PERAMALAN KUNJUNGAN WISATAWAN KE PALEMBANG: PEMODELAN DATA TIME SERIES LINEAR VS NONLINEAR

Abstract — Forecasting is one of the statistical models play animportant role in decision making. Forecasting aims topredict / forecast what will happen in the future based on pastdata. One of the models used in forecasting is time seriesmodel. Forecasting techniques used in modeling of time seriesdata is a time series model linear and non-linear time series.Linear time series model include exponential smoothing, AutoRegressive Integrated Moving avarege (ARIMA) orBox-Jenkins and others. While non-linear time series modelsinclude Artifisal Neural Network (ANN), Fuzzy and others.The models are typically used to forecast financial data (suchas forecasting the exchange rate (exchange rate), forecastinggross domestic product, forecasting stock prices, and others).But in this study, both models will be used to forecast datatourist visits to Palembang of South Sumatra province, wherethe data of tourists visit marked by patterns of seasonalityand strong volatility, causing the data tend to benon-stationary and it becomes difficult to model. Forecastingis intended for South Sumatra tourism planning and to planfor infrastructure development needs. The secondperformance of each model for MSE and MAE is for thelinear model 0.6564 and 10:36, while for the nonlinear modelis 1.09E-22 and 7.31E-12. From this it appears that thenonlinear models are superior in predicting the number oftourists compared to the linear model.Keywords— Forecasting, linear and nonlinear time series,tourist visits . Abstrak— Forecasting adalah salah satu model statistikmemainkan peran penting dalam pengambilan keputusan.Peramalan bertujuan untuk memprediksi / perkiraan apayang akan terjadi di masa depan berdasarkan data masa lalu.Salah satu model yang digunakan dalam peramalan modeltime series. teknik yang digunakan dalam pemodelan datatime series Peramalan adalah model rangkaian waktu lineardan non-linear time series. waktu linier seri model termasukpemulusan eksponensial, Auto Regresif Integrated Movingavarege (ARIMA) atau Box-Jenkins dan lain-lain. Sementaranon-linear model time series termasuk Artifisal NeuralNetwork (ANN), Fuzzy dan lain-lain. Model biasanyadigunakan untuk meramalkan data keuangan (sepertiperamalan nilai tukar (kurs), peramalan produk domestikbruto, peramalan harga saham, dan lain-lain). Namun dalampenelitian ini, kedua model akan digunakan untuk meramalkan data kunjungan wisatawan ke PalembangProvinsi Sumatera Selatan, di mana data kunjunganwisatawan ditandai dengan pola musiman dan volatilitas yangkuat, menyebabkan data cenderung non-stasioner danmenjadi sulit untuk model. Peramalan ditujukan untukperencanaan pariwisata Sumatera Selatan dan merencanakanuntuk kebutuhan pembangunan infrastruktur. Kinerja keduamasing-masing model untuk MSE dan MAE adalah untukmodel linear 0,6564 dan 10:36, sedangkan untuk modelnonlinear adalah 1.09E-22 dan 7.31E-12. Dari sini tampakbahwa model nonlinear lebih unggul dalam memprediksijumlah wisatawan dibandingkan dengan model linear.Kata kunci— Peramalan, linear dan nonlinear time series,kunjungan wisatawan

Model Estimasi Garch dalam Mengukur Kinerja Nilai Tukar Rupiah

The exchange rate is determined by the demand and supply relationship of the currency. If the demand for a currency increases, while the supply remains or even decreases, then the exchange rate will rise vice versa. The ups and downs of exchange rates on the money market indicate the magnitude of the volatility that occurs in the currency of a State against the currencies of other countries. The volatility phenomenon indicates difficulty in analyzing the exchange rate. Increasing volatility indicates an even greater movement of currency exchange rates even if currency exchange rates experience extreme volatility resulting in economic instability both from the micro and macro sides. The high volatility seen from the pattern of price movements that occur in financial markets, and the impact that can be generated from the high volatility data is the error that will have a variance that is not constant. That is, a relatively high data variability at a time indicates the presence of heteroscedasticity. Heteroscedasticity can lead to errors in drawing a conclusion to the estimated model obtained. Therefore, we need a model that is able to solve the problem that is Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model in order to get more accurate estimation model to estimate exchange rate. From the simulation result, all data contain the volatility seen from the result of heteroscedasticity test, and obtained estimation model for all data

Penerapan Metode Principal Component Analysis (PCA) Pada Klasifikasi Status Kredit Nasabah Bank Sumsel Babel Cabang KM 12 Palembang Menggunakan Metode Decision Tree

Bank Sumsel Babel merupakan penyedia jasa layanan keuangan daerah yang berwenang dalam menghimpun dana dari masyarakat dan menyalurkannya kembali kepada masyarakat dalam bentuk pinjaman modal kerja dengan tujuan untuk meningkatkan taraf hidup masyarakat umum. Produk yang disediakan oleh Bank Sumsel Babel diantaranya tabungan, deposito, pinjaman dan lain sebagainya. Pemberian pinjaman pada suatu nasabah dilakukan berdasarkan beberapa variabel, salah satunya adalah melihat status pembayaran calon nasabah pada proses peminjaman sebelumnya. Oleh karena itu, pada penelitian ini akan dilakukan penerapan metode Principal Component Analysis (PCA) dalam menentukan status kredit nasabah Bank Sumsel Babel Cabang KM 12 Palembang menggunakan metode Decision Tree. Hasil dari penelitian ini akan diperoleh pengaruh metode pre-processing PCA pada metode klasifikasi Decision Tree dalam penentuan status kredit nasabah. Analisis dilakukan dengan memperhatikan tingkat akurasi serta nilai precision, recall dan f1-score yang dihasilkan. Berdasarkan analisis yang dilakukan diperoleh bahwa metode PCA memberikan dampak baik terhadap kinerja dari metode Decision Tree dalam klasifikasi, hal tersebut terlihat dengan adanya peningkatan tingkat akurasi sebesar 10% dengan model klasifikasi dengan kinerja lebih baik

NEURAL NETWORK OPTIMIZATION USING ENSEMBLE METHOD IN FORECASTING FINANCIAL DATA

Forecasting is a time series data analysis technique for predicting future data by obtaining patterns of change in past data. Exponential smoothing, AutoRegressive Integrated Moving Average (ARIMA), and Box-Jenkins are common forecasting algorithms for linear time series data. Meanwhile, models such as Artificial Neural Networks (ANN), Fuzzy, and others are frequently utilized for nonlinear time series data. One of the most generally used model selection procedures is to evaluate each model that has been trained in time series data learning and then used to predict the model's performance, and then allow the forecaster determine if the model is acceptable or choose the best model from a list of candidates. Forecasts created with the best model, on the other hand, rarely produce generalized outcomes for the full data set. As a result, it's crucial to put the results of the learning training to the test. The ensemble method is employed instead of learning from a large number of models. The objective of this research is to apply ANN and the Ensemble Approach to optimize a forecasting model. When forecasting with a neural network, the ensemble approach is used to limit the occurrence of over fitting so that the resulting model can beat individual NN models and be consistent in lowering mistakes

PENGARUH PEMBELAJARAN GEOMETRI ANALITIK MENGGUNAKAN PENDEKATAN PAIKEM

Geometri analitik adalah suatu cabang ilmu matematika yang merupakan penggabungan antara aljabar dan geometri. Hal ini berarti untuk dapat memahami aljabar dapat menggunakan gemotri ataupun sebaliknya. Berdasarkan pengamatan peneliti terhadap mahasiswa yang mengambil mata kuliah geometri analitik, mahasiswa sering mengalami kesulitan untuk memahami materi. Penyebab utamanya adalah mahasiswa kurang antusias mengikuti pembelajaran, daya kreativitasnya rendah, dan bersikap acuh tak acuh sedangkan materi geometri analitik mentut keaktifan siswa untuk lebih memahami konsep aljabar secara geometrik. Hal ini menunjukkan bahwa proses pembelajaran secara konvensional yang biasa dilakukan tidak mampu mendorong mahasiswa untuk menggunakan daya pikirnya secara optimal, akibatnya mahasiswa menjadi kurang aktif dan proses pembelajaran menjadi kurang efektif. Untuk meningkatkan kemampuan mahasiswa dalam mengaitkan konsep-konsep aljabar menggunakan geometrik, maka dalam penelitian ini dilakukan pembelajaran dengan menggunakan pendekatan PAIKE

BPNN's Empirical Analysis of Daily Rupiah Exchange Rate Volatility Utilizing Hidden Neuron Optimization

The exchange rate is the greatest financial market in its application. As a result, traders, investors, and other money market participants must be aware of the movement of currency exchange rate data. The fluctuation, or rise and fall, of currency exchange rates reveals the level of volatility in a country. The Backpropagation Neural Network is one of the models that can grasp the features of currency exchange rates (BPNN). BPNN is made up of three layers: input, hidden, and output, and each layer contains neurons. One of the challenges in designing a BPNN network architecture is determining the ideal number of hidden layer neurons. In this work, ten methodologies will be utilized to determine the number of hidden neurons; the ten approaches provide distinct empirical results in accordance with the goal of this study, which is to perform an empirical analysis of currency exchange rates by maximizing the number of hidden neurons. Empirical results reveal that the approach for calculating the number of hidden neurons performs well in terms of MAE and MSE. For the following seven periods, the best approach is used to forecast the Rupiah exchange rate

MODEL ESTIMASI GARCH DALAM MENGUKUR KINERJA NILAI TUKAR RUPIAH

The exchange rate is determined by the demand and supply relationship of the currency. If the demand for a currency increases, while the supply remains or even decreases, then the exchange rate will rise vice versa. The ups and downs of exchange rates on the money market indicate the magnitude of the volatility that occurs in the currency of a State against the currencies of other countries. The volatility phenomenon indicates difficulty in analyzing the exchange rate. Increasing volatility indicates an even greater movement of currency exchange rates even if currency exchange rates experience extreme volatility resulting in economic instability both from the micro and macro sides. The high volatility seen from the pattern of price movements that occur in financial markets, and the impact that can be generated from the high volatility data is the error that will have a variance that is not constant. That is, a relatively high data variability at a time indicates the presence of heteroscedasticity. Heteroscedasticity can lead to errors in drawing a conclusion to the estimated model obtained. Therefore, we need a model that is able to solve the problem that is Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model in order to get more accurate estimation model to estimate exchange rate. From the simulation result, all data contain the volatility seen from the result of heteroscedasticity test, and obtained estimation model for all data

PENERAPAN BAURAN PEMASARAN (MARKETING MIX) SEBAGAI STRATEGI PEMASARAN PRODUK GULO PUAN DESA BANGSAL

Gulo puan is one of the indigenous cuisines from the district of Pampangan, Regency of Ogan Komering Ilir (OKI), South Sumatra. Gulo means sugar and Puan  means milk. Gulo Puan is made from sugar and caramel milk. The milk used in making gulo puan is from swamp buffalo. Gulo puan is very popular in several regions in South Sumatra. However, not many people are familiar with gulo puan like other typical South Sumatra cuisines. The team from the Indo Global Mandiri University (UIGM) carried out a Stimulus Community Partnership Program activity funded by the Ministry of Technology, Research and Higher Education Republic of Indonesia in order to provide solutions to the target partners namely Gulo Puan Business group in Bangsal Village by implementing the Marketing Mix. Improving product quality is conducted through making logos and product packaging labels, using stand pouch packaging and plastic jars, and fascinating innovation in the form of gulo puan candy products (Puan Candy). Promotion and distribution channels are increased by marketing the products through e-commerce to reach consumers widely and bypassing distribution channels, while an increase in price stays is conducted by providing products with various weight variations, ranging from 100 grams to 1000 grams. Based on the results of the analysis, it could be stated that the product, price, promotion and location or place (distribution channel) of consumer loyalty in re-buying gulo puan products could be seen from all the significance values of the independent variables  that is less than 0.05

WORKSHOP MEMBUAT DAN MENGGUNGAH VIDEO PEMBELAJARAN SECARA ONLINE BAGI PARA GURU SMP NEGERI 30 PALEMBANG

Di era pandemic saat ini, metode pembelajaran mengalami perubahan yang cukup signifikan. Hal ini terjadi karena pemberlakukan pembatasan aktivitas dan berkumpul bagi peserta belajar. Kejadian ini mengakibatkan metode pembelajaran menggunakan daring (online) dimana siswa dapat tetap belajar dari rumah. Tuntutan inilah yang menjadikan para pengajar yaitu guru harus memiliki kemampuan dalam akses dan memanfaatkan internet serta kreatif dalam membuat konten materi pembelajaran. Oleh karena itu, SMP Negeri 30 Palembang, menyelenggarakan kegiatan workshop membuat dan mengunggah video pembelajaran pada Youtube Channel, guna memberikan peningkatan pengalaman para guru sebagai bentuk materi pembelajaran secara daring. Kegiatan pengabdian masyarakat ini dilakukan secara langsung dalam ruang rapat dengan mematuhi Protokol Kesehatan Pencegahan Penyebaran Covid-19 di SMP Negeri 30 Palembang pada tanggal 7 Desember 2021.Kata kunci : membuat akun, materi pembelajaran, video, youtube channe

Sistem Informasi Company Profile Kantor Kecamatan Sematangborang Berbasis Website

Website Company profile adalah website yang menampilkan informasi tentang latar belakang perusahaan, produk atau jasa, informasi kontak dan berita singkat tentang perusahaan. Saat ini, Kantor Kecamatan Sematangborang menyampaikan informasinya hanya melalui spanduk, brosur, surat dan baliho yang membutuhkan biaya dan waktu yang lebih banyak. Banyak masyarakat yang tidak mengetahui tentang Informasi Pelayanan dan Profil Kantor Kecamatan Sematangborang dikarenakan minimnya informasi. Dengan keadaan tersebut maka dengan ini penulis tertarik menyusun kegiatan penelitian ini dengan mengambil judul “Sistem Informasi Company Profile Kantor Kecamatan Sematangborang Berbasis Website”. Diharapkan dengan adanya Sistem Informasi tersebut memudahkan masyarakat dalam mendapatkan informasi tentang profil Kantor Kecamatan Sematangborang. Menggunakan bahasa pemrograman PHP, database MySQL. Metode pengembangan perangkat lunak yang akan digunakan dalam penelitian ini adalah metode Waterfall dengan tahapan meliputi analysis, design, coding dan testing. Pengujian sistem informasi ini dilakukan dengan metode   blackbox testing