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All Journal Jurnal Informatika Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Nasional Komputasi dan Teknologi Informasi J-Intech (Journal of Information and Technology) Journal of Information Technology
Syntia Widyayuningtias Putri Listio
STIKI Malang
Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Library & Information Science Neuroscience Transportation

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PENGUJIAN PERFORMA PADA WEBSITE LOMBA NASIONAL KREATIVITAS MAHASISWA Hilman Nuril Hadi; Addin Aditya; Febry Eka Purwiantono; Syntia Widyayuningtias Putri Listio
Jurnal Informatika Vol 22, No 1 (2022): Jurnal Informatika
Publisher : IIB Darmajaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30873/ji.v22i1.3194

Abstract

A website is typically used as a medium for open, quick, and widespread information dissemination. Additionally, the website has been used for competition-related activities sponsored by an organization, such as information portal websites, registration portals, and competition evaluation media. One of the elements that determine how reliable a website is is its capacity to respond to and handle user requests. Additionally, a website that handles some information related to national competitions needs to be highly reliable. Performance testing was used in this study to evaluate how well the LO KREATIF website responded to and served users, particularly at the same time. The JMeter tool was used to conduct the performance test. The test results show that some web pages, in general, can serve up to 500 users at the same time stably without errorsWebsite pada umumnya digunakan sebagai media penyebaran informasi secara terbuka, cepat, up to date dan meluas. Website juga telah dikembangkan pemanfaatannya untuk kegiatan kompetisi yang diadakan oleh suatu organisasi/instansi seperti website sebagai portal informasi, media pendaftaran, maupun media penyampaian penilaian lomba. Kemampuan untuk melayani dan memproses permintaan pengguna menjadi salah satu faktor keandalan dari websitenya. Apalagi website yang mengelola sejumlah informasi berkaitan dengan kompetisi lomba di level nasional pasti membutuhkan tingkat keandalan tinggi. Dalam penelitian ini, dilakukan pengujian performa untuk mengetahui kualitas website lomba LO KREATIF dalam merespon dan melayani pengguna khususnya di waktu yang bersamaan. Pengujian performa dilakukan dengan menggunakan alat bantu JMeter. Dari hasil pengujian menunjukkan bahwa beberapa halaman website secara umum dapat melayani sampai 500 pengguna dalam satuan waktu bersamaan dengan stabil tanpa eror
Performance of Deep Learning Inception Model and MobileNet Model on Gender Prediction Through Eye Image Listio, Syntia Widyayuningtias Putri
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 4 (2022): Article Research: Volume 6 Number 4, October 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i4.11887

Abstract

Convolutional neural network (CNN) is one of the neural networks used in image data. CNN has a good ability to detect objects in an image. This study discusses the comparison of two deep learning models based on convolutional neural network, namely the Inception-V3 method and the MobileNet method. Both algorithms are analyzed fairly on gender classification using eye images. There have been many research completions that have conducted studies on gender classification based on faces, but gender classification based on eyes has many challenges. This gender classification is grouped into two classes, namely male and female. This study aims to build a gender classification model from eye image. The processes in this research include selecting the dataset, preprocessing the data, dividing the data which is divided into training data and test data, modeling, and evaluating the performance of the model. This study uses a public dataset, where the data contains a total of 2,681 images consisting of 1251 male eyes and 1430 female eyes. This study concludes that gender classification using eye image using the Inception-V3 method is better than the MobileNet method. This is obtained based on the accuracy value generated by the Inception-V3 method which is higher than the MobileNet-V2 method which obtains an accuracy of 91.82%.
Visit Recommendation Model: Recursive K-Means Clustering Analysis of Retail Sales Data Kristanto, Bagus Kristomoyo; Putri Listio, Syntia Widyayuningtias; Amien, Mukhlis; Baskoro, Panji Iman
Journal of Applied Informatics and Computing Vol. 8 No. 1 (2024): July 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v8i1.8138

Abstract

In the context of retail distribution, this study employs recursive K-means clustering on retail sales data to optimize clusters of nearest-distance stores for salesperson route recommendations. This approach addresses the stochastic salesperson problem by generating effective routes, enhancing cost reduction, and improving service efficiency. The recursive K-means algorithm dynamically adjusts to continuous changes in store numbers, locations, and transaction data. Consequently, this research successfully developed a model that automatically re-clusters the data with each change, providing continuously updated and effective store recommendations.
Perancangan Integrasi Sistem Informasi Rumah Sakit Kristen Mojowarno Modul Instalasi Gawat Darurat dengan Satu Sehat Kementerian Kesehatan Indonesia Menggunakan Metode Scrum Kristanto, Bagus Kristomoyo; Listio, Syntia Widyayuningtias Putri; Palandi, Jozua Ferjanus
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 7, No 6 (2024): Desember 2024
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v7i6.8429

Abstract

Abstrak - Bersamaan dengan diterbitkannya Peraturan Menteri Kesehatan Nomor 24 Tahun 2022  oleh Kementerian Kesehatan (KEMENKES) Republik Indonesia, penerapan Rekam Medis Elektronik ( RME) di setiap rumah sakit di Indonesia menjadi suatu persyaratan yang harus dipatuhi. Dari tahun 2022 hingga 2024, Satu Sehat yang dikembangkan oleh KEMENKES menjadi rujukan utama dalam intgerasi data Rekam Medis Elektronik yang terdiri dari 3 buah bagian yaitu Instalasi Gawat Darurat (IGD) , Rawat Jalan (RJ), dan Rawat Inap (RI). Penilitian ini memiliki tujuan untuk merancang sistem Rekam Medis Elektronik yang efisien dan sesuai dengan peraturan Kementerian Kesehatan, terutama pada modul instalasi gawat darurat menggunakan metode Scrum. Metode Scrum sendiri digunakan untuk mempermudah fleksibilitas pengembangan sistem sesuai dengan kebutuhan dan prioritas dari manajemen rumah sakit. Selain itu metode scrum dipilih karena sistem satu sehat dari KEMENKES masih tahap pengembangan sehingga dapat terjadi perubahan integrasi dari sistem RME milik rumah sakit ke sistem satu sehat milik KEMENKES.  Dalam pengembangan sistemnya. menerapkan prinsip Model-View-Controller (MVC) menggunakan framework PHP Laravel serta metode scrum untuk manajemen dan pengelolaan proyek. Hasil dari penelitian ini menunjukkan data rekam medis pasien telah berhasil ditambahkan ke dalam sistem RME yang terintegrasi dengan platform SATUSEHAT memungkinkan pertukaran data yang efisien. Kesimpulannya,  sistem RME ini berhasil melakukan interoperabilitas data rekam medis pasien dengan platform milik Kementrian Kesehatan dan juga memastikan bahwa Rumah Sakit Kristen Mojowarno mematuhi regulasi yang berlaku, sehingga mengurangi risiko sanksi administratif.Kata kunci: Rekam Medis Elektronik ,EMR , Satu Sehat, Scrum Abstract -  The Indonesian Ministry of Health (KEMENKES) published Regulation Number 24 of 2022, which requires the implementation of Electronic Medical Records (EMR) in all hospitals across Indonesia. Between 2022 and 2024, KEMENKES created One Healthy, a system that consolidates electronic medical record data into three components: Emergency Installation (IGD), Outpatient (RJ), and Inpatient (RI). This study is to develop an efficient electronic medical record system that adheres to the standards of the Ministry of Health, particularly in the emergency installation module utilizing the Scrum methodology. Hospital management employs the Scrum methodology to enable adaptable system development aligned with their requirements and goals. The use of the scrum approach arises from the continuous evolution of KEMENKES' one healthy system, facilitating seamless interaction between the hospital's EMR system and KEMENKES' one healthy system. During the system's development. The system is being created according to the Model-View-Controller (MVC) paradigm, employing the PHP Laravel framework and the Scrum methodology for project management and administration. The study's findings indicate the effective incorporation of patient medical record data into the RME system via the SATUSEHAT platform, enabling efficient data interchange. In conclusion, this RME system has effectively integrated patient medical record data with the Ministry of Health's platform while guaranteeing that Mojowarno Christian Hospital adheres to relevant regulations, hence mitigating the danger of administrative penalties.Keywords: Medical Records, Electronic Medical Records, EMR, Satu Sehat, Scrum
Penerapan Metode Convolutional Neural Network (CNN) Dalam Mengklasifikasikan Penyakit Daun Tanaman Padi Christiawan, Gracia Yoel; Putra, Roy Andani; Sulaiman, Azis; Poerbaningtyas, Evy; Putri Listio, Syntia Widyayuningtias
J-INTECH (Journal of Information and Technology) Vol 11 No 2 (2023): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v11i2.1006

Abstract

Rice is a staple crop in Indonesia. Most farmers choose rice as the main crop for agricultural land. Starting from the land to the tropical climate that occurs in Indonesia, it is very suitable for rice plants. Among these supports arise obstacles faced by farmers. Rice leaf diseases include Brownspot, Blas, Bacterial Leaf Blight (HDB). Classification of these diseases can be done using the CNN (Convolutional Neural Network) method. So far, the detection process for rice plant leaf diseases has been done manually. The CNN method can detect images from pixel to pixel so it is considered effective for detecting disease from images alone. This research uses a dataset of 1630 data which is divided into 3 disease classes. This research compares the number of epochs and uses the CNN InceptionV3 architecture. The results of this research show very good results with a lift of 98% with data that is not overfitting.
Penerapan Metode Convolutional Neural Network (CNN) Dalam Mengklasifikasikan Penyakit Daun Tanaman Padi Gracia Yoel Christiawan; Roy Andani Putra; Azis Sulaiman; Evy Poerbaningtyas; Syntia Widyayuningtias Putri Listio
J-INTECH ( Journal of Information and Technology) Vol 11 No 2 (2023): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v11i2.1006

Abstract

Rice is a staple crop in Indonesia. Most farmers choose rice as the main crop for agricultural land. Starting from the land to the tropical climate that occurs in Indonesia, it is very suitable for rice plants. Among these supports arise obstacles faced by farmers. Rice leaf diseases include Brownspot, Blas, Bacterial Leaf Blight (HDB). Classification of these diseases can be done using the CNN (Convolutional Neural Network) method. So far, the detection process for rice plant leaf diseases has been done manually. The CNN method can detect images from pixel to pixel so it is considered effective for detecting disease from images alone. This research uses a dataset of 1630 data which is divided into 3 disease classes. This research compares the number of epochs and uses the CNN InceptionV3 architecture. The results of this research show very good results with a lift of 98% with data that is not overfitting.
Co-Authors Addin Aditya Azis Sulaiman Bagus Kristomoyo Kristanto Baskoro, Panji Iman Christiawan, Gracia Yoel Evy Poerbaningtyas Evy Poerbaningtyas Febry Eka Purwiantono Gracia Yoel Christiawan Hilman Nuril Hadi Jozua Ferjanus Palandi Mukhlis Amien Putra, Roy Andani Roy Andani Putra Sulaiman, Azis