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All Journal FORUM STATISTIKA DAN KOMPUTASI CAUCHY: Jurnal Matematika Murni dan Aplikasi Desimal: Jurnal Matematika Xplore: Journal of Statistics Journal of Mathematics, Computation and Statistics (JMATHCOS) Indonesian Journal of Statistics and Its Applications
Aam Alamudi
Department Of Statistics, Bogor Agricultural University (IPB)
Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Mathematics Social Sciences Other

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Journal : Indonesian Journal of Statistics and Its Applications

 1 
PENDUGAAN PARAMETER FUNGSI COBB-DOUGLAS GALAT ADITIF DENGAN ALGORITME GENETIKA Iqbal Hanif; Agus M Soleh; Aam Alamudi
Indonesian Journal of Statistics and Applications Vol 1 No 1 (2017)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v1i1.54

Abstract

Cobb-Douglas function with additive errors is a function which can be used to analyse the relationship between production output and production factors. The method commonly used to estimate the parameter of that function is Nonlinear Least Square (NLS) and a common algorithm for this method is Gauss Newton iteration (NLS-GN). However, NLS-GN method has less-optimum results when analysing multicolinearity data. A possibly better method for this analysis is Genetic Algorithm (NLS-GA). The purpose of this study is to analyse the use of Genetic Algorithm to estimate parameters of Cobb-Douglas function with additive errors. The results show that NLS-GA method could not produce a better parameter estimator than NLS-GN method does but it produced a better parameter estimator in analysing multicolinearity data. NLS-GA method is capable of producing a better model with predictive ability than NLS-GN method does with real data. Keywords: cobb-douglas function, genetic algorithm, nonlinear least square
CONSTRUCTING EARTHQUAKE DISASTER-EXPOSURE LIKELIHOOD INDEX USING SHAPLEY-VALUE REGRESSION APPROACH Rahma Anisa; Bagus Sartono; Pika Silvianti; Aam Alamudi; Indonesian Journal of Statistics and Its Applications IJSA
Indonesian Journal of Statistics and Applications Vol 3 No 1 (2019)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v3i1.198

Abstract

Indonesia is very prone to earthquake disaster because it is located in the Pacific ring of fire. Therefore, a reference level of earthquake disaster exposure likelihood events in Indonesia is needed in order to increase people's awareness about the risks. This study aims to determine the index that describes the risk of possible future earthquake disaster. As initial research, this study is focus on earthquake disasters in Java region, as it has the largest population in Indonesia. Several indicators that are related to the severity of earthquake disaster impact, were used in this study. The weights of each indicators were determined by considering its shapley-value, thus all indicators gave equal contribution to the proposed index. The results showed that shapley-value approach can be utilized to construct index with equal contribution of each indicators. In general, the resulted index had similar pattern with the number of damaged houses in each districts.
Sentiment Analysis of Twitter Users’ Opinion Towards Face-to-Face Learning: Analisis Sentimen Tanggapan Masyarakat Pengguna Twitter terhadap Pembelajaran Tatap Muka Silmi Annisa Rizki Manaf; Aam Alamudi; Anwar Fitrianto
Indonesian Journal of Statistics and Applications Vol 7 No 1 (2023)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v7i1p15-31

Abstract

In early 2022, the government allowed face-to-face learning again after approximately one year of online learning. When face-to-face learning will be held again in several areas, the number of Covid-19 has increased and the government has imposed the enforcement of restrictions on community activities. The pros and cons of face-to-face learning also occur on social media, one of them is on Twitter. This study used twitter data for January 30th – February 7th 2022. Opinions on twitter regarding face-to-face learning were studied by sentiment analysis using the binary logistic regression method with sentiment classes being positive and negative. Labeling uses based on the final score of the difference between the number of positive and negative words. The purpose of this study is to determine the public’s perception of the policy of implementing face-to-face learning in the era of the Covid-19 on social media especially Twitter. From this study, public’s perception tends to be in a negative direction which indicates that they have not agreed enough with the existence of face-to-face learning in the period of February 2022 with the accuracy was 85%, sensitivity was 77%, specificity was 88%, and AUC was 91%.
Comparison Between SARIMA and DeepAR with Optuna Hyperparameter Optimization for Estimating Rice Production Data in Indonesia Muhammad Farhan Zahid; Anwar Fitrianto; Pika Silvianti; Aam Alamudi
Indonesian Journal of Statistics and Applications Vol 8 No 2 (2024)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v8i2p95-111

Abstract

Forecast is a prediction of future events that had taken a significant role in our society especially when facing time-sensitive issues like food availability. Food is a critical aspect in ensuring people's welfare, especially in a country like Indonesia with a large population. Availability and access to rice are a vital need for the people of Indonesia. Rice is not only the main source of carbohydrates, but also has a central role in the cultural and social aspects of Indonesian society. Forecasting can be a strategy to anticipate fluctuations in food demand and supply. Forecasting can be an important instrument for the government and stakeholders to make the right and effective decisions. The growing period of rice which is heavily influenced by seasonality makes DeepAR and SARIMA techniques a good solution to solve this problem. Both methods offer the ability to address features in rice production such as trends, seasonality, and anomaly effects. This study demonstrates that DeepAR, especially when optimized with Optuna, outperforms SARIMA in forecasting rice production in Indonesia, as evidenced by superior performance in key evaluation metrics such as Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE).
Missing Value Estimation Using Fuzzy C-Means in Classification of Chronic Kidney Disease: Pendugaan Missing Values Menggunakan Fuzzy C - Means Pada Pengklasifikasian Penyakit Ginjal Kronik Eria, Raisa Nida; Alamudi, Aam; Sulvianti, Itasia Dina; Silvianti, Pika; Rahardiantoro, Septian
Indonesian Journal of Statistics and Applications Vol 9 No 1 (2025)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v9i1p21-32

Abstract

Based on World Health Organization (WHO) the cases of death due to Chronic Kidney Disease (CKD) ranked the 10th worldwide in 2020. CKD need to be done prevent early. History data to identify individuals predisposed to CKD in this research. In this research data contains missing values, therefore using Fuzzy C - Means (FCM) method to address it. The percentage of error in clustering CKD using FCM method is 20,25% and balanced accuracy of 84,80%. The result from classification using Classification and Regression Trees (CART) shows that accuracy value of 97,50%; sensitivity of 100,00%; and specificity of 92,86%. Individual suffer from CKD if having (1) hemoglobin more than or equal 13; spesific gravity 1,020 or 1,025; serum creatinine less than 1,3; albumin 1 or 2 or 3 or 4 or 5; and sugar 0 or 2 or 3 or 4 or 5, (2) hemoglobin more than or equal 13; spesific gravity 1,020 or 1,025; and serum creatinine more than or equal 1,3, (3) hemoglobin more than or equal 13 and spesific gravity 1,005 or 1,010 or 1,015, (4) hemoglobin less than 13 and red blood cell count less than 5,5.
Co-Authors . Aunuddin Agus M Soleh Agus M Soleh Agus Soleh Akmala Firdausi Anik Djuraidah Aulia Dwi Oktavia Ayoe Indria Winuri Azira Irawan Bagus Sartono Budi Susetyo Dhika Firmansyah Dian Kusumaningrum Else Virdiani Eria, Raisa Nida Erlinda Widya Widjanarko Farit Mochamad Afendi Fitrianto, Anwar Hanifatun Nufusia Hiola, Yani Prihantini Indahwati Indonesian Journal of Statistics and Its Applications IJSA Iqbal Hanif Itasia Dina Sulvianti Kusman Sadik Mahdiyah Riaesnianda Maya Deanti Mega Maulina Muhammad Farhan Zahid Nadhif Nursyahban Ni Kadek Manik Dewantari Nisa Nur Aisyah Pika Silvianti Pika Silvianti Putri, Oktaviani Aisyah Rahardiantoro, Septian Rahma Anisa Rahma Anisa Resty Fanny Riansyah, Boy Silmi Annisa Rizki Manaf Tania Amalia Darsono Utami Dyah Syafitri Yasmin Erika Faridhan Yenni Angraini