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INDONESIA
JURNAL ILMIAH INFORMATIKA
ISSN : 23378379     EISSN : 26151049     DOI : -
Core Subject : Science,
Jurnal Teknologi Informatika dan Sistem Informasi Fakultas Teknik dan Komputer UPB, telah menerbitkan publikasi ilmiah dengan topik yang mencakup tentang Information System, Geographical Information System, Remote Sensing, Cryptography,artificial intelligence, Computer Network, Security dan Database.
Arjuna Subject : -
Articles 50 Documents
ANALISIS ALGORITMA AES DALAM MENGAMANKAN DATA PADA KANTOR WALIKOTA PEMATANGSIANTAR hartato, eko; Gunawan, Indra; Parlina, Iin; Solikhun, Solikhun; Wanto, Anjar
JURNAL ILMIAH INFORMATIKA Vol 8 No 01 (2020): Jurnal Ilmiah Informatika (JIF)
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v8i1.1799

Abstract

Data is information that is kept very confidential because it contains important information about the company or agency. Computers are currently the main component in the company that is able to store data, speed up work, improve the quality and quantity of services, simplify the transaction process, and others. But in terms of computer security still has several loopholes that allow a person or group to easily retrieve data or information on the computer. To avoid theft and manipulation of data, it is necessary to implement a security system. Cryptography is the study of how to change information from normal conditions / forms (can be understood) into a form that cannot be understood. One method that can be used to secure messages / information is the Advanced Encryption Standard (AES). The application of the AES cryptographic algorithm in securing data at the Pematangsiantar Mayor's Office shows that this algorithm can generate encryption that cannot be understood by humans and produces the exact decryption with the initial plaintext input.
METODE PROFILE MATCHING MENENTUKAN PENERIMA BANTUAN PERBAIKAN RUMAH PADA KECAMATAN SIANTAR MARTOBA Paranthi, Yurri Widya
JURNAL ILMIAH INFORMATIKA Vol 8 No 01 (2020): Jurnal Ilmiah Informatika (JIF)
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v8i1.1848

Abstract

Home Improvement Assistance in Siantar Martoba District is one of the government programs. The assessment process and decision making in this program is still subjective. The middle class people who have permanent jobs and have valuables thing such as motorbikes and television are still listed as a recipient of the Home Improvement Assistance. The application made in this research is a decision support system for recipients of home improvement assistance in Siantar Martoba district using the Profile Matching method.This application is used to help assess the competency of prospective recipients of home improvement assistance in Siantar Martoba and provide recommendations in decision making. The assessment criteria used include aspects of the state of the house and economic aspects. This profile matching method will compare the profiles of participants with ideal profiles of recipients of home improvement assistance. The smaller gap will make the opportunity to pass the assessment even greater. It is expected that the decision support system for recipients of home improvement assistance can help the government in determining prospective recipients entitled to help with housing repairs in Siantar Martoba with a faster, more accurate and effective assessment.
SISTEM PENDUKUNG KEPUTUSAN PENILAIAN KINERJA JASA PRAMUBAKTI MENGGUNAKAN METODE MOORA Hamria Hamria, Hamria; Azwar, Azwar; Arja, Khaerul
JURNAL ILMIAH INFORMATIKA Vol 8 No 01 (2020): Jurnal Ilmiah Informatika (JIF)
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v8i1.1824

Abstract

Decision support system is a system that can help problems that can help problems that occur for decision making quickly and can know the highest to lowest value to determine the selection results. In this research there is a case study which is an example of solving a problem with a decision support system, where the problem of the case at the Boalemo District Police is how to conduct performance appraisal of pre serving services that still use the manual method making the performance appraisal process take a long time to get results. Therefore created a system that supports decisions that can help the assessment process. This study aims to test the performance and effectiveness of the decision support system of the Pramubakti service performance assessment using the MOORA method as a basis for decision making. Based on the results of research that has been carried out it can be concluded that the system can assist the decision makers in carrying out performance appraisals quickly. Evidenced by the results of testing conducted  with the white box testing method and base path testing which produces a value of V(G) = 4 CC, so it is obtained that the logic of the flowchart calculation of normalization and assessment is correct based on black box testing which includes test input processes and output with reference to software design has been met with results in accordance with the design.
SCRAPING WEB MARKETPLACE MENGGUNAKAN METODE DOM PARSING UNTUK PENGUMPULAN DATA PRODUK Bahrudin, Muhammad Joko Umbaran Haris; Gutama, Hardan
JURNAL ILMIAH INFORMATIKA Vol 8 No 01 (2020): Jurnal Ilmiah Informatika (JIF)
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v8i1.1852

Abstract

Web Scraper is a way of extracting scripts that run there that are commonly chosen to do web memos via DOM parsing. Specific nodes that are collected using DOM parsers and tools like XPath help the process of scraping web pages. In this study using the DOM Parsing method to obtain product data on the market. Sraper can be further developed as a data collection technique on the internet for further research that can be provided about the concept of big data to be used for forecasting or getting the information needed. Alone Parsing is a way of breaking data or symbols, both in language and in language, according to formal grammar rules. After using the parshing technique, it will be generated again using Parse Tree, which is a process of compiling product data that forms like a tree, using siyntak analysis to break down product categories.
PENGGUNAAN FITUR WORDCLOUD DAN DOCUMENT TERM MATRIX DALAM TEXT MINING Pradana, Musthofa Galih
JURNAL ILMIAH INFORMATIKA Vol 8 No 01 (2020): Jurnal Ilmiah Informatika (JIF)
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v8i1.1838

Abstract

Much information and data can be extracted from social media differences, with more and more social media users. Data in 2019 states that there are 150 million users of social media in Indonesia. Based on the number of active users of social media, it can be exploited for deeper information extraction and analysis. One way that can be done is by taking comment data on social media for further processing or mining. In this research, we do data crawling and utilize the Term Document Matrix and Word Cloud features to find the most frequently written words on Facebook and Twitter social media. The words that appear most often based on the Word Cloud feature will be analyzed to infer from words written on social media. In this study the word that often appears on Facebook is the word garuda for 3621 words and on Twitter is the Indonesian word for 1572. On the Facebook platform the resulting word has a positive tendency because the topics discussed are still around airlines, while on Twitter it has a negative tendency because of the word what appears is a personal name that has a negative tendency for the company.
IMPLEMENTASI ALGORITMA K-MEANS CLUSTERING TINGKAT KEPENTINGAN TAGIHAN RUMAH SAKIT DI PT PERTAMINA (PERSERO) novia, ema ainun; Isti Rahayu, Woro; Fachri Pane, Syafrial
JURNAL ILMIAH INFORMATIKA Vol 8 No 01 (2020): Jurnal Ilmiah Informatika (JIF)
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v8i1.1844

Abstract

Claims are claims that can be in the form of money, services or goods that are the obligations of another party to an entity. Problems that occur in this department do not yet have information about the bills to be paid based on their level of importance.Therefore this study aims to create a billing grouping system based on the level of importance in each hospital using a data mining algorithm with the K-means method. This method is considered appropriate because of group data based on the closest cluster center point with the data. Billing based on hospitals into 2 clusters namely urgent cluster (C1) and non-urgent cluster (C2).From the calculation of 104 data samples consisting of 4 hospitals, 14 data are in the "Urgent" cluster (C1), 90 data are in the "Not Urgent" cluster (C2). The results are then grouped again based on hospitals so that the grouping obtained at Pertamina Center hospitals cluster 1 there are 3 data and cluster 2 there are 2 data. Pertamina Jaya hospital for cluster 1, there is 1 data and in cluster 2 there are 44 data. In Pertamina Balikpapan hospital for cluster 1, there is 7 data and for cluster 2 there are 25 data. And at Pertamina Plaju hospital for cluster 1 there is 1 data and for cluster 2 there is 13 data.
PENGENALAN SUARA PADA KAMUS BANJAR-INDONESIA DAN INDONESIA-BANJAR MENGGUNAKAN STATISTIK INFERENSI Purnajaya, Akhmad Rezki; Indriani, Fatma; Faisal, Mohammad Reza
JURNAL ILMIAH INFORMATIKA Vol 8 No 01 (2020): Jurnal Ilmiah Informatika (JIF)
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v8i1.1727

Abstract

Banjar language used in conversation and daily life around the area. So foreigners who come to the regions of South Kalimantan will have difficulty in communicating. Besides, most local residents in the backwoods of South Kalimantan can not use Indonesian language properly, they would be more convenient to use regional language to interact. For that reason we need an Android application can help users to find the translation of a word or phrase whenever and wherever. With the help of Google Voice Search, this application can also listen to the voice of the user to be converted into text and insert into the input translation. Speech recognition of Banjar language required a literacy training data by using the method of statistical inference to make results appropriated. Testing using method of Black Box Testing to measure the percentage of suitability of the results of translation, speech recognition for Indonesian language and speech recognition Banjar language using method of Statistical inference. So the results of translation accuracy 100% and accuracy of speech recognition Indonesian language and Banjar language by 97.85% and 82.74%.
EVALUASI REVOLUSI INDUSTRI 4.0 PADA BIDANG PERTANIAN MENGGUNAKAN MODEL INTEGRASI DELONE AND MCLEAN, UTAUT DAN HOT FIT. Saputro, Pujo Hari; Faizah, Arbiati; Augusta J.F, Reza
JURNAL ILMIAH INFORMATIKA Vol 8 No 01 (2020): Jurnal Ilmiah Informatika (JIF)
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v8i1.1845

Abstract

This study tries to evaluate the industrial revolution 4.0 implementation results in agriculture in form of oyster mushroom temperature management technology. This implementation is intended to improve the quality and quantity of mushroom harvests, however further evaluation is still needed to determine the success and acceptance of the community towards the proposed technology. Evaluations were carried out using the integration of the DeLone and Mclean Success Models, the UTAUT acceptance model coupled with the Hot FIT model. The three models are then integrated to form a new model that is used to construct the questionnaire as an assessment. From the results of the 7-steps fit model, it can be concluded that the proposed model can be used and suitable for this study. From the results of the path analysis test it was concluded that human and technological factors will positively influence the use of the technology implemented. Lastly, as long as the proposed technology is used by mushroom farmers, it can be categorized as successful or successful..
ANALISA DAN PENERAPAN METODE KLASIFIKASI DALAM DATA MINING UNTUK PENERIMAAN SISWA JALUR NON-TULIS Kurniah, Reni
JURNAL ILMIAH INFORMATIKA Vol 8 No 01 (2020): Jurnal Ilmiah Informatika (JIF)
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v8i1.1766

Abstract

Plus Negeri 7 Bengkulu City is needed an information that can help the school to be younger in accepting new students in accordance with the criteria school. From the admission data the student will get useful information for the school where the existing data will be an information and policy in accepting students who will go to school. Importance Information obtained from the school will help the school in determining students who will accepted. C4.5 algorithm is a classification technique in which there is a data mining process using the CRISP-DM method so that a simple but accurate data classification will be obtained. Therefore the use of the C4.5 algorithm will make it easier for schools to make policies in accepting students. new
PREDIKSI PRODUKSI SUSU SEGAR DI INDONESIA MENGGUNAKAN ALGORITMA BACKPROPAGATION Saragih, Jonas Rayandi; Hartama, Dedy; Wanto, Anjar
JURNAL ILMIAH INFORMATIKA Vol 8 No 01 (2020): Jurnal Ilmiah Informatika (JIF)
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v8i1.1847

Abstract

Milk is a white liquid produced from female mammals that contain carbohydrates that are useful for humans. Based on data from the Indonesian Statistics Agency, milk productivity in Indonesia from 2012 to 2018 experienced an unstable curve. Therefore this research was conducted to predict and find out the level of development of milk productivity in Indonesia for the following years, so that companies that use milk have a reference to continue to strive to increase milk productivity in Indonesia to remain stable in order to meet the needs of the community and  minimize milk imports. This algorithm used is backpropagation neural network. This algorithm is able to predict good data especially data that is sustainable in a certain period of time. to simplify this research the author uses the Matlab 2011 application. To facilitate writers, authors use 5 architectural model, namely 5-9-1 = 94%, 5-12-1 = 88%, 5-14-1 = 88%, 5-15-1 = 94%, 5-17-1 = 94 %. So we get the best architectural model using the architectural mode 5-15-1 with an accuracy rate of 94% with MSE = 0,000999842.  Finally, this model is good enough to predict fresh milk production by province in Indonesia