Article Per Year (5 Year)
p-Index From 2020 - 2025
4.288
P-Index
This Author published in this journals
All Journal Dinamik Semantik Techno.Com: Jurnal Teknologi Informasi Telematika : Jurnal Informatika dan Teknologi Informasi Jurnas Nasional Teknologi dan Sistem Informasi JAIS (Journal of Applied Intelligent System) Proceeding SENDI_U Journal of Information System Sistemasi: Jurnal Sistem Informasi Journal of Applied Geospatial Information Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Eksplora Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Techne : Jurnal Ilmiah Elektroteknika Jurnal Sistem Cerdas EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Teknik Informatika (JUTIF) Journal of Applied Computer Science and Technology (JACOST) Journal La Multiapp Community: Jurnal Pengabdian Pada Masyarakat
Ardytha Luthfiarta
Teknik Informatika S1, Fakultas Ilmu Komputer, Universitas Dian Nuswantoro
Aerospace Engineering 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 Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Physics Social Sciences Other

Published : 44 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 5 Documents
Search
Journal : JAIS (Journal of Applied Intelligent System)

 1 
Naive Bayes Classifier Based Geographic Information System for University Search Information Junta Zeniarja; Ardytha Luthfiarta; Catur Supriyanto
Journal of Applied Intelligent System Vol 2, No 2 (2017): December 2017
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v2i2.1587

Abstract

Information about the geographical location of universities is necessary for graduates of Senior High School who want to continue their education to a university. Most of the graduate students do not know the location of the universities since the geographical location of Google Maps is less clear and less precise. Therefore, the application of Geographic Information Systems (GIS) based on Information Retrieval (IR) is expected to facilitate the graduate students to know the exact location of the university. In this paper, IR-based GIS application is developed by using web programming. The web is used as a search engine when someone wants to find a college. The application shows the map and information of the college in the area according to the query of the user. Naive Bayes algorithm is used to classify the user query and locate the query on the map. Based on our prototype, the application is promising to be implemented for the student.
Penerapan Algoritma K-Nearest Neighbor pada Information Retrieval dalam Penentuan Topik Referensi Tugas Akhir Ramadhan Rakhmat Sani; Junta Zeniarja; Ardytha Luthfiarta
Journal of Applied Intelligent System Vol 1, No 2 (2016): Juni 2016
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v1i2.1189

Abstract

Perpustakan sebagai bagian penting universitas,   berperan sebagai sumber pustaka dan referensi laporan Tugas Akhir(TA). Semua koleksi tersebut ditempatkan dalam ruangan tertentu sesuai dengan kategorinya dan data tersebut sudah terkomputerisasi dengan baik di dalam server database. Permasalahan penelitian adalah  pencarian dan pengidentifikasian laporan Tugas  Akhir  berdasarkan  topik  yang  diangkat. Tujuan penelitian ini mendapatkan akurasi klasifikasi yang baik menggunakan algoritma K-Nearest Neighbor (KNN) dan menerapkannya kedalam sebuah program. Sehingga klasifikasi topik TA dapat menjadi solusi untuk menyelesaikan permasalahan tersebut. Kata kunci — Information Retrieval, K-Nearest Neighbor, Text Mining, Klasifikasi
Prediction on Deposit Subscription of Customer based on Bank Telemarketing using Decision Tree with Entropy Comparison Ardytha Luthfiarta; Junta Zeniarja; Edi Faisal; Wibowo Wicaksono
Journal of Applied Intelligent System Vol 4, No 2 (2019): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v4i2.2772

Abstract

Banking system collect enormous amounts of data every day. This data can be in the form of customer information,  transaction  details,  risk profiles,   credit   card   details,   limits   and   collateral    details, compliance  Anti Money Laundering (AML) related information, trade  finance  data,  SWIFT  and  telex  messages. In addition,  Thousands  of decision  are  made in Banking system. For example, banks everyday creates credit decisions,  relationship  start  up,  investment   decisions, AML  and  Illegal  financing  related decision.  To create this decision, comprehensive review on various  reports  and drills  down  tools  provided  by the banking systems is needed.  However, this is a manual process which  is  error  prone  and  time  consuming  due  to  large volume of transactional  and historical  data available. Hence, automatic knowledge mining is needed to ease the decision making process.  This research focuses on data mining techniques to handle the mentioned problem. The technique will focus on classification method using Decision Tree algorithms.  This research provides an overview of the data mining techniques and   procedures will be performed.   It also provides   an insight   into how these techniques can be used in deposit subscription  in banking system to make a decision making process easier and more productive. Keywords - Telemarketing, bank deposit, decision tree, classification, data mining, entropy.
Pattern Recognition Of Javanese Letter Using Template Matching Correlation Method Irham Ferdiansyah Katili; Fairuz Dyah Esabella; Ardytha Luthfiarta
Journal of Applied Intelligent System Vol 3, No 2 (2018): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v3i2.1954

Abstract

In this modern age, the impact of globalization is increasingly entering and expanding into most societies. One impact of globalization makes people prefer to learn the language and use a foreign language rather than the local language, especially the Java language. It is very influential on the knowledge of the community about the existence or the existence of Javanese Letter, especially in the field of education. In this study, In this research will be made an application to recognize the writing of Javanese Letter based on Optical Character Recognition (OCR). Matching templates correlation can be used as pattern recognition methods. How the Template Matching Algorithm works by matching the template image with the test image after going through the Pre-processing and segmentation process. From the research that has been done by using 10 character template and 20 data testing get accuracy equal to 93.44% and error rate 6.56%. So the Matching Template Algorithm can well recognize the Javanese Letter pattern.
Transfer Learning with Xception Architecture for Snakefruit Quality Classification Rismiyati Rismiyati; Ardytha Luthfiarta
Journal of Applied Intelligent System Vol 7, No 2 (2022): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v7i2.6797

Abstract

Machine learning has been greatly used in the field of image classification. Several machine learning techniques perform very well in this task. The development of machine learning technique in recent years are in the direction of deep learning. One of the main challenge of deep learning is that it requires the number of the samples to be extremely large for the model to perform well. This is because the number of feature that trainable parameter are huge. One of the solution to overcome this is by introducing transfer learning. One of the architecture that is currently introduced is Xception architecture. This architecture is claimed to outperform VGG16, ResNet50, and inception in terms of model accuracy and model size. This research aims to classify snakefruit quality by using transfer learning with Xception architecture. This is to explore possibility to achieve better result as Xception architecture generally perform better than other available architecture in transfer learning. The snakefruit quality is classified into two classes. Hyperparameter value is optimized by several scenario to determine the best model. The best performance is achieved by using learning rate of 0.0005, momentum 0.9 and dropout value of 0 or 0.25. The accuracy achieved is 94.44%.
Co-Authors ., Junta Zeniarza ., Junta Zeniarza Abu Salam Abu Salam Adhitya Nugraha Adhitya Nugraha Adhitya Nugraha Affandy Affandy Althoff, Mohammad Noval Aris Febriyanto Aryanti, Firda Ayu Dwi Astuti, Yani Parti Bagus Dwi Satya, Mohammad Wahyu Basiron, Halizah Cahya, Leno Dwi Catur Supriyanto Catur Supriyanto Defri Kurniawan Dhita Aulia Octaviani Dzaki, Azmi Abiyyu Edi Faisal Edi Sugiarto Egia Rosi Subhiyakto, Egia Rosi Erwin Yudi Hidayat Fahreza, Muhammad Daffa Al Fahrezi, Sahrul Fahrezi Fahrezi, Sahrul Yudha Fahri Firdausillah Fairuz Dyah Esabella Farandi, Muhammad Naufal Erza Farsya, Nabila Zibriza Fauzyah, Zahrah Asri Nur Firmansyah, Gustian Angga Ganiswari, Syuhra Putri Hafiizhudin, Lutfi Azis Haresta, Alif Agsakli Harun Al Azies Hasan Shobri Heru Lestiawan Huda, Alam Muhammad Ika Novita Dewi Imam Muttaqin, Almas Najiib Indrawan, Michael Irham Ferdiansyah Katili Ivan Zuhdiansyah Julius Immanuel Theo Krisna Junta Zeniarja Krisna, Julius Immanuel Theo L. Budi Handoko Leno Dwi Cahya Maharani, Zahra Nabila Mahardika, Pramesthi Qisthia Hanum Md. Mahadi Hasan, Md. Mahadi Michael Indrawan Muhammad Daffa Al Fahreza Muhammad Jamhari Muhammad Rafid Mumtaz, Najma Amira Muttaqin, Almas Najiib Imam Nauval Dwi Primadya Nisa, Laila Rahmatin Octaviani, Dhita Aulia Primadya, Nauval Dwi Rafid, Muhammad Ramadhan Rakhmat Sani Rismiyati Rismiyati Sahrul Yudha Fahrezi Salsabila, Pramesya Mutia Satya, Mohammad Wahyu Bagus Dwi Setiawan, Dicky Soeroso, Dennis Adiwinata Irwan Sri Winarno Sri Winarno Suprayogi Suprayogi Suryaningtyas Rahayu Syarifah, Ulima Muna Utomo, Danang Wahyu Wibowo Wicaksono Wibowo Wicaksono Wulandari, Kang Andini Wulandari, Kang, Andini Zarifa, Yasmine Zuhdiansyah, Ivan