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SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN PRODUK UNGGULAN DAERAH MENGGUNAKAN METODE ENTROPY DAN ELECTRE II (STUDI KASUS: DINAS KOPERASI, INDUSTRI DAN PERDAGANGAN KABUPATEN LAMONGAN) Handoyo, Eko; Cahyani, Andharini Dwi; Yunitarini, Rika
JURNAL TEKNOLOGI TECHNOSCIENTIA Technoscientia Vol 7 No 1 Agustus 2014
Publisher : Lembaga Penelitian & Pengabdian Kepada Masyarakat (LPPM), IST AKPRIND Yogyakarta

Competition superior product in the future become more and more stringent with the increasing pace of economic development, industrial growth and technological progress. This competition makes each industry should be more careful in formulating policy formulation stratgi. Making the decision to get a superior product that suits your needs and abilities required an accurate and effective decisions so that no one and minimize the loss in terms of cost and time. This study uses the entropy method and elactre II. Research with this method of ranking the results based on the amount of gain dominance resulted in ranking the more partial and sensitive than perangkingan based level. Criterion in this system is the turnover, labor, investment value, the target market, the amount of raw materials and the number of firms in a superior product. This study matches the accuracy of the system reaches 30%.

SISTEM REKOMENDASI: BUKU ONLINE DENGAN METODE COLLABORATIVE FILTERING Irfan, Mohammad; Cahyani, Andharini Dwi; R, Fika Hastarita
JURNAL TEKNOLOGI TECHNOSCIENTIA Technoscientia Vol 7 No 1 Agustus 2014
Publisher : Lembaga Penelitian & Pengabdian Kepada Masyarakat (LPPM), IST AKPRIND Yogyakarta

The book is a source of information regarding all aspects of life, especially education. However, low interest in reading among the public is a major issue in education today. Recommendation systems can help recommend the reader to more easily obtain information about the books to be read. Therefore, in this study made an online book recommendation system using Collaborative Filtering. Collaborative Filtering is one of the methods that can be used in making the recommendation system. The results of this study showed that the average value of the MAE (Mean Absolute Error) on trial 1 (1.064) is smaller than 2 trials (1.21), 4 trials (2,474) and test 5 (3.526). This shows that the more the amount of data used and if there is a user who has never rate a, then the resulting system is relatively inaccurate and generate recommendations if using Collaborative Filtering bad.

PERBANDINGAN METODE SOM (SELF ORGANIZING MAP) DENGAN PEMBOBOTAN BERBASIS RBF (RADIAL BASIS FUNCTION) Cahyani, Andharini Dwi; Khotimah, Bain Khusnul; Rizkillah, Rafil Tania
JURNAL TEKNOLOGI TECHNOSCIENTIA Technoscientia Vol 7 No 1 Agustus 2014
Publisher : Lembaga Penelitian & Pengabdian Kepada Masyarakat (LPPM), IST AKPRIND Yogyakarta

In many clustering systems many methods was used to cluter-ization, one of which is the SOM (Self Organizing Maps). In our study we used two approaches. The first approach was a lawyer-cluster's using SOM-RBF used in the training data and could be expected to result in better cluster. And the second approach clustering was used of SOM.Comparison of both methods is based on the application of the data derived from the dataset movielens.org site. Comparative assessment using three scenarios, namely the MSE as a stop condition on the running time, the MSE as the stop condition of the epoch and the learning rate, and MSE as the stop condition of the actual value of the MSE. With this running time is detected which is more rapid approach to the time span for extracting training data. Based on the results of experiments performed using 500 data, which is applied to clusters 3 and 4 lead to the conclusion that the first approach has the value of MSE is actually closer to the absolute value of MSE as compared to the second approach.

SISTEM PENILAIAN ESAI OTOMATIS PADA E-LEARNING DENGAN ALGORITMA WINNOWING Astutik, Sariyanti; Cahyani, Andharini Dwi; Sophan, Mochammad Kautsar
Jurnal Informatika Vol 12, No 2 (2014): NOVEMBER 2014
Publisher : Institute of Research and Community Outreach - Petra Christian University

Exam essay is an evaluation of learning in the form of essay questions that have answers more variable than multiple choice questions. Variations of these answers provide its own difficulties for teachers in assessing response. Essay grading system is built to be one solution that can speed up and simplify the process of grading. Essay grading system in this study was done by measuring the similarity of responses of the students and teacher answer key. This research use winnowing algorithm. Winnowing algorithm is an algorithm for text similarity measure. Winnowing algorithm produces fingerprint of text that will represent the answer to the calculation of similarity with jaccard coeficient equation. Testing was conducted to determine the ability of the algorithm winnowing to provide an essay grading using n-gram and window value changes of the winnowing algorithm. The test results showed the use of the value of n-grams and window on the method of winnowing effect on fingerprint similarities were found. The more similarities fingerprint found, the value of the resulting system also be higher. The accuracy of the grading system showed better results on text answers that have the answer sentence structure same with key answer.

Sistem Pendukung Keputusan Pengelompokan Siswa Berdasarkan Gaya Belajar Felder-Silverman Cahyani, Andharini Dwi
Jurnal Sistem Komputer Vol 4, No 1 (2014)
Publisher : Jurnal Sistem Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jsk.v4i1.61

Penerapan teknologi informasi dalam bidang edukasi dewasa ini meningkat pesat. Penerapan TI tersebut tidak hanya dalam penggunaan media pembelajaran berbasis multimedia saja, tetapi juga dalam pelaksanaan pembelajaran berupa e-learning, Dalam perkembangannya, agar proses pembelajaran berjalan dengan efektif, maka diperlukan belajar secara berkelompok. Ide tersebut bukanlah suatu hal baru karena bekerja dalam kelompok memberikan lingkungan untuk belajar secara kolaboratif serta berbagi ide dan pengetahuan. Agar tiap anggota kelompok merasa nyaman, maka siswa dikelompokkan berdasarkan gaya belajar yang dimilikinya. Dari hasil kuesioner gaya belajar siswa, kemudian dilakukan teknik clustering fuzzy c-means untuk membentuk kelompok siswa. Hasil clustering tersebut kemudian dianalisa dengan menggunakan indeks Davis-Bouldin. Dari hasil ujicoba menunjukkan bahwa hasil clustering paling homogen ketika set parameter jumlah cluster = 4 dan jumlah iterasi = 20 kali.

Rancang Bangun Sistem Informasi Akademik menggunakan Agile Model Driven Siswanto A, Zaenal; Cahyani, Andharini Dwi; Sophan, Moch. Kautsar
Jurnal Masyarakat Informatika Vol 7, No 1 (2016): JURNAL MASYARAKAT INFORMATIKA
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmasif.7.1.31516

SMK Negeri 2 Surabaya merupakan salah satu SMK teknologi dan industri unggulan di Surabaya, namun pemanfaatan teknologi informasi dan komunikasi (TIK) belum maksimal. Banyak kelemahan yang ditemukan pada sistem lama sehingga menghambat penyebaran arus informasi. Dibutuhkan suatu sistem yang dirancang untuk membantu mengakomodasi pengelolaan informasi akademik sehingga mempermudah pekerjaan guru dan staf yang bertugas mengelola data akademik dan membantu mempercepat penyebaran informasi akademik sekolah. Metode pengembangan sistem yang digunakan dalam penulisan tugas akhir ini adalah Agile Model Driven dengan UML sebagai pemodelannya. Dengan menerapkan prinsip Agile Model Driven dalam pengembangan sistem dimodelkan menggunakan UML kemudian dilakukan proses membangun aplikasi dari model driven design menggunakan framework django sehingga menghasilkan komponen arsitektur basis data sesuai dengan perancangan untuk kemudian dikembangkan menjadi sebuah aplikasi. Hasil dari penelitian menunjukkan bahwa sistem informasi akademik sudah layak pakai dan mudah dikembangkan berdasarkan hasil pengujian functionality, usability, portability, reliability dan maintainability.

SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN PRODUK UNGGULAN DAERAH MENGGUNAKAN METODE ENTROPY DAN ELECTRE II (STUDI KASUS: DINAS KOPERASI, INDUSTRI DAN PERDAGANGAN KABUPATEN LAMONGAN) Handoyo, Eko; Cahyani, Andharini Dwi; Yunitarini, Rika
JURNAL TEKNOLOGI TECHNOSCIENTIA Technoscientia Vol 7 No 1 Agustus 2014
Publisher : Lembaga Penelitian & Pengabdian Kepada Masyarakat (LPPM), IST AKPRIND Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34151/technoscientia.v7i1.590

Competition superior product in the future become more and more stringent with the increasing pace of economic development, industrial growth and technological progress. This competition makes each industry should be more careful in formulating policy formulation stratgi. Making the decision to get a superior product that suits your needs and abilities required an accurate and effective decisions so that no one and minimize the loss in terms of cost and time. This study uses the entropy method and elactre II. Research with this method of ranking the results based on the amount of gain dominance resulted in ranking the more partial and sensitive than perangkingan based level. Criterion in this system is the turnover, labor, investment value, the target market, the amount of raw materials and the number of firms in a superior product. This study matches the accuracy of the system reaches 30%.

SISTEM REKOMENDASI: BUKU ONLINE DENGAN METODE COLLABORATIVE FILTERING Irfan, Mohammad; Cahyani, Andharini Dwi; R, Fika Hastarita
JURNAL TEKNOLOGI TECHNOSCIENTIA Technoscientia Vol 7 No 1 Agustus 2014
Publisher : Lembaga Penelitian & Pengabdian Kepada Masyarakat (LPPM), IST AKPRIND Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34151/technoscientia.v7i1.612

The book is a source of information regarding all aspects of life, especially education. However, low interest in reading among the public is a major issue in education today. Recommendation systems can help recommend the reader to more easily obtain information about the books to be read. Therefore, in this study made an online book recommendation system using Collaborative Filtering. Collaborative Filtering is one of the methods that can be used in making the recommendation system. The results of this study showed that the average value of the MAE (Mean Absolute Error) on trial 1 (1.064) is smaller than 2 trials (1.21), 4 trials (2,474) and test 5 (3.526). This shows that the more the amount of data used and if there is a user who has never rate a, then the resulting system is relatively inaccurate and generate recommendations if using Collaborative Filtering bad.

PERBANDINGAN METODE SOM (SELF ORGANIZING MAP) DENGAN PEMBOBOTAN BERBASIS RBF (RADIAL BASIS FUNCTION) Cahyani, Andharini Dwi; Khotimah, Bain Khusnul; Rizkillah, Rafil Tania
JURNAL TEKNOLOGI TECHNOSCIENTIA Technoscientia Vol 7 No 1 Agustus 2014
Publisher : Lembaga Penelitian & Pengabdian Kepada Masyarakat (LPPM), IST AKPRIND Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34151/technoscientia.v7i1.619

In many clustering systems many methods was used to cluter-ization, one of which is the SOM (Self Organizing Maps). In our study we used two approaches. The first approach was a lawyer-cluster's using SOM-RBF used in the training data and could be expected to result in better cluster. And the second approach clustering was used of SOM.Comparison of both methods is based on the application of the data derived from the dataset movielens.org site. Comparative assessment using three scenarios, namely the MSE as a stop condition on the running time, the MSE as the stop condition of the epoch and the learning rate, and MSE as the stop condition of the actual value of the MSE. With this running time is detected which is more rapid approach to the time span for extracting training data. Based on the results of experiments performed using 500 data, which is applied to clusters 3 and 4 lead to the conclusion that the first approach has the value of MSE is actually closer to the absolute value of MSE as compared to the second approach.

Design an Adaptive E-learning Application Architecture based on IEEE LTSA reference model Andharini Dwi Cahyani; Ari Basuki; Eka Mala Sari Rohman; Yeni Kustiyahningsih
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 1: March 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i1.112

Adaptivity in the field of e-learning and an innovative framework for personalised adaptive e-learning is often considered to be new or in an early development stage. In this paper, we propose an architecture for development of adaptive e-learning system. This architecture is based on the IEEE 1484 LTSA (Learning Technology System Architecture) reference model. The learner model is based on the learners’ preference and knowledge level. According to these profiles, the learners are served with learning material that best matches their educational needs. Furthermore, we also accomodate the learner feeback regarding to difficulty level of learning material. The design of our proposed models is prepared using UML notation. Our goal is to assist the instructional designers in developing adaptive e-learning system based on the IEEE LTSA models efficiently.

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