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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Public Health Science (IJPHS) Jurnal Ilmu Komputer dan Informasi Berkala Ilmiah Pendidikan Biologi (BioEdu) Bulletin of Electrical Engineering and Informatics Jurnal Kimia dan Kemasan Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JPM (Jurnal Pemberdayaan Masyarakat) Communications in Science and Technology JPF : JURNAL PENDIDIKAN FISIKA Jurnal Ilmu Fisika Jurnal Informatika Global Jurnal Abdimas Mandiri Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Indonesian Journal of Electrical Engineering and Computer Science Abdimas Galuh : Jurnal Pengabdian Kepada Masyarakat Reswara: Jurnal Pengabdian Kepada Masyarakat Indonesian Journal of Engagement, Community Services, Empowerment and Development (IJECSED) Malcom: Indonesian Journal of Machine Learning and Computer Science Prosiding Seminar Nasional Official Statistics Hexatech: Jurnal Ilmiah Teknik Eduvest - Journal of Universal Studies Molekul: Jurnal Ilmiah Kimia Al-Ashri: Ilmu-Ilmu Keislaman AQILA : Acceleration, Quantum, Information Technology and Algorithm Journal
Evi Yulianti
Pusat Teknologi Bahan Industri Nuklit-BATAN Kawasan PUSPIPTEK Serpong, Tangerang 15314, Indonesia
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Pembuatan Bahan Polimer Elektrolit Padat Berbasis Nanokomposit Kitosan Montmorillonite Untuk Aplikasi Baterai Yulianti, Evi; Saputri, Rosiana Dwi; Sudaryanto, Sudaryanto; Jodi, Heri; Salam, Rohmad
Jurnal Kimia dan Kemasan Vol. 35 No. 2 Oktober 2013
Publisher : Balai Besar Kimia dan Kemasan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (937.378 KB)

Abstract

Telah dilakukan pembuatan bahan polimer elektrolit padat berbasis nanokomposit kitosan montmorillonite yang diaplikasikan dalam sistem baterai. Penelitian ini dilakukan dengan tujuan untuk menentukan komposisi optimal antara kitosan, montmorillonite dan LiClO4 sehingga diperoleh membran dengan karakteristik yang paling baik. Teknik pembuatan membran dilakukan menggunakan metode casting. Terdapat dua seri sampel yang akan di uji, yaitu membran dengan variasi komposisi montmorillonite dan variasi komposisi LiClO4. Komposisi kitosan dan montmorillonite yang digunakan pada sampel seri kedua diperoleh dari komposisi optimal membran kitosan-montmorillonite pada sampel seri pertama. Karakterisasi yang dilakukan meliputi uji tarik, pengukuran konduktivitas ionik dan identifikasi menggunakan difraksi sinar X. Penambahan montmorillonite meningkatkan kuat tarik membran dan konduktivitas ionik setelah ditambah LiClO4. Pada kondisi optimal diperoleh konduktivitas ionik 2,383 x 10-5 S/cm dan kuat tarik 15,19 Mpa pada komposisi montmorillonit 5% b/b dan LiClO4 40%. Hasil analisis difraksi sinar X menunjukkan terjadi proses interkalasi polimer kitosan ke dalam montmorillonite. 
VALIDITAS LKS PENGAMATAN BERDASARKAN PENDEKATAN SAINTIFIK PADA SUB POKOK BAHASAN ANGIOSPERMAE YULIANTI, EVI
Berkala Ilmiah Pendidikan Biologi (BioEdu) Vol 3 No 3 (2014)
Publisher : Program Studi Pendidikan Biologi, FMIPA, Universitas Negeri Surabaya

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Abstract

Kurangnya keterlibatan siswa secara langsung dalam kegiatan pengamatan dan cakupan materi yang luas menjadikan siswa sering menemui kesulitan dalam memahami konsep Angiospermae. Diperlukan kegiatan pembelajaran yang dapat melatih siswa bersikap ilmiah, kreatif, dan mandiri untuk memudahkan siswa memahami konsep. Pendekatan saintifik merupakan pendekatan yang menerapkan kaidah ilmiah dalam pembelajaran meliputi kegiatan mengamati, menanya, mencoba, menalar, dan mengkomunikasikan. Penelitian ini bertujuan untuk mengetahui kelayakan LKS ditinjau dari aspek validitas. Penelitian ini merupakan penelitian pengembangan dengan mengacu pada model pengembangan Research & Development (R&D). Hasil penelitian menunjukkan bahwa LKS yang dikembangkan layak berdasarkan hasil validasi (91,25%) dengan interpretasi sangat layak. Kata Kunci: Lembar Kegiatan Siswa, Pendekatan Saintifik, Angiospermae
PENGELOMPOKAN KABUPATEN/KOTA DI PROVINSI JAWA TENGAH BERDASARKAN JUMLAH PEREMPUAN (USIA 18+) KORBAN KEKERASAN DENGAN MENGGUNAKAN K-MEANS CLUSTERING Yulianti, Evi; Sugandha, Agus
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 13 No 2 (2021): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2021.13.2.5014

Abstract

ABSTRACT. Violence against women is one of the cases that often gets attention and news in various mass media and electronic media today. In Komnas Perempuan's Annual Records, there were 406,178 cases of violence against women reported and handled throughout 2018. This number increased compared to the previous year's 348,466 cases. This study was conducted to try to group 35 districts/cities in Central Java into 3 clusters based on the number of women (age 18+) victims of violence. Grouping is done using the k-means cluster method. The regencies/cities in Central Java are grouped into 3 clusters, namely: cluster 1 there is 1 Regency/City with a high number of women (age 18+) victims of violence, cluster 2 there are 4 Regency/City with a high number of victims of violence. female (age 18+) victims of violence. moderate, and cluster 3 there are 30 districts/cities with a low number of women (age 18+) victims of violence.Keywords: k-means cluster, women, victim of violence ABSTRAK. Kekerasan terhadap perempuan merupakan salah satu kasus yang sering menjadi perhatian dan pemberitaan diberbagai media masa maupun media elektronik saat ini. Dalam Catatan Tahunan Komnas Perempuan, terdapat 406.178 kasus kekerasan terhadap perempuan yang dilaporkan dan ditangani selama tahun 2018. Angka ini meningkat dibandingkan dengan tahun sebelumnya sebanyak 348.466 kasus. Penelitian yang dilakukan mencoba untuk melakukan mengelompokan 35 Kabupaten/Kota di Jawa Tengah kedalam 3 cluster berdasarkan jumlah perempuan (usia 18+) korban kekerasan. Pengelompokan dilakukan dengan menggunakan metode k-means cluster. Pengelompokan Kabupaten/Kota di Jawa Tengah kedalam 3 cluster yaitu : cluster 1 terdapat 1 Kabupaten/Kota dengan jumlah perempuan (usia 18+) korban kekerasan yang tinggi, cluster 2 terdapat 4 Kabupaten/Kota dengan jumlah perempuan (usia 18+) korban kekerasan yang sedang, dan cluster 3 terdapat 30 Kabupaten/Kota dengan jumlah perempuan (usia 18+) korban kekerasan yang rendah.Kata Kunci: k-means cluster, perempuan, korban kekerasan
Analysis of Critical Thinking Skills of High School Students Haris, Abdul; Martawijaya, M. Agus; Dahlan, Ahmad; Yulianti, Evi; Nua, Muh. Tri Prasetia
Jurnal Pendidikan Fisika Vol 12, No 1 (2024): PENDIDIKAN FISIKA
Publisher : Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/jpf.v12i1.12677

Abstract

Critical thinking skills are one of the essential 21st-century competencies that students must possess, as outlined by the Indonesian Ministry of Education's competency standards for graduation. The Minister of Education and Culture Decree No. 56 of 2022, which mandates the implementation of the independent curriculum, has prompted schools to change their existing curricula. This necessitates research to provide an overview of students' critical thinking skills as developed by schools. This study aims to describe the critical thinking skills of public high school students in Makassar City in the subject of Physics. The research is a quantitative descriptive survey, with the main variable being critical thinking skills, which are measured through three indicators: analysis, interpretation, and inference. The research instrument used was a six-item essay test. The population for this study consisted of all public high school students in Makassar City studying Newton's laws of motion, specifically students from SMAN 2 Makassar, SMAN 4 Makassar, SMAN 5 Makassar, SMAN 8 Makassar, and SMAN 16 Makassar. Using purposive sampling, the sample included all students from one class at each of the five schools in the population. The results indicate that 75.50% of the students' critical thinking skills in solving physics problems fall into the low category. The specific skills in analysis, interpretation, and inference are also categorized as low. Additionally, female students demonstrated a higher ratio of critical thinking skills compared to male students. In conclusion, the critical thinking skills of high school students in Makassar City remain at a low level.
Named entity recognition on Indonesian legal documents: a dataset and study using transformer-based models Yulianti, Evi; Bhary, Naradhipa; Abdurrohman, Jafar; Dwitilas, Fariz Wahyuzan; Nuranti, Eka Qadri; Husin, Husna Sarirah
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i5.pp5489-5501

Abstract

The large volume of court decision documents in Indonesia poses a challenge for researchers to assist legal practitioners in extracting useful information from the documents. This information can also benefit the general public by improving legal transparency, law enforcement, and people's understanding of the law implementation in Indonesia. A natural language processing task that extracts important information from a document is called named entity recognition (NER). In this study, the NER task is applied to legal domains, which is then referred to as legal entity recognition (LER) task. In this task, some important legal entities, such as judges, prosecutors, and advocates, are extracted from the decision documents. A new Indonesian LER dataset is built, called IndoLER data, consisting of approximately 1K decision documents with 20 types of fine-grained legal entities. Then, the transformer-based models, such as multilingual bidirectional encoder representations from transformers (BERT) or M-BERT, Indonesian BERT or IndoBERT, Indonesian robustly optimized BERT pretraining approach (RoBERTa) or IndoRoBERTa, XLM (cross lingual language model)-RoBERTa or XLMR, are proposed to solve the Indonesian LER task using this dataset. Our experimental results show that the RoBERTa-based models, such as XLM-R and IndoRoBERTa, can outperform the state-of-the-art deep-learning baselines using BiLSTM (bidirectional long short-term memory) and BiLSTM-conditional random field (BiLSTM-CRF) approaches by 7.2% to 7.9% and 2.1% to 2.6%, respectively. XLM-RoBERTa is shown to be the best-performing model, achieving the F1-score of 0.9295.
Javanese part-of-speech tagging using cross-lingual transfer learning Enrique, Gabriel; Alfina, Ika; Yulianti, Evi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp3498-3509

Abstract

Large datasets that are publicly available for POS tagging do not always exist for some languages. One of those languages is Javanese, a local language in Indonesia, which is considered as a low-resource language. This research aims to examine the effectiveness of cross-lingual transfer learning for Javanese POS tagging by fine-tuning the state-of-the-art Transformer-based models (such as IndoBERT, mBERT, and XLM-RoBERTa) using different kinds of source languages that have a higher resource (such as Indonesian, English, Uyghur, Latin, and Hungarian languages), and then fine-tuning it again using the Javanese language as the target language. We found that the models using cross-lingual transfer learning can increase the accuracy of the models without using cross-lingual transfer learning by 14.3%–15.3% over LSTM-based models, and by 0.21%–3.95% over Transformer-based models. Our results show that the most accurate Javanese POS tagger model is XLM-RoBERTa that is fine-tuned in two stages (the first one using Indonesian language as the source language, and the second one using Javanese language as the target language), capable of achieving an accuracy of 87.65%
Analyzing public perception toward COVID-19 vaccines in Indonesia Rizqiyah, Putri; Yulianti, Evi; Jiwanggi, Meganingrum Arista
International Journal of Public Health Science (IJPHS) Vol 13, No 1: March 2024
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijphs.v13i1.23134

Abstract

The research is prompted by the dearth of studies addressing public perceptions of various COVID-19 vaccines in Indonesia using extensive datasets spanning and a wide timeframe. This study examined public perception toward COVID-19 vaccines in Indonesia using a dataset of tweets. We further detect whether there are any changes in sentiment toward each type of vaccine. The five most commonly used vaccines in Indonesia (AstraZeneca, Moderna, Pfizer, Sinopharm, and Sinovac) were analyzed for sentiment using a lexicon-based method: Valence Aware Dictionary and Sentiment Reasoner (VADER), with changes in sentiment detected using Pruned Exact Linear Time (PELT). The 280,826 tweets collected between 2021 and 2022, 39% were positive, 18% were negative, and 43% were neutral. While Indonesian citizens generally responded positively and neutrally to each vaccine, with Sinopharm and Pfizer receiving the highest sentiment scores and AstraZeneca receiving the lowest, some change points in sentiment were associated with real-world events. Jakarta had the highest number of tweets (22%), while Maluku had the highest sentiment score (0.498). A significant positive correlation was also found between the total number of tweets and two variables: new cases of COVID-19 (r=0.9, p=0.001) and total new deaths caused by COVID-19 (r=0.8, p=0.008). Overall, the discussion of COVID-19 vaccines is still ongoing, and Indonesian citizens tend to respond neutrally and positively regardless of location or time.
ABSA of Indonesian customer reviews using IndoBERT: single- sentence and sentence-pair classification approaches Yulianti, Evi; Nissa, Nuzulul Khairu
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.8032

Abstract

Aspect-based sentiment analysis (ABSA) task is important to identify user satisfaction from customer reviews by recognizing the sentiments of all aspects discussed in the reviews. This work investigates a novel study on the effectiveness and efficiency of three IndoBERT-based models for solving the ABSA task in Indonesian language. IndoBERT is a state-of-the-art transformer-based model, i.e., bidirectional encoder representations from transformers (BERT), that was pre-trained on Indonesian language. Our first model utilizes IndoBERT in a feature-based mode, paired with the convolutional neural network (CNN) and machine learning models, for single-sentence classification. Next, our second model is obtained by fine- tuning the IndoBERT model for a typical single-sentence classification to build an end-to-end model. At last, our third model also adopts a fine-tuning approach to use IndoBERT, but for sentence-pair classification by utilizing auxiliary sentences. Our results demonstrate that the third model, the fine- tuned IndoBERT for sentence-pair classification, gains the highest effectiveness. It demonstrates significant improvement over deep learning baselines (Word2Vec-CNN-XGBoost) by 23.6% and transformer-based baselines (mBERT-aux-NLIB) by 2.2% in terms of F-1 score. When considering both effectiveness and efficiency, the results show that the best- performing model is our second model, the fine-tuned IndoBERT for single- sentence classification.
PENGABDIAN PADA MASYARAKAT MELALUI KULIAH KERJA MAHASISWA (KKM) DI KELURAHAN KEPUH KECAMATAN CIWANDAN KOTA CILEGON Hendrawati, Sulkiah; Fatari, Fatari; Sumarsih, Rani Sri; Febrianto, Muhamad Rizki; Gupron, Akhmad; Yulianti, Evi; Abro, Fikri; Pratama, Mochamad Jodi
Indonesian Journal of Engagement, Community Services, Empowerment and Development Vol. 4 No. 2 (2024): Indonesian Journal of Engagement, Community Services, Empowerment and Developme
Publisher : Yayasan Education and Social Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53067/ijecsed.v4i2.163

Abstract

Community service through Student Work Lectures conducted by group 46 students in the Kepuh sub-district, Ciwandan sub-district by providing community assistance in social, economic, health, educational, legal and religious aspects as well as appropriate technology. Student Work Lectures are field activities carried out by students over a certain period of time and are an implementation of the Tridharma of higher education. The method for student work study activities currently focuses more on implementing work programs that have been prepared systematically. Carried out by Group 46 Students and Field Supervising Lecturers and Field Supervising Lecturers by going directly to the field to visit the community and the data sources needed to ask for information through direct interviews both personally and organizationally or data sources obtained through sub-district offices or sub-district offices. subdistrict. Results and Discussion; forming work programs, implementing work programs, implementing work programs and the role of Field Supervisors and Field Assistant Lecturers. In conclusion; there is an understanding related to digital marketing specifically for entrepreneurship, there is awareness about healthy living, there is legal awareness and an understanding of the importance of education. The creation of outcomes as a result of Community Service
Pelatihan Pembuatan Materi Ajar Menggunakan PopAi di SD Negeri 13 Palembang Putri, Indah Pratiwi; Marcelina, Dona; Yulianti, Evi; Saluza, Imelda
Abdimas Galuh Vol 6, No 2 (2024): September 2024
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/ag.v6i2.15981

Abstract

Pengabdian masyarakat ini bertujuan untuk mendalami penerapan kecerdasan buatan (Artificial Intelligence/AI) dalam pembelajaran di Sekolah Dasar (SD), khususnya di SD Negeri 13 Palembang. Melalui kemitraan dengan sekolah tersebut, para guru SD menjalani pelatihan untuk meningkatkan kualitas pembelajaran dengan memanfaatkan teknologi AI, terutama melalui platform PopAi. Pelatihan ini menitikberatkan pada pemahaman konsep dasar kecerdasan buatan, aplikasi praktisnya dalam pembelajaran, dan aspek-etika dalam penggunaannya. Diharapkan bahwa pengabdian ini akan memberikan kontribusi yang signifikan dalam meningkatkan kualitas pembelajaran di tingkat SD, dengan peserta yang memiliki pengetahuan mendalam tentang penggunaan AI dan keterampilan praktis untuk menghasilkan materi ajar inovatif dan sesuai dengan kebutuhan siswa.
Co-Authors Abdul Haris Abdurrohman, Jafar Abro, Fikri Adriana, Risda Agung Bambang Setio Utomo Agus Sugandha Ahmad Dahlan Alfina, Ika Alie, M. Fadhiel Aminuddin, Jamrud Anandez, Arum Adisha Putra Annas, Dicky Atmoko, Indri A’yun, Nidha Aulia Qurrata Berghuis, Nila Tanyela Bhary, Naradhipa Bilalodin Bilalodin Busral, Busral Coyanda, John Roni Cyndika Dari, Qorinah Wulan Dwitilas, Fariz Wahyuzan Eka Qadri Nuranti Enrique, Gabriel Faradillah Fatari, Fatari Febrianto, Muhamad Rizki Fridarima, Shanny Gupron, Akhmad Hananto, Djoko Haryadi, Arifin Nur Muhammad Hayati, Atika Trisna Hendrawati, Sulkiah Heri Jodi, Heri Humairoh, Nayu Nur Husin, Husna Sarirah Imelda Saluza, Imelda Indah Permatasari Iskandar Zulkarnaen Jayawarsa, A.A. Ketut Khusaenah, Nur Kurniawan, Alfin Laugiwa, Matiin Lukman Hakim Madiabu, Muhammad Jihad Marcelina, Dona Martawijaya, M. Agus Meganingrum Arista Jiwanggi Ndruru, Sun Theo Constan Lotebulo Nissa, Nuzulul Khairu Nua, Muh. Tri Prasetia Pisgamargareta, Abel Praktino, Budi Prasetyo, Ridho Pratama, Mochamad Jodi Pratiwi, Indah Putri Putri Rizqiyah Putri, Indah Pratiwi Rabiyatul Adawiyah Siregar Rachmadhanti, Elvira Nur Rachmawati, Nur Ramadhan, Mustafa Rohmad Salam, Rohmad Rosiana Dwi Saputri, Rosiana Dwi Sampora, Yulianti Saputra, Muklas Ade Sofyan, Muhammad Ihsan Sudaryanto Sumarsih, Rani Sri Sunardi Sunardi Suryati Syazali, Muhammad Rizki Terttiavini, Terttiavini Zulham Zulham