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All Journal Jurnal Neutrino : jurnal fisika dan aplikasinya Jurnal Rekayasa Mesin SMARTICS Journal Jurnal SOLMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurnal Pendidikan Fisika dan Teknologi INTI Nusa Mandiri Journal of Mathematics Education and Science Inovasi Fisika Indonesia (IFI) Journal of Mechanical Engineering, Science, and Innovation Abdimas Indonesian Journal Scientific Journal of Informatics
Pelangi Eka Yuwita
Universitas Nahdlatul Ulama Sunan Giri
Religion Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Other

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Aplikasi Komputasi Bayesian Regresi Dummy Pada Kasus Kanker Serviks di Kabupaten Tuban Nur Mahmudah; Pelangi Eka Yuwita
Journal of Mathematics Education and Science Vol. 5 No. 2 (2022): Journal of Mathematics Education and Science
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (253.561 KB) | DOI: 10.32665/james.v5i2.415

Abstract

Kanker serviks adalah kanker yang paling banyak diderita oleh wanita yang menjadi penyebab kematian. Penyebab utama kanker serviks adalah infeksi Human Papilloma Virus (HPV). Kanker serviks merupakan penyakit yang disebabkan oleh pertumbuhan sel- sel jaringan tubuh yang tidak normal di dalam leher rahim/ serviks yang terdapat dalam organ bagian reproduksi pada tubuh wanita dan menyebabkan kematian. Untuk mencegah munculnya fase ganas dibutuhkan program screening pada lama rawat inap pasien kanker serviks. Penelitian ini bertujuan untuk mengetahui faktor-faktor yang mempengaruhi lama rawat inap pasien kanker serviks di Kabupaten Tuban dengan metode komputasi Bayesian Regresi Dummy. Metode Bayesian adalah salah satu teknik komputasi pada estimasi parameter yang menggabungkan fungsi likelihood dan distribusi prior menjadi distribusi posterior dalam menduga parameter model. Bayesian regresi dummy menghasilkan suatu variabel yang memiliki pengaruh signifikan terhadap lama rawat inap pasien kanker serviks, yaitu variabel Komplikasi (X1). Dengan nilai alpha 2.17, menunjukan bahwa terdapat dependensi/error yang tidak bisa dijelaskan dalam model regresi dummy pada kasus lama rawat inap kanker serviks di Kabupaten Tuban.
CHARACTERIZATION OF CARBON NANOCRISTRAL STRUCTURE BASED ON CORN COB CHARCOAL Pelangi Eka Yuwita; Roihatur Rohmah
Jurnal Neutrino:Jurnal Fisika dan Aplikasinya Vol 15, No 1 (2022): October
Publisher : Department of Physics, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/neu.v15i1.17067

Abstract

Carbon has an amorphous structure and a crystalline structure. The amorphous structure of carbon is usually found in charcoal, while the crystalline structure of carbon can be obtained from heat treatment. In the present study, the synthesis of carbon nanocrystals based on corn cob charcoal was successfully carried out. The synthesis began with the carbonization process of corn cobs to produce charcoal. Corn cob charcoal powder was then put into 80 mL of HCl solution and stirred using a magnetic stirrer by a speed of 750 rpm at room temperature and 80 mL of NH4OH solution was titrated into it. After the synthesis, the carbon powder was calcined at 400°C and activated using PEG 2000 template. The samples were tested using XRD (X-ray Diffraction) and SEM-EDX (Scanning Electron Microscope-Energy Dispersive X-ray). The carbon component (C) from the EDX test after the synthesis and carbonization process had an atomic percentage of 56.89% and increased by 81.06 % after PEG 2000 activation. The results of the X-ray diffraction pattern show that in all samples a broad and weak diffraction pattern was the characteristic of amorphous carbon. However, on carbon heated for 5 hours at 400°C and the addition of PEG 2000 activator, the crystal structure pattern with higher diffraction peaks was obtained and the peaks of diffraction were matched with CIF data 9008569 from phase C Graphite which had a space group P of 63 mc. SEM data on the morphology of the material showed that after receiving PEG activator, the carbon particles were split into smaller ones so that it increased in surface area and showed fairly even distribution of pores which was also seen in the surface morphology of the carbon
Pemanfaatan Rempah-Rempah sebagai Bahan Pembuatan Jamu Herbal Berbasis Kearifan Lokal di Desa Ngunut Yuwita, Pelangi Eka
Abdimas Indonesian Journal Vol. 4 No. 1 (2024)
Publisher : Civiliza Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59525/aij.v4i1.346

Abstract

Jamu is a traditional medicine that can increase endurance. The use of abundant medicinal plants in Indonesia is currently being developed by the community in preventing and overcoming the Covid-19 case. One of them is by the people of Ngunut Village, Dander District, Bojonegoro Regency, East Java. So that in this case education and training in the manufacture of traditional herbal medicine are given to the people of Ngunut Village, especially among women. The results of the education show that the residents of Ngunut village can process traditional herbal medicine in the form of powder using ginger, as the main ingredient which is then called millineal herbal medicine. In addition, the public response to the educational agenda and training in making millineal herbal medicine is very encouraging. This is evidenced by the higher agree points than the other option
Pendampingan Pelaksanaan Modul Projek Penguatan Profil Pelajar Pancasila Berbasis Etnomatematika Kurikulum Merdeka Bagi Peserta Didik SDN Tambakejo 1 Kabupaten Tuban Yuli Amreta, Midya; Yuwita, Pelangi Eka; Sa’diyah, Zumrotus
Jurnal SOLMA Vol. 13 No. 3 (2024)
Publisher : Universitas Muhammadiyah Prof. DR. Hamka (UHAMKA Press)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/solma.v13i3.16444

Abstract

Background: Permasalahan yang dihadapi adalah tantangan baru dunia pendidikan dalam menghadapi kurikulum Merdeka, khususnya dalam urgensi kompetersi dimensi projek penguatan profil pelajar pancasila yang harus di ajarkan kepada peserta didik. Tujuan pelaksanaan pengabdian kepada masyarakat ini adalah untuk ini pada pendampingan pelaksanaan modul projek penguatan profil pelajar pancasila berbasis etnomatematika kurikulum merdeka bagi peserta didik SDN Tambakrejo 1 Kabupaten Tuban. Metode: Etnomatematika digunakan sebagai integrasi kurikulum, pedagogi, dan matematika. Kegiatan pengabdian kepada masyarakat ini dibagi dalam lima tahapan yaitu sosialisasi, pelatihan, penerapan teknologi, pendampingan dan evaluasi, dan keberlanjutan program. Kegiatan tersebut bekerjasama dengan pihak sekolah, paguyupan wali murid, dan peserta didik UPT SDN Tambakrejo 1 Tuban. Hasil pelaksanaan projek penguatan profil Pelajar Pancasila (P5) terdapat enam dimensi yang dirumuskan dalam kunci keberhasilan projek. Hasil: Hasil dari penguatan profil Pelajar Pancasila, 1) beriman, bertakwa kepada Tuhan Yang Maha Esa dan berakhlak mulia dengan 75,5%, 2) berkebinekaan global dengan 77,6 %, 3) bergotong-royong dengan 77,6 %, 4) mandiri dengan 76,8 %, 5) bernalar kritis dengan 77,2 %, dan 6) kreatif dengan 72,7 %. Keenam dimensi tersebuut sebagai satu kesatuan agar setiap peserta didik dapat menjadi pelajar sepanjang hayat yang kompeten, berkarakter, dan berperilaku sesuai nilai-nilai Pancasila. Kesimpulan: Penggunaan kearifan lokal sebagai integrasi modul projek penguatan profil pelajar pancasila membuat peserta didik terlatih dan mampu menggali konsep pengetahuan yang ada di lingkungan budaya mereka.
ANALISIS SENTIMEN PENGGUNA TWITTER TERHADAP SKINCARE DENGAN METODE SUPPORT VECTOR MACHINE (SVM) Dwi Tiyas Novitasari; Barata, Mula Agung; Yuwita, Pelangi Eka
INTI Nusa Mandiri Vol. 19 No. 2 (2025): INTI Periode Februari 2025
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v19i2.6297

Abstract

The Originote Hyalucera Moisturizer skincare product has attracted public attention because it offers superior quality at an affordable price. Social media, especially Twitter, is used by consumers to express opinions regarding this product, whether positive, negative, or neutral. However, the large number of reviews with various sentiments can confuse potential consumers in assessing product quality. Therefore, this study aims to understand user perception through sentiment analysis and evaluate the effectiveness of the Support Vector Machine (SVM) algorithm in sentiment classification. A total of 1,820 tweets were collected using the crawling technique with Python. The data undergoes preprocessing, including text cleaning, tokenization, stopword removal, and stemming, reducing it to 902 tweets. Key text features are extracted using Term Frequency-Inverse Document Frequency (TF-IDF). For sentiment classification, this study used the SVM algorithm, which is known as an effective method in text processing. Model evaluation showed good results with an accuracy of 87%, precision of 89%, and recall of 87%. This study provides insight into public perception of The Originote Hyalucera Moisturizer and measures the effectiveness of SVM in social media-based sentiment analysis. The results of the study can be utilized by manufacturers for more targeted marketing strategies, product quality improvement, and more effective communication in responding to opinions on social media. In addition, this study contributes to the development of machine learning-based sentiment analysis methods in the context of skincare products.
Pelatihan Inovasi Surat Berbasis Barcode Untuk Meningkatkan Administrasi Pelayanan di Desa Kujung Kecamatan Widang Kabupaten Tuban Ningrum, Ifa Khoiria; Mahmudah, Nur; Yuwita, Pelangi Eka
Jurnal SOLMA Vol. 14 No. 1 (2025)
Publisher : Universitas Muhammadiyah Prof. DR. Hamka (UHAMKA Press)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/solma.v14i1.17590

Abstract

Latar Belakang: Administrasi Desa adalah bagian penting dalam tata kelola pemerintahan yang efisien dalam pembangunan Desa. Desa Kujung masih menggunakan sistem administrasi konvensional dalam pengelolaan surat-menyurat, yang sering kali menimbulkan keterlambatan, kesalahan pencatatan, dan ketidakefektifan dalam pelayanan. Untuk mengatasi permasalahan ini, diperlukan inovasi dalam administrasi desa melalui penerapan teknologi berbasis barcode pada dokumen surat-menyurat. Sistem ini memungkinkan verifikasi dokumen yang lebih cepat, mengurangi risiko pemalsuan, serta mempermudah pencarian arsip digital. Oleh karena itu, kegiatan pengabdian ini bertujuan untuk memberikan pelatihan kepada aparatur desa mengenai pembuatan dan penerapan barcode dalam surat-menyurat guna meningkatkan efisiensi pelayanan administrasi Desa Kujung Kecamatan Widang Kabupaten Tuban. Metode: Kegiatan pengabdian kepada masyarakat ini dilaksanakan di Balai Desa dan dihadiri oleh 15 perangkat desa, 4 anggota Badan Permusyawaratan Desa (BPD), dan 6 anggota Lembaga Pemberdayaan Masyarakat Desa (LPMD) pada tanggal 25 September 2024. Kegiatan ini meliputi sosialisasi dan pelatihan terkait penggunaan surat berbasis barcode dalam meninkatkan validasi surat masuk dan keluar. Hasil: Hasil dari kegiatan ini menunjukkan bahwa peserta memahami pengelolaan dokumen persuratan secara efektif dengan menggunakan Google Drive yang berisi dokumen-dokumen seperti template surat dan tanda tangan pengesahan berupa barcode. Tingkat pemahaman peserta meningkat menjadi 70%, dari sebelumnya 51,63%. Hal ini menunjukkan antusiasme peserta dalam mengimplementasikan aplikasi persuratan ini, yang dimulai dengan input dan pembaruan data pada aplikasi digital persuratan melalui Google Drive dan website. Kesimpulan: Kegiatan ini memberikan dampak positif terkait dengan implementasi penggunaan aplikasi dokumen surat berbasis digital melalui barcode dalam meningkatkan efisiensi dan pelayanan administrasi di Desa Kujung.
Pelatihan dan Pendampingan Pembelajaran Diferensiasi 1 untuk Meningkatkan Keterampilan Guru di Desa Kujung dalam Implementasi Kurikulum Merdeka Yuwita, Pelangi Eka; Mahmudah, Nur; Ningrum, Ifa Khoiria
Jurnal SOLMA Vol. 14 No. 1 (2025)
Publisher : Universitas Muhammadiyah Prof. DR. Hamka (UHAMKA Press)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/solma.v14i1.17878

Abstract

Background: Merdeka Belajar adalah transformasi pendidikan yang berfokus pada kesejahteraan siswa melalui pembelajaran berdiferensiasi sesuai kebutuhan masing-masing. Kegiatan ini bertujuan meningkatkan keterampilan guru SD dan MI di Desa Kujung dalam menerapkan metode tersebut. Metode: Pelatihan dilaksanakan melalui lima tahap: sosialisasi, pelatihan, penerapan teknologi, pendampingan, dan evaluasi serta keberlanjutan program. Kegiatan yang dilaksanakan pada 5 Oktober 2024 di Balai Desa Kujung ini mendapat antusiasme tinggi dari peserta. Hasil: Hasil pelatihan menunjukkan peningkatan signifikan, dengan rata-rata pretest 52,83 dan posttest 76,6. Selain itu, disediakan juga pendampingan online untuk mendukung pembuatan dan implementasi kurikulum berdiferensiasi secara daring. Kesimpulan: Kegiatan ini berhasil meningkatkan pemahaman dan keterampilan guru dalam menerapkan konsep Merdeka Belajar. Peningkatan hasil posttest menunjukkan efektivitas program, sementara antusiasme peserta mencerminkan tingginya kebutuhan akan pelatihan semacam ini. Program ini juga memperkuat kesiapan guru dalam mendukung implementasi kurikulum Merdeka melalui pendekatan yang lebih personal dan berbasis teknologi.
Optimization of Random Forest Algorithm with Backward Elimination Method in Classification of Academic Stress Levels Amalia, Salsabila Dani; Barata, Mula Agung; Yuwita, Pelangi Eka
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9280

Abstract

Stress is a phenomenon experienced by all individuals as a natural response to pressure, which can impact mental and physical health. In an academic setting, the stress experienced by students is known as academic stress, which can affect their performance and mental well-being. Therefore, there is a need for effective prediction methods to aid in the management and prevention of academic stress. Therefore, there is a need to predict the level of academic stress to aid more effective management and prevention. This study uses a public dataset categorized based on the Student-life Stress Inventory (SSI), which includes psychological, physiological, social, environmental, and academic factors. Data mining is often used to detect diseases, one of which is the Random Forest algorithm. The Random Forest algorithm is applied as a classification technique for academic stress levels, with optimization using the Backward Elimination method for feature selection to improve model accuracy. The results showed that the accuracy of the Random Forest algorithm without feature selection obtained an accuracy of 86%, compared to the random forest algorithm with feature selection using the Backward Elimination method obtained a higher accuracy of 88%. This increase shows that the feature selection method can optimize model performance by selecting more relevant features. Thus, this research is expected to contribute to the management of student academic stress against the risk of academic stress.
A Improving House Price Clustering Results with K-means through the Implementation of One-hot Encoding Pre-processing Technique Maulani, Vicka Rizqi; Barata, Mula Agung; Yuwita, Pelangi Eka
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9481

Abstract

Basic human needs include a house that serves as a place to live and a shelter from everything. In Indonesia, owning a house is still a challenging aspect due to its high price. Information on house prices is needed for prospective buyers or consumers, so that buyers can adjust their needs and finances, and for producers or sellers it is used as a way to determine the segmentation of targeted market groups. House prices are influenced by several factors including, building area, number of bedrooms, number of bathrooms, location, condition and the presence of a garage. This research aims to improve the quality of house price clustering with K-means and the application of one-hot encoding in the data pre-processing process in representing categorical data. The dataset used has two types of data, namely numeric and categorical. The cluster evaluation is based on the silhouette score matrix and the determination of k is based on the elbow graph. The results showed an increase in the silhouette score value after applying one-hot encoding 0.15 which was previously 0.09, with the number of k = 3. The 0.15 matrix result is relatively low, which is caused by the overlap of house price values in the dataset, but it has been shown that one-hot encoding can represent categorical data well in the data pre-processing process so that the data can be processed with the k-means algorithm.
Penerapan Data Mining pada Algoritma Multiple Linear Regression dalam Peramalan Harga Emas Dina, Intan Rachma; Barata, Mula Agung; Yuwita, Pelangi Eka
SMARTICS Journal Vol 11 No 1 (2025): SMARTICS Journal (April 2025)
Publisher : Universitas PGRI Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/smartics.v11i1.11710

Abstract

Gold, a precious metal, is highly favored for its ease of maintenance and low risk of loss, making it a popular investment choice. However, gold prices are subject to fluctuations influenced by factors such as the dollar exchange rate, market demand and supply, and monetary crises. Understanding these fluctuations is crucial for investors to minimize losses and maximize profits. The dataset, sourced from Investing.Com, spans from January 2019 to December 2024 and includes 1548 records with five attributes. The error rate was evaluated using Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). This study aims to forecast gold prices using the Multiple Linear Regression algorithm, with the K-Fold Cross Validation method applied to enhance model accuracy. The results show RMSE and MAPE values of 695.7909 and 0.27%, respectively, indicating that the Multiple Linear Regression algorithm is effective in predicting gold prices.
Co-Authors Aditya, Ziedan Agus Sulistiawan Amalia, Salsabila Dani Dina, Intan Rachma Dwi Tiyas Novitasari Faila, Rizka Nur Farikhah, Ainun Nurul Habib, Ahsanul Hilmi, Allif Rosyidy Ifa Khoiria Ningrum Ilmiyah, Miftakhul Indra Kusuma Maulani, Vicka Rizqi Midya Yuli Amreta Mula Agung Barata Nisa, Siti Khoirun Nur Mahmudah Nur Mahmudah Nurma*, Nur Mahmudah Pangestu, Prayoga Dewa Roihatur Rohmah Sa’diyah, Zumrotus Togik Hidayat Vibianto, Erlangga Dwi Aprila