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All Journal Perfecting a Video Game with Game Metrics Teknik dan Ilmu Komputer JIKSI (Jurnal Ilmu Komputer dan Sistem Informasi) Computatio : Journal of Computer Science and Information Systems Jurnal Sinergitas PkM & CSR Jurnal Muara Ilmu Sosial, Humaniora, dan Seni Jurnal Bakti Masyarakat Indonesia Prosiding Konferensi Nasional PKM-CSR Indonesian Journal of Multidisciplinary Science Prosiding Seri Seminar Nasional
Viny Christanti M
Program Studi Teknik Informatika Fakultas Teknologi Informasi Universitas Tarumanagara Jakarta - Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Nursing Public Health Social Sciences Other

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Measuring Reading Difficulty Using Lexile Framework And Gunning Fog Index Christanti, Viny; Naga, Dali S.; Benedicta, Cheria
Teknik dan Ilmu Komputer Vol. 06 No. 22 April - Juni 2017
Publisher : Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This article describes the development of readability measuring  tools for Indonesian Text by using Lexile Framework, Gunning Fog Index, and Cloze Test. Lexile Framework and Gunning Fog Index are used in English Text and are implemented to Indonesian Text. Lexile Framework measures the difficulty level of the text by using the text itself and other readings’ frequencies as reference parameters, while the Gunning Fog Index uses the text itself as parameter. Lexile  Framework is implemented to Indonesian by using a corpus of Indonesian, while the Gunning Fog Index is implemented to Indonesian by changing the rule in defining difficult words. The rule depends on the syllables of the words contained in the text with the addition of stemming process. Cloze Test is needed for comparing the measurement results. The result showed that the three methods of measurement have different values. Lexile logit requires some adjustments and a very large corpus, Gunning Fog Index needs improvement in stemming and cutting syllables, Cloze Test is needed on all readings and requires more respondents. Keywords: Taraf Sukar Bacaan, Lexile Framework, Gunning Fog Index, Cloze Test
IMPLEMENTASI BRILL TAGGER UNTUK MEMBERIKAN POS-TAGGING PADA DOKUMEN BAHASA INDONESIA Christanti M, Viny; Pragantha, Jeanny; Purnamasari, Endah
Teknik dan Ilmu Komputer vol. 1 no. 3 July-September 2012
Publisher : Teknik dan Ilmu Komputer

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Abstract

Part-of-speech (POS) tagging is the process of marking up a word in a text. The aim of this program application is to design a system that is able to proceed POS-Tagging in Indonesian documents by implementing Brill Tagger program. The results showed that of 11.411 words (20 news) used in testing process, 154 words underwent incorrect tagging and 11.257 words were properly labeled according to their part of speech. This indicated that the accuracy of POS-Tagging application program which implemented Brill Tagger Program was 98.65%. The accuracy became 99.75 % after being adapted with lexical and contextual rules.     Keywords:             Brill Tagger, natural language processing, part-of-speech tagging, rule based, transformation based learning
Fast and Accurate Spelling Correction Using Trie and Damerau-levenshtein Distance Bigram Viny Christanti M.; Rudy Rudy; Dali S. Naga
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 2: April 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i2.6890

Abstract

This research was intended to create a fast and accurate spelling correction system with the ability to handle both kind of spelling errors, non-word and real word errors. Existing spelling correction system was analyzed and was then applied some modifications to improve its accuracy and speed. The proposed spelling correction system is then built based on the method and intuition used by existing system along with the modifications made in previous step. The result is a various spelling correction system using different methods. Best result is achieved by the system that uses bigram with Trie and Damerau-Levenshtein distance with the word level accuracy of 84.62% and an average processing speed of 18.89 ms per sentence.
APLIKASI CLUSTERING BERITA DENGAN METODE K MEANS DAN PERINGKAS BERITA DENGAN METODE MAXIMUM MARGINAL RELEVANCE Edy Susanto; Viny Christanti Mawardi; Manatap Dolok Lauro
Jurnal Ilmu Komputer dan Sistem Informasi Vol 9, No 1 (2021): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1927.973 KB) | DOI: 10.24912/jiksi.v9i1.11560

Abstract

News is information about facts or opinions that are interesting to know. News can be obtained from various media such as newspapers and the internet. As is well known, news has various topics, such as politics, sports and others. There is also the same story written with the addition of a little information. This causes it to take more time to get the headline of the news. Therefore we need a system for news clustering using the K-Means method and news summarizing using the Maximum Marginal Relevance (MMR) method in order to obtain information from news more easily and efficiently. News that is processed in the form of a collection of files (multi document) with the extension txt. The summarization process goes through the text preprocessing stage, which consists of sentence segmentation, case folding, tokenizing, filtering, stemming. The next step is TF-IDF calculation to calculate word weight then Cosine Similarity to calculate the similarity between documents. After that, enter the K-Means stage for clustering division and proceed with determining the summary with MMR. Based on the results testing that has been done, this application is running well, the results of clustering and summarizing news can make it easier for users to get news summaries from some similar news.
PERANCANGAN RETRIEVE, CLUSTER, SUMMARIZE (RCS) SYSTEM DENGAN METODE MULTI FEATURES COMBINATION Joko Joko; Viny Christanti Mawardi; Tony Tony
Jurnal Ilmu Komputer dan Sistem Informasi Vol 3, No 1 (2015): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v3i1.3274

Abstract

Retrieve, Cluster, Summarize (RCS) System merupakan sistem yang dapat digunakan untuk mencari dokumen relevan, mengelompokkan dokumen relevan, serta menghasilkan ringkasan dari setiap kelompok dokumen relevan tersebut. RCS System terdiri dari beberapa tahapan, yaitu tahap input query oleh user, tahap pencarian kumpulan dokumen yang relevan dengan query, tahap pengelompokkan kumpulan dokumen relevan ke dalam sejumlah cluster, dan tahap peringkasan setiap cluster dari dokumen relevan. Metode yang digunakan untuk sistem retrieval, clustering, dan automatic text summarization secara berturut-turut adalah Language Model (LM), K-Means, dan Multi Features Combination. Dalam proses perancangan RCS System, sistem retrieval dan sistem clustering dijalankan dengan menggunakan bantuan dari Lemur Development Toolkit yang telah disesuaikan untuk proses pengolahan dokumen bahasa Indonesia. Proses pengujian RCS System dilakukan dengan menggunakan 3000 dokumen Bahasa Indonesia, yang terdiri dari dokumen berita dengan kategori teknologi, kesehatan, dan olahraga. Hasil pengujian terhadap sistem retrieval menghasilkan nilai average precision sebesar 0,91 untuk top 10 dokumen, sistem clustering menghasilkan nilai average purity sebesar 78,32% dengan jumlah cluster sebesar 5, dan sistem automatic text summarization menghasilkan nilai average answer recall strict sebesar 80,00%. Kata Kunci:K-Means Clustering, Language Model Retrieval, Multi Features Combination Text Summarization, RCS System
Analisis Penutupan Kartu Kredit Menggunakan Metode Analytical Hierarchy Process dan Preference Ranking Organization Methode for Enrichment Evaluation Gerry Geraldicky; Viny Christanti Mawardi; Tri Sutrisno
Jurnal Ilmu Komputer dan Sistem Informasi Vol 9, No 1 (2021): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1775.255 KB) | DOI: 10.24912/jiksi.v9i1.11565

Abstract

The rapid development in Indonesia is information technology. Today's computer technology can collaborate with other fields of science. One of them is a Computer Based Decision Support System (DSS). Decision Support System (DSS) is a system that is useful for increasing effectiveness in terms of decision making. A credit card is a payment instrument in the form of a card that has a credit facility to the owner in lieu of cash payment, where at maturity it can be paid with the minimum payment amount and the rest is used as credit. In applying for credit card closure, it can be combined with a decision support system. The decision support system for this case uses the Analytical Hierarchy Process (AHP) method and the Preference Ranking Organization Methods for Enrichment Evaluations (Promethee). The Analytic Hierarchy Process (AHP) method has proven its reliability in weighting the criteria value and the Preference Ranking Organization Methods for Enrichment Evaluations (Promethee) is used to rank the alternatives provided. Establishing this decision support system will produce fast and accurate recommendations to credit card management on this issue.
APLIKASI PENDETEKSI POLA KALIMAT HEADLINE COPYWRITING DENGAN METODE SHIFT REDUCE PARSING Jeffri Alimin; Viny Christanti Mawardi; Novario Jaya Perdana
Jurnal Ilmu Komputer dan Sistem Informasi Vol 9, No 1 (2021): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1759.952 KB) | DOI: 10.24912/jiksi.v9i1.11579

Abstract

This research aims to produce an application that assesses copywriting headline sentences with correct grammar and word mismatches. Copywriting is an activity of a work through writing to made the readers get response that the writers want to convey and in it there is one of the constituent elements, namely the headline which is a sentence that will be seen first before reading the main content of the work and in the headline there is an RTO formula for making it.In this research, the problem raised was implementing the shift reduce parsing method as a detection of sentence patterns and grammar in the headline copywriting from the preprocessing stage which provides part-of-speech (POS) labels using the HMM model with an accuracy value of 94.69% to the steps parsing and grading of sentences. In making this application, the SDLC waterfall model is carried out in a sequence of several processes in stages in designing and developing a system.The result of this research is an application with the form of a web framework using ASP.net as a web interface. After the application has been built, it will be tested using the blackbox test which results in 98% successful parsing that goes according to design.
GEOGRAPHICAL INFORMATION RETRIEVAL MENGGUNAKAN METODE GEOVSM Dessy Yanti; Viny Christanti Mawardi; Ery Dewayani
Jurnal Ilmu Komputer dan Sistem Informasi Vol 4, No 1 (2016): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (11.291 KB) | DOI: 10.24912/jiksi.v4i1.143

Abstract

Sistem Geographical Information Retrieval (GIR) yang dibangun dengan menggunakan metode GeoVSM berfokus dalam upaya pencarian jawaban yang berupa teks jawaban, dokumen pendukung, dan visualisasi jawaban dalam suatu peta geografis. Jawaban tersebut akan dicari di dalam suatu koleksi dokumen tematik serta dokumen geografis Bahasa Indonesia yang berkaitan dengan kota Surakarta. Di dalam penelitian ini, percobaan dilakukan untuk mencari di Top-n dokumen serta Top-n jawaban ke berapa yang paling tepat dan sesuai untuk diterapkan dalam sistem yang dibangun. Percobaan ini akan dilakukan dengan menggunakan Top-5 dokumen, Top-10 dokumen, Top-5 jawaban, serta Top-10 jawaban. Berdasarkan percobaan yang dilakukan, sistem yang dibangun menunjukkan hasil Mean Reciprocal Rank (MRR) yang paling baik dengan nilai sebesar 0.817 pada saat penggunaan Top-5 dokumen dan Top-10 jawaban.
IMPLEMENTASI CASE-BASED REASONING UNTUK SISTEM TANYA JAWAB PENYAKIT PADA ANJING Andre Raymond; Viny Christanti Mawardi
Jurnal Ilmu Komputer dan Sistem Informasi Vol 4, No 2 (2016): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (10.079 KB) | DOI: 10.24912/jiksi.v4i2.78

Abstract

This debriefing question answering system using Case Base Reasoning algorithm. Case Base Reasoning is an algorithm to solve new problems by comparing the old problems or solve new problems by providing answers from a document.In this system uses several methods to process the document as an information / knowledge that makes the system increasingly relevant in answering the question. The method used is the Modified K-Nearest Neighbour, Vector Space Model and Paragraph Based Passage. M-KNN method is used to facilitate in classifying diseases in dogs, VSM method is used to search for relevant documents that match the query. then to provide answers to relevant documents obtained by the system used method Based Paragraph Passage. This level of accuracy obtained from this exchange system using training data 228 is equal to 92% with a value of k = 3.
IMPLEMENTASI APLIKASI JUAL BELI MOBIL BEKAS DENGAN METODE ANALYTICAL HIERARCHY PROCESS DAN NAIVE BAYES Widi Santoso; Viny Christanti Mawardi; Tri Sutrisno
Jurnal Ilmu Komputer dan Sistem Informasi Vol 9, No 1 (2021): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (658.34 KB) | DOI: 10.24912/jiksi.v9i1.11597

Abstract

One area of life that is affected by the rapid development and advancement of technology is the automotive sector. Information technology bridges various groups who participate in automotive transaction activities. Therefore, the physical condition and performance of an automotive are determining factors for a buyer who wants to make a purchase.Not all types of automotive offered meet the buyers' standards, nor do they have a selling price in accordance with the quality described by the seller. The Analytical Hierarchy Process (AHP) method helps determine the type of automotive that suits the buyers' wishes and the Naïve Bayes method helps determine the selling price according to the quality of the automotive offered.The Analytical Hierarchy Process (AHP) method is a decision support model that describes a complex multi-factor or multi-criteria problem into a hierarchy, which in turn can organize complex problems into a more orderly and systematic manner. The Naïve Bayes method is a classification using probability and statistical methods that predict future opportunities based on past experiences. Naïve Bayes calculates a set of probabilities by adding up the frequency and value combinations from the given dataset. Based on the comparison of the calculation results with the tests carried out, the AHP method obtains an accuracy rate of 100% in displaying the criteria for cars being sold. Meanwhile, the Naïve Bayes method obtains an accuracy rate of 100% in determining whether a dealer is interested in buying a car or not.
Co-Authors Agus Budi Dharmawan Albert Jeremy Aleksander Nihcolson Andre Ertanto Andre Raymond Andreas Andreas Andreas Andreas Andreas Khosasi Ardianto Ardianto Bagus Mulyawan bagus Mulyawan Benedicta, Cheria Berlin Ong Karo Karo Billy Fernando Bryan Filemon Carlene Lim Carlene Lim Caroline Wili Harto Dali S Naga Dali S. Naga Dali S. Naga Dali S. Naga Dali S. Naga, MMSI Dali S.Naga Dali Santun Naga Daniel Daniel Daniel Daniel Darius A Haris Darius Andana Haris Darryl Kresnadi Nugroho Davin Pratama Denis Kusbowo Desi Arisandi Desi Arisandi Dessy Yanti Destu Adiyanto Devin Abipraya Dewi Triani Edward Darmaja Edy Susanto Endah Purnamasari Erikson T Erikson T Erwin Erwin Ery Dewayani Fendy Augusfian Ferry Ruben Yudistira Ferry Ruben Yudistira Yudistira, Ferry Ruben Yudistira Freddy Kurniawan Fredickson Dinata Fundroo Orlando Gerry Geraldicky Handoko Susanto Handoko Susanto, Handoko Handry Wardoyo Hanven Pradana Hendri Yukianto Hendri Yukianto, Hendri Henry Hartono James Eklie Janson Hendryli Janson Hendryli Janson Hendryli Janson Hendryli Janson Hendryli Januar Mansur Jeanny Pragantha Jeanny Pragantha Jeffri Alimin Jesica Jesica Jesica Kurniadi, Jesica Jesslyn Jesslyn Jimmy Jimmy Joko Joko Jonathan Adrian Wibowo Joshua Octavianus Joshua Octavianus, Joshua Julius Evan Harya Chandra Kenneth Hakim Kevin kevin Kevin Kurniawan H. Kevin Prasetio Kevin The Kuncoro Yoko Lely Hiryanto Livienia Livienia Manatap Dolok Lauro, Manatap Dolok Maria Asinta Marpaung Maria Asinta Marpaung, Maria Asinta Marsel Dwiputra Marsel Dwiputra, Marsel Marvellino Meiriani Tjandra Meiriani Tjandra Meiske Yunitree Suparman Muhammad Farras Mutiara Ramadhani Sugiri Mutiara, Maitri Widya Nadia Natha Lie Naga, Dali S. Niki Valentine Niki Valentine, Niki Novario Jaya Perdana Pharadya Ajeng Swari Sukmawati Prabu Alif Anggadiputra Prof. Dr. Ir. Dali S. Naga, MMSI Pusaka, Semerdanta Radika Yudha Riyanto Rendi Kristyadi Ricky Martin Robertus Budihalim Robertus Budihalim, Robertus Rudy Rudy Stenly Tirta Wijaya stephanie stephanie Steven Steven Dharmawan Steven Muliadi Steven Muliadi, Steven Steven Steven Sylvia Wulandari, Sylvia Tania Rizgitta Tony Tony Tony Tony TRI SUTRISNO Vanesa Nellie Vincent Marcellino Widi Santoso Wilson Gozal, Wilson Yagyu Munenori M.E. Yohan Prasetyo Sugianto Yosua Pandapotan Sianipar Yulianto Yulianto Yulianto Yulianto Zyad Rusdi Zyad Rusdi