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All Journal Jurnal Ilmu Komputer Jurnal Ekonomi Kuantitatif Terapan Statistika Epsilon: Jurnal Matematika Murni dan Terapan CAUCHY: Jurnal Matematika Murni dan Aplikasi Bulletin of Electrical Engineering and Informatics Jurnal Sosioteknologi Jurnal Administrasi Kesehatan Indonesia Jurnal Akuntansi dan Perpajakan UNEJ e-Proceeding KEUNIS Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Ecodemica : Jurnal Ekonomi Manajemen dan Bisnis Perspektif : Jurnal Ekonomi dan Manajemen Universitas Bina Sarana Informatika Indonesian Journal of Applied Statistics International Humanities and Applied Science Journal Journal of Regional and Rural Development Planning MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Sosio e-kons Zero : Jurnal Sains, Matematika, dan Terapan KEUDA : JURNAL KAJIAN EKONOMI DAN KEUANGAN DAERAH Jurnal TAMBORA Journal Of Management Science (JMAS) ECOPLAN : JOURNAL OF ECONOMICS AND DEVELOPMENT STUDIES Jurnal Mantik Journal of Business and Applied Management TEKNOKOM : Jurnal Teknologi dan Rekayasa Sistem Komputer Jurnal Ilmiah Dinamika Sosial Bappenas Working Papers Jurnal Sosial Humaniora Sigli Jurnal Ekonomi Dan Bisnis Jurnal Educatio FKIP UNMA Jurnal Sistem Komputer & Kecerdasan Buatan Aksara: Jurnal Ilmu Pendidikan Nonformal PUBLIKASI PENELITIAN TERAPAN DAN KEBIJAKAN Alifmatika: Jurnal Pendidikan dan Pembelajaran Matematika Udayana Journal of Social Sciences and Humanities (UJoSSH) Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Jurnal Statistika dan Aplikasinya EPSILON Jurnal Pendidikan Matematika Jurnal Teknik Informatika (JUTIF) Jurnal Manajemen Publik dan Kebijakan Publik (JMPKP) Lombok Journal of Science Infinity Jurnal Matematika dan Aplikasinya (IJMA) Scientax: Jurnal Kajian Ilmiah Perpajakan Indonesia Jurnal Litbang Edusaintech Berdikari : Jurnal Ekonomi dan Statistik Indonesia Educoretax Journal of Law, Administration, and Social Science Jurnal Ilmu Ekonomi dan Sosial (JIES) Nusantara Journal of Behavioral and Social Science Jurnal Multidisiplin Madani (MUDIMA) Soshum: Jurnal Sosial dan Humaniora Jurnal Akuntansi dan Keuangan Indonesia Jurnalku Jurnal Manajemen dan Pemasaran Jasa Bandung Conference Series: Mathematics Khatulistiwa: Jurnal Pendidikan dan Sosial Humaniora Indonesia Auditing Research Journal Priviet Social Sciences Journal Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika Jurnal Ilmiah Kesehatan Pernus Buletin Ilmiah Litbang Perdagangan Advance Sustainable Science, Engineering and Technology (ASSET) Hasina: Jurnal Akuntansi dan Bisnis Syariah

Pardomuan Robinson Sihombing

BPS-Statistics Indonesia

Author-ID : 5437779

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 Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Perbandingan Metode Artificial Neural Network (ANN) dan Support Vector Machine (SVM) untuk Klasifikasi Kinerja Perusahaan Daerah Air Minum (PDAM) di Indonesia Pardomuan Robinson Sihombing
Jurnal Ilmu Komputer Vol 13 No 1 (2020): Jurnal Ilmu Komputer
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Indikator kinerja Perusahan Daerah Air Minum (PDAM) dapat diartikan sebagai suatu ukuran yang dapat digunakan untuk memberikan gambaran tingkat keberhasilan kegiatan pengelolaan PDAM. Tingkat keberhasilan pengelolaan PDAM ini diukur melalui proses penilaian terhadap kinerja PDAM yang didasarkan pada indikator kinerja penyelenggaraan pengembangan SPAM meliputi: aspek keuangan, operasional, pelayanan pelanggan dan sumber daya manusia sesuai dengan ketentuan di dalam Pasal 59 Permen PU No. 18/PRT/M/2007. Berdasarkan aspek dan indikator diatas, PDAM dapat memprediksikan kinerja mereka untuk tahun berjalan. Namun butuh banyak indikator perhitungannya cenderung rumit dan memerlukan audit internal PDAM terlebih dahulu yang mana membutuhkan waktu banyak. Dalam penelitian ini bertujuan membuat model dari algoritma Artificial Neural Network (ANN) dan Support Vector Machine (SVM) untuk mengklasifikasikan kinerja PDAM berdasarkan indikator terpilih. Hasil penelitian perusahaan dapat menggunakan model klasifikasi ANN untuk memprediksi kinerja perusahaan di tahun berjalan dengan menggunakan 3 atribut yaitu Rasio Operasi, Jam Operasi Layanan/hari, dan Rasio Jumlah Pegawai/1000 pelanggan dengan tingkat akurasi keseluruhan 80.00% dan tingkat presisi prediksi untuk kinerja Tidak Sehat sebesar 86.36%.

Metode ROBPCA (Robust Principal Component Analysis) dan Clara (Clustering Large Area) pada Data dengan Outlier Bekti Endar Susilowati; Pardomuan Robinson Sihombing
Jurnal Ilmu Komputer Vol 13 No 2 (2020): Jurnal Ilmu Komputer
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIK.2020.v13.i02.p04

Principal Component Analysis (PCA) merupakan salah satu analisis multivariat yang digunakan untuk mengganti variable dengan Principal Component yang sedikit jumlahnya namun tidak terlalu banyak informasi yang hilang. Atau dengan kata lain, it used to explain the underlying variance-covariance structure of the large data set of variables through a few linear combination of these variables. PCA sangat dipengaruhi oleh kehadiran outlier karena didasarkan pada matriks kovarian yang sensitive terhadap outlier. Oleh karena itu, pada analisis ini akan digunakan PCA yang robust terhadap outlier yaitu ROBPCA atau PCA Hubert. Selanjutnya, dari Principal Component yang terbentuk digunakan sebagai input (masukan) untuk cluster analysis dengan metode Clara (Clustering Large Area). Clustering Large Area merupakan salah satu metode k-medoids yang robust terhadap outlier dan baik digunakan pada data dalam jumlah besar. Dalam studi kasus terhadap variabel penyusun indeks kebahagiaan berdasarkan The World Happiness Report 2018 dengan metode Clara yang menggunakan jarak manhattan didapatkan nilai rata-rata Overall Average Silhouette Width yang terbaik pada 5 cluster.

KNOWLEDGE, ATTITUDES AND PRACTICES RELATED TO PREVENTING THE TRANSMISSION OF COVID 19 AMONG SOCIAL MEDIA USERS IN INDONESIA Boby Febri Krisdianto; Leni Merdawati; Mulyanti Roberto Muliantino; Hema Malini; Feri Fernandes; Hastoro Dwinantoaji; Januar Ramadhan; Taufik Febriyanto; Pardomuan Robinson Sihombing
UNEJ e-Proceeding 2020: Proceeding of The 4th International AgroNursing Conference
Publisher : UPT Penerbitan Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar

Background: Several countries have implemented health protocols in order to prevent the spread of covid-19. One of the promotional media used by the government is social media. The effectiveness of this prevention is very much dependent on community cooperation. Knowledge, attitudes and practices of the community in preventing Covid 19 have an important role in the new normal era. Purpose The purpose of this study is to describe the trust of the Indonesian people to information on the prevention of Covid 19 on social media and public knowledge, attitudes and practices regarding prevention of the spread of COVID-19. Methods This research is a cross sectional online survey. The survey instrument consisted of respondent characteristics consisting of 5 demographic characteristics items and 5 social media use characteristics items, 13 items of trust in social media, 18 items of knowledge, 6 items of attitude and 12 items of practice. The research, which was conducted from 1 September 2020 to 25 September 2020, received 1129 responses. The questionnaire items were modified from the published paper. This research was tested statistically descriptively. Results: Most of the Indonesian people have high trust in Covid 19 prevention information on social media (mean 2.56 and standard deviation 0.55), good knowledge (mean 2.78 with standard deviation 0.60), good affective (mean 2.58 with standard deviation 0.70), good practices (mean 2.42 with a standard deviation of 0.70) regarding Covid-19 prevention. The social media trend chosen by the Indonesian people is Instagram (33.2%) Conclusion. The findings reported in this study are important because they are useful for increasing awareness of institutional and government leaders about the trust in information on social media, knowledge, attitudes, and practices of the prevention of COVID-19 in the Indonesian community. Keywords: Social media; Trustworthiness; COVID-19; Knowledge; Attitude; Practice

Klasifikasi Status Bekerja Individu di Provinsi Banten Tahun 2020 dengan Menggunakan Metode LASSO dan Adaptive LASSO Pardomuan Robinson Sihombing; Khairil Anwar Notodiputro; Bagus Sartono
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 21, No 1 (2021)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v21i1.7810

Penelitian ini bertujuan membandingkan metode LASSO dan Adaptive LASSO dengan penggunaan imbalanced data pada regresi binary logistik. Studi kasus yang digunakan adalah pemodelan klasifikasi status bekerja individu di Provinsi Banten tahun 2020. Hasil yang didapat performa LASSO maupun Adaptive LASSO memberikan hasil yang sama baiknya. Dengan mempertimbangkan berbagai kriteria performa dalam accuracy, sensitivity dan specificity, maka model terbaik adalah model LASSO dengan simulasi data balanced 60 persen dan 40 persen dengan nilai masing-masing sebesar 79,16 persen; 80.29 persen dan 68,75 persen. Terdapat beberapa paradoks/anomali dalam hasil penelitian di antaranya peluang status tidak bekerja seseorang menurut lokasi tempat tinggal, gender dan pendidikan. Status disabilitas masih menjadi masalah dalam mencari pekerjaan. Semakin banyak anggota rumah tangga maka akan semakin tinggi peluangnya berstatus tidak bekerja. Semakin tinggi usia seseorang maka akan semakin kecil peluangnya berstatus tidak bekerja. Peluang status tidak bekerja seseorang yang menikah lebih kecil daripada yang belum/tidak kawin

Comparison Of Normal-Based and Beta-Based Regression Models on Ratio/ Proportion Data Pardomuan Robinson Sihombing
Jurnal Ekonomi Dan Statistik Indonesia Vol 2 No 1 (2022): Berdikari: Jurnal Ekonomi dan Statistik Indonesia (JESI)
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/jesi.02.01.03

This study compares the regression using the assumption of a normal distribution with a beta distribution on ratio/proportion data. The data used is the Gini ratio data as the dependent variable and the percentage of the poor, economic growth and unemployment as independent variables in 2021. The data used is sourced from the Central Statistics Agency. The criteria for selecting the best model are based on the smallest AIC and BIC criteria. The results obtained by the beta regression model are better than the model based on the normal distribution. This result is reflected by the probability value of the model suitability test and the error value which the smaller AIC and BIC reflect. The poverty variable has a significant effect on the Gini ratio. On the other hand, there is not enough evidence that the variables of economic growth and open unemployment affect the Gini ratio. From the results obtained, it is hoped that the government will be able to implement appropriate policies in overcoming inequality so that every level of society can feel welfare without exception.

HOW MACHINE LEARNING METHOD PERFORMANCE FOR IMBALANCED DATA : Case Study: Classification of Working Status of Banten Province Pardomuan Robinson Sihombing
TEKNOKOM Vol. 4 No. 2 (2021): TEKNOKOM
Publisher : Department of Computer Engineering, Universitas Wiralodra

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.

PEMODELAN MATEMATIKA TERHADAP PENYEBARAN VIRUS KOMPUTER DENGAN PROBABILITAS KEKEBALAN Neni Nur Laili Ersela Zain; Pardomuan Robinson Sihombing
Alifmatika (Jurnal pendidikan dan pembelajaran Matematika) Vol 3 No 2 (2021): Alifmatika - December
Publisher : Fakultas Tarbiyah Universitas Ibrahimy

The increase in the number of computer viruses can be modeled with a mathematical model of the spread of SEIR type of diseases with immunity probability. This study aims to model the pattern of the spread of computer viruses. The method used in this research is the analytical method with the probability of mathematical immunity. Based on the analysis of the model, two equilibrium points free from disease E1 and endemic equilibrium points E2 were obtained. The existence and local stability of the equilibrium point depends on the basic reproduction number R0. Equilibrium points E1 and E2 tend to be locally stable because R0<1 which means there is no spread of disease. While the numerical simulation results shown that the size of the probability of immunity will affect compartment R and the minimum size of a new computer and the spread of computer viruses will affect compartments S and E on the graph of the simulation results. The conclusion obtained by the immune model SEIR successfully shows that increasing the probability of immunity significantly affects the increase in the number of computer hygiene after being exposed to a virus.

Does the Gap Between East and West Still Exist? a Study of Indonesia’s Disparities Pardomuan Robinson Sihombing
Udayana Journal of Social Sciences and Humanities Vol 3 No 1 (2019): UJoSSH, Feburary 2019
Publisher : Research and Community Services Institutes of Udayana University

Indonesia is a large country with many classical problems. One of the problems still faced by Indonesia is the disparity between Western Indonesia and Eastern Indonesia. Western Indonesia is synonymous with developed and prosperous regions, while East Indonesia is identical to the developing region, the area that left behind. The Indonesian government is implementing various programs to reduce disparities between the two regions. This study aims to map the most striking aspects of the disparity between Western and Eastern Indonesia using discriminant analysis. The variables used are poverty, gini ratio, unemployment, HDI, GEI, GDI, economic growth, sanitation access, and IDI. The results showed that the most distinguishing aspects of the two regions were poverty, unemployment, GDI, and access to sanitation. Thus, it is expected that the policies implemented by the government can prioritize these issues to accelerate equity throughout Indonesia.

The Application Of Autoregressive Integrated Moving Average Generalized Autoregressive Conditional Heteroscedastic (Arima - Garch) Pardomuan Robinson Sihombing; Oki Prasetia Hendarsin; Sarah Sholikhatun Risma; Bekti Endar Susilowati
Udayana Journal of Social Sciences and Humanities Vol 4 No 2 (2020): UJoSSH, September 2020
Publisher : Research and Community Services Institutes of Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/UJoSSH.2020.v04.i02.p04

Rice farming for Indonesia is vital. Rice farming is inseparable from the fact that rice farming is the livelihood of most of the population, while rice is the staple food of almost all Indonesians. The nature of rice that is easy to process and, following the public consumption culture, causes a very high dependence on rice. On the other hand, the price of rice is quite volatile. If the price of rice is soaring high, it can cause changes in the pattern of rice consumption. Some people want a stable supply and rice price, available at all times and evenly distributed and at affordable prices. Because the cost of rice is quite fluctuating, it is necessary to have a model that can be used to predict future rice prices so that the right policies can be implemented. Autoregressive Integrated Moving Average Model Generalized Autoregressive Conditional Heteroscedastic (ARIMA-GARCH) is a useful model for evaluating and predicting price fluctuations. This model's application is implemented in the national average retail rice price data between January 2007 and December 2017. In this study, rice data in the study period was not stationary at the level so that differentiating was carried out in the data. The best model is ARIMA (1,1,2) and Garch model (2,0). In this model, the data has complied with the white noise assumption, and the resulting GARCH model is free from the heteroscedasticity assumption.

PEMODELAN DATA KEMISKINAN PROVINSI SUMATERA BARAT MENGGUNAKAN REGRESI SPASIAL Pardomuan Robinson Sihombing; Fitri Mudia Sari; Hendry Frananda Nasution
Infinity: Jurnal Matematika dan Aplikasinya Vol. 2 No. 1 (2021): Terbitan Ketiga-Agustus 2021
Publisher : Program Studi Matematika Fakultas Sains Universitas Cokroaminoto Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30605/27458326-66

Kemiskinan merupakan suatu masalah yang menjadi perhatian di setiap negara. Permasalahan kemiskinan di suatu daerah tidak hanya dipengaruhi oleh faktor-faktor kemiskinan di daerah tersebut, tetapi juga dapat dipengaruhi oleh kemiskinan di daerah lain sehingga kasus kemiskinan dapat dikaji dengan analisis spasial. Model spasial yang dapat digunakan untuk permasalahan ini adalah regresi spasial, diantaranya yaitu model autoregresif spasial dan model galat spasial. Tujuan dari penelitian ini adalah menentukan faktor-faktor yang mempengaruhi kemiskinan di Provinsi Sumatera Barat dengan menggunakan regresi spasial. Hasil penelitian menunjukkan model terbaik adalah model SAR dan faktor-faktor yang mempengaruhi yaitu persentase rumah tangga penduduk dengan sanitasi layak dan persentase penduduk dengan air bersih dan kemiskinan kabupaten/kota di sekitarnya.

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 Adina Astasia Ahid Nur Istinah Ahmaddien, Iskandar Aji, Lexi Jalu Al Aqilah, Muhamad Refkhi Amin Prawiro Madhani Anang Kurnia Anita, Tiurida Lily 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 Bungkus Sasongko Purnomo Bungkus Sasongko Purnomo Busminoloan Busminoloan Cahya Alkahfi Daqiqil Id, Ibnu Deden Achmad Sunarjo Desak Ari Gita Wahyuni Deva A. Nurul Huda Devitama Patria Nagara Dhinnessa Prabowo Drajat Indra Purnama DRAJAT INDRA PURNAMA Dwi Muslianti Dyah Purwanti Ekowati Retnaningsih Erfiani Erfiani Erfiani Erfiani, Erfiani Erica Indryani Fadlol Muhammad Fajar Faiza Aina Nurrizqi Feri Fernandes Fitri Mudia Sari Frisca Adriana Gregorius Ivan Aditya Purwahendra Gultom, Yulifar Amin Gunawan, Ghina Hanifa HAMIDAH Hastoro Dwinantoaji Hema Malini, Hema Hendiva Tri Nugraha Hendry Frananda, Hendry Herman, Nur Ashilah Raihanah I Dewa Gede Sunanjaya I Gede Heprin Prayasta I Gede Heprin Prayasta Ida Ayu Candrawati 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 Kartika Maulidya Irzain Khairil Anwar Notodiputro Krisdianto, Boby Febri Kuat Sidik Wahyono Kurnia, Anang Leni Merdawati Lina Sari Lisna Sari Lisna Sari Luh Putu Widya Adnyani Mahuda, Isnaini Marta Sundari Marta Sundari Maryani, Sri Masruri Mochtar Maydita Ayu Nursaskiawati Mella Anisa Miftahul Huda Miftakhul Jannah Mohamad Arif Kurniawan Mohamad Arif Kurniawan Muchtar, Masruri Muhammad Hafiz Fadhilah Muhammad Heru Akhmadi Muhammad Ramadhan Zulfi Muliantino, Mulyanti Roberto Mun'im, Akhmad Neni Nur Laili Ersela Zain Ng, Kah Choon Ni Kadek Sinarwati Novitha, Irni Nurhidayati Nurhidayati Nurhidayati Nurhidayati Nuryanto Nuryanto Oki Prasetia Hendarsin Padhilah Dikri Pascal, Emilio Pradita Galih Sekar Palupi Puput Puspito Rini Putri Indi Rahayu Putu Pande Wahyu Diatmika Rahayu, Putri Indi Rahmi Lathifah Islami Rama Bhaskara Praja Ramadhisa Fadli, Diva Aisyaliani Rini Rahani Risqi Nurika Fatha Hidayati Saeful Hidayat Sarah Sholikhatun Risma Septie Wulandary Sigit Budiantono Sigit Budiantono Sigit Budiantono Sigit Budiantono Sigit Budiantono Sinarta Putra P. Surbakti Sodiqin, Achmad Sri Murdaningrum Stephanus, Matthew Supriatna, Yayat Suryadiningrat Suryadiningrat Suryadiningrat Taufik Febriyanto Temy Setiawan, Temy Triana Mauliasih Aritonang Triana Mauliasih Aritonang Ulfa Anggraini Usep Nugraha Wahyu Puji Lestari Widdia Angraini Wijaya, Lianna Wiradinata Lambok Silaban Wiranegara, Hanny Wahidin Wisnu Pratiko Y Yunita Yanti, Ni Komang Semara Yesi, Desri Yoshep Paulus Apri Caraka Yuda Yudhie Andriyana Yuninda Anggraini Putri Yunita Yunita Yunita Zain Yudha Prawira Zakir, Supratman

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