Rotua Natalina Siahaan Dessy Siahaan Devi Permata Sari Dian Handayani Dwi Jumansyah, L.M. Risman Erfiani Erfiani Erfiani Erfiani Erfiani Erfiani Erfiani Erfiani Erfiani Erfiani Fadilah, Anggita Rizky Fajar Athallah Yusuf Farit M Affendi Farit M. Afendi Farit Mochamad Afendi Fatimah Fatimah Fauziah, Monica Rahma Fulazzaky, Tahira Ghina Fauziah Gustiara, Dela Hari Wijayanto Harismahyanti A., Andi Hasnataeni, Yunia Hasnita Hasnita Heri Cahyono I Made Sumertajaya Ilham Azagi Ilmani, Erdanisa Aghnia Imam Hanafi Indah, Yunna Mentari Indahwati Indahwati Indahwati Indahwati, Indahwati Irsyifa Mayzela Afnan Irzaman, Irzaman Ismah, Ismah Isna Shofia Mubarokah Iswan Achlan Setiawan Iswati Jamaluddin Rabbani Harahap Jap Ee Jia Jia, Jap Ee Jumansyah, L. M. Risman Dwi Jumansyah, L.M. Risman Dwi Khairil Anwar Notodiputro Khikmah, Khusnia Nurul Khusnia N. K. Khusnia Nurul Khikmah Kriswan, Suliana Kusman Sadik L.M. Risman Dwi Jumansyah L.M. Risman Dwi Jumansyah La Ode Abdul Rahman La Ode Abdul Rahman Lai Ming Choon Linganathan, Punitha lmam Hanafi M. Aiman Askari M.S, Erfiani Marshelle, Sean Megawati Megawati Mohamad Solehudin Zaenal Muftih Alwi Aliu Muftih Alwi Aliu Muhadi, Rizqi Annafi Muhammad Farhan Zahid Muhammad Irfan Hanifiandi Kurnia mutiah, siti Nabila Ghoni Trisno Hidayatulloh Nadira Nisa Alwani Nafisa Berliana Indah Pratiwi Nashir, Husnun Nisa Nur Aisyah Novi Hidayat Pusponegoro Nugraha, Adhiyatma Nur Hidayah Nur Khamidah Pangestika, Dhita Elsha Pika Silvianti Pika Silvianti Pradnya Sri Rahayu Punitha Linganathan Putri Auliana Rifqi Mukhlashin Putri, Oktaviani Aisyah Rachmat Bintang Yudhianto Rafika Aufa Hasibuan Rahmatun Nisa, Rahmatun Rais Reka Agustia Astari Reni Amelia Reni Amelia Retna Nurwulan Riansyah, Boy Rifda Nida’ul Labibah Riska Yulianti, Riska Rizki Manaf, Silmi Anisa Rizki, Akbar Rizqi, Tasya Anisah Sachnaz Desta Oktarin salsa bila Seta Baehera Setyowati, Silfiana Lis Siau Hui Mah Siau Man Mah Silmi Annisa Rizki Manaf Silmi Annisa Rizki Manaf Siregar, Indra Rivaldi Siti Hafsah Siti Hasanah Siti Nur Azizah, Siti Nur Sofia Octaviana Sony Hartono Wijaya Suantari, Ni Gusti Ayu Putu Puteri Suliana Kriswan Tahira Fulazzaky Titin Agustina Titin Yuniarty Yuniarty Uswatun Hasanah Utami Dyah Syafitri Vitona, Desi Vivin Nur Aziza Waliulu, Megawati Zein Wan Muhamad, Wan Zuki Azman Wan Zuki Azman Wan Muhamad Wan Zuki Azman Wan Muhamad Wan Zuki Azman Wan Muhamad Wan Zuki Azman Wan Muhamad Waode, Yully Sofyah Winata, Hilma Mutiara Xin, Sim Hui Yenni Angraini Yuniarsyih R.A, Rizqi Dwi Zein Rizky Santoso