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All Journal MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Pilar Nusa Mandiri Jurnal Informasi dan Komputer JSAI (Journal Scientific and Applied Informatics) Journal of Applied Data Sciences Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS SWAGATI: Journal of Community Service
Sukmawati Anggraeni Putri, Sukmawati Anggraeni
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Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Mathematics Social Sciences Other

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Sistem Informasi Monitoring Perjanjian Kerja Sama Berbasis Web Pada PT Dayamitra Telekomunikasi Jakarta Marsuyitno, Marsuyitno; Putri, Sukmawati Anggraeni; Utami, Lilyani Asri; Dwiantoro, Tino
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 1 (2020): Januari 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i1.1497

Abstract

The development of the telecommunications world is developing very rapidly throughout the world and is no exception in Indonesia. The telecommunications business mostly involves companies providing equipment and providing telecommunications infrastructure, in this case, towers. PT Dayamitra Telekomunikasi or also known as Mitratel is a subsidiary of PT Telkom Indonesia. Tbk, which is engaged in providing telecommunications infrastructure in Indonesia. In carrying out its business activities, PT Dayamitra Telekomunikasi has collaborated extensively with external parties in terms of land use for the construction of telecommunications towers. Land use is currently divided into two land categories, namely private land and government land. The current condition in managing cooperative assets is still done manually or not systematically so that it is not effective and a monitoring information system is needed to monitor the use of assets listed in this cooperation document. The monitoring information system that will be created is web-based which will facilitate the user in monitoring, updating the status of the monetize point quota listed in the employment agreement document with the government. The software used in making this monitoring information system uses the PHP and MySQL programming languages.
Implementasi Algoritma Apriori Dalam Menentukan Penjualan Mobil Yang Paling Diminati Pada Honda Permata Serpong Anggraini, Dewi; Putri, Sukmawati Anggraeni; Utami, Lilyani Asri
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 2 (2020): April 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i2.1496

Abstract

The development of information technology is growing rapidly so that it enters various fields, the need for fast, accurate and accurate information is needed. But the fact is that high information needs are not balanced by the presentation of adequate information. Business development and competition are increasingly complex because consumers are very perspective making business people have to be smart in reading situations. So that business people can make a prediction of consumer interest to be used as a prediction of the company in making a decision, and change a strategy that is most appropriate for consumers. Decision makers try to utilize the available data warehouse, this encourages the emergence of new branches of science to overcome the extraction of information in very large amounts of data. To find out which Honda cars are most in demand by consumers, Data Mining techniques are required using the Apriori Algorithm method, and supported by the Tanagra Application by examining sales data for 1 year. Data Mining is an amalgamation of data analysis techniques, while Apriori Algorithm is the most frequently used method because it is very simple, easy and most widely proposed by some researchers, because there are two parameters namely Support Value and Confidence Value. Then the prediction results of the study found that Honda's car sales that most demanded by consumers were Brio Satya, HRV, Mobillio, Jazz, and CRV
Penerapan Finite State Automata Pada Vending Machine Susu Kambing Etawa Handayani, Kartika; Ismunandar, Dinar; Putri, Sukmawati Anggraeni; Gata, Windu
MATICS Vol 12, No 2 (2020): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v12i2.9270

Abstract

Susu kambing peranakan etawa merupakan susu bergizi tinggi yang memiliki banyak manfaat untuk tubuh manusia. Persebaran produk susu kambing etawa saat ini hanya sebatas penjualan di kendai atau market place sehingga manfaatnya belum merata dirasakan oleh masyarakat.Oleh karena itu, dirancang Vending Machine (VM) untuk penjualan susu kambing etawa untuk persebaran produk susu kambing etawa varian rasa menggunakan Finite State Automata (FSA)  jenis Non-Deterministic Finite Automata (NFA). FSA digunakan untuk menggambarkan alur logika VM susu kambing etawa ini. FSA merupakan mesin abstrak berupa sistem model matematika dengan masukan dan keluaran diskrit terdiri dari string dan label dengan output terdiri dari 0s dan 1s yang dapat mengenali bahasa paling sederhana (bahasa reguler) yang menangkap  pola dalam data dan dapat diimplementasikan secara nyata sehingga dapat dipahami oleh logika manusia. Dalam VM susu kambing etawa menggunakan FSA dilengkapi dengan dua metode pembayaran yaitu menggunakan uang tunai dan menggunakan e-money. Perancangan VM susu kambing etawa menggunakan FSA diharapkan dapat dikembangkan sehingga manfaat dari produk susu kambing etawa dapat dinikmati oleh masyarakat luas, khususnya masyarakat perkotaan.
ANALISA PEMILIHAN PLATFORM JASA PEMESANAN MAKANAN ONLINE METODE SAW Melati, Melati; Putri, Sukmawati Anggraeni
Jurnal informasi dan komputer Vol 11 No 01 (2023): Jurnal Informasi dan Komputer yang terbit pada tahun 2023 pada bulan 04 (April)
Publisher : LPPM Institut Teknologi Bisnis Dan Bahasa Dian Cipta Cendikia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35959/jik.v11i01.472

Abstract

Technology and Information is growing, including Information Technology in online food ordering service platforms. The presence of an online food ordering service platform is a means of connecting and technology that provides convenience for food entrepreneurs and consumers. Where Gofood, Grabfood, and Shopeefood are platforms that are often used by most people at this time. The growing number of online food ordering service platforms, makes it difficult for consumers to choose which platform provides a lot of convenience. Starting from delivery fees, discounted prices, speed of delivery and which platforms provide many restaurants. Therefore, the purpose of this research is to provide information to consumers or users of the online food ordering service platform to determine the best online food ordering service platform by applying calculations using the Simple Additive Weighting (SAW) method. Based on data collected through questionnaires, and through calculations using the Simple Additive Weighting (SAW) method, the best online food ordering service platform is Shopee food.
PENERAPAN FEATURE SELECTION PADA BAYESIAN NETWORK UNTUK PREDIKSI CACAT PERANGKAT LUNAK Putri, Sukmawati Anggraeni; Larasati, Dewi
Jurnal Pilar Nusa Mandiri Vol 13 No 2 (2017): Pilar Nusa Mandiri : Journal of Computing and Information System Periode Septemb
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1202.808 KB)

Abstract

Pada perkembangannya penelitian pada bidang prediksi cacat perangkat lunak, semakin banyak diminati oleh para peneliti. Untuk mengurangi biaya perawatan dan menjaga kualitas perangkat lunak. Salah satunya dengan, pemilihan modul cacat dan tidak cacat pada perangkat lunak menggunakan machine learning. Salah satunya adalah machine learning Bayesian Network, yang memiliki kinerja lebih baik dari Naive Bayesian. Seperti yang telah dilakukan pada penelitian ini, bahwa Bayesian Network dengan mengintegrasikan algoritma pemilihan atribute seperti Chi Square, Information Gain dan Relief. Model tersebut dapat menghasilkan tingkat akurasi hingga 0,9 % pada salah satu dataset Nasa yang digunakan pada penelitian ini. Oleh karenanya kinerja dan tingkat akurasi Bayesian Network pada prediksi cacat perangkat lunak sangat baik.
Physical Violence Detection System to Prevent Student Mental Health Disorders Based on Deep Learning Putri, Sukmawati Anggraeni; Rifai, Achmad; Nawawi, Imam
Jurnal Pilar Nusa Mandiri Vol 19 No 2 (2023): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v19i2.4600

Abstract

Physical violence in the educational environment by students often occurs and leads to criminal acts. Apart from that, repeated acts of physical violence can be considered non-verbal bullying. This bullying can hurt the victim, causing physical disorders, mental health, impaired social relationships and decreased academic performance. However, monitoring activities against acts of violence currently being carried out have weaknesses, namely weak supervision by the school. A deep Learning-based physical violence detection system, namely LSTM Network, is the solution to this problem. In this research, we develop a Convolutional Neural Network to detect acts of violence. Convolutional Neural Network extracts features at the frame level from videos. At the frame level, the feature uses long short-term memory in the convolutional gate. Convolutional Neural Networks and convolutional short-term memory can capture local spatio-temporal features, enabling local video motion analysis. The performance of the proposed feature extraction pipeline is evaluated on standard benchmark datasets in terms of recognition accuracy. A comparison of the results obtained with state-of-the-art techniques reveals the promising capabilities of the proposed method for recognising violent videos. The model that has been trained and tested will be integrated into a violence detection system, which can provide ease and speed in detecting acts of violence that occur in the school environment.
Sistem Cerdas Deteksi Tindak Kekerasan Untuk Pengawasan Perundungan Dengan Model Deep Learning Putri, Sukmawati Anggraeni; Rifai, Achmad; Nawawi, Imam
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 2 (2024): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i2.6451

Abstract

Bullying in schools is a severe problem that has both short- and long-term harmful implications for victims. However, surveillance of bullying, particularly acts of violence such as kicking, pushing, and striking at school, remains inadequate. Using Artificial Intelligence is one of the recommended solutions for detecting incidents of aggression in video footage. Deep learning methods, specifically Convolutional Neural Network and Long Short-Term Memory, are used in this study to construct Artificial Intelligence for detecting acts of aggression. The model can achieve an average accuracy of up to 92%. Based on these accuracy results, the model can be implemented into online intelligent applications. It is envisaged that sophisticated software that detect such acts of aggression will be effective in monitoring bullying incidents and reducing the number of bullying cases in schools.
PELATIHAN PENGGUNAAN APPSHEET UNTUK PENGELOLAAN ARSIP DIGITAL ORGANISASI DI JPRMI DKI Oktaviana R, Shinta; Kurniawati, Laela; Putri, Sukmawati Anggraeni; Utami, Lilyani Asri
Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Vol. 2 No. 3 (2024): Juni
Publisher : CV. Alina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59407/jpki2.v2i3.925

Abstract

Jaringan Pemuda Remaja Muslim Indonesia (JPRMI) Jakarta merupakan organisasi yang sudah cukup sering menjadi mitra pengabdian masyarakat dengan Universitas Nusa Mandiri. Organisasi ini merupakan organisasi sosial yang berangotakan remaja masjid se Jakarta. Di era teknologi digital, JPRMI Jakarta mulai mengganti arsip manual (hardcopy) menjadi arsip digital. Arsip digital menjadi salah satu elemen penting dalam pengelolaan organisasi modern. Appsheet merupakan salah satu aplikasi google yang menyediakan fitur-fitur untuk membuat suatu aplikasi tanpa harus mengerti dan melakukan pemrograman. Appsheet mampu mengotomisasi proses bisnis organisasi dengan menghubungkan semua dokumen digital yang tersedia pada aplikasi google. Untuk itu, kegiatan ini diharapkan dapat memberikan pengetahuan dan keterampilan bagi pengurus untuk pembuatan web organisasi dengan menggunakan data-data ditigal organisasi yang ada di spredsheet dan google drive menggunakan appsheet. Kegiatan ini dilakukan dalam bentuk pelatihan langsung kepada pengurus. Sehingga para pengurus mendapat keterampilan dalam menggunakan aplikasi appsheet. Hasil pelatihan diharapkan membantu meningkatkan kinerja oraganisasi dalam melakukan adaptasi teknologi informasi.
HU Variance Moment Optimizes Keyframe Selection Based on Deep Learning for Violence Detection Putri, Sukmawati Anggraeni; Andono, Pulung Nurtantio; Purwanto, Purwanto; Soeleman, Moch Arief
Journal of Applied Data Sciences Vol 6, No 2: MAY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i2.648

Abstract

Violence in public spaces poses a serious threat to individuals and society. Manual monitoring and violence detection require much time and human resources, ultimately hindering detection accuracy and speed. Therefore, an automated method is needed to detect violence to ensure fast and efficient action. Along with technological advances, violence detection research has adopted various methods and models, including deep learning, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs). In this study, the classification process for detecting violence and non-violence uses the VGG19 model, one of the CNN models that has good performance with limited computing. In addition, the Long Short-Term Memory (LSTM) model is the best RNN model for processing temporal data in videos. However, this performance will decrease with noise and irrelevant data in the classification process. Therefore, to optimize deep learning performance, this study in the pre-processing phase selects keyframes in frame extraction using the Hu Variance Moment Technique. This method calculates each frame’s Hu and Variance Moment values and selects keyframes based on high Hu values. Next, we use Adaptive Moment Estimation (Adam) to optimize the gradient of the selected keyframes. This study produces a Hu19LSTM model tested on three datasets: hockey fight, crowd, and AIRTLab. The proposed Hu19LSTM model produces an accuracy of 97% on the Hockey Fight dataset, 97% on the Crowd dataset, and 95% on the AIRTLab dataset. These results indicate that the Hu19LSTM model can increase its accuracy on the hockey fight and Crowd dataset by 97%.
Pelatihan Perancangan UI/UX Aplikasi Arsip Digital Bagi PKK Kelurahan Ragunan Kurniawati, Laela; Utami , Lilyani Asri; Oktaviana , Shinta; Putri, Sukmawati Anggraeni
SWAGATI : Journal of Community Service Vol. 1 No. 3 (2023): November
Publisher : Universitas AMIKOM Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24076/swagati.2023v1i3.1081

Abstract

Dalam menjalankan operasional pekerjaan, PKK Kelurahan Ragunan telah memanfaatkan TIK untuk mendukung dan memfasilitasi dalam menyelesaikan kegiatan administrasif kepada masyarakat. Pengelolaan arsip oleh pengurus PKK Kelurahan Ragunan masih dilakukan secara konvensional melalui pencatatan buku besar, hal ini dapat mengurangi efektivitas dan memperpanjang proses pengelolaan administrasi. Untuk merancang sebuah prototipe aplikasi arsip digital, maka harus memiliki User Interface dan User Experience (UI/UX) pengguna yang baik sehingga pengguna tidak kesulitan dalam mengoperasionalkan aplikasi yang telah dirancang dan mendapatkan pengalaman yang mengesankan oleh pengguna setelah menggunakan prototipe tersebut. Pelatihan desain menggunakan Aplikasi Figma yang dapat diakses gratis pada web untuk membuat desain interface. Kegiatan ini diharapkan menjadi kontribusi ilmu dan keterampilan bagi peserta untuk dapat mengimplementasikan suatu rancangan aplikasi yang dinamis, interaktif, dan user friendly sebelum membangun aplikasi arsip digital sehingga membantu petugas arsip dalam mengelola seluruh data yang akan menjadi value penting bagi pihak yang berkepentingan.
Co-Authors ACHMAD RIFAI Dewi Anggraini Dewi Larasati, Dewi Dinar Ismunandar Dwiantoro, Tino Gata, Windu Imam Nawawi, Imam Kartika Handayani Laela Kurniawati, Laela Lilyani Asri Utami, Lilyani Asri Marsuyitno, Marsuyitno Melati Melati Moch Arief Soeleman, Moch Arief Oktaviana , Shinta Oktaviana R, Shinta Pulung Nurtantio Andono Purwanto Purwanto Utami , Lilyani Asri