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Implementasi Vigenere Cipher Sebagai Pengaman Pada Proses Deskripsi Steganografi Least Significant Bit Alawiyah, Tuti; Ardianto, Rian; Purnia, Dini Silvi
Jurnal Informatika Vol 7, No 1 (2020): April 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Kemajuan teknologi diiringi dengan meningkatnya ancaman terhadap keamanan serta kerahasiaan pesan/informasi. Salah satu cara untuk menjaga keamanan dan kerahasiaan pesan/informasi dapat menggunakan teknik steganografi. Steganografi adalah teknik untuk menyembunyikanÂ pesan/informasi padaÂ sebuah media,Â bisa berupa mediaÂ gambar,Â suaraÂ ataupunÂ video, sehingga pesan yang disembunyikan sulit dikenali oleh indera manusia. Penelitian ini bertujuan untuk membuat aplikasi steganografi dengan metode least significant bit serta implementasi vigenere cipher untuk meningkatkan keamanan pesan/informasi. Informasi/pesan akan disisipkan pada satu bit paling kanan ke pixel file objek tanpa merubah medianya. Penelitian ini menghasilkan aplikasi Â yang dapat menyembunyikan informasi/pesan pada media gambar. Untuk meningkatkan sistem pengamanannya, proses deskripsi disertai dengan metode vigenere cipher jika pesan/informasi diakses oleh orang yang tidak berhak atas informasi/pesan tersebut.

Pemberian Kredit Telepon Seluler Menggunakan Metode Topsis Pada Mars Phone Cell Tasikmalaya Rian Ardianto; Asti Herliana; Annisa Risqi Sulistya Kusuma Wardhani; Tb. Dedy Fuady; Dasril Aldo
JURSIMA (Jurnal Sistem Informasi dan Manajemen) Vol 10 No 1 (2022): Jursima Vol. 10 No. 1, April Tahun 2022
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i1.458

Adanya ide baru dalam strategi penjualan gadget sangat diperlukan untuk dapat memenuhi kebutuhan segmentasi masyarakat tersebut dengan memberikan kemudahan dan keringanan secara persyaratan dan prosedur membeli handphone secara kredit. Dengan semakin mudahnya sistem jual beli secara kredit sehingga menarik perhatian masyarakat untuk lebih mudah lagi dalam memiliki telepon seluler dengan keringanan pembayaran yang diberikan secara diangsur. Opsi terakhir yang disarankan diperoleh dengan menggabungkan alternatif statis dengan nilai bobot terbesar untuk setiap kriteria berfungsi mengidentifikasi debitur yang layak mendapatkan kredit ponsel. Jarak euclidean digunakan untuk mengukur seberapa dekat suatu alternatif dengan solusi ideal dalam metode TOPSIS, yang merupakan proses pengambilan keputusan multi kriteria. Alternatif yang dipilih harus, dari sudut pandang geometris, menjadi yang paling dekat dengan solusi ideal positif dan terjauh dari solusi ideal negatif. Keluaran sistem dapat menawarkan saran peringkat tergantung pada bobot yang paling signifikan. Dengan penggunaan pendekatan ini, kreditur dapat memilih debitur yang memenuhi syarat untuk kredit.

Desain Sistem Informasi Geografis (GIS) untuk Pengelolan Infrastruktur Telekomunikasi di Daerah Terpencil: Geographic Information System (GIS) Design for Telecommunication Infrastructure Management in Remote Areas Moh. Khoridatul Huda; Rian Ardianto; Hadi Jayusman; Rosyid Ridlo Al-Hakim
Jurnal Kolaboratif Sains Vol. 7 No. 7: July 2024
Publisher : Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/jks.v7i7.5903

Penelitian ini bertujuan untuk merancang Sistem Informasi Geografis (GIS) guna mendukung pengelolaan infrastruktur telekomunikasi di Desa Kutorojo, Kecamatan Kajen, Kabupaten Pekalongan. Menggunakan pendekatan kualitatif dengan metode survei, penelitian ini melibatkan wawancara mendalam dan observasi lapangan untuk mengumpulkan data terkait kondisi infrastruktur dan kebutuhan masyarakat. Hasil penelitian menunjukkan bahwa penerapan GIS meningkatkan akses dan kualitas layanan telekomunikasi, dengan 75% rumah tangga kini memiliki akses telekomunikasi yang lebih baik. Mayoritas pengguna melaporkan kepuasan tinggi terhadap kualitas layanan, berkat peningkatan kecepatan dan stabilitas jaringan. Partisipasi masyarakat dalam pengelolaan infrastruktur juga meningkat, mencapai 60%, yang berdampak positif pada pemeliharaan jangka panjang. Efisiensi pengelolaan infrastruktur ditingkatkan dengan pengurangan waktu perawatan sebesar 30% dan biaya sebesar 25%. Penelitian ini menyimpulkan bahwa GIS adalah solusi efektif dalam pengelolaan infrastruktur telekomunikasi di daerah terpencil, memberikan dampak ekonomi dan sosial yang positif. Penerapan GIS tidak hanya meningkatkan kualitas hidup masyarakat, tetapi juga menawarkan model pengelolaan infrastruktur yang dapat diterapkan di wilayah lain dengan tantangan serupa.

Analisis Pengaruh Good Corporate Governance dan Konservatisme Akuntansi Terhadap Tax Avoidance Herman Sjahruddin; Karyaningsih Karyaningsih; Rini Novianti; Rian Ardianto; Sonny Santosa
Jurnal Akuntansi dan Pajak Vol 23, No 2 (2023): JAP : Vol. 23, No. 2, Agustus 2022 - Januari 2023
Publisher : ITB AAS INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/jap.v23i2.7290

This study aims to examine and analyze the effect of good corporate governance and accounting conservatism on tax avoidance. This type of research is an explanation research with a quantitative approach. The independent variables in this study are good corporate governance and conservatism. While the dependent variable in this study is tax avoidance. The data used in this research is quantitative by analyzing secondary data. The population listed in this study consists of property companies during the 2016-2021 period. Where this research was conducted by means of a survey to the Indonesia Stock Exchange. The collected data is processed and analyzed by multiple linear regression analysis with the help of SPSS 23 program. The results of this study indicate that: 1) good corporate governance has a positive and significant effect on tax avoidance and 2) conservatism has a positive and significant effect on tax avoidance. The results of this study suggest that if the company wants to do tax avoidance well, the company must understand good corporate governance and accounting conservatism so that tax avoidance by the company does not have a negative impact on the company in the long term.

Klasifikasi Berisiko Stunting pada Balita: Perbandingan K-Nearest Neighbor, Naïve Bayes, Support Vector Machine Ramadya Wahyu Dwinanto; Arif Setia Sandi A; Rian Ardianto
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No2.pp264-273

Stunting in children under five is a significant health problem that impacts child development. This study aims to develop a classification model to predict stunting risk using SVM, KNN, and Naïve Bayes algorithms. Data from the Jatilawang Health Center included 523 under-fives with variables such as age, weight, length, arm circumference, z-score, parental education, and maternal health history. Following the CRISP-DM steps, the data was processed through handling missing data, feature selection, and dividing the data into training and testing sets with a ratio of 80:20. Results showed SVM had the highest accuracy of 90%, followed by KNN 89%, and Naïve Bayes 85%. This research produces a stunting risk prediction model that is implemented in a simple website, supporting early intervention and decision-making in stunting prevention efforts.

Sosialisasi Pencegahan Stunting Sebagai Upaya Pemberdayaan Masyarakat Muh. Jaelani Al-Pansori; Rian Ardianto; Dewi Lestari; Nurul Wahyuni Mahmud; Tia Rohliana; Aina Filhiam; Yazid Ilham Dia Uddin
Jurnal Pengabdian Kepada Masyarakat Al-Amin Vol. 3 No. 1 (2025): January 2025
Publisher : STAI Al-Amin Gersik Kediri Lombok Barat-NTB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54723/jpa.v3i1.274

Stunting is a serious nutritional issue in Indonesia that has the potential to hinder children's growth and development. This article discusses the role of students participating in the Community Service Program (KKN) in promoting stunting prevention in South Masbagik Village. Through the KKN activities, students collaborate with the local community to raise awareness about the importance of balanced nutrition and healthy lifestyles. The methods used include counseling and training. The results of these activities show an increase in the community's knowledge about stunting and its prevention measures. Additionally, this program has contributed to community empowerment by involving them in the decision-making process related to family health. Through the active role of students, it is hoped that awareness and preventive actions against stunting can be effectively implemented, leading to a positive impact on children's health and the quality of human resources in the village.

CNN-based Classification of Bladder Tissue Lesions from Endoscopy Images Lutviana, Lutviana; Rian Ardianto; Purwono
IT Journal Research and Development Vol. 9 No. 2 (2025)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/itjrd.2025.17867

Bladder cancer is one type of tumor that frequently occurs in the urinary system, and early diagnosis is essential to improve the prognosis and survival of patients. The study aims to develop a Convolutional Neural Network (CNN) model for bladder tissue lesion classification from endoscopic images. This study uses a dataset consisting of 1754 images, which are divided into four classes: High-Grade Cancer (HGC), Low-Grade Cancer (LGC), Non-Specific Tissue (NST), and Non-Tumorous Lesion (NTL). The proposed CNN model showed a validation accuracy of 96.29%, with high recall, precision, and F1-score in most classes. The results show that CNN-based automated methods can improve efficiency and accuracy in the early diagnosis of bladder cancer, reduce manual visual interpretation errors, and improve the quality of patient care. This study suggests increasing the training data, especially for the NTL class, and applying more complex model architecture to better results.

Klasifikasi Berisiko Stunting pada Balita: Perbandingan K-Nearest Neighbor, Naïve Bayes, Support Vector Machine Ramadya Wahyu Dwinanto; Arif Setia Sandi A; Rian Ardianto
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No2.pp264-273

Stunting in children under five is a significant health problem that impacts child development. This study aims to develop a classification model to predict stunting risk using SVM, KNN, and Naïve Bayes algorithms. Data from the Jatilawang Health Center included 523 under-fives with variables such as age, weight, length, arm circumference, z-score, parental education, and maternal health history. Following the CRISP-DM steps, the data was processed through handling missing data, feature selection, and dividing the data into training and testing sets with a ratio of 80:20. Results showed SVM had the highest accuracy of 90%, followed by KNN 89%, and Naïve Bayes 85%. This research produces a stunting risk prediction model that is implemented in a simple website, supporting early intervention and decision-making in stunting prevention efforts.

Analisis Sel Darah Putih dengan Pendekatan Bioinformatika menggunakan Arsitektur MobileNetV2 Dimas Febri Kuncoro; Rian Ardianto
Jurnal IT UHB Vol 5 No 1 (2024): Jurnal Ilmu Komputer dan Teknologi
Publisher : Universitas Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35960/ikomti.v5i1.1469

The identification and classification of white blood cells have become important in medical image analysis for disease diagnosis and health monitoring. Traditional classification methods often consume time and are less reliable. Based on these issues, this study aims to implement a Convolutional Neural Network (CNN) with the MobileNetV2 architecture in the classification of white blood cells to improve efficiency and accuracy. This research method emphasizes the use of the MobileNetV2 architecture in CNN. The training process is conducted using Google Colaboratory with the aid of TensorFlow. Model evaluation is carried out using various standard metrics, including accuracy, precision, recall, and F1-score. The results of the study show that the implementation of CNN with the MobileNetV2 architecture produces an efficient and accurate white blood cell classification model. Through a training process with 15 epochs, the model achieved a high accuracy rate and a low error rate. The accuracy rate in this study indicated an accuracy result of 94.8%. The model evaluation demonstrated good performance in classifying different types of white blood cells, as shown by the evaluation metrics and the confusion matrix. This model implementation has great potential to be used in medical image analysis for efficient and accurate disease diagnosis and health monitoring. Implementasi model ini memiliki potensi besar untuk digunakan dalam analisis citra medis untuk diagnosis penyakit dan pemantauan kesehatan yang efisien dan akurat.

Analisis Deep Learning Metode Convolutional Neural Network Dalam Klasifikasi Varietas Gandum: Analysis of Convolutional Neural Network Deep Learning Method in Durum Wheat Variety Classification Rian Ardianto; Sony Kartika Wibisono
Jurnal Kolaboratif Sains Vol. 6 No. 12: DESEMBER 2023
Publisher : Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar

Selama ini, Indonesia memenuhi kebutuhan gandum dengan mengimpor dari beberapa negara, seperti Australia, Ukraina, Kanada, Argentina, Amerika Serikat, Bulgaria, Moldova, Rusia, India, dan lain-lain. Tanaman ini umumnya tumbuh subur di wilayah subtropis dengan suhu berkisar 10–25°C dan curah hujan antara 350–1.250 mm. Penelitian ini bertujuan untuk menjelaskan metode transfer learning pada arsitektur Convolutional Neural Network (CNN) guna mendukung identifikasi otomatis. Keunggulan CNN terletak pada kemampuannya yang tidak memerlukan ekstraksi fitur karena fitur ekstraksi sudah terintegrasi secara otomatis dalam CNN. Studi ini melakukan perbandingan antara dua arsitektur CNN pada tiga jenis gandum yang berbeda. Hasil analisis menggunakan 150 citra data latih dan 45 citra data uji menunjukkan bahwa arsitektur MobileNet mampu memodelkan dataset dengan tingkat akurasi mencapai 98%, sementara tingkat kesalahan mencapai 0,02%.

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