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All Journal Jurnal Statistika Universitas Muhammadiyah Semarang Jurnal Ilmiah Kursor Jurnal Sistem dan Informatika Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) WARTA Journal of Information Systems Engineering and Business Intelligence Binus Business Review Jurnal Sinergitas PkM & CSR MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer WIDYABHAKTI Jurnal Ilmiah Populer Journal of Educational Research and Evaluation International Journal of Natural Science and Engineering Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Simtek : Jurnal Sistem Informasi dan Teknik Komputer Bhakti Persada Jurnal Aplikasi IPTEKS SENSITEK E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi Jurnal Teknologi Informasi dan Multimedia Jurnal Varian Informatika Publik: Jurnal Manajemen Sumber Daya Manusia, Administrasi dan Pelayanan Publik REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Community Empowerment Jurnal Teknimedia: Teknologi Informasi dan Multimedia Jurnal Pengabdian kepada Masyarakat Naratif : Jurnal Nasional Riset, Aplikasi dan Teknik Informatika Journal of Innovation Research and Knowledge Paradigma Seminar Ilmiah Nasional Teknologi, Sains, dan Sosial Humaniora (SINTESA) SATIN - Sains dan Teknologi Informasi
I Ketut Putu Suniantara
Institut Teknologi & Bisnis Stikom Bali, Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Public Health Social Sciences Other

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Hierarchical Clustering for Functionalities E-Commerce Adoption Evi Triandini; Fajar Astuti Hermawati; I Ketut Putu Suniantara
Jurnal Ilmiah Kursor Vol 10 No 3 (2020)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v10i3.230

Abstract

Web functionality is one driver for e-commerce adoption. It is appeared the level of technological capabilities as well as the accentuation of the strategy put on e-commerce by the organization. Web functionality is related to the level of e-commerce relocation. Website with more functionality will give way better benefits for shoppers and trade partners. Functionalities of web are components that support the achievement of adoption benefits. Hierarchical clustering and ranking availability of e-commerce functionality is a challenging task. Ward Linkage algorithm was used to measure distance. This study proposed to get a grouping of e-commerce functionalities that influence e-commerce adoption and to get the ranking of the groups that most influence the achievement of these benefits. Result shows that functionalities that supports the achievement of every benefit of e-commerce has been clustered into two or three clusters, where each cluster also has been ranked to facilitate the achievement of these benefits
Multimedia Interaktif Pengenalan Pura Lingga Bhuwana dengan Metode 2D Hybrid Animation I Kadek Wahyu Adi Gunawan; Pande Putu Gede Putra Pertama; I Ketut Putu Suniantara
Jurnal Sistem dan Informatika (JSI) Vol 15 No 1 (2020): Jurnal Sistem dan Informatika (JSI)
Publisher : Bagian Perpustakaan dan Publikasi Ilmiah - Institut Teknologi dan Bisnis (ITB) STIKOM Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30864/jsi.v15i1.327

Abstract

Pura Lingga Bhuwana adalah pura Kahyangan yang berlokasi di Pusat Pemerintahan Kabupaten Badung. Pura ini dibangun bagi masyarakat Badung untuk meningkatkan srada bhakti-nya kepada Ida Sang Hyang Widhi Wasa. Bagi masyarakat Bali khususnya masyarakat Badung belum mengetahui lokasi pura dan bagaimana arsitektur bangunan dan sejarah asal mula tentang berdirinya pura ini. Kurangnya informasi mengenai Pura Lingga Bhuwana membuat masyarakat khususnya masyarakat di Bali belum mengetahui tentang informasi mengenai Pura tersebut. Maka dari itu diperlukan sebuah media pengenalan dan dokumentasi keberadaan Pura Lingga Bhuwana berupa video 2D Hybrid Animation. Video ini dijalankan di aplikasi Android dan dilengkapi dengan berbagai informasi mengenai Pura Lingga Bhuwana. Hasil akhir dari penelitian ini berupa Aplikasi Pengenalan Pura Lingga Bhuwana dengan menggunakan animasi 2 Dimensi yang berperan sebagai karakter yang mengenalkan Pura Lingga Bhuwana dengan latar video nyata. Berdasarkan hasil pengujian yang dilakukan dengan menggunakan metode Black Box Testing didapatkan hasil semua fungsi dapat berjalan sesuai rancangan. Hasil pengujian terhadap kategori video pengenalan pura dengan metode 2D Hybrid Animation dinyatakan sangat baik dengan persentase sebesar 88%.
Pengenalan Proses Produksi Kerajinan Berbahan Sampah Industri Berbasis Multimedia (Studi Kasus Bank Sampah Abukasa) I Made Tresna Wardana; I Gede Suardika; I Ketut Putu Suniantara
E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi Vol 9 No 1 (2020): e-Jurnal JUSITI
Publisher : Universitas Dipa Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36774/jusiti.v9i1.640

Abstract

Pengenalan Proses Produksi Kerajinan Berbahan Sampah Industri Berbasis Multimedia (Studi Kasus Bank Sampah Abukasa) merupakan aplikasi multimedia interaktif yang berisikan informasi berupa pengenalan Bank Sampah Abukasa, Bali Recycle Paper, serta proses produksi kerajinan berbahan dasar sampah industri dan menjawab kuis sebagai ringkasan kembali terhadap informasi pengenalan yang ada pada aplikasi yang dikemas dalam aplikasi mobile. Bank Sampah Abukasa merupakan salah satu badan usaha pengelolaan sampah kering secara kolektif yang mendorong masyarakat untuk berperan serta aktif di dalamnya, agar pelaksanaan pengenalan informasi mengenai pemanfaatan sampah kertas untuk produksi kerajinan tangan oleh Bank Sampah Abukasa dapat dikenal, maka dikembangkanlah sebuah aplikasi berupa Pengenalan Proses Produksi Kerajinan Berbahan Sampah Industri Berbasis Multimedia. Metode yang digunakan dalam mengembangkan aplikasi ini adalah metode MDLC (Multimedia Development Life Cycle). Pada aplikasi ini pengujian dilakukan dengan menggunakan metode black box testing dan menghasilkan output yang sesuai dengan harapan dan pengujian beta dengan kuesioner dapat disimpulkan hasil perhitungan intervalnya dikategorikan sangat baik.
Pengembangan E-Commerce Tembe Nggoli (Sarung) Khas Bima Berbasis Web Responsive di Desa Nata Halilurahman Halilurahman; Evi Tandriani; I Ketut Putu Suniantara
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol 3 No 2 (2021): August
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v3i2.134

Abstract

Tembe Nggoli is a typical Bima sarong made by weaving which is still preserved by the community in Neta Village, Palibelo District, Bima Regency. Tembe Nggoli is a hand-crafted art that has been passed down from generation to generation for the sake of preserving the weaving art. Currently, the selling process of Tembe Nggoli is still manual or conventional by selling directly to the public without marketing media so that it is only known by the surrounding community. This resulted in relatively lower income from the sale of Tembe Nggoli, so the process of returning capital was very slow. These problems can be solved by developing e-commerce in the sales process or introducing the craft. The purpose of this research is to build an e-commerce selling Tembe Nggoli based on a responsive website. The method used in building this application is the Software Development Life Cycle (SDLC) with the Waterfall Model. The results of this study have resulted in an e-commerce application selling the Tembe Nggoli Khas Bima sarong that is web-based responsive, so that the appearance of the application can adapt to various types of devices. With this application, it is expected to be able to provide convenience in the shopping process that can assist consumers in finding the desired product quickly and done anywhere and anytime. In addition, this application provides various kinds of information related to Tembe Nggoli products. Testing this system using blackbox testing which states that the system has been running in accordance with the functionality and procedures that are the purpose of developing the system. The functional suitability of the built system reaches 100%.
ANALISIS DATA PANEL PADA KINERJA REKSADANA SAHAM I Gede Agus Astapa; Gede Suwardika; I Ketut Putu Suniantara
Jurnal Varian Vol 1 No 2 (2018)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v1i2.72

Abstract

Mutual funds is another investment opportunity with a more measurable risk as well as return high enough with enough capital is affordable for the community. Mutual fund performance can be measured by several indicators.. Modeling the performance of mutual funds modeled by regression of the data panel. The regression model estimation data panel will do with the three approaches, namely the approach of common effect, fixed effects and random effects. This research purpose to know the performance of mutual funds from stock selection skill variable influences, market timing ability and level of risk with the use of panel data analysis. The results shows that the Fund's performance is affected by the stock selection skill, market timing ability, and the level of risk. Model the right approach to model the performance of mutual funds by using a random effects model.
Pemodelan Menggunakan Metode Spasial Durbin Model untuk Data Angka Putus Sekolah Usia Pendidikan Dasar Luh Putu Safitri Pratiwi; Shofwan Hanief; I Ketut Putu Suniantara
Jurnal Varian Vol 2 No 1 (2018)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v2i1.314

Abstract

Masalah anak yang putus sekolah perlu mendapatkan perhatian karena salah satu indikator yang berguna untuk mengukur kemajuan sumber daya manusia pada bidang pendidikan. Untuk menekan laju pertambahan jumlah anak putus sekolah tersebut dapat dilakukan dengan cara mengetahui faktor-faktor yang berpengaruh terhadap jumlah anak putus sekolah dan berpotensi dalam meningkatkan laju pertumbuhan anak yang putus sekolah. Pemodelan yang menggunakan pengaruh daerah (area) disebut pemodelan spasial. Ciri dari pemodelan spasial adalah adanya matriks pembobot yang merupakan penanda adanya hubungan antara suatu wilayah dengan wilayah lain. Salah satu model spasial yaitu Spasial Durbin Model (SDM). Penelitian ini bertujuan untuk mengetahui jumlah anak putus sekolah di wilayah Bali dengan menggunakan metode SDM dan ingin menetahui faktor-faktor yang mempengaruhi anak putus sekolah di wilayah Bali. Model yang didapat ialah pemodelan SDM menghasilkan nilai AICc yang lebih kecil dibandingkan pemodelan dengan OLS. Tidak adanya lag variabel independen yang signifikan menyebabkan hasil estimasi parameter menggunakan SDM menjadi tidak signifikan akan tetapi pada identifikasi nilai Moran’s I mengidentifikasikan adanya dependensi spasial pada variabel independen yang artinya ada kemiripan sifat untuk lokasi yang saling berdekatan.
Ketidaktepatan Waktu Kelulusan Mahasiswa Universitas Terbuka dengan Metode Boosting Cart Gede Suwardika; I Ketut Putu Suniantara; Ni Putu Nanik Hendayanti
Jurnal Varian Vol 2 No 2 (2019)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v2i2.361

Abstract

The classification tree method or better known as Classification and Regression Tree (CART) has capabilities in various data conditions, but CART is less stable in changing learning data which will cause major changes in the results of the classification tree prediction. Predictive accuracy of an unstable classifier can be corrected by a combination method of many single classifiers where the prediction results of each classifier are combined into the final prediction through the majority voting process for classification or average voting for regression cases. Boosting ensemble method is one method that combines many classification trees to improve stability and determine classification predictions. This research purpose to improve the stability and predictive accuracy of CART with boosting. The case used in this study is the classification of inaccuracies in the Open University student graduation. The results of the analysis show that boosting is able to improve the accuracy of the classification of the inaccuracy of student graduation which reaches a classification prediction of 75.94% which previously reached 65.41% in the classification tree.
Penerapan Support Vector Regression (Svr) Dalam Memprediksi Jumlah Kunjungan Wisatawan Domestik Ke Bali Ni Putu Nanik Hendayanti; I Ketut Putu Suniantara; Maulida Nurhidayati
Jurnal Varian Vol 3 No 1 (2019)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v3i1.506

Abstract

Bali is one of the most popular tourism sectors in Indonesia. In the arena of international tourism, the island of Bali is considered as the most famous national destination compared to other destinations. The high level of domestic tourism visits to Bali annually must be strictly noted especially for local governments and Bali provincial tourism agencies in optimizing facilities, infrastructure to the safety of tourists Visit. Therefore, it takes a method that can predict the number of tourists visiting Bali annually. One method used to predict the number of tourists visiting Bali is Support Vector Regression (SVR). SVR is a method to estimate a mapped function from an input object to a real amount based on the training data. SVR has the same properties about maximizing margins and kernel tricks for mapping nonlinear data. Results of this research. Based on forecasting using MAPE value training data obtained by 11.34% while use data testing of MAPE value obtained by 7.30%. Based on the resulting MAPE value can be categorized well for the number of tourism visitors.
Perbandingan Pembobotan Seemingly Unrelated Regression – Spatial Durbin Model Untuk Faktor Kemiskinan Dan Pengangguran Luh Putu Safitri Pratiwi; Ni Putu Nanik Hendayanti; I Ketut Putu Suniantara
Jurnal Varian Vol 3 No 2 (2020)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v3i2.596

Abstract

Hukum I Tobler menduga segala sesuatu di suatu wilayah berhubungan erat dengan wilayah lainnya sehingga pemodelan analisis spasial lebih tepat digunakan untuk memodelkan faktor yang berpengaruh terhadap kemiskinan dan pengangguran di suatu wilayah dengan memperhatikan efek spasialnya Salah satu metode spasial yang bisa digunakan ialah Seemingly Unrelated Regression-Spatial Durbin Model (SUR-SDM). Di dalam penelitian SUR SDM diperlukan suatu pembobot yang digunakan untuk menghitung koefisien autokorelasi. Matriks pembobot yaitu matriks yang elemen-elemennya adalah nilai pembobot yang diberikan untuk perbandingan setiap daerah tertentu. Metode penentuan matriks pembobot dalam penelitian ini dengan menggunakan Queen Contiguity dan pembobot customize. Penelitian ini bertujuan untuk mendeskripsikan kemiskinan dan pengangguran serta faktor – faktor yang diduga mempengaruhinya menggunakan metode SUR-SDM dengan bobot Queen Contiguity dan Customize. Adapun variabel-variabel yang digunakan yaitu Variabel respon terdiri dari persentase rumah tangga miskin (%) (y1) dan angka pengangguran (%)(y2). Sedangkan variabel bebasnya yaitu terdiri dari: persentase jumlah sarana pelayanan kesehatan meliputi posyandu, poliklinik, puskesmas, puskesmas pembantu, dokter praktek, klinik bersalin, dan pos KB (%) (x1), persentase jumlah sarana sekolah meliputi TK, SD, SLTP, SMU, dan SMK (%) (x2), persentase penduduk yang bekerja di sektor pertanian (%) (x3), persentase rumah tangga yang menggunakan air bersih (PDAM) (%) (x4), dan rasio penduduk yang belum tamat SD (x5). Hasil yang didapat yaitu pemodelan SUR-SDM dengan bobot Customize menghasilkan nilai R-Square yang lebih kecil dibandingkan bobot queen di kedua variable respon yaitu sebesar 80.60% dibandingkan queen sebesar 80.64 untuk variable kemiskinan dan untuk variable pengangguran bobot Customize mengasilkan nilai 92.51% lebih kecil disbanding queen sebesar 92.53%
Peningkatan Akurasi Klasifikasi Ketidaktepatan Waktu Kelulusan Mahasiswa Menggunakan Metode Boosting Neural Network I Ketut Putu Suniantara; Gede Suwardika; Siti Soraya
Jurnal Varian Vol 3 No 2 (2020)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v3i2.651

Abstract

Supervised learning in Machine learning is used to overcome classification problems with the Artificial Neural Network (ANN) approach. ANN has a few weaknesses in the operation and training process if the amount of data is large, resulting in poor classification accuracy. The results of the classification accuracy of Artificial Neural Networks will be better by using boosting. This study aims to develop a Boosting Feedforward Neural Network (FANN) classification model that can be implemented and used as a form of classification model that results in better accuracy, especially in the classification of the inaccuracy of Terbuka University students. The results showed the level of accuracy produced by the Feedforward Neural Network (FFNN) method had an accuracy rate of 72.93%. The application of boosting on FFN produces the best level of accuracy which is 74.44% at 500 iterations
Co-Authors Agus Tatang Sopandi Ayu Chrisniyanti Candra Ahmadi Dadang Hermawan Dedy Panji Agustino Dian Rahmani Putri Dian Rahmani Putri EDWAR EDWAR Evi Tandriani Evi Triandini Evi Triandini Fajar Astuti Hermawati Gede Agus Dirtha Kristian Gede Suwardika Gusti Ayu Made Arna Putri Halilurahman Halilurahman Hendayanti, Ni Putu Nanik I Gede Agus Astapa I Gede Agus Astapa I Gede Darsana I Gede Eka Wiantara Putra I Gede Eka Wiantara Putra I Gede Endy Permana Putra I Gede Nika Wirawan I Gede Suardika I Gusti Ngurah Satria Wijaya I Kadek Wahyu Adi Gunawan I Made Agus Wirahadi Putra I Made Ari Santosa I Made Ari Santosa I Made Ari Yudana I Made Bagus Dwi Mahadita I Made Hendra M. Pramayasa I Made Rudita I MADE RUDITA I Made Sujana I Made Tresna Wardana I Nyn Suraja Antarajaya I Nyoman Dwi Arysna Mahendra I Putu Andi Ariawan I Putu Ramayasa, I Putu Joko Santoso Kadek Adi Saputra Kadek Heri Budi Arsana Kadek Masakazu Kadek Masakazu Kadek Masakazu Kadek Surya Adi Saputra Ketut Gus Oka Ciptahadi Lilis Yuningsih Luh Putu Ersamiya Ika Jayanthi LUH PUTU SAFITRI PRATIWI M. Rusli M. Rusli, M. Rusli Masakazu, Kadek Ni Nyoman Supuwiningsih Ni Wayan Cahya Ayu Pratami Nurhidayati, Maulida Pande Putu Gede Putra Pertama Putra, I Gede Eka Wiantara Putu Adi Wiryawan Putu Citra Darmika Dewi Rahmani Putri, Dian Riza Wulandari Samuel Hutajulu Shofwan Hanief Siti Soraya Stefani Yarra Canista Subali, Made Agus Putra T.M. Kusuma Tifany Chandrarani Tria Hikmah Fratiwi Wijaya, I Gusti Ngurah Satria