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All Journal Jurnal Teknoin Jurnal Teknologi INFORMAL: Informatics Journal Proceeding SENDI_U Sebatik Jurnal Sisfokom (Sistem Informasi dan Komputer) AMALIAH: JURNAL PENGABDIAN KEPADA MASYARAKAT JMAI (Jurnal Multimedia & Artificial Intelligence) Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Pengabdian Nasional (JPN) Indonesia Jurnal Teknik Informatika (JUTIF) Jurnal Pendidikan dan Teknologi Indonesia Konstelasi: Konvergensi Teknologi dan Sistem Informasi Jurnal Sains dan Teknologi Journal Of Information System And Artificial Intelligence Jurnal Pengabdian Nasional (JPN) Indonesia
Agus Sidiq Purnomo
Universitas Mercu Buana Yogyakarta
Religion Aerospace Engineering Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Other

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Journal : INFORMAL: Informatics Journal

 1 
Penyisipan Citra Pesan Ke Dalam Citra Berwarna Menggunakan Metode Least Significant Bit dan Redundant Pattern Encoding Sannawira, Rahmandhita Fikri; Purnomo, Agus Sidiq
INFORMAL: Informatics Journal Vol 1, No 1 (2016): INFORMAL: Informatics Journal
Publisher : Program Studi Sistem Informasi - Universitas Jember

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Abstract

Teknik steganografi memiliki peranan penting menyangkut hal yang berkaitan dengan pesan rahasia. Steganografi merupakan teknik penyisipan pesan yang telah digunakan oleh orang-orang jaman dulu untuk menjaga kerahasiaan pesan tersebut. Seiring dengan kemajuan teknologi, teknik ini dapat diaplikasikan menggunakan komputer. Sebagai contoh, pembuatan aplikasi steganografi yang dapat dilakukan menggunakan bahasa pemrograman yang berbeda-beda. Metode least significant bit merupakan cara penyisipan yang mengambil bit rendah dari data piksel yang menyusun sebuah file citra gambar. Penggunaan metode ini memungkinkan adanya perubahan atau penambahan sejumlah besar informasi tanpa adanya perubahan tampilan dari citra itu sendiri. Citra pesan disisipkan secara berulang yang ditempatkan pada piksel citra tujuan mulai dari piksel pertama sampai piksel yang terakhir. Secara garis besar, hasil yang didapat dari penelitian ini yaitu: Pertama, cara menyisipkan citra pesan secara berulang ke dalam citra berwarna yang menjadi citra tujuan penyisipan. Ke-dua, cara meng-ekstrak citra hasil penyisipan tersebut sehingga citra pesan yang telah disisipkan dapat diketahui maksudnya.
Rekomendasi Pemilihan Produk Simpanan Tabungan Bank Menggunakan Metode Weighted Product (WP) Agus Sidiq Purnomo; Jevi Ariyanti
INFORMAL: Informatics Journal Vol 4 No 1 (2019): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v4i1.10124

Abstract

Many banks in Indonesia, both public and private banks, offer different advantages to the customers. As a result, it is often difficult for the public to decide where to save their money. For this reason, the writer propose a decision support system to help recommend a bank as a smart solution for saving. This study employed the Weighted Product (WP) with seven criteria, namely initial deposit, subsequent deposits, administrative costs, depositional balances, interest rates, age range, and facilities. This system can help the prospective customers determine the ideal savings place for the future needs. This study shows that the highest final value after calculation is 0.0320 for Batara of BTN bank, and the lowest value is 0.0132 for Tapres of BCA bank.
Rekomendasi Pemilihan Minat Studi Menggunakan Metode Mamdani Studi Kasus : Program Studi Sistem Informasi FTI UMBY Anief Fauzan Rozi; Agus Sidiq Purnomo
INFORMAL: Informatics Journal Vol 2 No 3 (2017): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

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Abstract

Determination of the concentration / interest of study for most students can’t be applied easily. Most students still do not know exactly what their concentration is. Only for students who are smart in IPK and mature in the pattern of thinking that can determine the concentration of studies easily and not wrong target. Besides still confused and tend to choose the concentration that is not in accordance with the interests and talents of each. Confusion or the majority of students' mistakes to specialization in accordance with the ability due to the number of elective courses offered in line with the interests offered. Based on this problem, it takes a decision making tool or recommendation to the student about the concentration/interest of study whether the most appropriate according to ability. In this research will be made decision support system for recommendation of study by implementing fuzzy inference (mamdani). Where this system will provide information on the interest of the study can be selected based on the value variable. So it can help students in choosing the interests of the study in accordance with the appropriate competence and interest talent. Based on the 20 data that have been tested, obtained 19 data and 1 data that is not appropriate, thus can be calculated the performance of the system that is equal to 95%.
Sistem Pendukung Keputusan Untuk Menentukan Status Gizi Balita Menggunakan Metode Fuzzy Inferensi Sugeno (Berdasarkan Metode Antropometri) Alfian Romadhon; Agus Sidiq Purnomo
INFORMAL: Informatics Journal Vol 1 No 3 (2016): INFORMAL: INFORMATICS JOURNAL
Publisher : Faculty of Computer Science, University of Jember

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Abstract

Perkembangan teknologi informasi diperlukan untuk membantu dan menunjang disegala bidang salah satunya bidang kesehatan. Penggunaan teknologi infrormasi dibidang kesehatan untuk mengurangi permasalahan dalam tindakan klinis maupun non klinis. Salah satu permasalahan yang ditemui dalam bidang kesehatan adalah gizi balita. Gizi balita merupakan salah satu dasar acuan perkembangan anak. Untuk melakukan pemeriksaan gizi balita diperlukan buku Kartu Menuju Sehat (KMS) yang digunakan pedoman dasar tumbuh kembang balita. Pemeriksaan gizi pada balita menggunakan KMS digunakan standar antropometri dalam penentuan status gizinya. Dalam Penentuan status gizi, terdapat empat kategori yang dijadikan standar yaitu umur balita, berat balita, tinggi balita dan jenis kelamin balita. Sedangkan dalam penelitian ini selain menggunakan antropometri juga digunakan metode inferensi fuzzy sugeno dalam penentuan status gizi pada balita. Berdasarkan hasil pengujian terhadap sistem pendukung keputusan (SPK) status gizi yang telah dibangun dengan menggunakan metode fuzzy sugeno dan pengujian menggunakan standar baku antropometri memiliki hasil 84% dari 25 data yang diujikan terdapat 4 yang tidak sesuai, sehingga dapat disimpulkan bahwa unjuk kerja sistem berhasil.
Analisis Perbandingan Implementasi Metode MADM dan Fuzzy MADM SAW Pada Sistem Pendukung Keputusan Agus Sidiq Purnomo; Anief Fauzan Rozi
INFORMAL: Informatics Journal Vol 7 No 1 (2022): Informatics Journal (INFORMAL)
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v7i1.30318

Abstract

There are so many studies that use the Multi-Attribute Decision Making (MADM) method as a solution in Decision Support Systems. In addition, there are also many studies that use additional fuzzy which is implemented in the MADM method which is commonly referred to as Fuzzy MADM. For example, using Simple Additive Weighting (SAW), which one is closer to the best solution, whether to use MADM SAW or FMADM SAW, which one is better to use. Based on these problems, in this study analysis will be carried out regarding which method is closer to the best solution to be implemented in the case of Decision Support System between MADM and FMADM, in this case using the case of selecting the best graduates in the study program and the SAW method. Based on the results of the discussion in this study, it can be concluded that the implementation of MADM uses SAW, with 2 approaches, namely: Likert and fuzzy scales. The results obtained from the comparison of assessment ranges using the Likert and fuzzy scales obtained suitability of 100%. While the results of testing using RSD on Likert and fuzzy scales obtained the same results, namely 12.24%. The use of a Likert scale or fuzzy numbers has no effect, what affects the results is the range of the rating scale.
Sistem Pakar Untuk Menentukan Status Pertumbuhan Pada Anak Menggunakan Inferensi Fuzzy (Sugeno) Emi Agustina; Agus Sidiq Purnomo
INFORMAL: Informatics Journal Vol 3 No 2 (2018): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v3i2.9991

Abstract

The detection of child growth should be done as early and as accurately as possible, so that if there is a deviation of child growth can be known earlier and can be found a solution to the deviation. In the examination of children who performed in pharmacies depok sleman pengelolahan data inspection done manually so that data is not well recorded, it causes the data is lost and not clear. For that we need a system capable of data menguin so as to minimize the things that are not desirable. In this study, the researchers aimed to create an expert system that gives an idea of the growth in children with fuzzy logic motede which requires several variables, namely age, height, gender and weight which will be taken z-score weight and z- Score height. Based on the test result which has been done with 85 examination data of children, it can be concluded that the implementation of fuzzy sugeno method can be used as a determination of the status of the child's growth with total accuracy of 81.18%.
Sistem Penunjang Keputusan Pemilihan Paket IndiHome Calon Pelanggan Menggunakan Metode Weighted Product Nadafi'ah Hari Fitri; Agus Sidiq Purnomo
INFORMAL: Informatics Journal Vol 5 No 3 (2020): Informatics Journal (INFORMAL)
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v5i3.19463

Abstract

PT Telekomunikasi Indonesia is one of big companies in Indonesia that focuses on technology field. PT Telekomunikasi Indonesia has an important role in providing internet access, of which product is IndiHome. There are several types of internet package to provide the internet access offered by PT Telekomunikasi Indonesia. In this research, the writer aims to help prospective customers make the best decision. Thus, the writer divides the prototype of Decision Support System for Choosing IndiHome Package for Prospective Customers Using WP Method in 4 (four) variables, namely speed, price, internet quota, and need. Based on the results of the test conducted with 48 data using both manual and system calculation, there are 42 compatible data with a percentage of 87,5%.
Sistem Pakar Untuk Mendeteksi Tingkat Resiko Penyakit Jantung Dengan Fuzzy Inferensi (Mamdani) Dany Suktiawan Irman Fiano; Agus Sidiq Purnomo
INFORMAL: Informatics Journal Vol 2 No 2 (2017): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

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Abstract

The development of information technology is needed to help and support in all areas one of the health field. Use of information technology in the field of health to reduce problems in clinical and non-clinical action. One of the problems encountered in the field of health is heart disease. The heart is one of the vital organs for humans. Because of the importance of this heart role, heart health must be maintained in order to function properly. Cardiac examination can be done in the hospital by handled by an internist. However, due to limited access and time for consultation with a medical specialist, it has to wait a relatively long time to find out the results of the examination. So it is necessary media to be able to help detect the risk of heart disease more easily and quickly. In this study will be designed an expert system to detect the risk of heart disease by implementing fuzzy inference (mamdani). Where this system will provide information about the level of risk of heart disease based on risk variables of heart disease that is blood pressure, blood sugar, cholesterol, Body Mass Index (BMI) and history of heart disease family. So it can help people in anticipating the risk of heart disease. Based on 20 data that have been tested against experts and systems, for patients detected having a small risk of heart disease have a percentage of 30%, for a moderate risk level has a percentage of 50%, for a large risk level has a percentage of 20%. As for the level of compliance based on the validation results of experts (doctors) and the system, obtained a percentage of 80% of the appropriate test data, and 20% of the test data is not appropriate.
Penyisipan Citra Pesan Ke Dalam Citra Berwarna Menggunakan Metode Least Significant Bit dan Redundant Pattern Encoding Rahmandhita Fikri Sannawira; Agus Sidiq Purnomo
INFORMAL: Informatics Journal Vol 1 No 1 (2016): INFORMAL: Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

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

Abstract

Teknik steganografi memiliki peranan penting menyangkut hal yang berkaitan dengan pesan rahasia. Steganografi merupakan teknik penyisipan pesan yang telah digunakan oleh orang-orang jaman dulu untuk menjaga kerahasiaan pesan tersebut. Seiring dengan kemajuan teknologi, teknik ini dapat diaplikasikan menggunakan komputer. Sebagai contoh, pembuatan aplikasi steganografi yang dapat dilakukan menggunakan bahasa pemrograman yang berbeda-beda. Metode least significant bit merupakan cara penyisipan yang mengambil bit rendah dari data piksel yang menyusun sebuah file citra gambar. Penggunaan metode ini memungkinkan adanya perubahan atau penambahan sejumlah besar informasi tanpa adanya perubahan tampilan dari citra itu sendiri. Citra pesan disisipkan secara berulang yang ditempatkan pada piksel citra tujuan mulai dari piksel pertama sampai piksel yang terakhir. Secara garis besar, hasil yang didapat dari penelitian ini yaitu: Pertama, cara menyisipkan citra pesan secara berulang ke dalam citra berwarna yang menjadi citra tujuan penyisipan. Ke-dua, cara meng-ekstrak citra hasil penyisipan tersebut sehingga citra pesan yang telah disisipkan dapat diketahui maksudnya.
Analisis Sentimen Masyarakat Terhadap Pandemi Covid-19 Pada Sosial Media Menggunakan Naïve Bayes Clasifier Ade Fitriadin; Agus Sidiq Purnomo
INFORMAL: Informatics Journal Vol 8 No 1 (2023): Informatics Journal (INFORMAL)
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v8i1.33937

Abstract

Social Media is an application internet based of communication. Twitter is one tool that Internet users frequently utilize. Twitter is one tool that Internet users frequently utilize., Twitter is a website that offers microblogging services so that users can communicate ideas, opinions, or just their daily lives through brief writings called Tweets. Social media is a communication tool that Internet users are currently using in large numbers. Tweets from Twitter users cover a wide range of topics, and from these tweets, data can be extracted for sentiment analysis, which can provide information to a variety of parties. The purpose of this project is to develop a system for sentiment analysis that can produce data and information in the form of positive sentiment, negative sentiment, and neutral sentiment. The Nave Bayes Classifier technique is used to categorize feelings. This system receives input in the form of public tweets on the Covid-19 Pandemic. Data visualizations of positive, negative, and neutral sentiment are produced by this system as its output. The Public Sentiment Analysis System with the Nave Bayes Classifier Algorithm can automatically do sentiment analysis with an accuracy of 70% when classifying a tweet using the Nave Bayes Classifier approach. The analysis's findings are presented in tabular form and visually using word clouds and diagrams.
Co-Authors Ade Fitriadin Alfian Romadhon Anief Fauzan Rozi Anief Fauzan Rozi Anief Fauzan Rozi Arif Wiji Setiyanto Arifi Zulaika Aris Susanto Bagas Irvan Bagaskara Berita Estu Widodo Dany Suktiawan Irman Fiano Emi Agustina Erlangga Samudera Kencana Fernando Bayu Andika Ficky Septian Ali Gita Prastianingrum Indah Susilawati Ismunu, R. Sumarwan Jevi Ariyanti M. Ridwan Nur Septian Mutaqin Akbar Muthia Gidriani Maelan Nadafi'ah Hari Fitri Natalia Anjela Sagat Nisriina Nuur Hasanah Octy Kartika Dewi Putri, Novita Anggraini Rahmandhita Fikri Sannawira Rahmandhita Fikri Sannawira, Rahmandhita Fikri Robi Adi Saputra Subardjo, Ratna Yunita Setiyani Supatman Supatman Widatin Mayasari Yasser Yazid Mohammad