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All Journal International Journal of Electrical and Computer Engineering International Journal of Advances in Applied Sciences IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Journal of ICT Research and Applications Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Ilmu Komputer dan Bisnis PREPOTIF : Jurnal Kesehatan Masyarakat ProBisnis : Jurnal Manajemen
Ignatius Wiseto Prasetyo Agung
Universitas Adhirajasa Reswara Sanjaya (ARS University)
Aerospace Engineering Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Physics Public Health Social Sciences

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Membangun Startup ARSpira Sebuah Platform E-Counseling Berbasis Website Untuk Pelajar SMA Junaedi, Novan; Hidayat, Fajar Mukti; Rizqi, Muhammad; Agung, I. Wiseto P.
Jurnal Ilmu Komputer dan Bisnis Vol. 12 No. 2a (2021): Vol. 12 No. 2a Special Issue (2021)
Publisher : STMIK Dharmapala Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47927/jikb.v12i2a.168

Abstract

Startup merupakan sebuah institusi manusia yang didesain untuk membuat sebuah produk baru atau jasa dibawah kondisi ketidakpastian yang ekstrim. Peluang usaha startup di era digital seperti sekarang ini sangatlah besar apalagi dengan kondisi pandemi yang sangatlah membatasi ruang gerak hampir seluruh manusia di muka bumi yang mengakibatkan kejenuhan dan juga berbagai masalah lainnya termasuk kesehatan mental siswa-siswi SMA yang mau tidak mau harus bersekolah dari rumah dan akses untuk melakukan bimbingan konseling dengan guru BK menjadi sangat sulit. Oleh karena itu sebuah terobosan diambil oleh perusahaan startup baru yang bergerak dibidang E-Counseling bernama ARSpira untuk memberikan solusi bagi permasalahan tersebut.
Penerapan Lean Canvas Pada Startup Pembelajaran Bahasa Inggris Lunchat Ardi, Wildan Khalifah; Salam, Regi; Alfaruk, Muhammad Harist; Agung, I. Wiseto P.
Jurnal Ilmu Komputer dan Bisnis Vol. 12 No. 2a (2021): Vol. 12 No. 2a Special Issue (2021)
Publisher : STMIK Dharmapala Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47927/jikb.v12i2a.171

Abstract

Lunchat merupakan sebuah startup di bidang pendidikan yang menciptakan sebuah aplikasi kursus bahasa Inggris berbasis website yang dapat mempermudah masyarakat Indonesia dalam belajar bahasa Inggris. Tujuan dari penelitian ini adalah untuk menentukan dan mempertajam model bisnis yang diterapkan di startup Lunchat. Metode pengembangan sistem yang digunakan pada penelitian ini adalah menggunakan metode lean canvas sebagai analisis bisnis. Dengan penerapan lean canvas dapat memudahkan pembuat dalam melakukan proses validasi, karena dapat melihat model bisnis secara keseluruhan, sehingga dapat mengurangi resiko dalam melakukan bisnis. Hal ini karena antara produk atau jasa yang ditawarkan sesuai dengan yang diinginkan oleh pasar. Hasil dari implementasi startup Lunchat menjadikan suatu peluang yang menjanjikan untuk memperluas sektor usaha sehingga Lunchat dapat bersaing di era Industry 4.0 ini.
Asymmetric Watermarking Scheme Based on Correlation Testing Rinaldi Munir; Bambang Riyanto; Sarwono Sutikno; Wiseto P. Agung
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 1, No 2 (2007): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.2281

Abstract

AbstractAsymmetric watermarking is the second generation of watermarking scheme which uses different keys for embedding and detecting watermark. Key for embedding is private or secret, but key for detecting can be available publicly and everyone who has the key can detect watermark Watermark detection does not need to be original multimedia data. Detection of watermark is realized using correlation test between public key and multimedia data received. In most of schemes, private key is the watermark itself; public key is public watermark which correlates to the private watermark This paper presents concept of asymmetric watermarking scheme that based on correlation test and reviews some schemes of asymmetric watermarking that have been proposed by researchers.Keywords: asymmetric watermarking, private key, public key, watermark., multimeelia,:correlation.
An Asymmetric Watermarking Method in the DCT Domain Based on RC4-Permutation and Chaotic Map Rinaldi Munir; Bambang Riyanto; Sarwono Sutikno; Wiseto P. Agung
Journal of ICT Research and Applications Vol. 1 No. 2 (2007)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.2007.1.2.1

Abstract

This paper presents an asymmetric watermarking method in the DCT domain for still images based on permutation and chaos. This method uses secret watermark as private key and public watermark as public key. The public watermark has a normal distribution with mean = 0 and variance = 1. The secret watermark is obtained by permutating the public watermark according to combination of a part of RC4 algorithm and a logistic map. The watermark is embedded into mid-frequency components of the DCT block for better robustness. The detection process is implemented by correlation test between the public watermark and the received image. Experiments show that the watermarking method was proved to be robust againts some typical image processings (cropping, JPEG compression, resizing, rotation, sharpening, and noising).
Optimasi Parameter Input pada Artificial Neural Network untuk Meningkatkan Akurasi Prediksi Indeks Harga Saham Ignatius Wiseto Prasetyo Agung
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 10, No 2 (2021): JULI
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v10i2.1166

Abstract

Stock trading is one of the businesses that has been done worldwide. In order to gain the maximum profit, accurate analysis is needed, so a trader can decide to buy and sell stock at the perfect time and price. Conventionally, two analyses are employed, namely fundamental and technical.  Technical analysis is obtained based on historical data that is processed mathematically. Along with technology development, stock price analysis and prediction can be performed with the help of computational algorithms, such as machine learning. In this research, Artificial Neural Network simulations to produce accurate stock price predictions were carried out. Experiments are performed by using various input parameters, such as moving average filters, in order to produce the best accuracy. Simulations are completed with stock index datasets that represent three continents, i.e. NYA (America, USA), GDAXI (Europe, Germany), and JKSE (Asia, Indonesia). This work proposes a new method, which is the utilization of input parameters combinations of C, O, L, H, MA-5 of C, MA-5 of O, and the average of O C prices. Furthermore, this proposed scheme is also compared to previous work done by Khorram et al, where this new work shows more accurate results.
Input Parameters Comparison on NARX Neural Network to Increase the Accuracy of Stock Prediction Ignatius Wiseto Prasetyo Agung
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 6, No 1 (2022): Issues July 2022
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v6i1.7158

Abstract

The trading of stocks is one of the activities carried out all over the world. To make the most profit, analysis is required, so the trader could determine whether to buy or sell stocks at the right moment and at the right price. Traditionally, technical analysis which is mathematically processed based on historical price data can be used. Parallel to technological development, the analysis of stock price and its forecasting can also be accomplished by using computer algorithms e.g. machine learning. In this study, Nonlinear Auto Regressive network with eXogenous inputs (NARX) neural network simulations were performed to predict the stock index prices. Experiments were implemented using various configurations of input parameters consisting of Open, High, Low, Closed prices in conjunction with several technical indicators for maximum accuracy. The simulations were carried out by using stock index data sets namely JKSE (Indonesia Jakarta index) and N225 (Japan Nikkei index). This work showed that the best input configurations can predict the future 13 days Close prices with 0.016 and 0.064 mean absolute error (MAE) for JKSE and N225 respectively. 
A Systematic Literature Review: Performance Comparison of Edge Detection Operators in Medical Images Mayangsari, Ariefa Diah; Agung, Ignatius Wiseto Prasetyo
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 8 No. 1 (2024)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v8i1.1012

Abstract

Medical images play a crucial role in the diagnosis of diseases. To make the diagnosis more accurate, the image should usually be enhanced first using image processing methods such as segmentation and edge detection stages. However, the complexity and noise that may arise in these images pose challenges in edge detection. Therefore, to portray the characteristics of edge detection operators, this research presents a systematic literature review of the performance of various edge detection operators in medical images, focusing on literature published between 2019 and 2023. After the selection process, 41 papers out of the initial 112 collected papers were chosen for further review. The study evaluates edge detection operators e.g., Canny, Sobel, Prewitt, Roberts, and Laplacian of Gaussian (LOG) on medical images such as X-rays, MRI, CT scans, ultrasound, Pap smears, and others. In the analysis, the accuracy, computational time, and response to noise of each operator are compared. The results indicate that despite longer computational times, Canny emerges as the most accurate operator, especially in Pap smear and CT scan images. The LOG operator offers high accuracy in MRI images with more efficient computational time. Evaluation of operator reliability against noise confirms the superiority of Canny. Furthermore, the future potential of edge detection in medical services is also reviewed. For instance, Canny, known for accurate and noise-resistant edges, enhances detection in complex CT-Scan and X-ray images. Meanwhile, LOG, handling artifacts with lower computational time, improves edge clarity in medical images. Potential applications include enhanced diagnosis, efficient patient monitoring, and improved image clarity in future medical services.
PENGARUH PERSEPSI KEGUNAAN DAN PERSEPSI KEMUDAHAN TERHADAP KEMAUAN TENAGA KESEHATAN MENGGUNAKAN SIMRS DI RUMAH SAKIT GRAHA HUSADA JEPARA Prawasari, Nindyan; Rohendi, Acep; Agung, Ignatius Wiseto Prasetyo
PREPOTIF : JURNAL KESEHATAN MASYARAKAT Vol. 8 No. 3 (2024): DESEMBER 2024
Publisher : Universitas Pahlawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/prepotif.v8i3.37808

Abstract

Seiring dengan perkembangan teknologi yang pesat, adopsi teknologi dalam bentuk sistem informasi telah menjadi hal yang penting dalam dunia kesehatan yang juga berkembang pesat. Sistem Informasi Manajemen Rumah Sakit (SIMRS) adalah salah satu aspek penting yang merupakan suatu proses yang diterapkan untuk membantu meningkatkan efisiensi dan efektivitas tenaga kerja dalam menjalankan fungsi dan mencapai tujuannya. Dalam implementasi ini, sumber daya manusia, terutama tenaga kesehatan selaku pengguna SIMRS juga berperan penting dalam memaksimalkan penggunaan SIMRS. Penelitian ini menyelidiki terkait kemauan tenaga kesehatan di rumah sakit dalam menggunakan SIMRS dalam bekerja. Mengadopsi kerangka Technology Acceptance Model (TAM), penelitian ini menguji pengaruh variabel persepsi kegunaan dan persepsi kemudahan terhadap kemauan tenaga kesehatan menggunakan SIMRS. Metode yang digunakan dalam penelitian ini adalah metode kuantitatif yang melibatkan 106 sampel tenaga kesehatan di Rumah Sakit Graha Husada Jepara. Hasil dari penelitian ini sejalan dengan teori yang ada bahwa persepsi kegunaan dan persepsi kemudahan berpengaruh positif terhadap kemauan tenaga kesehatan menggunakan SIMRS.
Stock’s selection and trend prediction using technical analysis and artificial neural network Agung, Ignatius Wiseto Prasetyo; Arifin, Toni; Junianto, Erfian; Rabbani, Muhammad Ihsan; Mayangsari, Ariefa Diah
International Journal of Advances in Applied Sciences Vol 14, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i1.pp151-163

Abstract

Stock trading offers potential profits when traders buy low and sell high. To maximize profits, accurate analysis is essential for selecting the right stocks, timing purchases, and selling at peak prices. The authors propose a new method for selecting potential stocks that are highly likely to rise in price. The method has two stages. First, technical analysis, using moving averages and stochastic oscillators, filters stocks with downward trends, anticipating a reversal and subsequent rise. Second, for selected stocks, future price trends are predicted using artificial neural networks, specifically long short-term memory (LSTM) with adaptive moment estimation (Adam) optimizer. The second step ensures that only stocks with increasing prices will be chosen for trading. This study analyzes five hundred Fortune 500 stocks over three different periods, with 250 days of data each. Simulations conducted in Python showed that technical analysis could filter 5 to 6 candidate stocks. Subsequently, the LSTM model predicted that only 4 of these stocks would have an upward trend. Validation shows that trend predictions are correct, resulting in an average profit of 5.51% within 10 working days. This profit outperforms the profits generated by other existing methods.
Health Information System Development Strategy at Gimpu Community Health Center, Sigi District Ramadhan, Fanky Fazdianki; Syaodih, Erliany; Agung, Ignatius Wiseto Prasetyo
ProBisnis : Jurnal Manajemen Vol. 16 No. 3 (2025): June: Management Science
Publisher : Lembaga Riset, Publikasi dan Konsultasi JONHARIONO

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

Abstract

The strategy for developing a health information system at the Gimpu Health Center, Sigi Regency aims to improve efficiency in managing patient service information, which has so far been done conventionally. The recording process that has not been computerized often causes duplication of information and takes a long time to process information. In addition, the manual recording system also has risks to information security, because it is prone to loss or damage. The information system designed in this study is in the form of a software application equipped with an information base (database), which functions as a center for storing information and a tool for entering, processing, and accelerating the preparation of reports. The forms available in the system are designed according to user needs to make them easier to use. Not only does it increase ease of operation, this system is also designed with a high level of security to ensure the accuracy and protection of patient information. The design of this system was developed by implementing the stages in the System Development Life Cycle (SDLC). The implementation of this information system is expected to be a solution to various obstacles faced by the Gimpu Health Center, Sigi Regency in the service process, especially related to recording and managing patient information. The information recorded in the system includes patient visit information, such as date of visit, patient identity (name, place and date of birth, name of head of family), gender, level of education, occupation, domicile area (district/city, sub-district, address/hamlet), and payment method for health services.
Co-Authors Acep Rohendi Agustin, Dari Dianata Alfaruk, Muhammad Harist Ardi, Wildan Khalifah Bambang Riyanto Erfian Junianto Erliany Syaodih Hidayat, Fajar Mukti Junaedi, Novan Mayangsari, Ariefa Diah Muhammad Rizqi Prawasari, Nindyan Rabbani, Muhammad Ihsan Ramadhan, Fanky Fazdianki Rinaldi Munir Rizal Rachman, Rizal Salam, Regi Sarwono Sutikno Sarwono Sutikno SATRIYAS ILYAS Toni Arifin Wibowo, Ilham Rachmat