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All Journal Jurnal Ulul Albab JTAM (Jurnal Teori dan Aplikasi Matematika) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Ilmiah Kesehatan Jurnal Medika Malahayati Jurnal Varian Inferensi Jurnal Bumigora Information Technology (BITe) Target : Jurnal Manajemen Bisnis JPMB: Jurnal Pemberdayaan Masyarakat Berkarakter Teknomatika (Jurnal Teknologi dan Informatika) Jurnal Pengabdian kepada Masyarakat Agrimansion: Agribusiness Management & Extension Jurnal Sains Teknologi dan Sistem Informasi juremi: jurnal riset ekonomi ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Unnes Journal of Mathematics JURNAL PENDIDIKAN INDONESIA: Teori, Penelitian, dan Inovasi Transformatif: Jurnal Pengabdian Masyarakat Jurnal Gizi dan Kuliner VARIANSI: Journal of Statistics and Its Application on Teaching and Research Bakti Sekawan : Jurnal Pengabdian Masyarakat Jurnal Ilmiah Pengabdian dan Inovasi Jurnal Edukasi dan Pengabdian kepada Masyarakat (JEPKM) Innovative: Journal Of Social Science Research Jurnal Sains Natural Jurnal Pelita Ilmu Pendidikan (JPIP) Jurnal Manajemen dan Ekonomi Terapan Journal of Mathematics and Applied Statistics Jurnal Ilmu Kesehatan Masyarakat (The Public Health Science Journal) Prosiding Seminar Nasional CORISINDO
Siti Soraya
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Journal : Jurnal Varian

 1 
PENERAPAN ALGORITMA GREEDY DALAM MENENTUKAN MINIMUM SPANNING TREES PADA OPTIMISASI JARINGAN LISTRIK JALA Didiharyono Didiharyono; Siti Soraya
Jurnal Varian Vol 1 No 2 (2018)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v1i2.66

Abstract

This article discusses the applied of greedy algorithm principle in finding the optimum solution in determine minimum spanning tree on graph. Graph theory is one of the studies in discrete mathematics that are widely applied in various scope. This article is a literature study and applied of nets electricity network optimization using Prims algorithm and Kruskal algorithm. Network Nets System is one type of electrical network system construction. Based on results of the study and discussion can be concluded that the application of greedy algorithm using Prims algorithm and Kruskal algorithm in determine minimum spanning tree on its principle is the same. However, after a comparison between the two algorithms we consider that the ideal algorithm used to optimize the nets electric network is the Kruskal algorithm because in the case of the electric network has few sides and many vertices.
Uji Normalitas Data Omzet Bulanan Pelaku Ekonomi Mikro Desa Senggigi dengan Menggunakan Skewness dan Kurtosi Dodiy Fahmeyzan; Siti Soraya; Desventri Etmy
Jurnal Varian Vol 2 No 1 (2018)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v2i1.331

Abstract

Ekonomi adalah salah satu ilmu sosial yang mempelajari aktivitas manusia yang berhubungan dengan produksi, distribusi dan konsumsi terhadap barang dan jasa. Ekonomi mikro adalah cabang dari ilmu ekonomi yang mempelajari perilaku konsumen dari perusahaan serta penentuan harga-harga pasar dan kuantitas faktor input, barang dan jasa yang diperjual belikan. Berkaitan dengan hal tersebut peneliti mengambil judul uji normalitas omzet bulanan bagi pelaku ekonomi mikro Desa Senggigi menggunakan skewness dan kurtosis yang bertujuan untuk mengetahui penyebaran omzet bulanan pelaku ekonomi mikro Desa Senggigi. Variabel yang digunakan dalam pengujian ini adalah omzet. Metode yang digunakan dalam penelitian ini adalah skewness dan kurtosis yang dianalisis menggunakan aplikasi IBM 24, guna melihat apakah data omzet bulanan, normal atau tidaknya dan juga melihat kemencengan datanya. Dari hasil penelitian diperoleh data omzet bulanan normal, tapi belum tentu data tersebut tidak baik, karena kita bisa melihat kemencengan datanya mengarah kearah kanan positif, hal tersebut menunjukkan omzet bulanannya termasuk tinggi, hanya saja omzet bulanan yang tinggi itu tidak merata untuk semua pelaku ekonomi mikro di Senggigi.
ARDL METHOD: Forecasting Data Curah Hujan Harian NTB Ulul Azmi; Zilullah Nazir Hadi; 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.v3i2.627

Abstract

Penelitian ini berisi tentang prediksi atau forecasting data iklim di Nusa Tenggara Barat (NTB) tahun 2011, yakni jumlah hari terjadinya hujan dengan menggunakan metode Autoregressive Distributed Lag (ARDL). Data yang digunakan yaitu data iklim di Nusa Tenggara Barat (NTB) dari tahun 2006 -2010, dengan menggunakan beberapa parameter error seperti Mean Absolute Deviation (MAD), Mean Squared Error (MSE), Root Mean Squared Error (RMSE) dan Mean Absolute Percentage Error (MAPE). Berdasarkan hasil simulasi data iklim di Nusa Tenggara Barat (NTB) tersebut, diperoleh prediksi jumlah hari terjadinya curah hujan pada tahun 2011 sebesar 226 hari dengan nilai MAD 20,8069, MSE 3,5569, RMSE 1,88597, dan MAPE 11,9297 . Dan prediksi jumlah hari terjadinya hujan pada tahun 2011 sebanyak 225,928 hari atau jika di bulatkan menjadi 226 hari dengan nilai parameter error MAD sebesar 20,8069, sehingga dapat disimpulkan pada tahun 2011 terjadi peningkatan jumlah hari terjadinya hujan di Nusa Tenggara Barat (NTB).
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
Spatial Econometric Model on Economic Growth in West Nusa Tenggara Siti Soraya; Baiq Candra Herawati; Muttahid Shah; Syaharuddin Syaharuddin
Jurnal Varian Vol 4 No 2 (2021)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v4i2.912

Abstract

Gross Regional Domestic Product (GRDP) is a reflection of a region's economic growth. West Nusa Tenggara (NTB) is one of the provinces that contributes to good GRDP for Indonesia. The purpose of this research is to modeling GRDP in NTB using spatial econmetrics. The data used is the GRDP data of each district / city in NTB Province as a response variable and factors that affect the number of workers, capital value and electrification ratio as predictor variables. The results showed that there is a spatial dependence on the district / city GRDP in NTB Province on the error model so that the model formed is the Spatial Error Model (SEM) with a rho of 71.1% and an AIC value of 173.34.
Forecasting Foreign Tourist Visits to West Nusa Tenggara Using ARIMA Method Siti Soraya; Maulida Nurhidayati; Baiq Candra Herawati; Anthony Anggrawan; Lalu Ganda Rady Putra; Didiharyono D
Jurnal Varian Vol 5 No 1 (2021)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v5i1.1441

Abstract

West Nusa Tenggara (NTB) is one of the provinces in Indonesia that has its own charm in the world of tourism and is known as a pioneer of halal tourism. In addition to domestic tourists, NTB tourism always has an attraction for foreign tourists. This is evidenced by the increasing number of foreign tourists visiting NTB from year to year before the Covid-19 pandemic. This condition certainly has a positive impact on increasing NTB’s economic growth in the tourism sector and indirectly on the optimization of existing infrastructure. The purpose of the study is to predict the number of foreign tourist visits to NTB so that it can assist the government in making decisions in preparing adequate facilities and infrastructure in the event of a surge in tourist visits. The method used in this study is the Box-Jenkins-ARIMA model. The ARIMA method is based on 3 models that are formed from the results of plot data. The data used in this study is secondary data sourced from the Central Statistics Agency (BPS) of West Nusa Tenggara (NTB), from January 2010 to June 2019. The results show that the ARIMA (4,1,1) model is the most widely used model. This model is suitable for predicting the number of foreign tourists visiting NTB because this model produces the lowest SSE and MSE values compared to other models.
Jurnal Varian Full Text Siti Soraya
Jurnal Varian Vol 5 No 2 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v5i2.2250

Abstract

The Implementation of Fuzzy Time Series in Forecasting The Number of Tourist Visits Aziza, Istin Fitriana; Soraya, Siti; Sahdan, Sahdan; Husain, Husain; Hendayanti, Ni Putu Nanik; Harsyiah, Lisa
Jurnal Varian Vol. 8 No. 3 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v8i3.4890

Abstract

The development of tourism in West Nusa Tenggara (NTB) Province is supported by its geographical conditions, including scattered small islands (gilis), a tropical climate, and the cultural peculiarities of the Sasak and Mbojo Tribes, thereby becoming an attraction in the development of global tourist destinations. Tourism development in NTB Province would be more attractive with the establishment of the Mandalika National Tourism Development Strategic Area (KSPPN). This research aims to predict the number of tourist visits. A method to forecast the number of tourist visits in NTB Province is needed to assist the government in preparing appropriate facilities and infrastructure in the event of a possible surge in tourist visits. The method used in this study is the Fuzzy Time Series to predict the number of tourist visits in NTB Province. The data used in this study were secondary data sourced from the NTB government tourism office. The result of this research was that the Fuzzy Time Series method was effective in predicting the number of tourist visits in NTB Province, with an accuracy of 90.29%. The forecast result, generated using the Fuzzy Time Series method, was not significantly different from the actual data; in other words, it was almost identical to the actual data. The forecast for tourist visits to the NTB province in the 48th period remains unchanged until the 53rd period, namely 80,739.7 people. The FTS method used in this study cannot be applied to data with long-term seasonal patterns. A suggestion for future researchers is to develop a classical FTS that captures additional long-term seasonal patterns. 
Co-Authors Afnidia, Tria Agus Sofian Eka Hidayat Ahmad Ahmad Ahmad Zuli Amrullah Al Jauziah, Hanief Ananda, Laraswati Andika Ellena Saufika Hakim Maharani Anggarawan, Anthony Anthony Anggrawan Aryani, Wiwik Dyah Ashar Banyu Lazuardi Ayu Dasriani, Ni Gusti Aziza, Istin Fitriani Azizah, Istin Fitriani Azmi, Rinda Fitriana Badriyah, Lulu'ul Baiq Chandra Herawati Baiq Dinda Puspita Ayu Bryan Hakim Sakti Pradana Choirul Anwar christofer satria Daniel Happy Putra desventri etmy Devi Yulianti Dewi, Puspita Didiharyono, D. Dodiy Fahmeyzan Ekaningrum, Annisa Yuri Erwin Suhendra Ferdinandus Lidang Witi Firmansyah Firmansyah Firmansyah, Dodiy Fitriana Aziza, Istin Fitriana, Laili Fitriani, Anisa Gede Suwardika Gilang Primajati Gilang Primajati Gusnayanti, Riski Gusti Ayu Aghivirwiati Habib Ratu Perwira Negara Harsyiah, Lisa Helna Wardhana Hendayanti, Ni Putu Nanik Herawat, Baiq Candra Herawati, Baiq Candra Herlina Putri, Novi Hidayat, Agus Sofian Eka Hisbullah Hisbullah Husain Husain I Gusti Ayu Desi Saryanti I Ketut Putu Suniantara I Nyoman Miyarta Yasa I Nyoman Yoga Sumadewa I Wayan Kusuma Di Biagi Ida Bagus Bayu Mahayana Indrawan Mulyadi Isasi, Widani Darma Ismoen, Muhaimin Istin Fitriana Aziza Juanda, M. Rizky Ujiana Julyanti , Nafi’ah Zahra Khairan marzuki Khasnur Hidjah Kurnia, Indri Lalu Ganda Rady Putra Maesaroh Maesaroh Malik Ibrahim Mayasari, Rossa Melati Rosanensi Mohammad Fajri Mukti, M Thoriq Panca Mustakim, Asep Muttahid Shah Nata, I Gede Anjas Kharisma Nurhidayati, Maulida Pangaribuan, Daniel Panji Tanashur Phyta Rahima Primajati , Gilang Primajati, Gilang Primajati, Gilang Puspita Dewi, Puspita Putrajip, Mohamad Yudisa Putri, Andri Qatrunnada R. Ayu Ida Aryani Rabbani, Muhammad Haikal Rahima, Pitha Rahmiati, Baiq Fitria Ratmaji, Muji Regina Pricilia Yunika Riana Riana Rianti, Andri Putri Rifani Nur Sindy Setiawan Rismayati, Ria Rizal, Ahmad Ashril Rizqi, Retno Inten Rizwan Arisandi, Rizwan Sahdan, Sahdan Santi Puteri Rahayu Saputra, Habibi Yusup Setiawan Setiawan Setyawan, Ari Shilvia Nurin Ni’mah Sirojul Hadi Subhan Hadi Sufahani, Suliadi Firdaus Supiarmo, M. Gunawan Suriyati ., Suriyati Syaharuddin Syaharuddin Ulul Azmi Verma, Kirti Widhi, Bidari Andaru Widia Febriana, Widia Wirajaya Kusuma Yunika, Regina Pricilia Yustina Hendrayati Baba Zilullah Nazir Hadi