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All Journal Elektron Jurnal Ilmiah TELKOMNIKA (Telecommunication Computing Electronics and Control) Scan : Jurnal Teknologi Informasi dan Komunikasi EMITTER International Journal of Engineering Technology JOIV : International Journal on Informatics Visualization Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat El-Mujtama: Jurnal Pengabdian Masyarakat
Entin Martiana Kusumaningtyas
Departemen Informatika Dan Komputer, Politeknik Elektronika Negeri Surabaya
Religion Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Nursing Public Health Social Sciences

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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.
Implementasi Fuzzy Query dalam Sistem Pendukung Keputusan untuk Investasi Properti Edelani, Renovita; Kusumaningtyas, Entin Martiana; Prasetyaningrum, Ira; Anggriawan, Bagus
Elektron : Jurnal Ilmiah Volume 16 Nomor 1 Tahun 2024
Publisher : Teknik Elektro Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/eji.0.0.467

Abstract

Rapid urbanization and the increasing demand for residential property have created significant challenges in the real estate market. Prospective homebuyers often face difficulties in finding properties that meet their specific criteria in a crowded and competitive market. This research proposes an approach to property investment decision-making based on the Fuzzy Query method, providing a web-based application designed to simplify the property search process. The application allows users to filter properties based on various criteria, such as price, land area, building area, number of bathrooms, number of bedrooms, certificate type, and environmental noise levels. The application features an intuitive user interface that enables users to quickly find properties that match their preferences. This decision support system effectively assists property investors in obtaining investment assessments.
Pembuatan Sistem Dashboard Pemantau Penerangan Jalan Umum (PJU) Terintegrasi di Daerah Keputih Surabaya Rahmawati, Weny Mistarika; Ahsan, Ahmad Syauqi; Asmara, Rengga; Permatasari, Desy Intan; Kusumaningtyas, Entin Martiana; Mu'arifin; Setiowati, Yuliana; Mubtada’i, Nur Rosyid; Setyorini, Fitri; Leksana, Bayu Hadi; Azhara, Khanza Fadila
Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Vol. 5 No. 3 (2025): Mei 2025 - Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/altifani.v5i3.701

Abstract

Sistem Dashboard Pemantau Penerangan Jalan Umum (PJU) Terintegrasi di Keputih, Surabaya, dikembangkan sebagai solusi inovatif untuk meningkatkan efisiensi pengelolaan PJU berbasis teknologi Internet of Things (IoT). Sistem ini bertujuan memantau kondisi lampu PJU, cuaca, dan kualitas udara secara real-time dengan integrasi sensor dan teknologi digital. Metode yang digunakan meliputi perancangan sistem, implementasi sensor, pengembangan dashboard berbasis web, serta pengujian dan evaluasi sistem. Hasil menunjukkan bahwa dashboard dapat menampilkan data kondisi lampu, suhu, kelembapan, curah hujan, dan kualitas udara secara akurat dalam satu platform yang mudah diakses. Selain itu, fitur seperti Live CCTV, Chatbot Service, dan kontrol lampu manual/otomatis berhasil diimplementasikan. Dengan adanya sistem ini, pengelolaan PJU menjadi lebih responsif, efisien, dan berbasis data, sehingga dapat meningkatkan keselamatan pengguna jalan dan mendukung pengambilan keputusan yang lebih baik.
Penerapan Aplikasi Klasifikasi Hukum Tajwid Menggunakan Image Processing Kindarya, Fabyan; Kusumaningtyas, Entin Martiana; Barakbah, Aliridho; Permatasari, Desy Intan; Al Rasyid, M. Udin Harun; Ramadijanti, Nana; Fariza, Arna; Syarif, Iwan; Sa'adah, Umi; Saputra, Ferry Astika; Ahsan, Ahmad Syauqi; Sumarsono, Irwan; Yunanto, Andhik Ampuh; Edelani, Renovita; Primajaya, Grezio Arifiyan; Kusuma, Selvia Ferdiana
El-Mujtama: Jurnal Pengabdian Masyarakat  Vol. 4 No. 2 (2024): El-Mujtama: Jurnal Pengabdian Masyarakat
Publisher : Intitut Agama Islam Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/elmujtama.v4i2.1930

Abstract

Tajwid is an important science that regulates the way of reading the verses of the Al-Qur’an properly. Learning Tajwid means knowing the meaning that corresponds to the correct recitation. Learning to read the Al-Qur’an tends to be done traditionally in a place of learning or by calling a teacher to the house. Learning in this way has some drawbacks, such as the limited availability of trained and competent teachers because not all areas have sufficient access to these teachers. Dependence on schedules and locations can be a constraint for students with limited mobility or busy schedules. The role of the teacher is still important in learning tajwid, especially in providing effective explanations, guidance, and feedback. However, to overcome these shortcomings, integration with independent and technology-based learning methods can help improve the accessibility, flexibility, and quality of tajwid learning. The classification of tajwid laws using image processing allows users to see the results of inputting images of verses of the Al-Qur’an into the type of detected nun sukun tajwid and how to recite it. The initial stage of this system in detecting tajwid laws from uploaded images is the input of images by users, which can be done in two ways, namely by directly taking pictures using a smartphone camera or uploading images from the gallery. This is followed by the OCR process to detect the Arabic text contained in the image and provide diacritics for that Arabic text. Finally, letter classification is carried out after nun sukun and classification of tajwid laws contained in accordance with the detected letters after nun sukun. This system has an accuracy rate of 92.18% from the classification results that have been carried out.
Semantic Multi-Query Model for Cultural Computing of Image Search System Barakbah, Ali Ridho; Suryani, Indah Yudi; Kusumaningtyas, Entin Martiana
JOIV : International Journal on Informatics Visualization Vol 9, No 5 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.5.4294

Abstract

The proliferation of digital images on the internet has increased the need for image search systems, especially for culturally significant images that contain a collection of impressions. However, traditional image search systems typically rely on a single query, making it difficult to discern user intent accurately. This paper introduces a novel model for describing user impressions using a semantic multi-query function for cultural computing in image search systems.  This model provides a culture-centric semantic multi-image query system to generate representative query impressions.  The proposed multi-query model provides an analytical tool to semantically construct representative query color attributes, involving four stages: (1) Local normalization of 3D-Color Vector Quantization, (2) Color distribution measurement, (3) Adaptive representative color adjustment, and (4) Representative color identification. For the experimental study, we evaluate our system with two types of experiments: (1) Multi-query image for image search to ensure that our multi-query model enhances the accuracy of the retrieval outcomes, and (2) Multi-query image for semantic image search of cultural paintings. In the first experiment using the SIMLIcity dataset, our proposed multi-query model achieved better retrieval performance across most categories, reducing the single-query error from 26.67% to 20%. In the second experiment using the Indonesian cultural painting dataset, our proposed multi-query model achieved better retrieval performance across most categories, improving the single-query average similarity from 46.6% to 72%.
Co-Authors Ahsan, Ahmad Syauqi Ali Ridho Barakbah Andhik Ampuh Yunanto Anggriawan, Bagus Arna Fariza Asmara, Rengga Azhara, Khanza Fadila Desy Intan Permatasari, Desy Intan Edelani, Renovita Ferry Astika Saputra Hermawan, Aditya Afgan Idris Winarno Ira Prasetyaningrum iwan Syarif Khasanah, A’at Kindarya, Fabyan Kusuma, Selvia Ferdiana Leksana, Bayu Hadi M Udin Harun Al Rasyid, M Udin Harun Marlisa Sigita, Marlisa Mu'arifin Mubtada’i, Nur Rosyid Nana Ramadijanti, Nana Nur Rosyid Primajaya, Grezio Arifiyan Sa'adah, Umi Setyorini, Fitri Sumarsono, Irwan Suryani, Indah Yudi Syd. Ali Zein Farmadi, Syd. Ali Zein Usmaida Agusetia Weny Mistarika Rahmawati Yuliana Setiowati, Yuliana