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All Journal Perfecting a Video Game with Game Metrics SCAN EMITTER International Journal of Engineering Technology
Entin Martiana Kusumaningtyas
Departemen Informatika Dan Komputer, Politeknik Elektronika Negeri Surabaya
Computer Science & IT

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Automatic Representative News Generation using On-Line Clustering Sigita, Marlisa; Barakbah, Ali Ridho; Kusumaningtyas, Entin Martiana; Winarno, Idris
EMITTER International Journal of Engineering Technology Vol 1, No 1 (2013)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (8313.353 KB)

Abstract

The increasing number of online news provider has produced large volume of news every day. The large volume can bring drawback in consuming information efficiently because some news contain similar contents but they have different titles that may appear. This paper presents a new system for automatically generating representative news using on-line clustering. The system allows the clustering to be dynamic with the features of centroid update and new cluster creation. Text mining is implemented to extract the news contents. The representative news is obtained from the closest distance to each centroid that calculated using Euclidean distance. For experimental study, we implement our system to 460 news in Bahasa Indonesia. The experiment performed 70.9% of precision ratio. The error is mainly caused by imprecise results from keyword extraction that generates only one or two keywords for an article. The distribution of centroid’s keywords also affects the clustering results.Keywords: News Representation, On-line Clustering, Keyword Aggregation, Text Mining.
Smart I’rab: Smart Aplicasion for Arabic Grammar Learning Farmadi, Syd. Ali Zein; Barakbah, Ali Ridho; Kusumaningtyas, Entin Martiana
EMITTER International Journal of Engineering Technology Vol 1, No 1 (2013)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

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Abstract

Arabic grammar, known as nahwu, is necessary to comprehend the Holy Qur’an that is completely written in Arabic. However, many people get trouble to study this skill because there are various kinds of word formation and sentences that may be created from a single verb, noun, adjective, subject, predicate, object, adverb or another formation. This research proposes a new approach to identify the position and word function in Arabic sentence. The approach creates smart process that employs Natural Language Processing (NLP) and expert system with modeling based on knowledge and inference engine in determining the word position. The knowledge base determines the part of speech while the inference engine shows the word function in the sentence. On processing, the system uses 82 templates consisting of 34 verb templates, 34 subject pronouns, 14 pronouns for object or possessive word. All the templates are in the form of char array for harakat (vowel) and letters which become the comparators for determining the part of speech from input word sentence. Output from the system is an i’rab (the explanation of word function in sentence) written in Arabic. The system has been tested for 159 times to examine word and sentence. The examination for word that is done 117 times has not made any error except for the word that is really like another word. While the detection for word function in sentence that is done 42 times experiment, there is no error too. An error happens when the part of speech from the word being examined is not included in the system yet, influencing the following word function detection.Keywords: I’rab, Arabic grammar, NLP, expert system, knowledge base, inference engine
Feature Extraction For Application of Heart Abnormalities Detection Through Iris Based on Mobile Devices Kusumaningtyas, Entin Martiana; Barakbah, Ali Ridho; Hermawan, Aditya Afgan
EMITTER International Journal of Engineering Technology Vol 5, No 2 (2017)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (369.888 KB) | DOI: 10.24003/emitter.v5i2.202

Abstract

As the WHO says, heart disease is the leading cause of death and examining it by current methods in hospitals is not cheap. Iridology is one of the most popular alternative ways to detect the condition of organs. Iridology is the science that enables a health practitioner or non-expert to study signs in the iris that are capable of showing abnormalities in the body, including basic genetics, toxin deposition, circulation of dams, and other weaknesses. Research on computer iridology has been done before. One is about the computers iridology system to detect heart conditions. There are several stages such as capture eye base on target, pre-processing, cropping, segmentation, feature extraction and classification using Thresholding algorithms. In this study, feature extraction process performed using binarization method by transforming the image into black and white. In this process we compare the two approaches of binarization method, binarization based on grayscale images and binarization based on proximity. The system we proposed was tested at Mugi Barokah Clinic Surabaya.  We conclude that the image grayscale approach performs better classification than using proximity.
APLIKASI PENENTUAN RUTE ALTERNATIF BERDASARKAN KONDISI KEPADATAN JALAN PADA PENJADWALAN PENGANGKUTAN SAMPAH DI SURABAYA Fariza, Arna; Kusumaningtyas, Entin Martiana; Khasanah, A’at
SCAN - Jurnal Teknologi Informasi dan Komunikasi Vol 10, No 2 (2015)
Publisher : Universitas Pembangunan Nasional "Veteran" Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/scan.v10i2.601

Abstract

Abstrak. Sebanyak 3.024.321 jiwa warga kota Surabaya menyumbang sampah setiap harinya. Pengangkutan sampah  dengan berbagai macam kombinasi harus dilaksanakan teratur dan tepat waktu agar sampah tidak menumpuk di Lokasi Pembuangan Sampah. Pengangkutan sampah dengan tuntutan jadwal angkut yang ada harus dihadapkan dengan kemacetan di kota Surabaya karena tingginya tingkat mobilitas 3 juta jiwa dalam 32.4 hektar wilayah Surabaya tersebut. Oleh karena itu, dikembangkan sebuah sistem penentuan rute alternatif  yang ditentukan berdasarkan tingkat kepadatan jalan serta jarak terpendek. Penelitian ini mengajukan pendekatan baru dengan menggunakan logika fuzzy untuk menghitung bobot suatu jalan dan algoritma djikstra sebagai pencari rute terbaik. Dengan proses logika fuzzy, kedua variabel yaitu jarak terdekat dan tingkat kepadatan jalan akan menghasilkan suatu nilai yang akan dijadikan bobot dalam algoritma djikstra untuk menentukan rute alternatif. Bobot yang dihasilkan dari proses fuzzy mengindikasikan tingkat kepadatan dan jarak terpendek. Semakin kecil nilai bobotnya, maka semakin rendah pula tingkat kepadatan dan jarak yang ditempuh. Untuk mempermudah pengguna melihat rute alternatif yang dihasilkan, maka rute akan disimulasikan dengan teknologi Google Maps API. Hasil dari sistem penentuan rute alternatif ini menunjukkan bahwa penggunaan dua varibel penentu yaitu tingkat kepadatan dan jarak terpendek mampu memberikan alternatif rute yang tidak hanya berdasarkan jarak terdekat saja, sehingga dapat mempercepat laju kendaraan pengangkut sampah dan menyingkat waktu tempuh truk pengangkut sampah.   Kata Kunci: Djikstra, Logika Fuzzy, Pengangkutan Sampah, Google Maps API
MESIN PENCARI DOKUMEN DENGAN PENGKLASTERAN SECARA OTOMATIS Entin Martiana; Nur Rosyid; Usmaida Agusetia
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 8, No 1: April 2010
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v8i1.603

Abstract

Web mining in searching based on keywords by automatic clustering is a document searching method by classifying documents based on its keyword. Following is the clustering by centroid linkage hierarchical method (CLHM) to the number of keywords from each document. In clustering, initialization is commonly required for the number of cluster to be formed first, however, in some clustering cases, the user cannot determine how many clusters can be built. Therefore, on this paper, the Valley tracing method is applied as a constraint which identifies variants movement from each cluster formation step and also analyzes its pattern to form automatic clustering. Document data used are from text mining process on documents. Based on 424 documents, this research shows that clustering method using CLHM algorithm can be generally used to classifying documents with exact number automatically.
Co-Authors Ali Ridho Barakbah Arna Fariza Hermawan, Aditya Afgan Idris Winarno Khasanah, A’at Marlisa Sigita, Marlisa Nur Rosyid Syd. Ali Zein Farmadi, Syd. Ali Zein Usmaida Agusetia