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All Journal International Journal of Electrical and Computer Engineering International Journal of Advances in Applied Sciences Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmiah Informatika Komputer Jurnal Psikologi Jurnal Ilmiah Teknologi dan Rekayasa Prosiding KOMMIT Prosiding PESAT Majalah Ilmiah Matematika Komputer Majalah Ilmiah Ekonomi Komputer TELKOMNIKA (Telecommunication Computing Electronics and Control) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer JUITA : Jurnal Informatika Jurnal Ilmiah KOMPUTASI Sistemasi: Jurnal Sistem Informasi Computatio : Journal of Computer Science and Information Systems Jurnal Ilmiah FIFO Informatika Pertanian JURNAL MANAJEMEN INFORMATIKA (JUMIKA) Prosiding Seminar Nasional Darmajaya Petir JUTEKIN (Jurnal Manajemen Informatika) Energy : Jurnal Ilmiah Ilmu-Ilmu Teknik Journal of Information System, Applied, Management, Accounting and Research Dinasti International Journal of Education Management and Social Science Jurnal Nasional Teknologi Komputer Jurnal Sistem Informasi International Journal Multidisciplinary Science
Dewi Agushinta R.
Gunadarma University
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences

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AUDIT SISTEM INFORMASI PERPUSTAKAAN UNIVERSITAS MUHAMMADIYAH KALIMANTAN TIMUR MENGGUNAKAN FRAMEWORK COBIT 5 fahrullah fahrullah; dewi agushinta r
JUTEKIN (Jurnal Teknik Informatika) Vol 6, No 1 (2018): JUTEKIN
Publisher : LPPM STMIK DCI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51530/jutekin.v6i1.207

Abstract

Universitas Muhammadiyah Kalimantan Timur telah menerapkan penggunaan teknologi informasi sebagai penunjang dalam hal pelayanan akademik yang diperuntukan bagi seluruh civitas akademika, salah satu sistem informasi yang telah diterapkan adalah sistem informasi perpustakaan yang ditangani oleh Perpustakaan Universitas Muhammadiyah Kalimantan Timur. Untuk mengatur sistem informasi itu sendiri memerlukan audit yang bertujuan untuk mengevaluasi dan memastikan pemenuhannya ditinjau dari pendekatan objektif dari suatu standar. Sistem Informasi Perpustakaan di Universitas Muhammadiyah Kalimantan Timur memerlukan audit untuk mengevaluasi, menilai kapabilitas, dan menyusun rekomendasi terhadap sistem informasi yang dipakai. Framework audit yang digunakan adalah COBIT 5 domain DSS (Deliver, Service, dan Support) yang fokus pada penilaian pengiriman dan layanan teknologi informasi serta dukungannya termasuk pengelolaan masalah agar keberlanjutan layanan tetap terjaga.Kata Kunci: audit, COBIT 5, domain DSS, Sistem Informasi Perpustakaan, Universitas Muhammadiyah Kalimantan Timur
Model Structure of Fetal Health Status Prediction Emirul Bahar; Dewi Agushinta R.; Yuti Dewita Arimbi; Mariono Reksoprodjo
JUITA : Jurnal Informatika JUITA Vol. 10 No. 2, November 2022
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1249.11 KB) | DOI: 10.30595/juita.v10i2.12179

Abstract

One of the issues of pregnant mothers in Indonesia is their access speed and accuracy services availability towards the prediction of fetus or baby conceived during pregnancy. Thus, the research aimed to obtain the ability to predict three ranges of a fetal target, namely normal, risk, and abnormal condition. This research emphasized the modeling aspect of supervised learning using seven different algorithms to obtain an optimal working score. Those are Decision Tree, Gradient Boosting, Random Forest, SVM, k-NN, AdaBoost, and Stochastic Gradient Descent (SGD). The structure process is mainly divided into two steps, pre-process model and the prediction model. An early data pre-process is needed before executing. Prediction output indicated that dataset test is valid, and can be proven by comparing between the testing data table and prediction and testing table diagram. The resulting model has described the sequence for simulating the training and testing data model to produce the highest working score from the seven selected algorithms. The simulated data based on the model created is proved its validity thru three main filter processes, which are missing data solution, outlier data control, and data normalization. The result obtained a working score that has data proximity with a low score range of 0.063 from model evaluation, confusion matrix, and prediction output.
KIMCHI: Aplikasi Pembelajaran Bahasa Korea Berbasis Android dengan Fitur Latihan Menulis HANGUL Hanifah Aprilia Nur’aini; Dewi Agushinta R.
Jurnal Ilmiah Komputasi Vol. 21 No. 1 (2022): Jurnal Ilmiah Komputasi Volume: 21 No. 1, Maret 2022
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32409/jikstik.21.1.2897

Abstract

Penulis, mohon diisi
Analisis Sentimen Twitter Terhadap Pembayaran ShopeePayLater Pada Aplikasi Belanja Online (Shopee) Menggunakan Metode Lexicon Based Dan Naive Bayes Classifier: Array Indira Mahayani; Dewi Agushinta R.; Muhammad Edy Supriyadi
Jurnal Ilmiah Komputasi Vol. 19 No. 4 (2020): Jurnal Ilmiah Komputasi Volume: 19 No. 4, Desember 2020
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32409/jikstik.19.4.293

Abstract

Shopee adalah sebuah aplikasi yang bergerak di bidang jual beli secara online dan dapat diakses secara mudah dengan menggunakan smartphone. Pada aplikasi Shopee terdapat fitur PayLater yaitu belanja terlebih dahulu dan membayar di awal bulan. Fitur PayLater pada aplikasi Shopee dinamakan ShopeePayLater. Setiap pengguna baru yang ingin menggunakan fitur ShopeePayLater, memiliki kemungkinan ingin mengetahui reaksi dari pengguna sebelumnya pada twitter berupa tweets yang telah menggunakan fitur ShopeePayLater. Sebuah analisis sentimen diperlukan untuk mengetahui opini pengguna mengenai seberapa besar fitur ShopeePayLater ini dapat memberikan kemudahan kepada pengguna. Tahapan proses analisis sentimen ini adalah pengambilan data (crawling), text pre-processing, klasifikasi sentimen yang terdiri dari metode lexicon Based dan Naïve Bayes Classifier serta penyusunan hasil analisis sentimen. Perhitungan pada penelitian ini menggunakan perhitungan tingkat keakurasian pengujian confusion matrix lalu hasil yang didapat berupa sentimen aktual sebesar 82,52 % dan kesalahan sistem atau error rate sebesar 17,48 %. Presisi positif sebesar 89,54 %, presisi negatif sebesar 47,06 %, dan recall sebesar 89,54 %. Hasil analisis sentimen pada penelitian ini menunjukkan bahwa pembayaran menggunakan ShopeePayLater memiliki kecenderungan sentimen positif pada saat data tweets diambil.
Identification of mangrove tree species using deep learning method Paranita Asnur; Rifki Kosasih; Sarifuddin Madenda; Dewi A. Rahayu
International Journal of Advances in Applied Sciences Vol 12, No 2: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v12.i2.pp163-170

Abstract

Artificial intelligence can help classify plants to make identification easier for everyone. This technology can be used to classify mangrove trees. The degradation of mangrove forests has resulted in a 20% loss of biodiversity, an 80% loss of microbial decomposers, reduced C-organic soil, and fish spawning grounds, resulting in estimated losses in the ecological and economic fields for up to IDR 39 billion. The identification of different mangrove species is the first step in ensuring the preservation of these forests. Therefore, this research aimed to develop algorithms and a convolutional neural network (CNN) architecture to classify mangrove tree species with the highest possible accuracy using Python software. The architecture selection for this model includes a batch size of 32, an input image size of 128x128 pixels, four classes, four convolution layers, four rectified linear unit (ReLU) layers, 2x2 max-pooling, and two fully connected layers (FCL). The finding showed that the resulting accuracy from the test was 97.50%, while the validation test was 81.25%, applied to four types of mangrove leaves, including Avicenia marina, Avicenia officialis, Rizophora apiculata, and Soneratia caseolaris.
Identification of mangrove tree species using deep learning method Paranita Asnur; Rifki Kosasih; Sarifuddin Madenda; Dewi A. Rahayu
International Journal of Advances in Applied Sciences Vol 12, No 2: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v12.i2.pp163-170

Abstract

Artificial intelligence can help classify plants to make identification easier for everyone. This technology can be used to classify mangrove trees. The degradation of mangrove forests has resulted in a 20% loss of biodiversity, an 80% loss of microbial decomposers, reduced C-organic soil, and fish spawning grounds, resulting in estimated losses in the ecological and economic fields for up to IDR 39 billion. The identification of different mangrove species is the first step in ensuring the preservation of these forests. Therefore, this research aimed to develop algorithms and a convolutional neural network (CNN) architecture to classify mangrove tree species with the highest possible accuracy using Python software. The architecture selection for this model includes a batch size of 32, an input image size of 128x128 pixels, four classes, four convolution layers, four rectified linear unit (ReLU) layers, 2x2 max-pooling, and two fully connected layers (FCL). The finding showed that the resulting accuracy from the test was 97.50%, while the validation test was 81.25%, applied to four types of mangrove leaves, including Avicenia marina, Avicenia officialis, Rizophora apiculata, and Soneratia caseolaris.
DESIGN OF MOBILE EXPERT SYSTEM FOR DIABETES RISK DIAGNOSIS AND INFORMATION Anindito Yoga Pratama; Dewi Agushinta R.; Remi Senjaya
Jurnal Sistem Informasi Vol. 9 No. 1 (2013): Jurnal Sistem Informasi (Journal of Information System)
Publisher : Faculty of Computer Science Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (623.123 KB) | DOI: 10.21609/jsi.v9i1.344

Abstract

Along with the development of information technology, mobile applications are widely applied to various fields. The use of mobile applications is considered effective to help user in understanding the problem. One example of the application of mobile applications needed today is an application that can help to determine a wide range of health. The designs discussed in this paper are the structure of the navigation and layout design of mobile applications created. There is a navigation structure and eight layout designs such as splash screen page, main menu page, diabetes risk test page, result page, diabetes prevention info page, food information page, list of hospitals page, and help page. The purpose of this paper is to design of mobile application for diabetes risk diagnosis and information based on android.
ASSOCIATION RULE ANALYSIS OF FP-GROWTH ALGORITHM ON DRUG PURCHASE PATTERNS Dewi Agushinta R.; Mega Maralisa Putri
Jurnal Ilmiah Teknologi dan Rekayasa Vol 27, No 3 (2022)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/tr.2022.v27i3.4626

Abstract

Salah satu teknik data mining adalah Association Rule yang sering disebut dengan prosedur Market Basket Analysis untuk mencari pengetahuan tentang pola pembelian konsumen. Riset ini menggunakan algoritma Frequent Pattern Growth (FP-Growth). FP-Growth dalam membentuk itemset dilakukan dengan membuat struktur data FP-Tree. Data yang digunakan memanfaatkan transaksi Klinik selama dua tahun. Analisis dilakukan untuk mempertimbangkan keputusan bagi pemangku kepentingan informasi di Klinik. Hasilnya diperoleh 118 rule dengan nilai minimal 30% support dan 75% confidence. Aturan yang dihasilkan 100% jika beli INJ Piralen maka beli INJ Ranitidine, 100% jika beli Genoint maka beli Genoint SK, jika beli Gastritis Cap maka beli 100% Myalgia Cap, jika beli Sanbe SP NACL Liquid maka beli 100% Glucose Dextrose Liquid, kalau beli Omecidal beli Omedeson 100%, dan kalau beli Omeprazole beli Gludepatik 87%. Riset ini membantu pemilik Klinik menentukan pola dan menampilkan obat yang paling laris dibeli konsumen.
Analisis Tingkat Korelasi Variabel Penilaian Perilaku Kerja Pegawai Dengan Metode Regresi Linier Berganda Armita Widyasuri; Lintang Yuniar Banowosari; Dewi Agushinta Rahayu
Jurnal Ilmiah Komputasi Vol. 22 No. 3 (2023): Jurnal Ilmiah Komputasi : Vol. 22 No 3, September 2023
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32409/jikstik.22.3.3388

Abstract

Komponen penilaian kinerja PNS terdiri dari aspek hasil yakni Sasaran Kinerja dengan bobot 60 % dan aspek Perilaku dengan bobot 40 %. Permasalahan terjadi pada penilaian aspek perilaku pada instansi BKN penilaian ini dilakukan berdasarkan orientasi pelayanan, komitmen, disiplin, integritas, dan kerjasama tetapi penilaian masih bersifat subyektif karena tidak memiliki acuan yang pasti. Penelitian ini menggunakan metode analisis regresi linier berganda. Tingkat korelasi pada pegawai dengan jabatan fungsional dan struktural menunjukkan terdapat hubungan linier positif antara setiap variabel independen terhadap variabel dependen. Disimpulkan bahwa hasil pengujian signifikansi antara orientasi pelayanan, disiplin, komitmen, dan kerjasama terhadap integritas pada jabatan fungsional dan hasil pengujian signifikansi antara orientasi pelayanan, disiplin, kerjasama, dan kepemimpinan pada jabatan sturuktural memiliki pengaruh signifikan sehingga semakin baik variabel tersebut diterapkan, semakin tinggi kemampuan pegawai dalam bertindak sesuai dengan nilai, normal, dan etika. Sedangkan hasil pengujian signifikansi untuk variabel komitmen pada jabatan struktural tidak terdapat pengaruh yang signifikan.
CONCEPTUAL REGIONAL ORIGIN RECOGNITION USING CNN CONVOUTION NEURAL NETWORK ON BANDUNG, BOGOR AND CIREBON REGIONAL ACCENTS Adam Huda Nugraha; Achmad Benny Mutiara; Dewi Agushinta Rahayu
International Journal Multidisciplinary Science Vol. 2 No. 2 (2023): June: International Journal Multidiciplinary
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijml.v2i2.696

Abstract

Sound detection is a challenge in machine learning due to the noisy nature of signals, and the small amount of (labeled) data that is usually available. The need for sound detection in Indonesia is quite important because there are many community organizations that form groups according to the land of their origin. Especially in big cities, where people from various tribes gather and exchange cultures. However, it has a disadvantage that affects these tribes, namely the loss of the original culture of certain areas. The Sundanese are the object of this research, including Bandung, Bogor and Cirebon. Voice data is divided into 2 types, namely male and female, each region consists of 50 respondents with 25 male and female voices with a maximum voting time of 1 minute. The method used is CNN architecture based on supervised learning, preprocessing using MFCC (Mel Frequency Cepstral Coefficients) to obtain feature extraction from voice data. CNN architecture is carried out 3 times convolution with max pooling and dropout on each convolution.
Co-Authors -, Hustinawaty Achmad Benny Mutiara Adam Huda Nugraha Aditia Arga Pratama Ahmad Hidayat Akbar, Rizky Alif Ahmad Syamsudduha Andi Shahreza Harahap Anggari, Elevanita Anindito Yoga Pratama Anindito Yoga Pratama Anindito Yoga Pratama Anindito Yoga Pratama Antonius Angga Kurniawan Ardhani Reswari Yudistari Armita Widyasuri Barchia, Azerwin Besty Ghina Cyntya Widyarsih Delvita Dita Putri Anggrayni Diana Tri Susetianigtias Dini Sundani Dyah Pratiwi Emirul Bahar Ety Sutanty Fajar Nugraha Ferina Ferdianti Gagah Lanang Ramadhan Grace Desi Geoloni Hafiz Ma'ruf Hanifah Aprilia Nur’aini Haniyah Haniyah Hardianti, Ayu Harya Iswara A.W. Henny Medyawati Henny Medyawati Henri Muel Herry Sussanto Hustinawaty Hustinawaty, Hustinawaty Ihsan Jatnika Ika Setiowati Suprihatin Indira Mahayani Irwan Bastian Jhordy Wong Johanna Sindya Widjaya Jonathan Hindharta Khoirul Islam Lia Ambarwati Lintang Yuniar Banowosari Lintang Yuniar Banowosari M. Abdul Mukhyi Mariono Reksoprodjo Martina Octavia Mega Maralisa Putri Metty Mustikasari Muhammad Edy Supriyadi Murniyati Murniyati Neneng Winarsih Nursanta, Edy Octavia, Martina Paujiah, Syifah Putri, Rizka Yulianti Regy Dwi Septian Remi Senjaya Remi Senjaya riamande jelita tambunan Rifki Kosasih Rindani, Fiena Rizka Yulianti Putri Rodiah Rodiah Rr. Dharma Tintri Edi Raras Rustam M. Ali Sandi Agung Sarifuddin Madenda Satria, Agung Sigit Widiarto Soeltan Zaki Sova, Erma Sri Rahayu Puspita Sari sugrio dwi darmawan Suryadi H. S. Suryadi Harmanto Trihapningsari, Denisha Vega Valentine Yahya Novi Andi Cuhwanto Yoga Yuniadi Yogi Oktopianto Yurista Vipriyanti Yusuf Triyuswoyo Yuti Dewita Arimbi