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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmu Pertanian Indonesia FORUM STATISTIKA DAN KOMPUTASI Media Statistika CAUCHY: Jurnal Matematika Murni dan Aplikasi Disease Prevention and Public Health Journal JURNAL PETERNAKAN Sosioinforma JUITA : Jurnal Informatika International Journal of Advances in Intelligent Informatics BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) JURNAL ILMIAH PETERNAKAN TERPADU J Statistika : Jurnal Ilmiah Teori Dan Aplikasi Statistika Zero : Jurnal Sains, Matematika, dan Terapan Jambura Journal of Mathematics ComTech: Computer, Mathematics and Engineering Applications J-ADIMAS (Jurnal Pengabdian kepada Masyarakat) JURNAL AKUNTANSI KEUANGAN DAN MANAJEMEN Inferensi Jurnal Pendidikan dan Kebudayaan Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Jurnal Statistika dan Aplikasinya JURNAL ILMIAH GLOBAL EDUCATION Jurnal Indonesia Sosial Sains Jurnal Natural Xplore: Journal of Statistics Jurnal Pengabdian Masyarakat dan Lingkungan Parameter: Jurnal Matematika, Statistika dan Terapannya PRAGMATIS Jurnal Manajemen dan Bisnis Jurnal Medika Veterinaria Scientific Journal of Informatics Journal of Mathematics, Computation and Statistics (JMATHCOS) Indonesian Journal of Statistics and Its Applications Jurnal Info Kesehatan Limits: Journal of Mathematics and Its Applications
Indahwati
Department Of Statistics, School Of Data Science, Mathematics And Informatics, IPB University, Campus IPB University, Bogor 16680, Indonesia
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Analisis Gerombol Pautan Ward Kabupaten/Kota di Provinsi Jawa Timur Berdasarkan Indikator Kesejahteraan Rakyat annida marsa salsabila; Mohammad Masjkur; Indahwati
Xplore: Journal of Statistics Vol. 11 No. 3 (2022): Vol. 11 No. 3 (2022)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (301.711 KB) | DOI: 10.29244/xplore.v11i3.1024

Abstract

The main goal in the development of a country is to improve the welfare ofthepeople. One of the causes of the problems of people's welfare in Indonesia is that thedevelopment carried out by the government is not carried out evenly and not on target,not least in East Java Province. to group and look at the characteristics of 38regencies/cities in East Java Province based on people's welfare indicators sothat thegovernment in making policies can be evenly distributed and on target. Thisstudy useshierarchical cluster analysis. The data used is the welfare indicator data for 38districts/cities of East Java Province in 2019. The hierarchical cluster analysismethodused is the Ward method. The results of the study using dendogram cuts and the ratioof standard deviations within clusters and standard deviations betweenclusters showedthat districts/cities in East Java province could be divided into six clusters. In eachcluster, the characteristics are seen using the average value of eachvariable. Areas withvery good development are in cluster six and areas that requiremore development inmany aspects are in cluster five.
Penerapan Bernoulli Naïve Bayes untuk Analisis Sentimen Pengguna Twitter Terhadap Layanan Online Food Delivery di Indonesia Dea Fisyahri Akhilah Putri; Ir. Mohammad Masjkur, M.S.; Indahwati Indahwati
Xplore: Journal of Statistics Vol. 12 No. 1 (2023): Vol. 12 No. 1 (2023)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (738.122 KB) | DOI: 10.29244/xplore.v12i1.1110

Abstract

Online food delivery is one of the drivers of the digital economy that all societies today are interested in. The trend of these services has intensified as changes in people's behavior and lifestyle in the Covid-19 pandemic. The digital platforms of food delivery services in Indonesia are GoFood, ShopeeFood, and GrabFood, present ease in both competitive transactions and multiple options by consumers. Its widespread use of these platforms certainly generates a variety of reviews and public opinion; one is through tweets on Twitter. This study aims to classify the sentiments on the various reviews into the label of positive and negative sentiments using the Bernoulli Naïve Bayes algorithm. The majority of reviews from March 15, 2022 to March 30, 2022 were positive sentiments, which indicated that people gave a positive impression during these online food delivery service. The results of this study show that Bernoulli Naïve Bayes with the feature selection of information gain generates a good performance in classifying sentiment labels based on accuracy scores obtained at 89%, 87%, 86%, and 85% in all data and each online food delivery platform (GoFood, ShopeeFood, and GrabFood).
Pemodelan Regresi Logistik Ordinal Backward dengan Imputasi K-Nearest Neighbour pada Indeks Pembangunan Manusia di Indonesia Tahun 2021 Muftih Alwi Aliu; Anwar Fitrianto; Erfiani; Indahwati; Khusnia N. K.
Jurnal Statistika dan Aplikasinya Vol 7 No 1 (2023): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.07105

Abstract

The human development index (HDI) is one of the important things to note in Indonesia today. The growth of HDI in Indonesia in 2021 is not evenly distributed in all regencies/cities and has high disparities. This study aims to find out the description of HDI data, get the best model to determine the factors that significantly affect the HDI of regencies/cities in Indonesia in 2021 and identify the classification accuracy results of the best model. The independent variables used in this study are average years of schooling, open unemployment rate, population growth rate, population density, percentage of poor people and sex ratio. The independent variables in this study contained missing values, so they were handled using k-nearest neighbour (KNN) imputation and continued modelling using ordinal logistic regression using the backward elimination technique to obtain significant factors. The results showed that the proportion of the low HDI category was 4.28%, the medium HDI category was 48.64%, and the high HDI category was 47.08%. Based on logistic regression modeling using backward elimination which has the smallest AIC value of 293.387, a model with independent variables of average years of schooling (X1), population density (X4), percentage of poor people (X5) and sex ratio (X6) is a variable that significantly affects the HDI of regencies/cities in Indonesia in 2021. The accuracy value of the classification accuracy of training data and test data from the ordinal logistic regression model of HDI of regencies/cities in Indonesia in 2021 is 83.46% and 86.61%, respectively, which means that the model is good for prediction.
The Comparison between Ordinal Logistic Regression and Random Forest Ordinal in Identifying the Factors Causing Diabetes Mellitus Assyifa Lala Pratiwi Hamid; Anwar Fitrianto; Indahwati Indahwati; Erfiani Erfiani; Khusnia Nurul Khikmah
Jambura Journal of Mathematics Vol 5, No 2: August 2023
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjom.v5i2.20289

Abstract

Diabetes is one of the high-risk diseases. The most prominent symptom of this disease is high blood sugar levels. People with diabetes in Indonesia can reach 30 million people. Therefore, this problem needs further research regarding the factors that cause it. Further analysis can be done using ordinal logistic regression and random forest. Both methods were chosen to compare the modelling results in determining the factors causing diabetes conducted in the CDC dataset. The best model obtained in this study is ordinal logistic regression because it generates an accuracy value of 84.52%, which is higher than the ordinal random forest. The four most important variables causing diabetes are body mass index, hypertension, age, and cholesterol.
BETA-BINOMIAL MODEL IN SMALL AREA ESTIMATION USING HIERARCHICAL LIKELIHOOD APPROACH Etis Sunandi; Khairil Anwar Notodiputro; Indahwati Indahwati; Agus Mohamad Soleh
MEDIA STATISTIKA Vol 16, No 1 (2023): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.16.1.88-99

Abstract

Small Area Estimation is a statistical method used to estimate parameters in sub-populations with small or even no sample sizes. This research aims to evaluate the Beta-Binomial model's performance for estimating small areas at the area level. The estimation method used is Hierarchical Likelihood (HL). The data used are simulation data and empirical data. Simulation studies were used to investigate the proposed model. The estimator's Mean Squared Error of Prediction (MSEP) and Absolute Bias (AB) estimator values determine the best estimation criteria. An empirical study using data on the illiteracy rate at the sub-district level in Bengkulu Province. The results of the simulation study show that, in general, the parameter estimators are nearly unbiased. Proportion prediction has the same tendency as parameters. Finally, the HL estimator has a small MSEP estimator. The results of an empirical study show that the average illiteracy rate in Bengkulu province is quite diverse. Kepahiang District has the highest average illiteracy rate in Bengkulu Province in 2021.
BCBimax Biclustering Algorithm with Mixed-Type Data Hanifa Izzati; Indahwati Indahwati; Anik Djuraidah
JUITA: Jurnal Informatika JUITA Vol. 12 No. 1, May 2024
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v12i1.21519

Abstract

The application of biclustering analysis to mixed data is still relatively new. Initially, biclustering analysis was primarily used on gene expression data that has an interval scale. In this research, we will transform ordinal categorical variables into interval scales using the Method of Successive Interval (MSI). The BCBimax algorithm will be applied in this study with several binarization experiments that produce the smallest Mean Square Residual (MSR) at the predetermined column and row thresholds. Next, a row and column threshold test will be carried out to find the optimal bicluster threshold. The existence of different interests in the variables for international market potential and the number of Indonesian export destination countries is the reason for the need for identification regarding the mapping of destination countries based on international trade potential. The study's results with the median threshold of all data found that the optimal MSR is at the threshold of row 7 and column 2. The number of biclusters formed is 9 which covers 74.7% of countries. Most countries in the bicluster come from the European Continent and a few countries from the African Continent are included in the bicluster.
Improving Stroke Detection with Hybrid Sampling and Cascade Generalization Widya Putri Nurmawati; Indahwati Indahwati; Farit Mochamad Afendi
JUITA: Jurnal Informatika JUITA Vol. 12 No. 1, May 2024
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v12i1.19386

Abstract

The prevalence of stroke in Indonesia has increased. One survey in Indonesia that contains information about the health conditions of the Indonesian people is the Indonesian Family Life Survey (IFLS). The proportion of respondents who had a stroke and non-stroke in IFLS5 showed an imbalance with an extreme level of imbalance; hence, this research aims to overcome this problem with SMOTE, SMOTE-Tomek Link, and SMOTE-ENN; then, the balanced dataset is classified using the ensemble and cascade approaches to improve the detection of stroke risk and to identify the important variables. However, the stroke respondents were still challenging to classify after imbalance class handling, presumably because of the large amount of data before and after balancing. The solution is to balance the training data with various percentages. The results showed the best percentage is applied to 5% of the training data, balanced by the SMOTE-ENN, and the ensemble method with the cascade approach increases the sensitivity and balanced accuracy values. Random forest and logistic regression combine models that produce the best performance, with a classification tree as the final model. The important variables obtained from this combination are the addition of probability from random forest, logistic regression, history of hypertension, age, and physical activity.
Menciptakan Produk Bernilai Ekonomis Melalui Pengelolaan Sisa Sampah Anorganik Berbasis Modal Sosial Masyarakat di Lingkungan Perumahan Larangan Mega Asri Kabupaten Sidoarjo Agustini, Ni Ketut Yulia; Indahwati, Indahwati
J-ADIMAS (Jurnal Pengabdian Kepada Masyarakat) Vol 11, No 2 (2023)
Publisher : (STKIP) PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/j-adimas.v11i2.4944

Abstract

Sampah dapat menimbulkan masalah lingkungan dalam berbagai aspek jika tidak ditangani dengan baik. Bukan bisa disangkal, sampah juga bisa menyebabkan peningkatan terhadap penurunan kesehatan masyarakat, degradasi lingkungan dan dampak ekonomi. Di sisi lain, tempat sampah memberikan rasa aman dan nyaman jika dikelola dengan baik. Selain itu, pengelolaan sampah yang tepat dapat berupa produk yang memiliki nilai ekonomi dan sosial. Hal itu dapat dilakukan melalui program pemberdayaan sosial. Program ditujukan untuk mengubah cara pandang dan pengetahuan masyarakat tentang sampah, sehingga sampah dapat dikelola dengan baik dan benar memiliki nilai ekonomis. Metode yang akan digunakan yakni pelatihan terbimbing, metode diskusi grup, ceramah, partisipatif, dan Praktik. Sedangkan sasaran program adalah masyarakat dilingkungan  Perumahan Larangan Mega Asri, Kecamatan Candi Kabupaten Sidoarjo, telah memiliki bank sampah, tetapi masih terdapat sampah-sampah yang merupakan sisa sampah anorganik yang dibuang. Berdasarkan hal tersebut Pentingnya mengedukasi masyarakat tentang pengelolaan sampah agar tercipta produk yang bernilai dan dapat dijual untuk membantu mengurangi jumlah sampah yang dihasilkan. Memberikan penyuluhan untuk membantu masyarakat memahami pengelolaan sampah secara umum dan bagaimana mengolah sampah sisa anorganik menjadi produk  bermanfaat yang dapat dijual.Kata  Kunci: 1.Pengolahan sampah, 2.Peran serta masyarakat, 3.Kesadaran diri, 4. Modal sosial, 5.lingkungan  bebas sampah.
Pengaruh Kepercayaan Merek, Persepsi Kualitas, Dan Harga Terhadap Loyalitas Pelanggan Kosmetik Maybelline (Studi Pada Mahasiswa Aktif Fakultas Ekonomi Dan Bisnis Universitas Wijaya Kusuma Surabaya) Reza, Charolina Therezia; Indahwati, Indahwati
PRAGMATIS Vol 5, No 1 (2024): March
Publisher : Faculty of Economic and Business Wijaya Kusuma Surabaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30742/pragmatis.v5i1.3793

Abstract

The focus of this research is to assess the effect of brand trust, perceived quality, and price on customer loyalty for Maybelline cosmetic products. The parameters of the independent variables studied are brand trust, perceived quality, and price with the dependent variables being customer loyalty. The population in this study were students of the Faculty of Economics and Business, Wijaya Kusuma University Surabaya. Sample determination using non probability sampling method with purposive sampling technique with criteria 1) Female and an active student of FEB UWKS, 2) Have made a purchase transaction for Maybelline cosmetic products, 3) Use the product personally, 4) Make purchases more than 2 times. The number of samples in this study were 47 respondents. This study uses linier regression analysis as the analysis technique. The research findings reveal that brand trust has a significant influence on customer loyalty. On the other hand, perceived quality does not show a significant effect on customer loyalty and price has a significant effect on customer loyalty. Based on the result of the f test, all independent variables can be used to predict Y.
PERBANDINGAN ANALISIS REGRESI LOGISTIK BINER DAN NAÏVE BAYES CLASSIFIER UNTUK MEMPREDIKSI FAKTOR RESIKO DIABETES Aristawidya, Rafika; Indahwati, Indahwati; Erfiani, Erfiani; Fitrianto, Anwar; A. A., Muftih
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 2 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i2.617

Abstract

Diabetes is a global health problem that is increasing in prevalence worldwide. This study compares the performance of two data analysis methods, namely binary logistic regression and naïve bayes classifier in predicting diabetes risk. This study aims to identify factors that significantly affect diabetes risk and classify diabetes risk using binary logistic regression, then compare the classification with the naive bayes classifier algorithm. Binary logistic regression models the relationship between independent predictor variables and binary dependent variables, while naïve bayes classifier uses the assumption of independence between variables. In this study, both methods were evaluated based on accuracy, sensitivity, specificity and positive predictive value. The results show that the factors that influence the risk of diabetes are Age, Gender, Polyuria, Polydipsia, Genital thrush, Itching, Irritability, and Partial paresis. Furthermore, the binary logistic regression results have a higher classification accuracy (92.31%) compared to the naïve bayes classifier (84.61%). Therefore, binary logistic regression was identified as the best method to predict diabetes risk in the context of this study
Co-Authors A. A., Muftih Aam Alamudi Aditya Ramadhan Agus Mohamad Soleh Agustini , Ni Ketut Yulia Agustini, Ni Ketut Yulia Aji Hamim Wigena Akbar Rizki Alahmad, Ali Omar Alfi Indah Nurrizqi Aliu, Mufthi Alwi ALIU, MUFTIH ALWI Amelia, Reni Amin, Yudi Fathul Anang Kurnia Andi Harismahyanti A. Anik Djuraidah annida marsa salsabila Antonius Benny Setyawan Ardi Surya Ari Handayani Arie Anggreyani Aristawidya, Rafika ASEP SAEFUDDIN Assyifa Lala Pratiwi Hamid Aunuddin . Bagus Sartono Baiq Dian Arianingsih Budi Susetyo Bukhari, Ari Shobri Cahya, Septa Dwi Cahyani Oktarina Chrisinta, Debora Dairul Fuhron Daswati, Oktaviyani Dea Fisyahri Akhilah Putri Dian Kusumaningrum Erfiani Erfiani Erfiani Erfiani Etis Sunandi Eva Wany, Eva Evita Purnaningrum Farit Mochamad Afendi Farit Mohamad Afendi Fatimah Fatimah Fira Nurahmah Al Aminy Fitrianto, Anwar Fulazzaky, Tahira Ghina Fauziah Hanifa Izzati Hanifa Izzati Hari Wijayanto Hasanah, Lailatul I Gusti Putu Purnaba I Made Sumertajaya Iin Maena Ilham Azagi Indah, Yunna Mentari Intan Juliana Panjaitan Irawan Irawan Jasmin Nur Hanifa Jaya, Eddy Santosa Julianti, Elisa D Kamil, Farid Ikram Karunia, Nia Kayla Fakhriyya Jasmine Kefi Amtiran, Chandraone Putra Khairil Anwar Notodiputro Khikmah, Khusnia Nurul Kholidiah, Kholidiah Khusnia N. K. Khusnia Nurul Khikmah Kristorio, Kevin Kusman Sadik Laily Nissa Atul Mualifah Latifah, Leli Lestari, Nila Lili Puspita Rahayu Logananta Puja Kusuma Made Sumertajaya Maghfiroh, Firda Aulia Mega Maulina Miranti, Ita Miranti, Ita Mohammad Masjkur Mualifah, Laily Nissa Muftih Alwi Aliu Muhammad Nur Aidi Naima Rakhsyanda Narindria, Yasmin Nadhiva Nurul Fadhilah Panjaitan, Intan Juliana Pika Silvianti Puput Cahya Ambarwati Putra, Stefanus Morgan Setyadi Perdana Putri, Christiana Anggraeni Ramdani, Indri Rasyid, Baharun Ray Sastri Regan, Regan Reni Amelia Reni Amelia Reza, Charolina Therezia Rifki Hamdani Rindy Anggun Pertiwi Rizka Annisa Mingka Salvina Salvina Setyo Wahyudi Silmi Annisa Rizki Manaf Siti Hafsah Siwi Haryu Pramesti Tina Aris Perhati Titin Agustina Titin Suhartini Titin Suhartini, Titin Titin Yuniarty Yuniarty Tri Wahyuni Utami Dyah Syafitri Vera Maya Santi Via Sulviana Vitona, Desi Wahyudi Setyo Wandee Wanishsakpong Widya Putri Nurmawati Yani Prihantini Hiola Yenni Angraini Yuniarty, Titin Yunna Mentari Indah Zulkarnain, Rizky _ Aunuddin