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Taqwa Hariguna
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IJIIS: International Journal of Informatics and Information Systems
Published by Bright Publisher
ISSN : -     EISSN : 25797069     DOI : https://doi.org/10.47738/ijiis
Core Subject : Science,
Computer Science & IT
The IJIIS is an international journal that aims to encourage comprehensive, multi-specialty informatics and information systems. The Journal publishes original research articles and review articles. It is an open access journal, with free access for each visitor (ijiis.org/index.php/IJIIS/); meanwhile we have set up a robust online platform and use an online submission system to ensure the international visibility and the rigid peer review process. The journal staff is committed to a quick turnaround time both in regards to peer-review and time to publication.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol 2, No 1: March 2019" : 5 Documents clear
Comparison of Cart and Naive Bayesian Algorithm Performance to Diagnose Diabetes Mellitus Santiko, Irfan; Subarkah, Pungkas
International Journal of Informatics and Information Systems Vol 2, No 1: March 2019
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v2i1.9

Abstract

Based on Indonesia's health profile in 2008, Diabetes Mellitus is the cause of the ranking of six for all ages in Indonesia with the proportion of deaths of 5.7% under stroke, TB, hypertension, injury and perinatal. This is reinforced by WHO (2003), Diabetes Mellitus disease reached 194 million people or 5.1 percent of the world's adult population and in 2025 is expected to increase to 333 million inhabitants. In particular, in Indonesia, people with Diabetes Mellitus are increasing. In 2000, Diabetes Mellitus sufferers have reached 8.4 million people and it is estimated that the prevalence of Diabetes Mellitus in 2030 in Indonesia reaches 21.3 million people.This allows researchers and practitioners to focus their attention on detecting/diagnosing diabetes mellitus and to prevent it because the disease can cause complications. The method used in this research was problem identification, data collection, pre-processing stage, classification method, validation and evaluation and conclusion. The algorithm used in this research was CART and Naïve Bayes using dataset taken from UCI Indian Pima database repository consisting of clinical data ofpatients who detected positive and negative diabetes mellitus. Validation and evaluation method used was 10-crossvalidation and confusion Matrix for the assessment of precision, recall and F-Measure. The result of calculation has been done, got the accuracy result on CART algorithm equaled to 76.9337% with precision 0.764%, recall 0.769%, and F-Measure 0.765%. Whilethe diabetes dataset was tested with the Naïve Bayes algorithm, got an accuracy of 73.7569% with precision 0.732%, recall 0.738%, and F-Measure 0.734%. From these results it can be concluded that to diagnose diabetes mellitus disease it is suggested to use CART algorithm.
Expert System for Simulation of Pest and Disease Diagnosis in Onion Plant Using Putty Shafer Method and Rule-Based Approach Dianingrum, Melia; Hermanto, Nandang; Rifa'i, Mohamad Iqbal
International Journal of Informatics and Information Systems Vol 2, No 1: March 2019
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v2i1.8

Abstract

The expert system is trying to adopt a system of human knowledge into a computer so that the computer can solve problems like the experts. The expert system is well designed in order to solve a particular problem by mimicking the work of the expert. The development of an expert system is expected to be resolved problems with the help of experts. The problems addressed by an expert not only the problems that rely on algorithms but sometimes elusive problems. An expert with knowledge and experience can overcome these problems. The application of an expert system in this study is made to diagnose pests and diseases in onion plants based on the web. The Data Collection method used is literature studies, interviews and observation. The stages of research used are literature review, data processing analyst, and Onion analyzed and photographed which then is uploaded and analyzed, Dempster Shafer method, application development, evaluation. In the last stage is the pilot study conducted using a Blackbox method and testing to the user. The result of the research is in the form of an expert system application that can diagnose pests and diseases of onion as many as 7 types of diseases. The output system is in the form of onion disease searching result obtained based on the symptoms inputted by the user. The result of Blackbox Testing is all functions of the application successfully run well. Testing to the users rated well both appearance and information of the application.
E-Government Asset Management Using the Extreme Programming Hariguna, Taqwa; Tsamara, Mirra
International Journal of Informatics and Information Systems Vol 2, No 1: March 2019
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v2i1.1

Abstract

Village Asset Management is a village property derived from the original property of the village, purchased or acquired for the expense of the village's income and expenditure budget (APBDes) or other legitimate acquisition of rights. In this study is the management of the village assets Kebumen Baturraden subdistrict and The problems acquired are the recording of village assets and the realization of the budget of the village assets that are still written so it takes A long time, Therefore the purpose in This research is to help and facilitate management performance in village Asset listing. Methods of collecting data using observations, interviews and Library studies. System development method using the Extreme programming method consisting of four phases of system development, namely planning, design, coding and test. The result of this research is a Village Asset Management E-Government using the Extreme Programming method of the Kebumen Village case study. The conclusion of this research is that it can simplify the management and realization of village assets budget due to the two interconnected reporting are reports of budget realization and village Asset report.
Community Opinion Sentiment Analysis on Social Media Using Naive Bayes Algorithm Methods Hariguna, Taqwa; Rachmawati, Vera
International Journal of Informatics and Information Systems Vol 2, No 1: March 2019
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v2i1.11

Abstract

The election of Governor is an election event for the Regional Head for the future of the region and the country. The Central Java Governor election in 2018 was held jointly on 27 June 2018, which was followed by 2 candidate pairs of the governor. Its many responses from people through twitter's social media to bring up opinions from the public. Sentiment analysis of 2 research objects of Central Java Governor 2018 candidates with a total of 400 tweets with each candidate being 200 tweets. The used of tweets are divided into 3 classes: positive class, neutral class and negative class. In this study the classification process used the Naive Bayes Classifier (NBC) method, while for data preprocessing is using Cleansing, Punctuation Removal, Stopword Removal, and Tokenisation, to determine the sentiment class with the Lexicon Based method produces the highest accuracy in the Ganjar Pranowo dataset with an accuracy of 87,9545%, Precision value is 0.891%, Recall value is 0.88% and F-Measure is 0.851% while Sudirman Said dataset has an accuracy rate of 84.322%, Precision value of 0.867%, Recall value of 0.843% and F-Measure of 0.815%. From these results, we can conclude that the Ganjar Pranowo dataset was higher compared to Sudirman Said's dataset.
Analysis of Sequential Book Loan Data Pattern Using Generalized Sequential Pattern (GSP) Algorithm Astuti, Tri; Anggraini, Lisdya
International Journal of Informatics and Information Systems Vol 2, No 1: March 2019
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v2i1.10

Abstract

As a center for learning and information services, STMIK Amikom Purwokerto Library is a source of learning and a source of intellectual activity that is very important for the entire academic community in supporting the achievement of the college Tridharma program. Book lending transaction data, can produce information that is important as supporting decision making when further analyzed. One useful information is that it can provide information in the form of user behavior patterns in borrowing books that are used to maintain the availability of related book stocks to be balanced. This study uses the Generalized Sequential Pattern (GSP) algorithm, which can be used to determine the behavior patterns of users in each transaction and can show relationships or associations between books, both requested simultaneously and sequentially. From the calculations that have been done, 295 frequent sequences are consisting of 3 sequence patterns that are formed from the minimum support of 0.53% or the minimum number of books borrowed, namely 2 books. Three book items have very strong linkages in book lending transactions, namely book code 6690, 2026, and 8131.

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