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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 Teknik Pertanian Lampung (Journal of Agricultural Engineering) 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 Jurnal Statistika Terapan (JSTAR) Jurnal Komputasi
Nooraeni, Rani
Politeknik Statistika STIS
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Physics Public Health Social Sciences Other

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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
Faktor-Faktor Yang Memengaruhi Kemiskinan Secara Langsung Dan Tidak Langsung Di Nusa Tenggara Timur Yezua Abel; Rani Nooraeni; Eni Lestariningsih
Jurnal Statistika Terapan (ISSN 2807-6214) Vol 3 No 01 (2023): Jurnal Statistika Terapan
Publisher : Badan Pusat Statistik Provinsi NTT

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

Abstract

Poverty is still a central issue for East Nusa Tenggara Province because alleviation efforts have not experienced a significant reduction. Lots of studies on poverty had been carried out during the pre-pandemic period, but after the pandemic, research on poverty has not been carried out much. This research analyzes the direct and indirect effects of economic growth, the human development index on unemployment and the poverty rate in NTT to obtain information that can support development policies. Data sourced from BPS and data analysis using path analysis. The results of the study show that the HDI has a significant effect on unemployment, while economic growth has no significant effect. Together economic growth and HDI can explain significant variations in unemployment. Unemployment has a fairly strong negative effect on poverty while economic growth and HDI do not have a significant effect. Together economic growth, HDI, and unemployment can explain significant variations in poverty. Economic growth and HDI do not have an indirect effect through unemployment on poverty.
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)
Publisher : Jurusan Ilmu Komputer Fakultas MIPA 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
Pan-Sharpening Analysis for Improved Detection Accuracy and Estimation of Coffee Plantation Land Area (Case Study: South OKU Regency, South Sumatra Province) Anasrul Anasrul; Rani Nooraeni
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 14 No. 2 (2025): April 2025
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v14i2.424-436

Abstract

The use of remote sensing technology in monitoring coffee plantations is becoming increasingly important considering the vital role of coffee in the economy as an export product that increases state revenue. However, challenges remain, especially regarding the low resolution of satellite imagery which hinders accurate and efficient monitoring of coffee fields. This study aims to improve the accuracy of coffee plantation land analysis in South OKU Regency, South Sumatra Province, by using a pan-sharpening method consisting of IHS, Brovey, and Gram-Schmidt and assisted by a composite index. Satellite image sampling data from Landsat-8 was carried out at 1800 points divided into six classes. The results of the study show that the characteristics of coffee plantation land have NDVI, EVI, and ARVI values that tend to be lower, but the NDBI and NDWI values tend to be higher than the non-coffee plantation and forest classes. This study also compares the data from the pan-sharpening method using machine learning and deep learning methods to get the best classification model. The results showed that the SVM model machine learning method on the pan-sharpening brovey data gave the best results with an ACCURACY value of 83.49 and an F1-score of 83.59 percent. Keywords: Coffee Plantations, Deep Learning, Machine Learning, Pan-sharpening, Remote Sensing.
Co-Authors Adinda Hermambang Aditya Firman Baktiar Afifatul Ilma Widyatami Aisyah Nur Fahira Amelia Syahadati Amirah Balqis Safiruddin Ana Pangestika Anasrul Anasrul 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 Eni Lestariningsih 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 Yezua Abel Yolanda Rizkie Aprilia Yongki Ramanda Putra Yulianus Ronaldias Yuniar Putri Awaliyah Risky Yusuf Yahya Zahrotul Firdaus