Garuda - Garba Rujukan Digital

Indriati .

Unknown Affiliation

Author-ID : 2843189

Computer Science & IT Education Engineering

Published : 3 Documents Claim Missing Document

Claim Missing Document

Articles

Pengklasifikasian Dokumen Berbahasa Indonesia Dengan Pengindeksan Berbasis LSI Achmad Ridok; Indriati .
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 2 No 2: Oktober 2015
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

AbstrakKlasifikasi dokumen teks bertujuan untuk menentukan kategori suatu dokumen berdasarkan kesamaannya dengan kumpulan dokumen yang telah berlabel sebelumnya. Namun demikian kebanyakan metode klasifikasi yang ada saat ini dilakukan berdasarkan kata-kata kunci atau kata-kata yang dianggap penting dengan mengasumsikan masing-masing merepresentasikan konsep yang unik. Padahal pada kenyataanya beberapa kata yang mempunyai makna atau semantik sama seharusnya diwakili satu kata unik. Pada penelitian ini pendekatan berbasis LSI (Latent Semantic Indexing) digunakan pada KNN untuk mengklasifikasi dokumen berbahasa Indonesia. Pembobotan term dari dokumen-dokumen latih maupun uji menggunakan tf-idf, yang direpresentasikan masing-masing dalam matrik term-dokumen A dan B. Selanjutnya matrik A didekomposisi menggunakan SVD untuk mendapatkan matrik U dan V yang tereduksi dengan k-rank. Kedua matrik U dan V digunakan untuk mereduksi B sebagai representasi dokumen uji. Evaluasi kinerja sistem terbaik berdasarkan hasil diperoleh pada klasifikasi KNN berbasis LSI tanpa stemming dengan threshould 2. Akan tetapi evaluasi kinerja terbaik berdasarkan waktu dicapai ketika KNN LSI dengan stemming pada threshould 5. Kinerja KNN berbasis LSI secara signifikan jauh lebih baik dibandingkan dengan KNN biasa baik dari sisi hasil maupun waktu.Kata kunci: KNN, LSI, K-Rank, SVD, Klasifikasi dokumen AbstractClassification of text documents aimed to determine the category of a document based on its similarity to set of documents which have been previously labeled. However, most existing methods of classification were conducted based on key words or words that are considered important by assuming each representing a unique concept. Whereas in fact some of the words that have the same meaning or semantics should be represented as a unique word. In this research LSI -based approach used on KNN to classify documents in Indonesian language. Weighting the terms of the training documents or testing using tf-idf, which represented respectively in term-document matrix A and B. Furthermore, the matrix A is decomposed using SVD to obtain matrices U and V are reduced by k-rank. Both matrices U and V are used to reduce B as a representation of test documents. The best system performance evaluation based on the results obtained LSI-based in the KNN classification without stemming with threshould 2. However, the best performance evaluation based on the time achieved when KNN LSI with stemming the KNN with threshould 5. Performance-based LSI is significantly much better than the tradisional KNN in term both the outcome and timing.Keywords: KNN, LSI, K-Rank, SVD, Documents classification

Klustering Dengan K-Means Berbasis LVQ Dan K-Means Berbasis OWA Dian Eka Ratnawati; Indriati .
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 2 No 1: April 2015
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Abstrak Pada penelitian ini dilakukan pembandingan hasil klustering pada data car evaluation dengan menggunakan K-Means berbasis LVQ (Learning Vector Quantization) dan K-Means berbasis OWA (Ordered Weighted Averaging). Pada kedua metode ini sama-sama mempergunakan K-Means tetapi yang sudah mengalami modifikasi. Hasil dari penelitian sebelumnya secara terpisah yang membandingkan metode K-Means modifikasi tersebut dengan K-Means konvensional menunjukkan bahwa kedua metode modifikasi tersebut sama-sama lebih baik daripada K-Means konvensional. Tetapi belum pernah ada penelitian yang membandingkan akurasi hasil klustering kedua metode modifikasi tersebut. Sehingga pada penelitian ini dilakukan klustering dengan menggunakan kedua metode tersebut untuk data car evaluation, karena dari penelitian sebelumnya kedua metode tersebut cukup handal dalam melakukan klustering. Hasil dari ujicoba menunjukkan rata-rata hasil akurasi dimulai yang tertinggi adalah K-Means berbasis LVQ(86.50%), K-Means berbasis OWA(86,16%) kemudian K-Means konvensional (56,50%). Tetapi dengan urutan atribut yang benar dan pemilihan nilai alpha yang tepat yakni 0.8, K-Means berbasis OWA bisa menghasilkan akurasi yang lebih tinggi yakni 93.33%. Kata kunci: K-Means berbasis LVQ, K-Means, K-Means berbasis OWA, bobot Abstract In this paper do a comparison with the results of klustering using K-Means based LVQ (Learning Vector Quantization) and K-Means based OWA (Ordered Weighted Averaging). In both of these methods used K-Means but which has been modified. Results from previous studies have shown that both methods are better than conventional K-Means. But there has never been a study comparing the accuracy of klustering results of the two methods. So in this study conducted klustering using both methods for data car evaluation, because of previous studies both methods are reliable enough to perform klustering In the researchs before it, both method are prefer than conventionalK-Means, but there are no researchs which compare them. So, in the research , we will compare it by using same data that is car evaluation. In order to know what it is method is the best. The result of research are that in the average , K-Means LVQ(86.50%) is more accuracy than K-Means – OWA(86,16%) and conventional K-Means(56,50). But if the order of selection attributes and alpha values is correct , K Means based OWA can generate higher accuracy that is 93.33 % using the alpha value of 0.8 Keywords: K-Means based LVQ, K-Means, K-Means based OWA, weight

PERANAN PEMAHAMAN PETUNJUK OPERASIONAL DALAM PROGRAM BORLAND DELPHI DAN KESERINGAN BERLATIH TERHADAP KEMAMPUAN MENGOPERASIKAN PROGRAM BORLAND DELPHI1 Suyono .; Indriati .
Media Penelitian Pendidikan : Jurnal Penelitian dalam Bidang Pendidikan dan Pengajaran Vol 9, No 1 (2015)
Publisher : Universitas PGRI Semarang

The course of Database System includes theory and practice . Consequently the students should master the theory before, they do the practice. The theory is provided by the course with a course book of Borland Delphy programming database system. The Borland Delpy program provides the operational instructions in English. To operate the program then they should understand the instructions. By understanding the instructions hopefully they can operate the program to produce listing of program codes and component graphs. To aquire the skill, they need to practice. The question undert study is which variable plays more significantly in acquiring the skill, their understanding the English instructions or their practice frequency. To find out the answer an ex post facto study was conducted at PGRI University Semarang to undergraduate students majoring in Information Technology Education, PMIPATI Faculty who were taking the course of Database System at semester 3. There were 2 classes with 21 students in each class, 16 of which were included in the study, so there were 32 participants of the study. There were 3 types of data in the study: (1) the data of the students skill in understanding Borland Delhpy Program operational instructions in English, (2) the data of practice frequency, and (3) the data of the mastery of operating Borland Delphy program. The first two data were collected bu using tests, and the third was collected by using a questionairre. It can be concluded from the follow up analyses and the partial correlation coefficient test that ability to understand English instructions in Borland Delphy program had a significant role in the ability to operate it. It was proven by the follow up analysis of t1=5,385>tsig.5%=2,04. It resulted from the course book in Indonesian they used as well as their paying attention to the operational instructionals of the program in English. On the other hand the practice frequency did not significantly contribute to the skill. It was confirmed by the follow up analysis of t2=-0,029<tsig.5% =2,04. It means the less they practice, the less skillful they were in operating the program and in understanding the English instructions of the Borland Delphy program. Keywords : The Role, Understanding, Practicing, Abitlity, The Borland Delphi Program

Title

Found 3 Documents
Search

Abstract

Abstract

Abstract

Title Search

Found 3 Documents Search

Abstract

Abstract

Abstract

Title

Found 3 Documents
Search