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PENERAPAN REGRESI NONPARAMETRIK KERNEL DAN SPLINE DALAM MEMODELKAN RETURN ON ASSET (ROA) BANK SYARIAH DI INDONESIA Rahayu, Putri Indi; Sihombing, Pardomuan Robinson
Epsilon: Jurnal Pendidikan Matematika Vol 2 No 2 (2020): Epsilon: Jurnal Pendidikan Matematika
Publisher : LPPM STKIP PGRI Bandar Lampung

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Abstract

Abstract: Sharia Bank Return On Assets (ROA) modeling in Indonesia in 2018 aims to analyze the relationship pattern of Return On Assets (ROA) with interest rates. The analysis that is often used for modeling is regression analysis. Regression analysis is divided into two, namely parametric and nonparametric. The most commonly used nonparametric regression methods are kernel and spline regression. In this study, the nonparametric regression used was kernel regression with the Nadaraya-Watson (NWE) estimator and Local Polynomial (LPE) estimator, while the spline regression was smoothing spline and B-splines. The fitting curve results show that the best model is the B-splines regression model with a degree of 3 and the number of knots 5. This is because the B-splines regression model has a smooth curve and more closely follows the distribution of data compared to other regression curves. The B-splines regression model has a determination coefficient of R^2 of 74.92%, meaning that the amount of variation in the ROA variable described by the B-splines regression model is 74.92%, while the remaining 25.8% is explained by other variables not included in the model.
HOW MACHINE LEARNING METHOD PERFORMANCE FOR IMBALANCED DATA : Case Study: Classification of Working Status of Banten Province Sihombing, Pardomuan Robinson
TEKNOKOM Vol. 4 No. 2 (2021): TEKNOKOM
Publisher : Department of Computer Engineering, Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (173.515 KB) | DOI: 10.31943/teknokom.v4i2.64

Abstract

This study will examine the application of several classification methods to machine learning models by taking into account the case of imbalanced data. The research was conducted on a case study of classification modeling for working status in Banten Province in 2020. The data used comes from the National Labor Force Survey, Statistics Indonesia. The machine learning methods used are Classification and Regression Tree (CART), Naïve Bayes, Random Forest, Rotation Forest, Support Vector Machine (SVM), Neural Network Analysis, One Rule (OneR), and Boosting. Classification modeling using resample techniques in cases of imbalanced data and large data sets is proven to improve classification accuracy, especially for minority classes, which can be seen from the sensitivity and specificity values that are more balanced than the original data (without treatment). Furthermore, the eight classification models tested shows that the Boost model provides the best performance based on the highest sensitivity, specificity, G-mean, and kappa coefficient values. The most important/most influential variables in the classification of working status are marital status, education, and age.
Regularized Ordinal Regression with Elastic Net Approach (Case Study: Poverty Modeling in Yogyakarta Province 2018) Sihombing, Pardomuan Robinson; Andriyana, Yudhie; Tantular, Bertho
CAUCHY Vol 6, No 4 (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.v6i4.11758

Abstract

Generally, modeling poverty aims to obtain the best criteria for assessing poverty status. There are two approaches to model the factors that affect poverty, namely consumption approach and discrete choice model. The advantage of the discrete choice model compared to the consumption approach is that the discrete choice model provides a probabilistic estimate for classifying samples into different poverty categories. This study aims to examined how the factors that affect poverty in Yogyakarta through Regularized Ordinal Regression with elastic net approach both for parallel, non-parallel, and semi-parallel models. The data used in this study is Susenas March 2018 for Yogyakarta provinces. The result of this study shows that the best discrete choice model for Yogyakarta’s modelling is the parallel model. Households that live in villages, have a large number of household members, are headed by women, have elderly household heads, have low education, and work in the primary sector tend to be more vulnerable to poverty. Therefore, a simultaneous policy with inclusive economic development is needed to reduce cross-border, cross-gender, and cross-sector inequality
Comparison of Imbalanced Data Methods on Logistics Regression (Case Study: Poverty in Indonesia In 2018) Sihombing, Pardomuan Robinson
International Humanities and Applied Science Journal Volume 4, Issue 3, 2021
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/ihasj.2021.v4i3.05

Abstract

Poverty is still one of the main problems in economic development and inequality, unemployment, and economic growth. This study aims to model poverty directly by using a discrete choice model using binomial regression. The data used is imbalanced data, where one of the value categories is relatively small. In this study, the logistic regression method applies several resample techniques. They include undersampling, oversampling, a combination of both, and Cost-Sensitive Learning (CSL). The results obtained that both sampling techniques provide optimal results when viewed from the indicators of accuracy, specificity, sensitivity, and AUC. In addition, the results show that in households in rural areas, the head of the household is female, unmarried, has low education, married at an early/old age, and has a large household size, has a greater chance of being poor than other categories. So that targeted and comprehensive policy is needed so that the poverty rate can continue to be reduced and welfare increases
Handling concept drifts and limited label problems using semi-supervised combine-merge Gaussian mixture model Ibnu Daqiqil Id; Pardomuan Robinson Sihombing; Supratman Zakir
Bulletin of Electrical Engineering and Informatics Vol 10, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i6.3259

Abstract

When predicting data streams, changes in data distribution may decrease model accuracy over time, thereby making the model obsolete. This phenomenon is known as concept drift. Detecting concept drifts and then adapting to them are critical operations to maintain model performance. However, model adaptation can only be made if labeled data is available. Labeling data is both costly and time-consuming because it has to be done by humans. Only part of the data can be labeled in the data stream because the data size is massive and appears at high speed. To solve these problems simultaneously, we apply a technique to update the model by employing both labeled and unlabeled instances to do so. The experiment results show that our proposed method can adapt to the concept drift with pseudo-labels and maintain its accuracy even though label availability is drastically reduced from 95% to 5%. The proposed method also has the highest overall accuracy and outperforms other methods in 5 of 10 datasets.
Do Internal Household Factors Affect Poverty Status? Evidence From Indonesia Pardomuan Sihombing; Ade Marsinta Arsani
Junal Ilmu Manajemen Vol 3 No 2 (2020): April: Management Science
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (459.907 KB) | DOI: 10.35335/jmas.v3i2, April.52

Abstract

Many factors affect poverty status. The purpose of this paper is to assess the determinants of poverty status in Indonesia, especially for internal household factors. By employing binary logistic regression using poverty status as the dependent variable, this study finds that internal household factors are significantly affecting poverty status in Indonesia. However, due to Yogyakarta's socio-economics characteristics, some findings are different from several previous studies. This study finds that age, education, and employment sectors of household heads and their spouse affect poverty status significantly. Gender, as well as the number of children and household size, also have a significant impact on poverty status in Indonesia. The implication of this result encourages investment not only for the household head but also for their spouse, as well as for all household members, enhance women's capability to get a better job and reduce dependency ratio.
Pengaruh Transparansi, LKPD dan PAD terhadap Kinerja Pemerintah Daerah Pardomuan Robinson Sihombing*; Ade Marsinta Arsani
Jurnal Ecodemica : Jurnal Ekonomi Manajemen dan Bisnis Vol 4, No 2 (2020): Jurnal Ecodemica: Jurnal Ekonomi, Manajemen dan Bisnis
Publisher : LPPM Universitas BSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (246.715 KB) | DOI: 10.31294/jeco.v4i2.8108

Abstract

Local governments' performance reflects the achievement of the goals and objectives set by the agency based on the vision and mission that has been prepared. Many factors affect the performance of local governments, including transparency, accountability of financial statements, and regional income. This study aims to determine the effect of transparency, local government financial report and local own revenue to the performance of local government. The test was conducted in 295 municipalities in Indonesia using secondary data in the form of  Local Government Accountability data, Audit Opinions of the BPK and the Budget Realization Report. The results found that both simultaneously and partially Transparency, Regional Government Financial Reports and the Original Revenue of the District had a significant positive effect on the performance of the local government. It means that the increase in transparency, regional government financial reports and local revenue will improve the performance of local government. The implications of this research can be used as a basis for making decisions regarding the management of local revenue, especially in budget transparency, as it can increase public confidence in local governments. The well-prepared financial reports and the management of local revenue for capital expenditure have a direct implication on public services, so that improve local government performance.
FAKTOR-FAKTOR YANG MENJELASKAN PREVALENSI ANAK PENGIDAP ISPA DI INDONESIA Pardomuan Robinson Sihombing
LOMBOK JOURNAL OF SCIENCE Vol 2 No 3 (2020): Lombok Journal of Science
Publisher : LOMBOK JOURNAL OF SCIENCE

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Abstract

Infeksi Saluran Pernafasan Akut (ISPA) merupakan jenis penyakit yang masih merupakan penyebab utama kesakitan dan kematian pada anak terutama di negara berkembang. Penelitian ini bertujuan untuk mengetahui faktor-faktor yang menjelaskan prevalensi anak pengidap ISPA di Indonesia. Metode yang digunakan adalah analisis regresi logistik biner yaitu metode untuk mendapatkan model terbaik dan sederhana untuk menjelaskan hubungan antara variabel respon dengan variabel-variabel prediktornya. Hasil penelitian menunjukkan bahwa faktor risiko terkait karekteristik rumah tangga yang meliputi ketersediaan ventilasi, tumpukan sampah di sekitar rumah, kandang ternak di sekitar rumah, letak dapur dan kamar dalam satu ruangan dan kebersihan rumah, dan perilaku kebiasaan merokok pada anggota keluarga dapat menjelaskan prevalensi anak pengidap ISPA di Indonesia.
Pemodelan Jumlah Kematian Bayi dengan Geographically Weighted Negative Binomial Regression Pardomuan Robinson Sihombing
LOMBOK JOURNAL OF SCIENCE Vol 3 No 2 (2021): Lombok Journal of Science
Publisher : LOMBOK JOURNAL OF SCIENCE

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Abstract

Penelitian ini bertujuan mengetahui pola ketergantungan spasial pada jumlah kematian bayi di Provinsi Sumatera Barat dengan model Geographically Weighted Negative Binomial Regression (GWNBR). Selain itu ingin memodelkan kasus kematian bayi untuk mengetahui faktor-faktor yang berpengaruh terhadap jumlah kematian bayi di Provinsi Sumatera Barat. Hasil penelitian ini memperlihatkan ada ketergantungan spasial antar kabupaten kota pada kasus kematian bayi di Sumatera Barat dimana terbentuk dua klaster. Klaster pertama yaitu Kabupatan Kep. Mentawai dimana hanya variabel persentase persalinan dengan bantuan tenaga non medis (dukun bayi) dan Jumlah tenaga medis dan kesehatan yang berpengaruh terhadap jumlah kematian bayi. Sedangkan pada kalster kedua adalah Kabupaten/Kota selain Kep.Mentawai. Pada klaster kedua variabe lpersentase persalinan dengan bantuan tenaga non medis (dukun bayi), jumlah tenaga medis dan kesehatan serta persentase penduduk miskin.berpengaruh signifikan terhadap jumlah kematian bayi.
Perbandingan Metode Analisis Gerombol K-Rataan Dan Bicluster Marta Sundari; Pardomuan Robinson Sihombing; Karel Fauzan Hakim
LOMBOK JOURNAL OF SCIENCE Vol 3 No 1 (2021): Lombok Journal of Science
Publisher : LOMBOK JOURNAL OF SCIENCE

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Abstract

Analisis gerombol merupakan suatu teknik yang bertujuan mengelompokkan objek-objek berdasarkan kemiripan karakteristik yang dimilikinya. Dua metode yang umum dalam algoritma gerombol adalah metode penggerombolan hierarki dan metode penggerombolan non hierarki. Salah satu penggunaan metode hirarki adalah menggunakan K-Rataan yang mengelompokkan terhadap satu dimensi. Analisis bicluster merupakan pegembangan dari metode hierarki dimana penggerombolan dilakukan untuk data dua arah atau dua dimensi. Penelitian ini membandingkan hasil pengelompokan menggunakan K-Rataan dengan Bicluster pada studi kasus data Kerentanan Kelurahan di Kota Depok Tahun 2020, dengan dua skema cluster yang terbentuk yaitu 5 dan 7 kluster. Dari kedua metode penggerombolan dengan dua skema yang digunakan, metode gerombol K-Rataan yang menghasilkan 5 gerombol dinilai lebih baik jika dibandingkan metode gerombol bicluster dengan kriteria yang sudah ditentukan.
Co-Authors Abdul Gofur Rochman Ade Famalika Ade Famalika Ade Marsinta Arsani Ade Marsinta Arsani Ade Marsinta Arsani Ade Marsinta Arsani Ade Marsinta Arsani Ade Marsinta Arsani Ade Marsinta Arsani Ade Marsinta Arsani Ade Marsinta Arsani Ade Marsinta Arsani Ade Marsinta Arsani Ade Marsinta Arsani Adina Astasia Ahid Nur Istinah Akhmad Mun'im Arsani, Ade Marsinta Artha Satwika Astawa, I Gede Putu Banu Avior Ocean Noya Bagus Sartono Bekti Endar Susilowati Bekti Endar Susilowati Bekti Endar Susilowati Bertho Tantular Bjardianto Pudjiono Budiantono, Sigit Bungkus Sasongko Purnomo Bungkus Sasongko Purnomo Busminoloan Busminoloan Cahya Alkahfi Deden Achmad Sunarjo Desak Ari Gita Wahyuni Deva A. Nurul Huda Dhinnessa Prabowo DRAJAT INDRA PURNAMA Drajat Indra Purnama Dwi Muslianti Dyah Purwanti Emilio Pascal Erica Indryani Fadlol Muhammad Fajar Faiza Aina Nurrizqi Feri Fernandes Fitri Mudia Sari Frisca Adriana HAMIDAH Hastoro Dwinantoaji Hema Malini, Hema Hendiva Tri Nugraha Hendry Frananda I Dewa Gede Sunanjaya I Gede Heprin Prayasta Ibnu Daqiqil Ida Ayu Candrawati Iis Hayyun Nurul Islam Ine Ratna Dewi Irma Nurmala Dewi Istiqomatul Fajriyah Yuliati Istiqomatul Fajriyah Yuliati Jaka Wijaya Kusuma Januar Ramadhan Karel Fauzan Hakim Krisdianto, Boby Febri Kuat Sidik Wahyono Lina Sari Lisna Sari Lisna Sari Luh Putu Widya Adnyani Mahuda, Isnaini Maisaroh Maisaroh Marta Sundari Marta Sundari Marta Sundari Masruri Mochtar Masruri Muchtar Masruri Muchtar Masruri Muchtar Masruri Muchtar Masruri Muchtar Masruri Muchtar Masruri Muchtar Maydita Ayu Nursaskiawati Mella Anisa Merdawati, Leni Miftakhul Jannah Mohamad Arif Kurniawan Mohamad Arif Kurniawan Muhammad Faiz El Haq Muhammad Hafiz Fadhilah Muhammad Ramadhan Zulfi Muliantino, Mulyanti Roberto Neni Nur Laili Ersela Zain Ni Kadek Sinarwati Ni Komang Semara Yanti Nurhidayati Nurhidayati Nurhidayati Nurhidayati Nurul Islam, Iis Hayyun Octaviana, Aniek Oki Prasetia Hendarsin Pradita Galih Sekar Palupi Puput Puspitorini Putri Indi Rahayu Putu Pande Wahyu Diatmika Rahayu, Putri Indi Rahmi Lathifah Islami Rahmi Lathifah Islami Rama Bhaskara Praja Rini Rahani Risqi Nurika Fatha Hidayati Saeful Hidayat Sarah Sholikhatun Risma Septie Wulandary Sigit Budiantono Sigit Budiantono Sigit Budiantono Sigit Budiantono Sigit Budiantoro Sinarta Putra P. Surbakti Sri Murdaningrum Sri Murtiningsih Suryadiningrat Suryadiningrat Suryadiningrat Taufik Febriyanto Temy Setiawan, Temy Triana Mauliasih Aritonang Triana Mauliasih Aritonang Usep Nugraha Wahyu Puji Lestari Widdia Angraini Wiradinata Lambok Silaban Wisnu Pratiko Y Yunita Yoshep Paulus Apri Caraka Yuda Yudhie Andriyana Yuninda Anggraini Putri Yunita Yunita Yunita Zain Yudha Prawira Zakir, Supratman