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Peringkasan Tweet Berdasarkan Trending Topic Twitter Dengan Pembobotan TF-IDF dan Single Linkage Angglomerative Hierarchical Clustering Annisa, Annisa; Munarko, Yuda; Azhar, Yufis
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol 1, No 1, May-2016
Publisher : Universitas Muhammadiyah Malang

Fitur yang paling sering digunakan pada Twitter ialah Trending Topic. Trending Topic merupakan fitur yang menampilkan beberapa hashtag berisi topik yang sedang trend saat ini. Jika pengguna ingin mengetahui informasi mengenai suatu trending topic, pengguna bisa mengklik salah satu hashtag dan barulah muncul beberapa tweet terkait dengan hashtag tersebut. Agar menghemat waktu pengguna Twitter dalam membaca suatu trending topic tanpa perlu membaca beberapa tweet terlebih dahulu, maka dilakukanlah analisa dengan tujuan membuat text summarization untuk trending topic pada Twitter menggunakan algoritma TF-IDF dan Single Linkage Agglomerative Hierarchical Clustering. Penelitian ini menggunakan 100 trending topic untuk data tes pada sistem dan setiap trending topic terdiri atas 50 tweet berbahasa indonesia, sedangkan untuk pengujian digunakan 30 data trending topic diambil secara acak (data mewakili trending topic dengan sub tema minimal 2 dan maksimal 9 dari 100 data tes pada sistem). Dari 30 data pengujian, 1 data menghasilkan semua ringkasan sama persis dengan ahli,Â dan 29 data menghasilkan 1-4Â ringkasan sama persis dengan ahli (terdiri atas 2-9 ringkasan untuk setiap trending topic).

PELATIHAN PEMBUATAN DAN PERAWATAN WEBSITE BERBAHASA INGGRIS UNTUK MENINGKATKAN PENJUALAN PAKET JASA TOUR DAN TRAVEL DI KECAMATAN KARANGPLOSO MALANG Munarko, Yuda; Eko Minarno, Agus
Jurnal Dedikasi Vol 13 (2016): Mei
Publisher : Direktorat Penelitian dan Pengabdian Kepada Masyarakat

PELATIHAN PEMBUATAN DAN PERAWATAN WEBSITE BERBAHASA INGGRIS UNTUK MENINGKATKAN PENJUALAN PAKET JASA TOUR DAN TRAVEL DI KECAMATAN KARANGPLOSO MALANGYuda Munarko1 & Agus Eko Minarno21,2Teknik Informatika, Fakultas Teknik, Universitas Muhammadiyah MalangE-mail: 1) yuda.munarko@gmail.comABSTRAKJasa tour dan travel saat ini adalah jenis usaha yang sedang marak di area Malang dan sekitarnya. Hal ini disebabkan oleh besarnya pangsa pasar wisata di area Malang dan meningkatnya perekonomian masyarakat pada umumnya. Permasalahan yang ada adalah persaingan yang sangat ketat diantara pengusaha jasa tour dan travel, yang menimbulkan persaingan tidak sehat, sehingga berimbas pada penetapan harga yang rendah dan tidak kompetitif, terutama untuk wisatawan domestik. Pada kenyataannya, jumlah wisatawan mancanegara yang berkunjung ke Malang, dan kebutuhan mereka belum cukup terwadahi dengan maksimal oleh jasa tour dan travel yang ada. Oleh karena itu, untuk meningkatkan potensi pendapatan jasa tour dan travel, maka harus dijalin komunikasi yang baik dan efisien dengan calon wisatawan mancanegara. Namun masalah yang dihadapi pengusaha tour dan travel pada umumnya adalah kendala bahasa dan tidak adanya media komunikasi yang efisien. Masalah ini juga yang dihadapi oleh mitra, yakni Manavin Tour and Travel dan MH Tour and Travel. Pendampingan pembuatan dan perawatan website berbahasa Inggris diharapkan mampu untuk membantu mitra dalam mengatasi permasalahan Mitra. Website tersebut menjadi media untuk promosi layanan dan juga media komunikasi yang efektif dengan calon wisatawan mancanegara. Hasil yang didapatkan, dengan adanya website ini mitra sudah mendapatkan klien dari mancanegara yang berhubungan dengan bidang usaha jasa tour dan travel.Kata Kunci: Website, Tour, Travel

Image Retrieval Based on Texton Frequency-Inverse Image Frequency Azhar, Yufis; Minarno, Agus Eko; Munarko, Yuda; Ibrahim, Zaidah
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 2, May 2020
Publisher : Universitas Muhammadiyah Malang

In image retrieval, the user hopes to find the desired image by entering another image as a query. In this paper, the approach used to find similarities between images is feature weighting, where between one feature with another feature has a different weight. Likewise, the same features in different images may have different weights. This approach is similar to the term weighting model that usually implemented in document retrieval, where the system will search for keywords from each document and then give different weights to each keyword. In this research, the method of weighting the TF-IIF (Texton Frequency-Inverse Image Frequency) method proposed, this method will extract critical features in an image based on the frequency of the appearance of texton in an image, and the appearance of the texton in another image. That is, the more often a texton appears in an image, and the less texton appears in another image, the higher the weight. The results obtained indicate that the proposed method can increase the value of precision by 7% compared to the previous method.

Convolutional Neural Network with Hyperparameter Tuning for Brain Tumor Classification Minarno, Agus Eko; Hazmi Cokro Mandiri, Mochammad; Munarko, Yuda; Hariyady, Hariyady
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 6, No. 2, May 2021
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v6i2.1219

Brain tumor has been acknowledged as the most dangerous disease through all its circles. Early identification of tumor disease is considered pivotal to identify the spread of brain tumors in administering the appropriate treatment. This study proposes a Convolutional Neural Network method to detect brain tumor on MRI images. The 3264 datasets were undertaken in this study with detailed images of Glioma tumor (926 images), Meningioma tumors (937 images), pituitary tumors (901 images), and other with no-tumors (500 images). The application of CNN method combined with Hyperparameter Tuning is proposed to achieve optimal results in classifying the brain tumor types. Hyperparameter Tuning acts as a navigator to achieve the best parameters in the proposed CNN model. In this study, the model testing was conducted with three different scenarios. The result of brain tumor classification depicts an accuracy of 96% in the third model testing scenario.

HII: Histogram Inverted Index For Fast Images Retrieval Yuda Munarko; Agus Eko Minarno
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

This work aims to improve the speed of search by creating an indexing structure in CBIR system. We utilised an inverted index structure that usually used in text retrieval with a modification. The modified inverted index is built based on histogram data that generated using Multi Texton Histogram (MTH) and Multi Texton Co-Occurrence Descriptor (MTCD) from 10,000 images of Corel dataset. When building the inverted index, we normalised value of each feature into a real number and considered pairs of feature and value that owned by a particular number of images. Based on our investigation, on MTCD histogram of 5,000 data test, we found that by considering histogram variable values which owned by maximum 12% of images, the number of comparison for each query can be reduced by 67.47% in a rate, the precision is 82.2%, and the rate of access to disk is 32.83%. Furthermore, we named our approach as Histogram Inverted Index (HII).

CBIR of Batik Images using Micro Structure Descriptor on Android Agus Eko Minarno; Yuda Munarko; Arrie Kurniawardhani
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

Batik is part of a culture that has long developed and known by the people of Indonesia and the world. However, the knowledge is only on the name of batik, not at a more detailed level, such as image characteristic and batik motifs. Batik motif is very diverse, different areas have their own motifs and patterns related to local customs and values. Therefore, it is important to introduce knowledge about batik motifs and patterns effectively and efficiently. So, we build CBIR batik using Micro-Structure Descriptor (MSD) method on Android platform. The data used consisted of 300 images with 50 classes with each class consists of six images. Performance test is held in three scenarios, which the data is divided as test data and data train, with the ratio of scenario 1 is 50%: 50%, scenario 2 is 70%, 30%, and scenario 3 is 80%: 20%. The best results are generated by scenario 3 with precision valur 65.67% and recall value 65.80%, which indicates that the use of MSD on the android platform for CBIR batik performs well.

Classification of batik patterns using K-Nearest neighbor and support vector machine Agus Eko Minarno; Fauzi Dwi Setiawan Sumadi; Hardianto Wibowo; Yuda Munarko
Bulletin of Electrical Engineering and Informatics Vol 9, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

This study is proposed to compare which are the better method to classify Batik image between K-Nearest neighbor and support vector machine using minimum features of GLCM. The proposed steps are started by converting image to grayscale and extracting colour feature using four features of GLCM. The features include energy, entropy, contras, correlation and 0o, 45o, 90o, and 135o. The classifier features consist of 16 features in total. In the experimental result, there exist comparison of previous works regarding the classification KNN and SVM using multi texton histogram (MTH). The experiments are carried out in the form of calculation of accuracy with data sharing and cross-validation scenario. From the test results, the average accuracy for KNN is 78.3% and 92.3% for SVM in the cross-validation scenario. The scenario for the highest accuracy of data sharing is at 70% for KNN and at 100% for SVM. Thus, it is apparent that the application of the GLCM and SVM method for extracting and classifying batik motifs has been effective and better than previous work.

PELATIHAN PEMBUATAN DAN PERAWATAN WEBSITE BERBAHASA INGGRIS UNTUK MENINGKATKAN PENJUALAN PAKET JASA TOUR DAN TRAVEL DI KECAMATAN KARANGPLOSO MALANG Yuda Munarko; Agus Eko Minarno
Jurnal Dedikasi Vol. 13 (2016): Mei
Publisher : Direktorat Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/dedikasi.v13i0.3139

PELATIHAN PEMBUATAN DAN PERAWATAN WEBSITE BERBAHASA INGGRIS UNTUK MENINGKATKAN PENJUALAN PAKET JASA TOUR DAN TRAVEL DI KECAMATAN KARANGPLOSO MALANGYuda Munarko1 & Agus Eko Minarno21,2Teknik Informatika, Fakultas Teknik, Universitas Muhammadiyah MalangE-mail: 1) yuda.munarko@gmail.comABSTRAKJasa tour dan travel saat ini adalah jenis usaha yang sedang marak di area Malang dan sekitarnya. Hal ini disebabkan oleh besarnya pangsa pasar wisata di area Malang dan meningkatnya perekonomian masyarakat pada umumnya. Permasalahan yang ada adalah persaingan yang sangat ketat diantara pengusaha jasa tour dan travel, yang menimbulkan persaingan tidak sehat, sehingga berimbas pada penetapan harga yang rendah dan tidak kompetitif, terutama untuk wisatawan domestik. Pada kenyataannya, jumlah wisatawan mancanegara yang berkunjung ke Malang, dan kebutuhan mereka belum cukup terwadahi dengan maksimal oleh jasa tour dan travel yang ada. Oleh karena itu, untuk meningkatkan potensi pendapatan jasa tour dan travel, maka harus dijalin komunikasi yang baik dan efisien dengan calon wisatawan mancanegara. Namun masalah yang dihadapi pengusaha tour dan travel pada umumnya adalah kendala bahasa dan tidak adanya media komunikasi yang efisien. Masalah ini juga yang dihadapi oleh mitra, yakni Manavin Tour and Travel dan MH Tour and Travel. Pendampingan pembuatan dan perawatan website berbahasa Inggris diharapkan mampu untuk membantu mitra dalam mengatasi permasalahan Mitra. Website tersebut menjadi media untuk promosi layanan dan juga media komunikasi yang efektif dengan calon wisatawan mancanegara. Hasil yang didapatkan, dengan adanya website ini mitra sudah mendapatkan klien dari mancanegara yang berhubungan dengan bidang usaha jasa tour dan travel.Kata Kunci: Website, Tour, Travel

Re-Ranking Image Retrieval on Multi Texton Co-Occurrence Descriptor Using K-Nearest Neighbor Yufis Azhar; Agus Eko Minarno; Yuda Munarko
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Some features commonly used to conduct image retrieval are color, texture and edge. Multi Texton Co-Occurrence Descriptor (MTCD) is a method which uses all three features to perform image retrieval. This method has a high precision when doing retrieval on a patterned image such as Batik images. However, for images focusing on object detection like corel images, its precision decreases. This study proposes the use of KNN method to improve the precision of MTCD method by re-ranking the retrieval results from MTCD. The results show that the method is able to increase the precision by 0.8% for Batik images and 9% for corel images.

IMPLEMENTASI STAR SCHEMA PADA STUDI KASUS PERPUSTAKAAN BERSKALA UNIVERSITAS Wildan Suharso; Abims Fardiansa; Yuda Munarko; Hardianto Wibowo
SINTECH (Science and Information Technology) Journal Vol. 4 No. 1 (2021): SINTECH Journal Edition April 2021
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v4i1.446

Libraries are service units with high storage complexity as evidenced by more data being stored for each year. The data that is not integrated makes the complex problem because every year the process that is carried out continues to increase, especially for the circulation of loans. As the number of books increases, the circulation of borrowing increases every year. On the other hand, the library must know exactly what collection of books they have and the transactions it has made. A lot of data is owned by the library cannot be utilized optimally, so that the managerial is unable to make full use of the data. In University scale libraries, this problem increases when the data is not fully integrated. In this study, the implementation of a star schema was carried out to solve problems related to data integration using a nine-step methodology, which includes selection, item selection, process dimensions, fact selection, fact storage, ensuring dimension tables, selecting database duration, changing dimensions, determining priorities, and query models. The results of this study indicate that the star schema can be implemented in the case of libraries, data warehouses and OLAP to support decision making for adding books, and produced 3 dimensions of the 4 grains found.

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