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All Journal Jurnal Ilmu Komputer dan Informasi Jurnal Matematika Media Statistika Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Paediatrica Indonesiana BAREKENG: Jurnal Ilmu Matematika dan Terapan Economics and Finance in Indonesia Jurnal Aplikasi Statistika & Komputasi Statistik Indonesian of Health Information Management Journal (INOHIM) Journal of Data Science and Its Applications Jurnal Kepariwisataan Indonesia: Jurnal Penelitian dan Pengembangan Kepariwisataan Indonesia The Journal of Indonesia Sustainable Development Planning (JISDeP) Jambura Journal of Biomathematics (JJBM) Jurnal Ekonomi Indonesia Narra J Indonesian Journal of Tourism and Leisure Jurnal Ketenagakerjaan Proceedings of International Conference on Multidiciplinary Research Enthusiastic : International Journal of Applied Statistics and Data Science JUSTIN (Jurnal Sistem dan Teknologi Informasi) International Journal Of Computer, Network Security and Information System (IJCONSIST) Prosiding Seminar Nasional Official Statistics PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Economic and Finance in Indonesia Indonesian Journal of Statistics and Its Applications

Pramana, Setia

Politeknik Statistika STIS

Author-ID : 803201

Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Immunology & microbiology Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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Development of Website-Based a Health Crisis Reporting System Rimadeni, Yeni; Sofyan, Hizir; Rahman, Safrizal; Pramana, Setia; Oktari, Rina S.
International Conference on Multidisciplinary Research Vol 4, No 1 (2021): ICMR
Publisher : Universitas Serambi Mekkah

Health crisis management is prioritized on health crisis risk reduction consisting of pre-health crisis stage, health crisis emergency response stage, and post-health crisis stage. Prevention and mitigation efforts at the pre-health crisis stage, in the context of our study, aim to develop an information system for health crisis management. Information system for health crisis, in general, is provided by the Health Agency. In this study, we discussed the system applied by the Health Agency of Aceh Tengah that still uses a manual information system for reporting during disasters. Hence, it causes a delay of the information updates despite the emergency situation. To overcome this problem, we proposed a newly developed health crisis management reporting system in disaster risk reduction. We used a Research and Development approach with Heuristic Review Analysis to assess the performance of the proposed system. The scope of the study was limited to the development of a new reporting system and system test on users. The research subjects were disaster officers and heads of 14 health centers involved in the health crisis reporting in Aceh Tengah. Improvements can be made in the future through trainings and system adjustments supported by institutional policies. Keywords: Health crisis, disasters, website, reporting system.

Improvement Method of Fuzzy Geographically Weighted Clustering using Gravitational Search Algorithm Setia Pramana; Imam Habib Pamungkas
Jurnal Ilmu Komputer dan Informasi Vol 11, No 1 (2018): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information
Publisher : Faculty of Computer Science - Universitas Indonesia

Geo-demographic analysis (GDA) is a useful method to analyze information based on location, utilizing several spatial analysis explicitly. One of the most efficient and commonly used method is Fuzzy Geographically Weighted Clustering (FGWC). However, it has a limitation in obtaining local optimal solution in the centroid initialization. A novel approach integrating Gravitational Search Algorithm (GSA) with FGWC is proposed to obtain global optimal solution leading to better cluster quality. Several cluster validity indexes are used to compare the proposed methods with the FGWC using other optimization approaches. The study shows that the hybrid method FGWC-GSA provides better cluster quality. Furthermore, the method has been implemented in R package spatialClust.

Pemanfaatan Big Data dalam Monitoring Pola Aktivitas Aviasi di Indonesia Nasiya Alifah Utami; Thosan Girisona Suganda; Setia Pramana
Jurnal Matematika Vol 11 No 2 (2021)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2021.v11.i02.p140

Abstract: Covid-19 which entered Indonesia in December 2019 has a significant impact on the aviation industry. According to BPS data for 2020, the aviation industry's contribution to Indonesia's GDP decreased from 1.21% to 0.28% in the second quarter of 2020. To overcome this setback, comprehensive monitoring by policy makers is needed. The use of big data in monitoring aviation industry activities can be an option. This study aims to analyze aviation activities using big data approach for monitoring basis. The data was collected by using web scraping method on one of the global aviation websites to obtain flight status data at 108 airports in Indonesia on April 2020 until June 2021. Other data used are google mobility index data, GDP data, and TPK. The analysis method used are descriptive analysis, correlation analysis and machine learning based time series modelling with ARNN, single layer ANN and MLP. The results show that the policy of restricting mobility has a significant effect on the productivity of aviation industry. Machine learning modeling shows that the MLP model is the best model for forecasting international aviation activity. In addition, it was found that the aviation industry has a strong correlation with the economy and tourism sector in Indonesia.

Ensemble Based Gustafson Kessel Fuzzy Clustering Achmad Fauzi Bagus Firmansyah; Setia Pramana
Journal of Data Science and Its Applications Vol 1 No 1 (2018): Journal of Data Science and Its Applications
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/jdsa.2018.1.6

Fuzzy clustering is a clustering method whcih allows an object to belong to two or more cluster by combining hard-clustering and fuzzy membership matrix. Two popular algorithms used in fuzzy clustering are Fuzzy C-Means (FCM) and Gustafson Kessel (GK). The FCM use Euclideans distance for determining cluster membership, while GK use Fuzzy Covariance Matrix that considering covariance between variables. Although GK perform better, it has some drawbacks on handling linearly correlated data, and as FCM the algorithm produce unstable result due to random initialization. These drawbacks can be overcame by using improved covariance estimation and cluster ensemble, respectively. This research presents the implementation of improved covariance estimation and cluster ensemble on GK method and compare it with FCM-Ensemble.

Forecasting Number of Passengers of TransJakarta using Seasonal ARIMAX Method Maftukhatul Qomariyah Virati; Diory Paulus Pamanik; Setia Pramana
Journal of Data Science and Its Applications Vol 3 No 1 (2020): Journal of Data Science and Its Applications
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/jdsa.2020.3.45

TransJakarta is one of the most common public transportation modes used by the public in Jakarta. Every day there are more than 300.000 people who use TransJakarta . The number of TransJakarta buses is still limited, so to optimize services, we should know when the number of users in peak time and when the number of users in low time. In addition to providing comfort to customers, maintenance for TransJakarta buses can also be optimized, thereby reducing incident and unwanted events. This study investigates the pattern of the number of TransJakarta passengers differs on weekends, weekdays, and holidays. Also, this study predict how many TransJakarta passengers in the future, by using SARIMAX method, which is SARIMA method with X - factor. In the implementation, the study is conducted using R application with the addition of x-factor in the form of dummy variable for tap-in data in holiday period.The predicted result being produced is not too far away with the actual figure with the best model is SARIMA(0,0,0)(2,1,0)[7] with x-factor and the error analys is MSE = 162402173, MAPE = 2.6122 and MASE = 0.211698.

Analysis of Indonesian People's Sentiments About the Side Effects of the COVID-19 Vaccine on Twitter Fajar Fatur Rachman; Setia Pramana
Journal of Data Science and Its Applications Vol 4 No 1 (2021): Journal of Data Science and Its Applications
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/jdsa.2021.4.73

The large number of people who refuse to get vaccines is one of the biggest challenges for the Indonesian government in dealing with the COVID-19 pandemic. Widespread misinformation and hoaxes about COVID-19 vaccines has made the level of public trust decreases. This paper was written to see how the public's opinion on the side effects of the three COVID-19 vaccines that have been spreading in Indonesia, among them are Sinovac, Astra Zeneca and Moderna. There will be a sentiment analysis and grouping of public conversations on Twitter with LDA regarding the side effects of the three vaccines. From the results obtained, it is expected to be a reference for the government or related parties in order to validate the issues that circulated among the society regarding the side effects of the COVID-19 vaccine. From the results of the analysis, it was found that in the Sinovac vaccine type, people tend to state that the side effects felt are quite mild, dominated by the words sleepy, achy & hungry. While for the Astra Zeneca & Moderna vaccine, people tend to state that the side effects are quite severe, such as fever, pain, and dizziness. The results of the analysis also found that the Astra Zeneca vaccine was the type of vaccine that received the most negative opinions from the public.

Multilevel survival analysis for under-fives in Indonesia 2015 Linta Ifada; Mieke Nurmalasari; Setia Pramana
Paediatrica Indonesiana Vol 60 No 2 (2020): March 2020
Publisher : Indonesian Pediatric Society

Background Marking the end of the Millennium Development Goals (MDGs) era, governments continue their plans via the Sustainable Development Goals (SDGs). One of the MDGs that has continued is the reduction in under-five mortality. Even though the trend of under-five mortality in Indonesia is decreasing, more efforts are needed to reduce the under-five mortality rate. Objective To determine the individual and contextual factors of the under-five survival rate and to assess for possible characteristics that may lead to variance among regencies in Indonesia. Methods Data from 2015 Intercensal Population Survey (Survei Penduduk Antar Sensus/SUPAS 2015) in Indonesia were analyzed using multilevel survival analysis. The Intercensal Population Survey covers all regions in Indonesia up to the regency level. Data were collected by direct interviews of selected household members, with regards to demographic and household characteristics, including births and deaths of under-fives. Our sample population was limited to all under-fives who were born and died during the 2010-2015 period. The number of subjects analyzed was 219,413 after exclusion of children with incomplete data. Results Individual factors associated with under-five survival rate were maternal education, maternal age at first birth, work status, sex, previous birth interval, type of birth, place of residence, and sanitation level. The contextual factor (health care facility ratio per 1000 under-fives per regency) was not associated with under-five survival rate. The 5.27% variance can be explained by the differing characteristics among regencies. Conclusion The individual factors affecting the survival of under-fives are maternal education, maternal age at first birth, maternal work status, sex, previous birth interval, type of birth, place of residence, and sanitation level.

Mobility Pattern Changes in Indonesia in Response to COVID-19 Setia Pramana; Yuniarti Yuniarti; Dede Yoga Paramartha; Satria Bagus Panuntun
Economics and Finance in Indonesia Volume 67, Number 1, June 2021
Publisher : Institute for Economic and Social Research

All countries affected by the COVID-19 pandemic have established several policies to control the spread of the disease. The government of Indonesia has enforced a work-from-home policy and large-scale social restrictions in most regions that result in the changes in community mobility in various categories of places. This study aims to (1) investigate the impact of large-scale restrictions on provincial-level mobility in Indonesia, (2) categorize provinces based on mobility patterns, and (3) investigate regional socio-economic characteristics that may lead to different mobility patterns. This study utilized Provincial-level Google Mobility Index, Flight data scraped from daily web, and regional characteristics (e.g., poverty rate, percentages of informal workers). A Dynamic Time Warping method was employed to investigate the clusters of mobility. The study shows an intense trade-off of mobility pattern between residential areas and public areas. In general, during the first 2.5 months of the pandemic, people had reduced their activities in public areas and preferred to stay at home. Meanwhile, provinces have different mobility patterns from each other during the period of the large-scale restrictions. The differences in mobility are mainly led by the percentage of formal workers in each region.

Analisis Perkembangan Kasus COVID-19 Berkaitan dengan Kebijakan Pemerintah di Pulau Jawa Charvia Ismi Zahrani; Setia Pramana
Indonesian of Health Information Management Journal (INOHIM) Vol 9, No 1 (2021): INOHIM
Publisher : Lembaga Penerbitan Universitas Esa Unggul

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47007/inohim.v9i1.224

AbstractCOVID-19 is a serious problem that faced by almost all countries in the world. Since announced as a pandemic by WHO on March, the number of positive COVID-19 cases in Indonesia has reached 287,008 patients until the end of September 2020. COVID-19 cases dispersion depends on the local government policies and the awareness of the public to obey. About 60 percent of positive cases and 65 percent of death cases were in Java. Therefore, the aim of this study is to analyze the growth of the COVID-19 case in Java from March to September 2020 in relation to the local government policies. The results showed that six provinces in Java had the same pattern. The large-scale social restriction (PSBB), which was implemented since April 10 2020, seen to be able to contain the dispersion of cases because from April to June the positive cases did not increase significantly. A very high increase occurred in August and September, this was probably due to the easing of the PSBB become new-normal where various public places and facilities have been reopened. Meanwhile, death cases, the number is very high in mid-April and June and late July to September 2020. For cured cases, there was a significant increase in late August to September 2020. The importance of information about the growth of the COVID-19 cases can help government to formulate strategies and policies to prevent the dispersion of COVID-19.Keyword: COVID-19, Pandemic, Java, cases growth AbstrakCOVID-19 merupakan suatu masalah serius yang sedang dihadapi oleh hampir seluruh negara. Sejak diumumkan sebagai pandemi oleh WHO pada Maret lalu, jumlah kasus positif COVID-19 di Indonesia mencapai 287.008 pasien hingga akhir September. Penyebaran kasus COVID-19 sangat bergantung pada kebijakan yang ditetapkan oleh pemerintah serta kesadaran masyarakat untuk mematuhinya. Sebesar 60 persen kasus positif dan 65 persen kasus meninggal berada di Pulau Jawa. Oleh karena itu, tujuan penelitian ini adalah menganalisis perkembangan kasus COVID-19 di Pulau Jawa sejak Bulan Maret-September 2020 dikaitkan dengan kebijakan pemerintah setempat. Hasil penelitian menunjukkan bahwa keenam provinsi memiliki pola yang sama. Pembatasan Sosial Berskala Besar (PSBB) yang dilakukan sejak 10 April 2020 terlihat dapat menahan penyebaran kasus karena pada bulan April-Juni 2020 kasus positif tidak mengalami kenaikan yang signifikan. Kenaikan yang sangat tinggi terjadi pada bulan Agustus dan September 2020, hal ini mungkin disebabkan oleh dilonggarkannya kebijakan PSBB menjadi PSBB Transisi dimana berbagai tempat dan fasilitas umum telah dibuka kembali. Sementara untuk kasus meninggal, angka tertinggi terjadi pada pertengahan April dan Juni serta akhir Juli hingga September 2020. Untuk kasus sembuh, terjadi peningkatan yang signifikan pada akhir Agustus hingga September 2020. Pentingnya informasi tentang perkembangan kasus COVID-19 ini dapat membantu pemerintah daerah untuk membuat strategi dan kebijakan untuk mencegah penyebaran rantai virus COVID-19.Kata Kunci: COVID-19, Pandemi, Jawa, perkembangan kasus

Analisis Sentimen Pro dan Kontra Masyarakat Indonesia tentang Vaksin COVID-19 pada Media Sosial Twitter Fajar Fathur Rachman; Setia Pramana
Indonesian of Health Information Management Journal (INOHIM) Vol 8, No 2 (2020): INOHIM
Publisher : Lembaga Penerbitan Universitas Esa Unggul

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47007/inohim.v8i2.223

AbstractIn order to accelerate the handling of the spread of COVID-19 in Indonesia, the Government of the Republic of Indonesia has issued a discourse on vaccination for the Indonesian people at the end of 2020. Although the government has not officially released the schedule or procedure for the vaccinations, the discourse is considered controversial so that it has invited many groups of people to give their opinions in various media. This opinion must be considered as material for evaluation so that the vaccination discourse that will be carried out can run well. By utilizing data from social media twitter, this study aims to analyze the public's response to the vaccination discourse by classifying these responses into positive and negative responses. Furthermore, there will also be grouping of public opinion using the Latent Dirichlet Allocation (LDA) method to find out what topics of conversation are often discussed by the community regarding the vaccination discourse. The results of the analysis show that the public gives more positive responses to the discourse (30%) than the negative responses (26%). The words with the most frequent appearances also indicate that there are more words with a positive sentiment than the words with a negative sentiment. The LDA model that was built can also capture the topics discussed by the community regarding the vaccination discourse, such as public talks about vaccine controversies which are considered hasty, halal certification of vaccines and public doubts about the quality of the vaccine to be used.Keyword: COVID-19, Latent Dirichlet Allocation (LDA), sentiment analysis, twitter, vaccineAbstrakDalam rangka melakukan percepatan penanganan penyebaran COVID-19 di Indonesia, Pemerintah Republik Indonesia telah mengeluarkan wacana vaksinasi untuk masyarakat Indonesia pada akhir tahun 2020 mendatang. Meskipun pemerintah belum secara resmi merilis jadwal maupun prosedur vaksinasi yang akan dilakukan, wacana tersebut dinilai kontroversial sehingga mengundang banyak kalangan untuk memberikan pendapatnya di berbagai media. Pendapat tersebut haruslah dipertimbangkan sebagai bahan evaluasi sehingga rencana vaksinasi yang akan dilakukan dapat berjalan dengan baik. Dengan memanfaatkan data dari media sosial twitter, penelitian ini bertujuan untuk menganalisis respon masyarakat terhadap wacana vaksinasi dengan cara mengklasifikasikan respon tersebut ke dalam respon positif dan negatif. Selanjutnya juga akan dilakukan pengelompokkan opini masyarakat menggunakan metode Latent Dirichlet Allocation (LDA) untuk mengetahui topik pembicaraan yang sering dibahas oleh masyarakat terkait dengan wacana vaksinasi tersebut. Hasil analisis menunjukkan bahwa masyarakat lebih banyak memberikan respon positif terhadap wacana tersebut (30%) dibandingkan dengan respon negatifnya (26%). Kata-kata bersentimen yang paling sering muncul juga mengindikasikan lebih banyak kata yang bersentimen positif dibandingkan dengan kata yang bersentimen negatif. Model LDA yang dibangun juga dapat menangkap topik yang dibicarakan masyarakat terkait wacana vaksinasi tersebut seperti pembicaraan masyarakat mengenai kontroversi vaksin yang dinilai terburu-buru, sertifikasi halal vaksin dan keraguan masyarakat terhadap kualitas vaksin yang akan digunakan.Kata Kunci: COVID-19, vaksin, analisis sentimen, Latent Dirichlet Allocation, twitter

Co-Authors Achmad Fauzi Bagus Firmansyah Addin Maulana Aditama, Farhan Satria Alifatri, La Ode Ana Lailatul Fitriyani Ana Lailatul Fitriyani Anang Kurnia Arie Wahyu Wijayanto Arif Handoyo Marsuhandi Arkandana, M. Tharif Astrinariswari Rahmadian Prasetyo Astuti, Erni Tri Busaina, Ladisa Cahyono, Bintang Dwitya Charvia Ismi Zahrani Cholifa Fitri Annisa Dandy Adetiar Al Rizki Dede Yoga Paramartha Dede Yoga Paramartha Deli, Nensi Fitria Dewi Krismawati Dewi Krismawati Dhiar Niken Larasati Diory Paulus Pamanik Erni Tri Astuti Erwin Tanur Fajar Fathur Rachman Fajar Fatur Rachman Farakh Khoirotun Nasida Farhan Y. Hidayat Fitriyani, Ana Lailatul Fitriyyah, Nur Retno Geri Yesa Ermawan Hady Suryono Hanafi, Zulfaning Tyas Hardiyanta, I Komang Y. Hendrawan, Daffa Hidayat, Farhan Y. Hizir Sofyan I Komang Y. Hardiyanta I Nyoman Setiawan Imam Habib Pamungkas Jane, Giani Jovita Khairani, Fitri Krismawati, Dewi Ladisa Busaina Linta Ifada Linta Ifada Maftukhatul Qomariyah Virati Magfirah, Deanty Fatihatul Mariel, Wahyu Calvin Frans Maulana Faris Muhammad Farhan Muhammad Nur Aidi Muhammad Tharif Arkandana Munaf, Alfatihah Reno Maulani Nuryaningsih Soekri Putri Nasiya Alifah Utami Nazuli, Muhammad Fachry Nensi Fitria Deli Nora Dzulvawan Novandra, Rio Nur Retno Fitriyyah Nurmalasari, Mieke Nurtia Nurtia Nurwijayanti Oktari, Rina S. Panuntun, Satria Bagus Paramartha, Dede Yoga Putro, Dimas Hutomo Rahmaniar, Masna Novita Rifqi Ramadhan Rimadeni, Yeni Rina S. Oktari Rini Rahani Rutba, Sita Aliya Safrizal Rahman Safrizal Rahman, Safrizal Salim Satriajati Salwa Rizqina Putri Satria Bagus Panuntun Satria Bagus Panuntun Satria Bagus Panuntun Satria Bagus Panuntun Silalahi, Agatha Siswantining, Titin SITI MARIYAH Siti Mariyah Soemarso, Ditoprasetyo Rusharsono Suadaa, Lya Hulliyyatus Sugiri Suhendra Widi Prayoga Takdir Tasriah, Etjih Thosan Girisona Suganda Thosan Girisona Suganda Tigor Nirman Simanjuntak Titin Siswantining Usman Bustaman Usman Bustaman Utami, Nandya Rezky Wahyu Calvin Frans Mariel Wiwin Srimulyani Yuniarti Yuniarti Zen, Rizqi Annisa

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