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All Journal Jurnal Informatika Universitas Pamulang MIND (Multimedia Artificial Intelligent Networking Database) Journal Jambura Journal of Informatics Building of Informatics, Technology and Science Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Teknik Informatika (JUTIF) Jumat Informatika: Jurnal Pengabdian Masyarakat Abdiformatika: Jurnal Pengabdian Masyarakat Informatika Jurnal Informatika: Jurnal Pengembangan IT
Sukmawati, Cici Emilia
Universitas Buana Perjuangan Karawang
Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Other

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Rancangan Penerapan Metode Spanning Tree untuk Transmisi Data Pada Jaringan Laboratorium Komputer Tohirin Al Mudzakir; Iin Kurniawati; Cici Emilia Sukmawati
Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Vol 3 No 2 (2018): Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi
Publisher : Teknik Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/technoxplore.v3i2.814

Abstract

Laboratorium Komputer (Labkomp) Universitas Singaperbangsa Karawang adalah salah satu fasilitas praktikum. Topologi LAN adalah topologi yang digunakan Labkomp untuk berkomunikasi. Karena selain memudahkan komunikasi internal (komunikasi antar komputer dalam pertukaran file dan data), juga dapat memfasilitasi komunikasi eksternal (jaringan internet ke komunikasi pengguna, seperti email, browsing, chatting dan streaming) .Tujuan dari komunikasi ini adalah untuk mendukung proses lab di Labkomp Fasilkom UNSIKA. Labkomp memiliki 2 jaringan, Lab. Dasar dan Lab. Melanjutkan pra-praktikum adalah memasang aplikasi untuk mendukung jalannya praktikum. tetapi karena file dan data yang terlalu besar dan sedikit media penyimpanan yang tidak dapat mencadangkan praktikum transfer data terlalu banyak. Metode penelitian adalah Network Development Life Cycle (NDLC). Dengan metode ini bertujuan memiliki fase, tahapan, langkah atau mekanisme proses perancangan jaringan komputer dengan baik. Desain jaringan mendesain Labkomp Fasilkom UNSIKA untuk bergabung dengan Lab. Dasar dan lab. Selanjutnya dengan menggunakan perangkat lunak pelacak paket cisco router tambahan baru dapat dihubungkan. Kemudian desain yang disarankan oleh penulis, aliran data pada jaringan berjalan dengan baik
Evaluasi Algoritma Pembelajaran Terbimbing terhadap Dataset Penyakit Jantung yang telah Dilakukan Oversampling MASRURIYAH, ANIS FITRI NUR; NOVITA, HILDA YULIA; SUKMAWATI, CICI EMILIA; ARIF, SITI NOVIANTI NURAINI; RAMADHAN, ANGGA RAMDA
MIND (Multimedia Artificial Intelligent Networking Database) Journal Vol 8, No 2 (2023): MIND Journal
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/mindjournal.v8i2.242-253

Abstract

AbstrakPenyakit jantung mengalami peningkatan setiap tahunnya dan menjadi penyebab kematian tertinggi di Indonesia, terutama pada usia produktif. Pola makan yang tidak seimbang dan gaya hidup tidak sehat menjadi faktor penyebab prevalensi penyakit jantung yang tinggi. Bidang ilmu kedokteran mulai beradaptasi dan mengandalkan model prediksi otomatis berbasis komputer untuk diagnosis secara tepat dan akurat. Data tentang penyakit jantung seringkali memiliki ketidakseimbangan, yaitu jumlah data pada kelas minoritas lebih kecil daripada kelas mayoritas. Oleh karena itu, teknik oversampling seperti SMOTE dan ADASYN digunakan untuk menangani masalah ini. Hasil dari penelitian ini Algoritma Random Forest Classifier menjadi model perbandingan terbaik dengan akurasi sekitar 90,71%. Penerapan teknik oversampling SMOTE + Random Forest, akurasi dapat meningkat hingga sekitar 94,54% dengan kurva ROC sebesar 98,4%. Model diagnosa yang akurat dapat menjadi media bagi tenaga medis untuk mengambil langkah pencegahan yang tepat dan meningkatkan kualitas perawatan pasien.Kata kunci: ADASYN, Klasifikasi, Pohon Keputusan, Regresi, SMOTEAbstractHeart disease is rapidly increasing in Indonesia and has become the primary cause of death, particularly among those in their productive years. The prevalence of heart disease is due to unhealthy lifestyle choices and an imbalanced diet. The medical field is relying more heavily on computer-based automatic prediction models to ensure precise and accurate diagnoses. However, data on heart disease is frequently imbalanced, with fewer cases in the minority class. To resolve this issue, oversampling techniques such as SMOTE and ADASYN have been implemented. The study demonstrates that the Random Forest Classifier Algorithm is the most effective comparison model, with an accuracy rate of approximately 90.71%. By implementing the SMOTE + Random Forest oversampling technique, the accuracy rate increased to around 94.54%, with a ROC curve of 98.4%. A highly accurate diagnostic model is essential for enabling medical personnel to take appropriate preventive measures and enhance the quality of patient care.Keywords: ADASYN, Classification, Decision Tree, Regresi, SMOTE
PUBLIC SENTIMENT ANALYSIS ON ELECTRIC CARS USING MACHINE LEARNING ALGORITMS Damaiarta Tejayanda, Rigger; Prasetyo, Bayu; Faisal, Muhamad Agus; Abigael, Rakha; Rohana, Tatang; Sukmawati, Cici Emilia
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2141

Abstract

The presence of electric vehicles has generated diverse opinions among the public, as widely discussed on social media. The lack of understanding about electric vehicle innovation can influence their perception. Issues such as infrastructure, high prices, pollution concerns, and adaptation to new technology present challenges for automotive companies in their innovation efforts. This study aims to analyze public sentiment towards electric vehicles through comments on the TikTok platform, which can serve as a reference for companies in evaluating and developing electric vehicle innovations. Six different classification algorithms were tested to determine the most effective and accurate one. The methods used include data collection of comments, pre-processing, data processing through stemming, tokenization, and stopwords removal techniques, as well as labeling and modeling stages. The results of the study show that Support Vector Machine are the most superior algorithms with the highest accuracy of 90%. This research provides new insights into public perception of electric cars and the effectiveness of various sentiment analysis algorithms in the context of social media.
Evaluasi Kinerja Algoritma AdaBoost dan XGBoost Menggunakan Dataset Penyakit Obesitas Pada Populasi Dewasa Sukmawati, Cici Emilia; Nur Masruriyah, Anis Fitri; Juwita, Ayu Ratna; Tejayanda, Rigger Damaiarta; Nurmayanti, Trisya
Jambura Journal of Informatics VOL 6, N0 2: OKTOBER 2024
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jji.v6i2.27342

Abstract

Penelitian ini membahas terkait evaluasi kinerja AdaBoost dan XGBoost pada penyakit obesitas . Penelitian tersebut menggunakan dataset yang diperoleh dari sumber kaggle dengan jumlah data 2111 dengan 17 atribut. Selanjutnya, data tersebut dilakukkan preprocessing data sehingga berkurang menjadi 591 data. Kemudian, data tersebut dilakukan split data dengan perbandingan 70:30 dengan rincian data uji 119 dan data training sebanyak 472. Pengujian dilakukan menggunakan accuracy, precision dan recall. Berdasarkan hasil penelitian yang telah dilakukan, bahwa metode XGBoost terbukti lebih unggul dibandingkan dengan AdaBoost. Adapun accuracy, precision dan recall sebesar 92%. Sedangkan untuk accuracy dan recall untuk metode AdaBoost sebesar 40% sertaa precision 39%.
Model Klasifikasi Nominal Mata Uang Kertas Republik Indonesia Menggunakan Convolutional Neural Network Saputra, Arbi Niandi; Handayani, Hanny Hikmayanti; Sukmawati, Cici Emilia; Siregar, Amril Mutoi
Journal of Information System Research (JOSH) Vol 6 No 1 (2024): Oktober 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i1.5927

Abstract

Uang kertas adalah alat pembayaran umum di seluruh dunia saat ini karena digunakan dalam transaksi jual beli barang dan jasa. Nilai uang kertas Rupiah di Indonesia memiliki variasi yang mencakup ukuran, warna, dan pola yang berbeda. Identifikasi manual dapat menyebabkan kesalahan, sehingga diperlukan sistem pengenalan uang kertas yang efisien dan akurat. Permasalahan dalam mata uang terbaru menekankan pentingnya sistem pendeteksi yang selalu memperbarui data referensinya agar tetap akurat. Mata uang baru dengan desain atau fitur keamanan yang berbeda dapat menantang kemampuan sistem dalam mengenali keasliannya. Sistem harus mampu dengan cepat mengidentifikasi elemen baru dan memperbarui database referensi untuk menghindari risiko kesalahan atau penipuan. Oleh karena itu, penelitian perlu difokuskan pada pengembangan mekanisme pembaruan data secara real-time untuk menjaga responsivitas sistem terhadap perubahan mata uang. Maka dari itu, dilakukan klasifikasi nominal mata uang kertas Republik Indonesia Tahun Emisi 2022 menggunakan Convolutional Neural Network. Tahapan yang dilakukan yaitu proses akuisisi citra, preprocessing, pelatihan model, dan evaluasi. Dengan teknik pengenalan berdasarkan pola bunga yang terdapat pada uang kertas Republik Indonesia. Hasil yang peroleh yaitu akurasi sebesar 99% dengan 694 data berhasil diklasifikasi dari 700 data pengujian.
Kompetensi Digital Guru-Guru Pesantren Al-Kautsar Melalui Pelatihan Teknologi Pendidikan Sukmawati, Cici Emilia; Juwita, Ayu Ratna; Latifah, Nurul; Khairani, Nova Pustita
Jumat Informatika: Jurnal Pengabdian Masyarakat Vol. 6 No. 1 (2025): April
Publisher : LPPM Universitas KH. A. Wahab Hasbullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32764/abdimasif.v6i1.5633

Abstract

The digital literacy skills of teachers in Islamic boarding schools are still low, especially in the use of technology to support learning activities and academic administration. One of the challenges faced is the lack of skills in using word processing software to systematically compile teaching materials and academic documents. This community service aims to improve the digital competence of Islamic boarding school teachers through training in the use of word processing software. The method used is a participatory approach with stages of planning, implementation of training based on direct practice, and evaluation through pre-tests and post-tests. This activity involves Islamic boarding school teachers as the main participants who receive intensive training in document creation and formatting, table management, and the use of automation features such as mass mailings and tables of contents. The results of the community service show an increase in participants' skills in operating word processing software, as indicated by an increase in post-test scores compared to the pre-test. In addition, this training also resulted in significant social changes, such as increased digital literacy of teachers, the emergence of individuals who act as mentors for colleagues, and the adoption of technology in academic administration. This program proves that a direct practice-based approach is effective in improving the digital skills of Islamic boarding school teachers. For the sustainability of the program, it is recommended that there be further training, a mentoring system between teachers, and technological infrastructure support so that the implementation of digital skills can take place optimally and sustainably.
Optimasi AdaBoost dan XGBoost untuk Klasifikasi Obesitas Menggunakan SMOTE Sukmawati, Cici Emilia; Pratama, Adi Rizky; Hikmayanti, Hanny; Juwita, Ayu Ratna
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 3 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i3.8536

Abstract

Obesity is a condition in which a person's weight exceeds the normal limit due to excessive accumulation of fat tissue. Thus, obesity is considered a global public health challenge. This is evidenced by the latest data from the World Health Organization (WHO) in 2022, namely that 2.5 billion adults aged 18 years and over are overweight and 890 million of them are obese. Therefore, it is very important to accurately identify these risk factors in order to implement effective interventions in the prevention and management of obesity. However, in previous studies there has been no application of SMOTE with the AdaBoost and XGBoost algorithms, so this study aims to compare the performance of the AdaBoost and XGBoost algorithms with SMOTE. The stages of this research begin with problem identification, data collection, preprocessing and model evaluation and model comparison. This study also applies the SMOTE technique to balance unbalanced data. Based on the results of the research that has been carried out, it shows that the accuracy and recall values of the XGBoost algorithm with SMOTE are 0.945 and precision 0.947. Meanwhile, the accuracy and recall values on AdaBoost with SMOTE are 0.388. Then, the precision is 0.371. Thus, it is expected that the results of the XGBoost model with SMOTE can be a source for other research and can help in efforts to prevent and manage obesity.
Membangun Identitas Digital Workshop Pembuatan Website Dengan Wordpress (Pesantren At-Taubah Karawang) Sukmawati, Cici Emilia; Juwita, Ayu Ratna; Novalia, Elfina; Nurmayanti, Trisya; Tejayanda, Rigger Damaiarta; Faisal, Muhamad Agus
Abdiformatika: Jurnal Pengabdian Masyarakat Informatika Vol. 4 No. 1 (2024): Mei 2024 - Abdiformatika: Jurnal Pengabdian Masyarakat Informatika
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/abdiformatika.v4i1.209

Abstract

Workshop "Membangun Identitas Digital: Workshop Pembuatan Website dengan WordPress" di Pesantren At Taubah Karawang merupakan kegiatan yang bertujuan untuk memberikan pemahaman dan keterampilan kepada peserta dalam membangun identitas digital lembaga pendidikan melalui pembuatan dan pengelolaan website. Workshop ini berhasil mencapai beberapa hasil yang signifikan, antara lain pemahaman konsep identitas digital yang lebih baik, keterampilan penggunaan platform WordPress yang lebih mahir, dan peningkatan kualitas konten digital lembaga. Selain memberikan manfaat bagi Pesantren At Taubah Karawang dalam memperkuat identitas digitalnya, workshop ini juga memberikan dampak positif jangka panjang dalam pengembangan sumber daya manusia dan pemberdayaan masyarakat di era digital saat ini. Saran yang diberikan meliputi pengembangan konten berkelanjutan, pemanfaatan media sosial, peningkatan interaksi dengan pengguna, pelatihan dan pembinaan lanjutan, serta evaluasi dan pembaruan reguler terhadap website. Diharapkan workshop ini dapat menjadi langkah awal yang bermanfaat bagi Pesantren At Taubah Karawang dalam memanfaatkan teknologi digital untuk meningkatkan kualitas pendidikan dan pelayanan kepada masyarakat.
Performance Evaluation of Popular Supervised Learning Algorithms Towards Cardiovascular Disease Masruriyah, Anis Fitri Nur; Novita, Hilda Yulia; Sukmawati, Cici Emilia
Jurnal Informatika Universitas Pamulang Vol 8 No 3 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v8i3.34103

Abstract

Many studies have discussed the advantages of supervised learning for dealing with extensive data on heart disease. However, only a few studies evaluate the performance of supervised learning algorithms. This research builds a classification model using supervised learning algorithms, including C4.5, Random Forest, Logistic Regression, and Support Vector Machine. The data processed is in the form of category data with character data types. The accuracy, precision, and performance evaluation results show that the Logistic Regression Algorithm has the most superior value compared to the others. On the other hand, it was found that the C4.5 and SVM algorithms had anomalous events. Although the accuracy and precision values of C4.5 were superior to SVM, SVM had better performance.
Kompetensi Digital Guru-Guru Pesantren Al-Kautsar Melalui Pelatihan Teknologi Pendidikan Sukmawati, Cici Emilia; Juwita, Ayu Ratna; Latifah, Nurul; Khairani, Nova Pustita
Jumat Informatika: Jurnal Pengabdian Masyarakat Vol. 6 No. 1 (2025): April
Publisher : LPPM Universitas KH. A. Wahab Hasbullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32764/abdimasif.v6i1.5633

Abstract

The digital literacy skills of teachers in Islamic boarding schools are still low, especially in the use of technology to support learning activities and academic administration. One of the challenges faced is the lack of skills in using word processing software to systematically compile teaching materials and academic documents. This community service aims to improve the digital competence of Islamic boarding school teachers through training in the use of word processing software. The method used is a participatory approach with stages of planning, implementation of training based on direct practice, and evaluation through pre-tests and post-tests. This activity involves Islamic boarding school teachers as the main participants who receive intensive training in document creation and formatting, table management, and the use of automation features such as mass mailings and tables of contents. The results of the community service show an increase in participants' skills in operating word processing software, as indicated by an increase in post-test scores compared to the pre-test. In addition, this training also resulted in significant social changes, such as increased digital literacy of teachers, the emergence of individuals who act as mentors for colleagues, and the adoption of technology in academic administration. This program proves that a direct practice-based approach is effective in improving the digital skills of Islamic boarding school teachers. For the sustainability of the program, it is recommended that there be further training, a mentoring system between teachers, and technological infrastructure support so that the implementation of digital skills can take place optimally and sustainably.
Co-Authors Abigael, Rakha Amril Mutoi Siregar ARIF, SITI NOVIANTI NURAINI Baihaqi, Kiki Ahmad Bayu Prasetyo, Bayu Damaiarta Tejayanda, Rigger Faisal, Muhamad Agus Fitri Nur Masruriyah, Anis Gozali, Gozali Gumilar, Rizki Bintang Hanny Hikmayanti Handayani Iin Kurniawati Juwita, Ayu Ratna Khairani, Nova Pustita Mudzakir, Tohirin Al Novalia, Elfina Novita, Hilda Yulia Nurmayanti, Trisya nurul latifah Pratama, Adi Rizky RAMADHAN, ANGGA RAMDA Rohana, Tatang Saputra, Arbi Niandi Siregar, Amril Mutoi Tejayanda, Rigger Damaiarta Wahiddin, Deden Yana Cahyana