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All Journal Jurnal Ekonomi Pembangunan JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Pendidikan Ekonomi (JUPE) Sistemasi: Jurnal Sistem Informasi Paradigma JIKO (Jurnal Informatika dan Komputer) Jurnal Komputasi Faktor Exacta Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Teknoinfo EIGEN MATHEMATICS JOURNAL Jurnal Saintika Unpam : Jurnal Sains dan Matematika Unpam Sains, Aplikasi, Komputasi dan Teknologi Informasi J-3P (Jurnal Pembangunan Pemberdayaan Pemerintahan) Jurnal Statistika dan Aplikasinya Business Economic, Communication, and Social Sciences Journal (BECOSS) Engineering, Mathematics and Computer Science Journal (EMACS) Jurnal Kependudukan Indonesia Indonesian Journal of Statistics and Its Applications
Nooraeni, Rani
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Sentiment Analysis Using Twitter Data Regarding BPJS Cost Increase and Its Effect on Health Sector Stock Prices Evita Dyah Wardhani; Satria Kurnia Areka; Arya Wahyu Nugroho; Ayufi Reyza Zakaria; Arya Damar Prakasa; Rani Nooraeni
Indonesian Journal of Artificial Intelligence and Data Mining Vol 3, No 1 (2020): March 2020
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v3i1.8245

Abstract

News about the increase in BPJS that will increase 2x gives a variety of responses in the community. One of the social media that people use in responding is Twitter. This research is used to see people's sentiment on Twitter about BPJS tariff policies. In addition, the impact of this sentiment will also be seen on the price of health shares. The analysis used is descriptive analysis and inference analysis. Descriptive analysis is used to look at the general picture of community sentiment and inference analysis is used to see the impact of community sentiment on the price of health stocks, namely Indo Farma and Kimia Farma. The results of this study indicate that public sentiment towards rising BPJS is dominated by negative sentiment. And for the level of tendency that has been processed through binary logistic regression analysis shows that negative sentiment will make Kimia Farma shares will go down while positive sentiment will make Kimia Farma shares will go up. As for IndoFarma shares, positive and negative sentiments from IndoFarma shares will tend to fall.
Kajian Penerapan Jarak Euclidean, Manhattan, Minkowski, dan Chebyshev pada Algoritma Clustering K-Prototype Rani Nooraeni; Ghita Nurfalah
Sains, Aplikasi, Komputasi dan Teknologi Informasi Vol 4, No 2 (2022): Sains, Aplikasi, Komputasi dan Teknologi Informasi
Publisher : Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/jsakti.v4i2.9241

Abstract

Clustering merupakan teknik data mining yang bertujuan mengelompokkan data yang memiliki kemiripan kedalam satu klaster, semakin tinggi tingkat kemiripan dalam satu klaster semakin baik hasil clustering yang dihasilkan. Kemiripan data tersebut diukur menggunakan fungsi jarak, sehingga memilih fungsi jarak yang tepat sangatlah penting dalam clustering. K-Prototype (KP) adalah algoritma clustering untuk data campuran yang telah banyak digunkan, pengembangan algoritma lainnya dari K-Prototype yang terkenal adalah Fuzzy K-Prototype (FKP) dan Genetic Algorithm K-Prototype (GAFKP). Namun ketiga algoritma tersebut hanya menggunakan jarak Euclidean dalam mengukur kesamaan datanya. Oleh karena itu, dalam penelitian ini dilakukan penerapan jarak Euclidean, Manhattan, Minkowski, dan Chebyshev pada ketiga algoritma tersebut untuk memperoleh kombinasi jarak dan algoritma yang memberikan hasil clustering yang lebih baik. Hasil penelitian menunjukkan bahwa diantara seluruh kombinasi jarak dan algoritma clustering, algoritma Fuzzy K-Prototype dengan jarak Euclidean memberikan hasil yang lebih baik berdasarkan metode evaluasi akurasi dan indeks CV
Optimasi Parameter ST-DBSCAN dengan KNN dan Algoritma Genetika Studi Kasus: Data Bencana Alam di Pulau Jawa 2021 Rani Nooraeni; Aisyah Nur Fahira
Jurnal Komputasi Vol 11, No 1 (2023): Jurnal Komputasi
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v11i1.3175

Abstract

Spatio Temporal DBSCAN (ST-DBSCAN) adalah metode yang dapat diterapkan pada data spasial yang diikuti dengan atribut temporal. Hasil dari ST-DBSCAN tergantung pada penentuan awal tiga parameter. Inisial parameter yang tidak optimal menyebabkan hasil pengelompokan dengan ST-DBSCAN tidak mencapai solusi yang global optimum. Penelitian ini bertujuan untuk mengoptimalkan penentuan parameter awal pada ST-DBSCAN menggunakan metode k Nearest neighborhood dan Algoritma Genetika yang diuji menggunakan data simulasi kemudian diterapkan dalam pengelompokan wilayah bencana alam. Hasil yang didapatkan adalah pemilihan parameter yang dioptimasi menggunakan algoritma genetika menghasilkan cluster dengan koefisien CDBw terbesar pada perbandingan evaluasi, akan tetapi perlu waktu yang lama untuk merunning sehingga metode tersebut diuji coba dengan data dengan jumlah observasi sedikit. Hasil dari implementasi metode terhadap data bencana alam menunjukkan terdapat 22 cluster
GROUPING PROVINCES IN INDONESIA BASED ON YOUTH DEVELOPMENT INDICATORS IN 2021 Muhamad Zidan Nuralifian; Rani Nooraeni
J-3P (Jurnal Pembangunan Pemberdayaan Pemerintahan) J-3P (Jurnal Pembangunan Pemberdayaan Pemerintahan) Vol. 8, No. 1, Juni 2023
Publisher : ipdn

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33701/j-3p.v8i1.3254

Abstract

Youth have a vital role in development. Indonesia has an uneven distribution of youth across provinces, with over half concentrated in Java. Many young people are also only sometimes in line with their qualities. Youth development was observed through youth development indicators in 2021. The method used is a multivariate method using cluster analysis. The cluster method applied in this research is hierarchy and partition. Based on internal and stability validity, the hierarchical method for five clusters and the number of clusters is the best. The hierarchical method that has the most significant agglomeration coefficient is complete linkage. There is one province with indicators that are very different from other provinces: Papua as cluster 1. Papua requires massive development in all aspects. Cluster 2 comprises Riau Island, Jakarta, the Special Region of Yogyakarta, Bali, and East Kalimantan. Cluster 3 consists of West Nusa Tenggara, Bengkulu, and Lampung. Cluster 4 consists of West Java, Banten, Central Java, Gorontalo, South Sumatra, and East Java. Meanwhile, cluster 5 consists of the remaining members, with the remaining 19 provinces having the most members. Keywords: Youth Development Indicators, Cluster Analysis, Hierarchy, Partition
KAJIAN EFEK SPASIAL KASUS DIFTERI DENGAN GEOGRAPHICALLY WEIGHTED NEGATIVE BINOMIAL REGRESSION (GWNBR) Diva Arum Mustika; Rani Nooraeni; 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.v3i1.185

Abstract

Diphtheria is an infectious disease caused by the Corynebacterium diphtheriae bacteria. Indonesia is the country with the most cases of diphtheria in Southeast Asia and ranks third in the world. In 2016, cases of diphtheria increased by 65 percent and became Extraordinary Events (KLB) in Indonesia, even though during 2013 to 2015 the number of cases of diphtheria has decreased. The province that has the highest number of diphtheria cases in Indonesia in 2016 is East Java. Diphtheria is centered and spread in certain districts / cities in East Java Province so that there are indications of spatial effects in the spread of diphtheria. Because data on the number of diphtheria cases overdispersed and indicated spatial effects in its spread, the main method used in this study was Geographically Weighted Negative Binomial Regression (GWNBR). This method will be compared with other alternative methods namely Poisson regression method and Negative Binomial Regression to get the best modeling. Based on the AIC value of each model it can be concluded that the best method for modeling the number of diphtheria cases is GWNBR. The modeling results with GWNBR show that there is indeed a spatial influence on the number of diphtheria cases and risk factors in East Java Province in 2016. The percentage of DPT-HB3 / DPT-HB-Hib3 immunization coverage is not significant in all observation areas, while the percentage of drug and vaccine availability is significant at entire observation area.
DAMPAK REDENOMINASI TERHADAP INFLASI INDONESIA: PENANGANAN MISSING MENGGUNAKAN METODE CASE DELETION, PMM, RF DAN BAYESIAN Windri Wucika Bemi; Rani Nooraeni
Indonesian Journal of Statistics and Applications Vol 3 No 3 (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.v3i3.360

Abstract

Indonesia is the country with the third largest currency digit after Vietnam and Zimbabwe. In 2010, Indonesia conveyed a discourse on the application of rupiah redenomination, but in its implementation it was necessary to estimate the economic factors that would be affected, especially inflation, where inflation was one of the decisive indicators of the success of the redenomination policy of the currency. To estimate the impact of redenomination on inflation, Indonesia can reflect on the historical data of countries that have implemented the policy. Based on historical data, a model can be applied to Indonesia. Historical data includes macroeconomic variables and forms of government. To get a model with better precision, complete data needs to be considered. The historical missing will make the inferencing obtained invalid and important information that can be used for analysis also diminishes. The case deletion method, mean matching predictive, random forest, and bayesian linear regression can be used to handle it. The results showed that there were 38.18% missing data from total observations and the case deletion method as the best method. Then the condition of hyperinflation, economic growth, and the index of government forms significantly impacted inflation after the implementation of redenomination. So, if Indonesia applies redenomination between the period 2010-2017, with the classification accuracy of 64.71%, it is estimated that it will have a negative impact because the inflation will increase after redenomination is implemented.
PENGARUH TINDAK KORUPSI TERHADAP KEMISKINAN DI NEGARA-NEGARA ASIA TENGGARA DENGAN MODEL PANEL DATA Aditya Firman Baktiar; Herpanindra Fadhilah; Margareth Dwiyanti Simatupang; Mula Warman; Salsa Vira; Rani Nooraeni
Indonesian Journal of Statistics and Applications Vol 4 No 2 (2020)
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.v4i2.634

Abstract

Poverty is still being an issue all over the world. It also happens in Southeast Asia that mostly consists of developing countries that identic with high poverty rates. Countries in the world have tried to eradicate the problem of poverty, it's just that it can be hampered due to the high level of corruption. This study aims to look at suitable models and the relationship between corruption and poverty. The data source in this study is secondary data from ten countries in Southeast Asia from 2015 to 2018. Analysis of the data used in this study is panel data. The result obtained is a panel data regression model that is more suitable for modeling the effect of corruption on poverty in Southeast Asian countries is a fixed effect model. Based on the model, the corruption represented by Corruption Perception Index (CPI) and the poverty represented by Human Development Index (HDI) is directly proportional which means every increase in one unit of CPI will also increase the HDI score by 0.001443 unit.
Co-Authors Adinda Hermambang Aditya Firman Baktiar Afifatul Ilma Widyatami Aisyah Nur Fahira Amelia Syahadati Amirah Balqis Safiruddin Ana Pangestika Anindia Wahyu Inayah Annisa Putri Ramadhanty Apriliansyah Mahmud Arul Fathurrahman Arya Damar Prakasa Arya Wahyu Nugroho Astrid C. A. Pangaribuan Astry Julyana Eliawati Aulia Adita Rahma Aulia Fatin Afifah Aulia Fikri Fadhilah Iskandar Ayufi Reyza Zakaria Cesaria Dewi Choirul Ummah Danty Welmin Yoshida Fatima Delvira Cindy Rosmilda Dewi Retno Oscarini Diana Agustin Dinda Desinta Diva Arum Mustika Dwi Cahyo Firmansyah Elina Mayasari Elvera Wahyu Triana Emban Permata Siam Ersa Budi Sutanto Eunike Sola Gratia Evita Dyah Wardhani Fadhilatul Khairi Fajar Hari Dwiono Fathin Nadillah Fathul Sanusi Frengky Sele Galang Madya Putra Galuh Sri Natungga Dewi Susilo Putri Garinca Firgiana Santoso Geraldi Putra Prasetya Balebu Ghita Nurfalah Ghytsa Alif Jabir Gona Asri Wijayanti Helen Fricylya Br Tobing Heny Dwi Sariyanti Hermarwan Hermarwan Herpanindra Fadhilah I Wayan Edy Darma Putra Ian Tryaldi Halim Ibnu Maruf Indonesian Journal of Statistics and Its Applications IJSA Ineke Kristin Dwi Astuti Isdhani Nurrahmah Ivana Yoselin Purba Siboro Krisna Dwi Agung Kuncoro Dwi Dhanutama Lady Deborah Latifah Hasanah Lisa Widyarsi Machsus Machsus Margareth Dwiyanti Simatupang Marita Mutiara Sinsyi Megananda Ghowo Rizky Meilani Thereza Saragih Mikha Aprilio Miko Oktavio Wijaya Monica Seftaviani Sijabat Muhamad Zidan Nuralifian Muhammad Rizqi Destanto Mula Warman Mustika Putri Nada Nabila Rosyad Nadhifan Humam Fitrial Nawang Indah Cahyaningrum Ni Luh Putu Yayang Septia Ningsih Ni Putu Gita Naraswati Novert Cyril Lengkong Nurfitri Aulia Nurul Hanifah Septiani Ouditiana Safitri Peterson Hamonangan Immanuel Sihotang Pramudya Kusuma Putri Tareka Navasha Qonita Raihananda Raihan Fitrika Azzahra Rhevita Lula Eksanti Ria Dotul Ilmia Riska Damaiyanti Rizka Wulandari Roy Pratama Wijaya Salsa Vira Satria Dirgantara Satria Kurnia Areka Sekar Ayu Ramadhani Sifa Rofatunnisa Siti Andhasah Siti Andhasah Siti Fatimatul Munawwaroh Sri Rahayu Yogyana Sinurat Suciarti Pertiwi Syifa Rahmawati Hakim Viana Mei Reistiani Vina Astriani Wilda Maria Ulfa Windri Wucika Bemi Wisnu Adi Kusuma Yakobus Natanael Tarigan Yolanda Rizkie Aprilia Yongki Ramanda Putra Yulianus Ronaldias Yuniar Putri Awaliyah Risky Yusuf Yahya Zahrotul Firdaus