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All Journal Jurnal Buana Informatika Perspektif : Jurnal Ekonomi dan Manajemen Universitas Bina Sarana Informatika Jurnal Teknik Komputer AMIK BSI Jurnal Teknik Informatika UNIKA Santo Thomas Jurnal Manajemen Informatika Jurnal Riset Informatika EVOLUSI : Jurnal Sains dan Manajemen Jurnal Informatika dan Rekayasa Elektronik JATI (Jurnal Mahasiswa Teknik Informatika) Abditeknika - Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Indonesian Journal Computer Science (ijcs) Abdi Teknoyasa Jurnal Aruna Mengabdi (ARMI)

Risa Wati - AMIK BSI Tasikmalaya Risa Wati - AMIK BSI Tasikmalaya

Universitas Bina Sarana Informatika

Author-ID : 1128107

Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Environmental Science Languange, Linguistic, Communication & Media Public Health Social Sciences Other

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Penerapan Metode Simple Additive Weighting Pada Sistem Pendukung Keputusan Pengangkatan Karyawan Berbasis Web Siti Ernawati; Risa Wati
JURNAL TEKNIK KOMPUTER Vol 5, No 2 (2019): JTK - Periode Agustus 2019
Publisher : Universitas Bina Sarana Informatika

The success or failure of a company depends on the human resources in the company. The quality of every human resource is needed to improve performance productivity. The process of appointing permanent employees is something that is often done by companies, one of the reasons is the company's appreciation of employee performance. For this reason, the process of appointing employees is more professional, so a decision support system is needed to assist in selecting employees who deserve to be appointed as permanent employees. The method will be applied in this research is simple additive weighting (SAW). SAW method is selected because it is very simple, can determine the value of weight then determine the ranking of the results of normalization. There are ten criteria and weights for each of the criteria used in this research. The purpose of this research is to design and create a web based information system as a tool for decision making in the process of appointment employees. It is hoped that this information system will benefit for the company so hat the employee appointment process do optimally and the time is more efficient.

Penerapan Algoritma Genetika Untuk Seleksi Fitur Pada Analisis Sentimen Review Jasa Maskapai Penerbangan Menggunakan Naive Bayes Risa Wati - AMIK BSI Tasikmalaya
Evolusi : Jurnal Sains dan Manajemen Vol 4, No 1 (2016): Jurnal Evolusi 2016
Publisher : Universitas Bina Sarana Informatika

Abstract - The quality of airline services can be seen from any opinions or reviews on passengers before. This reviewer classification grouped into positive opinion and a negative opinion. Data mining classification algorithm used is Naive Bayes are widely used in research because it serves well as a text classifier method however has the disadvantage that is very sensitive in the selection of features. Genetic Algorithm (GA) is one of the optimization algorithms, which is invented to mimic some of the processes observed in natural evolution. After testing the two models, namely models Naive Bayes algorithm and Naive Bayes algorithm based on the results obtained GA is Naive Bayes algorithm produces an accuracy of 60.00% while for Naive Bayes algorithm based on GA value amounted to 89.50% accuracy. Difference in value by 29.5% accuracy and included into the category of excellent classification. Keywords: Sentiment Analysis, Review, Naive Bayes, Text Classification Abstrak - Kualitas layanan maskapai dapat dilihat dari pendapat atau review penumpang sebelumnya. Klasifikasi resensi ini dikelompokkan menjadi opini positif dan pendapat negatif. algoritma klasifikasi data mining yang digunakan adalah Naive Bayes secara luas digunakan dalam penelitian karena berfungsi juga sebagai metode classifier teks namun memiliki kelemahan yang sangat sensitif dalam pemilihan fitur. Algoritma genetik (GA) merupakan salah satu algoritma optimasi, yang diciptakan untuk meniru beberapa proses yang diamati dalam evolusi alam. Setelah menguji dua model, yaitu model algoritma Naive Bayes dan algoritma Naive Bayes berdasarkan hasil yang diperoleh GA adalah algoritma Naive Bayes menghasilkan akurasi 60,00% sedangkan untuk algoritma Naive Bayes berdasarkan nilai GA sebesar akurasi 89,50%. Selisih nilai dengan akurasi 29,5% dan termasuk ke dalam kategori klasifikasi sangat baik.Kata Kunci: Analisis Sentimen, Ulasan, Naif Bayes, Klasifikasi Teks

Pelatihan Dasar Aplikasi Desain Grafis Bagi Anak-Anak Santri Pesantren Penghafal Al Quran Nahwa Nur Hilda Rachmi; Ahmad Fauzi; Imam Nawawi; Risa Wati; Widi Intan Priyanti; Siti Hani Nurlaela
Abditeknika Jurnal Pengabdian Masyarakat Vol. 2 No. 1 (2022): April 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/abditeknika.v2i1.1146

Pesantren Penghafal Al Quran Nahwa Nur terletak di desa Sukmajaya Kecamatan Tajur Halang Kota Bogor. Anak-anak santri Pesantren Penghafal Al Quran Nahwa Nur memerlukan kemampuan di bidang desain grafis untuk meningkatkan keterampilan dalam kreatifitas desain grafis agar tidak hanya berprestasi dalam hafalan alquran saja tapi juga dapat berprestasi di bidang seni desain grafis. Pelaksanaan pengabdian kepada masyarakat ini bertujuan untuk memberikan pemahaman dan wawasan kepada anak-anak santri Pesantren Penghafal Al quran Nahwa Nur mengenai teknik Desain Grafis yang mana pelaksanaanya akan dilakukan secara dalam jaringan. Peserta akan dilatih bagaimana cara memanipulasi gambar mendesain gambar baru, dan menggunakan tools pada aplikasi desain grafis. Dengan pemberian pelatihan ini anak-anak santri pesantren penghafal Al Quran Nahwa Nur akan memiliki keahlian dalam bidang desain grafis. Evaluasi kegiatan dilakukan melalui survey kepuasan peserta. Dari hasil survey didapatkan hasil kepuasan peserta sebesar 99,41%.

Support Vector Classification with Hyperparameters for Analysis of Public Sentiment on Data Security in Indonesia Siti Ernawati; Risa Wati; Nuzuliarini Nuris
Jurnal Riset Informatika Vol 5 No 1 (2022): Priode of December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.481

The development of Information Technology makes increasing use of the internet. This raises the vulnerability of data security. Cyber attacks in Indonesia caused many tweets on social media Twitter. Some are positive, and some are negative. The problem of this study is to determine the public sentiment towards data security in Indonesia, while the purpose of this study is how the response or evaluation of the government of Indonesia to the many perceptions of people who lack confidence in data security in Indonesia. Data obtained from twitter with as much as 706 data was processed using python with a percentage of 10% test data and 90% training data. Weighting is done using TF-IDF, and then the Data is processed using the Support Vector Machine algorithm using the SVC (Support Vector Classification) library. Support Vector Classification with RBF kernel classifies Text well to obtain AUC value with good classification category. Utilizing one of the hyperparameter techniques, which is a grid search technique that can compare the accuracy of test results. The test results using SVC with RBF kernel obtained an accuracy value of 0.87, Precision of 0.82, recall of 0.94, and F1_Score of 0.87. This study is expected to be used by decision-makers related to public confidence in data security in Indonesia

Pembobotan TF-IDF Menggunakan Naïve Bayes pada Sentimen Masyarakat Mengenai Isu Kenaikan BIPIH Risa Wati; Siti Ernawati; Hilda Rachmi
Jurnal Manajemen Informatika JAMIKA Vol 13 No 1 (2023): Jurnal Manajemen Informatika (JAMIKA)
Publisher : Program Studi Manajemen Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jamika.v13i1.9424

The Ministry of Religious Affairs proposes to increase the cost of Hajj Travel (Bipih) in 1444 H/2023 M to Rp.69.19 million. There is a fairly high increase in costs compared to 2022. This raises sentiment in the community, there are public opinions for and against the issue of rising Bipih on social media twitter. The purpose of this study was to analyze the sentiment on the issue of increasing the cost of Hajj Travel and to prove whether Naive Bayes is a good classifier of text on the issue of incremental sentiment. Naive Baye is one of the best text classifier algorithms. Data taken from social media twitter. The Data are grouped into pro and Contra opinions and then processed using python programming language and jupyter as text editor. Data used as much as 850 data. The Data is divided into training data and testing data with a ratio of 80:20. With the number of training data of 679 data and the number of testing data of 170 data. Then implement Multinominal Naive Bayes algorithm (MNB) as text classifier and word weighting using TF-IDF. The test results obtained accuracy value of 89% and ROC value of 0.91. It is proven that Multinominal Naive Bayes algorithm (MNB) is a good classifier of text for sentiment analysis of opinion on the issue of increasing the cost of Hajj travel because it is included in the Excellent Classification.

Pelatihan Google Spreadsheet Untuk Mempermudah Pekerjaan Bagi PKK Kelurahan Paledang Risa Wati; Ahmad Fauzi; Imam Nawawi; Hilda Rachmi; Silvy Nur Azizah
Jurnal Aruna Mengabdi Vol. 1 No. 1 (2023): Periode Mei 2023
Publisher : Lotus Aruna Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61398/armi.v1i1.4

Di Kecamatan Bogor Tengah, Kota Bogor terdapat Kelurahan Paledang. Salah satu kegiatan kelompok Ibu-ibu PKK di Kelurahan Paledang adalah melakukan sensus terhadap jenis pekerjaan seluruh warga Kelurahan Paledang. Pengolahan data masih dilakukan secara manual yang memakan waktu lama dan kurang efisien. Oleh karena itu, diperlukan kegiatan Pengabdian kepada Masyarakat. Kegiatan ini bertujuan untuk membantu kelompok Ibu-ibu PKK di Kelurahan Paledang dalam pengolahan data menggunakan Microsoft Excel melalui Google Spreadsheet melalui media handphone, sehingga pengolahan data dapat dilakukan oleh siapa saja, kapan saja, dan di mana saja, sambil tetap menjaga kerahasiaan informasi. Pengabdian masyarakat dilaksanakan dengan cara penyampaian materi secara langsung dan memberikan pelatihan dalam penggunaan Google Spreadsheet

Pengolahan Data Akuntansi Menggunakan MYOB Accounting V16 (Studi Kasus: PT ICSM Indonesia) Riani, Meifana Regita; Wati, Risa
Perspektif : Jurnal Ekonomi dan Manajemen Akademi Bina Sarana Informatika Vol 18, No 1 (2020): Maret 2020
Publisher : www.bsi.ac.id

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jp.v18i1.6819

PT ICSM Indonesia merupakan salah satu bentuk organisasi di bidang jasa sertifikasi ISO, pengolahan data akuntansi pada PT ICSM Indonesia di nilai belum efektif dimana pencatatan pengolahan data akuntansinya masih di catat dalam Microsoft Excel sehingga memperlambat dalam mengambil keputusan bisnis. Penelitian ini bertujuan untuk mengetahui sistem yang sedang berjalan, melakukan analisis dan pengujian sistem serta untuk melakukan implementasi pengolahan data akuntansi. Penelitian ini berguna untuk membangun sistem pengolahan data akuntansi pada PT ICSM Indonesia. Metode penelitian yang dilakukan meliputi metode observasi terhadap sistem yang berlaku, metode wawancara dengan manager keuangan yang menangani masalah pengolahan data keuangan, serta metode studi pustaka dengan melakukan penelitian kepustakaan yang relevan dengan masalah pengolahan data akuntansi. Dalam pengolahan data akuntansi peneliti menggunakan MYOB Accounting V16. Sehingga sistem keuangan manual yang ada dapat digantikan dengan sistem terkomputerisasi yang bertujuan untuk membangun sistem akuntansi yang terkomputerisasi sehingga memudahkan PT ICSM Indonesia dalam melakukan pengolahan data akuntansi.

ANDROID-BASED QURAN APPLICATION ON THE FLUTTER FRAMEWORK BY USING THE FOUNTAIN MODEL Siti Ernawati; Risa Wati
Jurnal Riset Informatika Vol. 3 No. 2 (2021): March 2021 Edition
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v3i2.64

Abstract With the development of technology, smartphones have become one of the communication tools and can be used as a tool entertainer. But smartphones have an impact on the declining interest in reading the Quran. It would be a good smartphone that can be used to remember the creator is to create a Quran application on android so that users do not need to carry the mushaf Quran while on the go. The purpose of the construction of the application is to always remember to the god that is by the way can read Quran whenever and wherever are. The Model used to build the application Model is the Fountain where at the time of building the application can be done in overlap by the needs. Quran application built using. net framework flutter with the programming language dart. To install the application at least the Android version used is version 5.0 Lollipop. Testing the application of the Quran using black-box testing. Give the questionnaire to potential users of the application to assess the feasibility of the application of the Quran. From the results of the questionnaire can be concluded that the application of the Quran is very user friendly and with the audio playing over and over can help the user to memorize the Quran.

Support Vector Classification with Hyperparameters for Analysis of Public Sentiment on Data Security in Indonesia Siti Ernawati; Risa Wati; Nuzuliarini Nuris
Jurnal Riset Informatika Vol. 5 No. 1 (2022): December 2022
Publisher : Kresnamedia Publisher

The development of Information Technology makes increasing use of the internet. This raises the vulnerability of data security. Cyber attacks in Indonesia caused many tweets on social media Twitter. Some are positive, and some are negative. The problem of this study is to determine the public sentiment towards data security in Indonesia, while the purpose of this study is how the response or evaluation of the government of Indonesia to the many perceptions of people who lack confidence in data security in Indonesia. Data obtained from twitter with as much as 706 data was processed using python with a percentage of 10% test data and 90% training data. Weighting is done using TF-IDF, and then the data is processed using the Support Vector Machine algorithm using the SVC (Support Vector Classification) library. Support Vector Classification with RBF kernel classifies Text well to obtain AUC value with good classification category. Utilizing one of the hyperparameter techniques, which is a grid search technique that can compare the accuracy of test results. The test results using SVC with RBF kernel obtained an accuracy value of 0.87, Precision of 0.82, recall of 0.94, and F1_Score of 0.87. This study is expected to be used by decision-makers related to public confidence in data security in Indonesia.

Evaluasi Performa Kernel SVM dalam Analisis Sentimen Review Aplikasi ChatGPT Menggunakan Hyperparameter dan VADER Lexicon Ernawati, Siti; Wati, Risa
Jurnal Buana Informatika Vol. 15 No. 01 (2024): Jurnal Buana Informatika, Volume 15, Nomor 01, April 2024
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jbi.v15i1.7925

ChatGPT merupakan model bahasa kecerdasan buatan yang merespon pertanyaan dan pernyataan pengguna. ChatGPT memiliki manfaat dan kelemahan bagi pengguna. Hal ini menimbulkan komentar pada media sosial tentang manfaat dari ChatGPT. Penelitian ini membahas tentang analisis sentimen review aplikasi ChatGPT menggunakan SVM kernel linier, RBF, polinomial dan sigmoid. Pelabelan menggunakan VADER lexicon dan hyperparameter untuk menghasilkan parameter terbaik. Tujuan penelitian yaitu apakah aplikasi ChatGPT dapat memberikan manfaat dan membuktikan apakah kernel pada SVM dapat meningkatkan nilai akurasi. Diskenariokan persentase pembagian antara data uji dan data latih adalah 70:30, 80:30, dan 90:10. Setelah dilakukan preprocessing, kemudian dikelompokkan menjadi review positif dan negatif. Dilakukan hyperparameter terhadap parameter C dan Gamma sehingga menghasilkan nilai maksimal. Hasil eksperimen diperoleh akurasi tertinggi menggunakan SVM kernel RBF skenario 90:10 dengan nilai accuracy 92.72%, precision 92.44%, f1-score 96.10% dan AUC 88%.

Co-Authors Ahmad Fauzi Akrom, Akrom Armahwati, Armahwati Ernawati*, Siti Ernawati, Siti Fauzi Ahmad Muda Fitriansyah, Lambang Hadidinar Hani, Siti Hasanudin Hasanudin Hilda Rachmi Ilham Maulana Ilham Maulana Imam Nawawi Imam Nawawi, Imam Nurlaela, Siti Hani Nuzuliarini Nuris Pranata, Fitano Priyanti, Widi Intan Ratih Yulia Hayuningtyas Riani, Meifana Regita Silvy Nur Azizah Siti Ernawati Siti Hani Nurlaela Widi Intan Priyanti

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