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All Journal CogITo Smart Journal JURNAL REKAYASA TEKNOLOGI INFORMASI Sebatik Indonesian Journal of Data and Science TEPIAN Ilmu Komputer untuk Masyarakat

Khoirunnita, Aulia

Amikom University

Author-ID : 3781044

Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Mathematics Other

Published : 14 Documents Claim Missing Document

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Articles

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Improving Database Quality by Applying Consistency Aspects to Naming Fields and Tables Raissa Maringka; Aulia Khoirunnita; Rodney Maringka; Ema Utami; Kusnawi
TEPIAN Vol 2 No 1 (2021): March 2021
Publisher : Politeknik Pertanian Negeri Samarinda

The database is one of the benchmarks that affect the quality of information systems. An effective information system certainly has a quality database. Aspects that can be measured to determine the quality of the database are aspects of truth, consistency, range, level of detail, completeness, minimalism, ability to integrate and readability. One of the mistakes that are often encountered in databases is related to the consistency aspect. Consistency aspects that are not paid much attention to its application can lead to data conflicts due to ambiguity and data duplication. This study aims to improve the quality of the database by applying consistency to the naming of fields and tables. A naming method to produce consistency in standardization was applied in this study.

Android App Rating Classification on Google Play Store Using Random Forest Algorithm with SQL Server Preprocessing Raissa Maringka; Aulia Khoirunnita; Rodney Maringka; Erna Utami; Kusnawi
TEPIAN Vol 2 No 2 (2021): June 2021
Publisher : Politeknik Pertanian Negeri Samarinda

The increasing number of Android applications available on the Google Play Store with the benefits the developers get has attracted the attention of many Android application developers. To benefit from developing Android apps, one way is to know the characteristics of highly rated apps on the Google Play Store. This research will investigate the features of size, installs, reviews, type (free / paid), rating, category, content rating, and price on applications on the Google Play Store to determine the characteristics of high-rated applications. This study uses the Random Forest algorithm to identify the most influential features in high ranking applications on the Google Play Store. At the preprocessing stage, this research uses data cleaning methods and data reduction using SQL Server. This study uses feature important to find out the attributes that most influence the high ranking of Android apps on the Google Play Store. To classify high-ranking applications, the authors use 8-fold cross validation using the Random Forest algorithm and get better results than the Gradient Boost, K-NN, and Decision Tree algorithms with an accuracy of 83%. The results of the Random Forest algorithm also have better performance than the algorithm from the previous research conclusions, with a 0.8% increase in accuracy. To classify high-ranking applications, the authors use 8-fold cross validation using the Random Forest algorithm and get better results than the Gradient Boost, K-NN, and Decision Tree algorithms with an accuracy of 83%. The results of the Random Forest algorithm also have better performance than the algorithm from the previous research conclusions, with a 0.8% increase in accuracy. To classify high-ranking applications, the authors use 8-fold cross validation using the Random Forest algorithm and get better results than the Gradient Boost, K-NN, and Decision Tree algorithms with an accuracy of 83%. The results of the Random Forest algorithm also have better performance than the algorithm from the previous research conclusions, with a 0.8% increase in accuracy.

Analysis of Indonesian Public Opinion Sentiment on Policy on Twitter Social Media “PPKM” Using K-Nearest Neighbor Aulia Khoirunnita; Kusnawi
TEPIAN Vol 2 No 4 (2021): December 2021
Publisher : Politeknik Pertanian Negeri Samarinda

COVID-19 or Coronavirus disease 2019 is currently a pandemic that is spreading very quickly throughout the world, including Indonesia. Various handling and policies have been carried out, one of which is called “PPKM” policy or what can also be called the Enforcement of Restrictions on Community Activities issued by the Indonesian government. “PPKM” is currently one of the topics that is often discussed by the public, one of which is on the Twitter social media platform. The existence of opinions given by the community, it is necessary to have a sentiment analysis. Sentiment analysis is an analytical process obtained from various social media platforms and the internet. The aim is to find out how the public's sentiment towards the implementation of “PPKM” policies in Indonesia is through tweets and comments on the Twitter social media platform. In this study, the process of analyzing public opinion regarding the “PPKM” policy will be carried out by classifying opinions into 3 sentiments, namely positive, negative or neutral. Classification is done using the K-Nearest Neighbor algorithm. The K-Nearest Neighbor (K-NN) algorithm is a classification method for a set of data based on previously classified data learning. Included in supervised learning, where the results of the new query instance are classified based on the majority of the distance proximity of the categories in K-NN. The results of data preprocessing and sentiment classification, in the first test positive sentiment 37.6% of 261 data, negative sentiment 65.9% of 636 data and neutral sentiment 9.

Development Intelligent Agent in Educational Game “Pesut Adventure – Borneo Animal Match-Up” with Shuffle Random Algorithm Khoirunnita, Aulia; Harpad, Bartolomius; Ikhsan, Nurul; Andrea, Reza; Beze, Husmul; Rudito, Rudito
TEPIAN Vol. 4 No. 4 (2023): December 2023
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v4i4.2891

Research developing Edu-game ”Pesut Adventure – Borneo Animal Educational Game” is a research develop Match-Up type game. In this type game, player must find match 2 images of the Borneo animals in the same time, the player must remember the position of the image to be matched. The shuffling-random algorithm used to make images position always scrambled and player never get bored playing. AI technology (artificial intelligence) is also applied on this research. Using the Finite State Machine (FSM) model, the game agent was created in funny-animals form. It will mentoring the children to play this game like a teacher

Decision Support System for Wedding Package Using Multi-Objective Optimization of Ratio Analysis Method Astuti, Indah Fitri; Kridalaksana, Awang Harsa; Alex, Rasni; Fitri, Dewi; Cahyadi, Dedy; Khoirunnita, Aulia
TEPIAN Vol. 5 No. 2 (2024): June 2024
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v5i2.2995

Some of the problems in preparing a wedding day are determining the venue, event concept, concept and others are very time-consuming. Wedding organizers are an option to overcome these problems; one of the wedding organizers in Samarinda is Galeri Shella, which has various wedding packages with facilities and prices, making it difficult for brides-to-be. To make it easier to make the right wedding package decision, a decision support system is made. The decision aims to provide wedding package recommendations with criteria that can be chosen by the bride and groom and their budget. The method used in this system is Multi-Objective Optimization of Ratio Analysis (MOORA) using six criteria catering, venue, decoration, documentation, makeup and price, as a reference calculation that can produce the best wedding package recommendations according to the wishes of the bride and groom. The research results show that the system functions well, is easy to use, and makes it easier for brides to choose wedding packages. From the results of accuracy testing, it is known that the results of manual calculations and the system make no difference, and this study obtained an accuracy value of 100%.

Geographical Information System of Chocolate Plantation Locations in Berau District Using QGIS Web Khoirunnita, Aulia; Ramadhani, Fajar; Andrea, Reza
TEPIAN Vol. 5 No. 1 (2024): March 2024
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v5i1.3024

The cultivation of cocoa plants in Berau Regency has been carried out traditionally with pre-conflict productivity of 700-800 kg/ha, but after the conflict and attacks PBK (Cocoa Fruit Borer) was reported to be only half. The yield quality is also low due to the pest attack and minimum post-harvest treatment. In addition, farmer institutions to be able to carry out activities in the garden together have not been well formed. According to Development Planning Agency at Sub-National Level of Berau Regency, in 2009 the area of cocoa plants in Berau Regency covered an area of 8,644 ha with a production of 2,362 tons. The area is spread across eight districts. With so many chocolate plantations in Berau regency, it certainly makes buyers or visitors, both from related ninas and individuals, become overwhelmed to find the location of chocolate plantations. Therefore, an application is needed to facilitate the search for location and data about the location you want to visit. Geographic Information Systems (GIS) or also known as Geographic Information Systems (GIS) have recently experienced significant developments along with the advancement of geographic information technology. GIS is a computer-based information system that combines map elements (geographical) and information about the map (attribute data) designed to obtain, process, manipulate, analyze, demonstrate and display special data to complete planning, processing and research problems. With the web-based designed GIS application, it is able to solve problems related to the vast chocolate plantation in Berau.

The Bajau-Tainment: An AI-Powered Puzzle Game for Learning the Bajau Language Using Finite State Machine and Shuffle Techniques Khoirunnita, Aulia; Alex, Rasni; Rosmasari , Rosmasari
TEPIAN Vol. 5 No. 3 (2024): September 2024
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v5i3.3140

The research titled "Bajau-tainment" Educational Game (Edu-game) is a research project that focuses on the development of a Puzzle Game designed to improve memory, specifically in language learning. In this game, players must arrange randomized letters to form a word in the Bajau language. This research applies the shuffle random algorithm, which aims to ensure that the arrangement of letters is always shuffled, making the gameplay dynamic, non-monotonous, and engaging. AI Artificial Intelligence (AI) technology will also be applied in this research. Using the Finite State Machine (FSM) model method, the game will feature a game agent character that will accompany children during gameplay, like how a friend accompanies students in a classroom. This virtual friend can display emotions such as happiness or sadness based on the game environment. The research aims to make this edu-game more appealing and interactive for children. The AI game agent will act as a friend who accompanies the child throughout the game.

Co-Authors Asro Nasiri Awang Harsa Kridalaksana Dedy Cahyadi, Dedy Dewi Fitri Ema Utami Erna Utami Fajar Ramadhani Febryan, Raihan Firdaus, Muhammad Bambang Harpad, Bartolomius Husmul Beze, Husmul Indah Fitri Astuti, Indah Fitri Iwan Muhamad Ramdan Jamil, Muh Kusnawi Kusnawi Maringka, Raissa Maringka, Rodney Giovanni Nanda, Arya Nur Rahmad , Didi Nur Rohmah Nurul Ikhsan Prafanto, Anton Putra, Gubtha Mahendra Rasni Alex Reza Andrea Rodney Maringka Rosmasari Rosmasari , Rosmasari Rosmasari Rosmasari, Rosmasari Rudito Rudito Saputra, Muhammad Fawaz Wardhana, Reza Wing Wahyu Winarno

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