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All Journal Jurnal Informatika Telematika : Jurnal Informatika dan Teknologi Informasi Telematika Seminar Nasional Informatika (SEMNASIF) Ekonomi-Qu (Jurnal Penelitian Ilmu Ekonomi) Conference SENATIK STT Adisutjipto Yogyakarta MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer
Santosa, Budi
Faculty Of Industrial Technology, UPN Veteran Yogyakarta, Indonesia
Aerospace Engineering Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Implementation of Steganography on Voice Over Internet Protocol (VOIP) Budi Santosa; Fandi Ahmad Juni Haryanto; Rifki Indra Perwira; Dessyanto Boedi Prasetyo
SENATIK STT Adisutjipto Vol 5 (2019): Peran Teknologi untuk Revitalisasi Bandara dan Transportasi Udara [ISBN 978-602-52742-
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/senatik.v5i0.334

Abstract

Steganography is the science of hiding messages into a container without changes detected by the human senses. Cryptography is the science to keeping the message still safe. Combine between Steganography and cryptography can be used, but if there is exchange information still use separately, worry about there is a change in file size, which can result in damage. VoIP is a technology that allows to communicate with use communication lines on a network. VoIP refers more to voice communication. I am utilizing VoIP as a voice communication channel with voice as a medium for inserting secret messages. The research results that steganography techniques can be used with VoIP. By inserting a text message that is first encrypted and then entered into sound by the Least Significant Bit method. The test results, the Alpha testing, and Beta testing, resulted in a percentage above 90%.
Rainfall prediction using artificial neural network with historical weather data as supporting parameters A H Pratomo; Budi Santosa; S P Tahalea; E T Paripurno; J D Peasetyo; Herlina Jayadianti; M F Pitayandanu
Jurnal Informatika Vol 16, No 2 (2022): May 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jifo.v16i2.a25422

Abstract

Changing climatic patterns are caused by changes in variables, such as rainfalland air temperature that occur continuously in the long term. Rainfall itself isinfluenced by several weather factors such as air humidity, wind speed, airpressure, and temperature. This study experimented to test a combination of9 additional weather parameters such as dew point, wind gusts, cloud cover,humidity, rainfall, air pressure, air temperature, wind direction, and windspeed to predict daily rainfall for one year using the main parameters of therainfall time series. Prediction is done using Artificial Neural Network(ANN). The ANN architecture used is to use 3 to 11 input parameters, 1hidden layer totaling 60 neurons with the ReLu activation function, and 1neuron in the output layer without an activation function. ANN withoutadditional weather parameters obtained an MSE of 0.01654, while predictionusing additional weather parameters obtained an MSE of 0.00884. So thecombination of rainfall time series parameters with additional weatherparameters is proven to provide a smaller MSE value
SISTEM INFORMASI GEOGRAFIS KOMANDO RAYON MILITER (KORAMIL) DAN KECAMATAN BINAAN KORAMIL DI KOTA YOGYAKARTA Budi Santosa; Sri Rahayu Astari; Wilis Kaswidjanti
Seminar Nasional Informatika (SEMNASIF) Vol 1, No 1 (2017): “e-Defense : Menjaga keamanan data menghadapi cyber warfare untuk memperkokoh ke
Publisher : Jurusan Teknik Informatika

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

Abstract

Komando Rayon Militer (Koramil) merupakan satuan komando kewilayahan terkecil dari Tentara Nasional Indonesia (TNI) yang terletak di setiap kecamatan yang berperan sebagai pelaksanaan Sistem Pertahanan Keamanan Rakyat Semesta (sishankamrata). Berdasarkan UU nomor 3 tahun 2002 tentang Pertahanan Negara, Koramil memiliki tugas pokok menyelenggarakan pembinaan teritorial dalam rangka mempersiapkan wilayah pertahanan di darat dan menjaga keamanan wilayahnya untuk mendukung tugas pokok Komando Distrik Militer (Kodim). Pembinaan territorial meliputi segala unsur wilayah geografi, demografi dan kondisi social agar tercipta suatu kekuatan wilayah yang tangguh dalam mengatasi segala ancaman, gangguan dan hambatan yang mengganggu kelangsungan hidup berbangsa dan bernegara serta jalannya pembangunan nasional. Mengingat pentingnya fungsi Koramil dan harus adanya kerja sama antara masyarakat dan Koramil, maka anggota Koramil harus mengetahui daerah binaannya, begitu juga masyarakat yang kesulitan mengetahui Koramil mana yang membina daerahnya dan kegiatan ataupun kejadian apa yang ada di daerahnya, maka di bangun Sistem Informasi Geografis Persebaran Komando Rayon Militer (Koramil) untuk mempermudah anggota serta masyarakat mengetahui informasi letak koramil dan wilayah yang dibina. Metodologi penelitian sistem menggunakan metode waterfall dalam pengembangannya dengan pemetaan menggunakan teknologi Google Maps. Pada sistem terdapat Admin (Kodim dan Koramil) dan User pengguna (Anggota dan Masyarakat). Sistem ini memiliki fitur perbesaran (zoom in) dan pengecilan (zoom out), menampilkan rute dan jarak terdekat menuju koramil, serta informasi kegiatan yang sudah dilaksanakan dan belum dilaksanakan. Pengunjung juga dapat melihat tingkat kejadian disetiap kelurahan melalui diagram statistik setiap bulannya sehingga masyarakat dapat bekerjsama untuk meningkatkan keamanan dan pertahanan wilayah.
Essay auto-scoring using N-Gram and Jaro Winkler based Indonesian Typos Herlina Jayadianti; Budi Santosa; Judanti Cahyaning; Shoffan Saifullah; Rafal Drezewski
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 22 No 2 (2023)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i2.2473

Abstract

Writing errors on e-essay exams reduce scores. Thus, detecting and correcting errors automatically in writing answers is necessary. The implementation of Levenshtein Distance and N-Gram can detect writing errors. However, this process needed a long time because of the distance method used. Therefore, this research aims to hybrid Jaro Winker and N-Gram methods to detect and correct writing errors automatically. This process required preprocessing and finding the best word recommendations by the Jaro Winkler method, which refers to Kamus Besar Bahasa Indonesia (KBBI). The N-Gram method refers to the corpus. The final scoring used the Vector Space Model (VSM) method based on the similarity of words between the answer keys and the respondent’s answers. Datasets used 115 answers from 23 respondents with some writing errors. The results of Jaro Winkler and N-Gram methods are good in detecting and correcting Indonesian words with the accuracy of detection averages of 83.64% (minimum of 57.14% and maximum of 100.00%). In contrast, the error correction accuracy averages 78.44% (minimum of 40.00% and maximum of 100.00%). However, Natural Language Processing (NLP) needs to improve these results for word recommendations.
Use of Hybrid Methods in Making E-commerce Product Recommendation Systems to Overcome Cold Start Problems Budi Santosa; Muhamad Azam Fuadi; Mangaras Yanu Florestiyanto; Vynska Amalia Permadi; Wilis Kaswidjanti
Telematika Vol 16, No 1: February (2023)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v16i1.2080

Abstract

The large number of users and the items offered in e-commerce make it difficult for buyers to choose the right items and sellers to offer their items to the right buyers. To overcome this problem, a system that can offer and recommend goods automatically, namely a recommendation system is needed. One of the most popular methods used to create a recommendation system is collaborative filtering, the recommendations are created based on similarities in user behavior. Unfortunately, this method has a weakness, namely cold start, where the recommendations will be inaccurate on data that has a lot of new users and items due to minimal historical data regarding user behavior. This problem will be tried to be solved in this study using a hybrid method, where this method combines more than 1 method to create a list of recommendations so that it will cover the shortcomings of each method. This study uses Amazon's e-commerce product and transaction data. The use of the hybrid method in this study can overcome the cold start problem by using switching and mixed methods, by not using the collaborative filtering model on new user recommendations or users who have little interaction. New users will receive recommendations based on the combination of popularity-based and content-based filtering models. This can be seen from the Mean Absolute Error (MAE) value of the model, where the MAE value for the data with a minimum user has at least 3 times rating is 0.566883, for the minimum 7 times, the MAE value is smaller, 0.487553.
Co-Authors A H Pratomo Agus Sasmito Aribowo Agus Sasmito Aribowo C Ambar Pujiharjanto Dessyanto Boedi Prasetyo Dessyanto Boedi Prasetyo Dian Bagus Saptonugroho Didi Setya E T Paripurno Fajar Kurnia Fandi Ahmad Juni Haryanto Herlina Jayadianti Herry Sofyan Heru Cahya Rustamaji Ial Irwan Arahman J D Peasetyo Judanti Cahyaning Juwairiah Juwairiah Ketut Nama M F Pitayandanu Mangaras Yanu F Mangaras Yanu Florestiyanto Markus Priharjanto Muhamad Azam Fuadi Muhammad Bagus Prasetyo Nabila Valinka Pusean Novrido Charibaldi Oliver Samuel Simanjuntak Rafal Drezewski Rahmat Adeputra Rahmat Nur Isni Rifki Indra Perwira Rifki Indra Perwira Rifki Perwira S P Tahalea Saifullah, Shoffan Sri Rahayu Astari Vynska Amalia Permadi Wahyu Ari Widiyastuti Wilis Kaswidjanti Wilis Kaswidjanti Yan Indra Putra