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All Journal Jurnal Matematika JURNAL SISTEM INFORMASI BISNIS Jupiter TELKOMNIKA (Telecommunication Computing Electronics and Control) GRADIEN Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Ilmiah Ekonomi Islam JPM (Jurnal Pemberdayaan Masyarakat) BAREKENG: Jurnal Ilmu Matematika dan Terapan Dinamisia: Jurnal Pengabdian Kepada Masyarakat SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal AKSI (Akuntansi dan Sistem Informasi) Martabe : Jurnal Pengabdian Kepada Masyarakat Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Eksakta : Berkala Ilmiah Bidang MIPA Jurnal Informatika Global Antivirus : Jurnal Ilmiah Teknik Informatika Jurnal Abdimas Mahakam DIKEMAS (Jurnal Pengabdian Kepada Masyarakat) Jurnal Abdimas Mandiri Abdimas Galuh : Jurnal Pengabdian Kepada Masyarakat Reswara: Jurnal Pengabdian Kepada Masyarakat Jurnal Generic Jurnal Nasional Ilmu Komputer Jurnal Pengabdian dan Peningkatan Mutu Masyarakat (JANAYU) Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Jurnal Penelitian Pendidikan Matematika JUSTIN (Jurnal Sistem dan Teknologi Informasi) Accounting and Finance Studies Aptekmas : Jurnal Pengabdian Kepada Masyarakat Jurnal Akuntansi INTECH (Informatika dan Teknologi)

Imelda Saluza, Imelda

Universitas Indo Global Mandiri

Author-ID : 1254373

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PENERAPAN BAURAN PEMASARAN (MARKETING MIX) SEBAGAI STRATEGI PEMASARAN PRODUK GULO PUAN DESA BANGSAL Dewi Sartika; Imelda Saluza; Roswaty Roswaty
Aptekmas Jurnal Pengabdian pada Masyarakat Vol 3 No 2 (2020): APTEKMAS Volume 3 Nomor 2 2020
Publisher : Politeknik Negeri Sriwijaya

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.

PEMANFAATAN EDUTAINMENT SEBAGAI MEDIA PEMBELAJARAN ALTERNATIF PADA RUMAH BELAJAR CERIA DESA PEDADO Dewi Sartika; Nazori Suhandi; Imelda Saluza
Aptekmas Jurnal Pengabdian pada Masyarakat Vol 4 No 3 (2021): APTEKMAS Volume 4 Nomor 3 2021
Publisher : Politeknik Negeri Sriwijaya

Rumah belajar Ceria (RBC) merupakan salah satu layanan pendidikan yang didirikan oleh orang - orang yang peduli akan pentingnya pendidikan. RBC didirikan pada tahun 2014 atas inisiatif dari 7 (tujuh) orang pemuda. RBC berlokasi di Jl. H. Sarkowi. B, Keramasan, Kec. Kertapati, Kota Palembang, Sumatera Selatan. RBC saat ini memiliki lebih dari 150 peserta didik yang merupakan anak-anak, dimulai dari kelas 1 SD sampai dengan SMP. Kegiatan yang dilakukan berupa kegiatan pembelajaran non formal yang diberikan oleh tutor kepada peserta didik secara berkala seminggu satu kali dengan teknik kooperatif, yaitu mengelompokkan siswa berdasarkan jenjang pendidikannya. Sedangkan media pembelajaran yang digunakan oleh tutor RBC merupakan media konvensional. Hal ini tentunya belum sejalan dengan perkembangan teknologi serta menyebabkan interaksi antara tutor dan peserta didik kurang terbangun. Edutainment merupakan konsep penggabungan pembelajaran dan hiburan. Edutainment mampu dimanfaatkan sebagai media pembelajaran alternatif yang menarik dan menyenangkan. Oleh karena itu, tim pelaksana memberikan penyuluhan serta demo langsung pemanfaatan edutainment dalam proses belajar dan mengajar. Berdasarkan hasil analisis yang diperoleh melalui pra test dan post test diperoleh bahwa terdapat peningkatan pemahaman peserta didik setelah melakukan proses belajar dengan media edutainment. Semula hanya 14,28% dari 42 peserta didik yang mampu menjawab 10 soal dengan benar dan 16,67% masih belum bisa menjawab 1 soal pun dengan benar, namun setelah kegiatan sebanyak 23,81% dari 42 peserta didik mampu menjawab 10 soal dengan benar dan tidak ada lagi peserta didik yang tidak dapat menjawab semua soal.

BPNN's Empirical Analysis of Daily Rupiah Exchange Rate Volatility Utilizing Hidden Neuron Optimization Imelda Saluza; Faradillah; Leriza Anggraini
Jurnal AKSI (Akuntansi dan Sistem Informasi) Vol. 7 No. 1 (2022)
Publisher : Politeknik Negeri Madiun

Show Abstract | Download Original | Original Source | Check in Google Scholar

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 Imelda Saluza
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 18 No. 02 (2017): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

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.

Optimalisasi Klasifikasi Kanker Payudara Menggunakan Forward Selection pada Naive Bayes Lastri Widya Astuti; Imelda Saluza; Faradilla Faradilla; M. Fadhiel Alie
Jurnal Informatika Global Vol 11, No 2
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jiig.v11i2.1235

Breast cancer is a type of malignant tumor which is still the number one killer where the process of spread or metastasis takes a long time. The number of breast cancer sufferers increases every year so that if detected or caught early, prevention can be done early so as to reduce the number of breast cancer sufferers. To reduce the risk of increasing the number of cancer patients, it is necessary to do early detection, several methods can be used to assist the early detection process such as cancer screening, or computational methods. Several machine learning methods that have been chosen to solve cases of breast cancer prediction, especially the classification algorithm, including Naive Bayes have the advantage of being simple but having high accuracy even though they use little data. Weaknesses in Naive Bayes, namely the prediction of the probability result is not running optimally and the lack of selection of relevant features to the classification so that the accuracy is low. This research is intended to build a classification system for detecting breast cancer using the Naive Bayes method, by adding a forward selection method for feature selection from the many features that exist in breast cancer data, because not all features are features that can be used in the classification process. The result of combining the Naive Bayes method and the forward selection method in feature selection can increase the accuracy value of 96.49% detection of breast cancer patients.

Feature Selection Menggunakan Binary Wheal Optimizaton Algorithm (BWOA) pada Klasifikasi Penyakit Diabetes Lastri Widya Astuti; Imelda Saluza; Evi Yulianti; Dhamayanti Dhamayanti
Jurnal Informatika Global Vol 13, No 1
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jiig.v13i1.2057

Diabetes Mellitus (DM) is a chronic disease characterized by blood glucose (blood sugar) levels exceeding normal, i.e. blood sugar levels being equal to or more than 200 mg/dl, and fasting blood sugar levels being above or equal to 126 mg/dl. The increase in the number of people with diabetes is due to delays in detection. Utilization of machine learning in helping to establish a fast and accurate diagnosis is one of the efforts made in the health sector. One of the important steps to produce high classification accuracy is through the selection of relevant features. The problem in feature selection is dimensionality reduction, where initially all attributes are required to obtain maximum accuracy while not all features are used in the classification process. This study uses the Binary wheal Optimization Algorithm (BWOA) as a feature selection method to increase accuracy in the classification of diabetes mellitus. The use of metaheuristic algorithms is an alternative to increase computational efficiency and avoid local minimums. The BWOA algorithm reduces the 8 attributes in the dataset to the 3 best attributes that are able to represent the original dataset. The results showed that from the six classification methods tested, namely: K-NN, Naïve Bayes, Random Forest, Logistics Regression, Decision Tree, Neural Network. then the three logistic regression methods, naive Bayes and neural network are in good classification criteria based on Area Under Curve (AUC) while the calculation of the accuracy value shows an average of above 70%. Keywords : Feature Selection, Classification, Diabetes Mellitus, Accuracy, Area Under Curve (AUC)

Prediksi Data Time Series Harga Penutupan Saham Menggunakan Model Box Jenkins ARIMA Imelda Saluza; Dewi Sartika; Lastri Widya Astuti; Faradillah Faradillah; Leriza Desitama; Endah Dewi Purnamasari
Jurnal Informatika Global Vol 12, No 2
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jiig.v12i2.1940

The ability to predict time series data on closing market prices is critical in determining a company's stock results. The development of an efficient stock market has a positive correlation with economic growth, in a country both in the short and long term. In practice, investors tend to invest in countries that have a stable economy, low crime. The rise and fall of stock prices has made many investors develop various effective strategies in predicting stock prices in the future with the aim of making investment decisions so that investors can guarantee their profits and minimize risk.As a result, the researchers developed a model that could accurately estimate precision. Time series data models are one of the most powerful methods to render assumptions in decisions containing uncertainty. The AutoRegressive Integrated Moving Average (ARIMA) model with the Box Jenskins time series procedure is one of the most commonly used prediction models for time series results. The steps for using the Box Jenskins ARIMA model for historical details of expected stock closing prices are outlined in this paper. BBYB and YELO stock data from yahoo.finance were used as historical data. The Aikake Information Criterion (AIC), Bayesian Information Criterion (BIC) / Schawrz Bayesia Criterion (SBC), Log Probability, and Root Mean Square Error (RMSE) are used to choose an effective model, and the model chosen is ARIMA (1 , 1,2). The findings suggest that the Jenkins ARIMA box model has a lot of scope for short-term forecasting, which may help investors make better decisions. Keywords: prediction, the stock's current closing price, Box Jenskins ARIMA model

Optimisasi Backpropagation Neural Network dalam Memprediksi IHSG Hartati Hartati; Alpin Herman Saputra; Imelda Saluza
Jurnal Informatika Global Vol 13, No 1
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jiig.v13i1.2066

Covid-19 has become a global epidemic and has spread to many countries in the world, including Indonesia. The COVID-19 pandemic is one source of uncertainty that causes financial data to fluctuate and cause data to be volatile. This outbreak had an impact on financial data, not only on the Rupiah exchange rate but also on the Jakarta Composite Index (JCI). The uncertainty of the JCI makes it difficult for investors, data managers, and business people to predict data for the future. JCI is one indicator of the capital market (stock exchange). The uncertainty of the JCI data causes the need for predictions, so that investors, data managers, and business people can make the right decisions so that they can reduce risk and optimize profits when investing. One of the factors causing the JCI's decline was sentiment caused by investor panic over the rapid spread of COVID-19 in various cities in Indonesia. This research uses Backpropagation Neural Network (BPNN) in making predictions and continues with optimization of BPNN using ensemble techniques. Historical data from the JCI used were obtained from yahoo.finance. The ensemble technique used consists of two approaches, namely combining different architectures and initial weights with the same data and combining different architectures and weights. The results of network performance using ensemble technique optimization show good performance and can outperform the individual network performance of BPNN. Keywords: prediction, JCI, Optimization, BPNN, volatile

Analisis Evaluasi Keberlanjutan E-Filling di Kota Palembang Dewi Sartika; Imelda Saluza
Jurnal Informatika Global Vol 9, No 2
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

AbstractDJP continues to optimize the collection of tax returns by facilitating a technology-based tax service system, one of which is e-filing that has been running since 2016. However, e-filing turned out to have less influence on the delivery of Tax Returns (SPT) as reflected in the electronic SPT monitoring data that only met 78% of the 2017 target. This is caused by various problems that arise during the use of e-filing such as individual technology capabilities, loss of efin, forgetting DJP Online account passwords to lack of awareness about the importance of submitting SPT. Problems encounter during the use of e-filing are the basis for evaluating the continued use of e-filling in Palembang. The development of a conceptual model was conducted to evaluate the sustainability of the use of e-filing. The development of a conceptual model basically has a scarcity of supporting theories used and has a complex model. To overcome this problem, Partial Least Squares (PLS) Structural Equation Model (SEM) could be applied to. The results of data analysis found that information quality and service quality did not have a positive influence on the sustainability of the use of e-filing and the level of correlation between information quality, system quality, service quality, and individual ability was still small towards the sustainability of the use of e-filing. The findings of this research are very important for the KPP Pratama in Palembang to analyze the sustainability of the use of e-filing that has been proven empirically, multidimensional and in a specific context. This knowledge could be used as a reference to improve overall quality of taxation for the sake of sustainable use of e-filing.Keywords : SPT, e-filing, PLS SEMAbstrakDJP terus berupaya mengoptimalkan pengumpulan Surat Pemberitahuan Tahunan (SPT) pajak dengan memfasilitasi sistem pelayanan perpajakan berbasis teknologi, salah satunya adalah e-filing yang telah berjalan sejak tahun 2016. Namun, e-filing ternyata kurang berpengaruh terhadap penyampaian SPT yang tergambar pada data hasil monitoring SPT elektronik yang hanya memenuhi 78% dari target sasaran tahun 2017. Hal ini disebabkan oleh berbagai masalah yang muncul selama pemanfaatan e-filing seperti kemampuan teknologi individu, kehilangan efin, lupa password akun DJP Online hingga kurangnya kesadaran tentang pentingnya penyampaian SPT. Permasalahan selama penggunaan e-filing menjadi dasar untuk melakukan evaluasi terhadap keberlangsungan penggunaan e-filling di Palembang. Pengembangan model konseptual dilakukan untuk mengevaluasi keberlanjutan penggunaan e-filing. Pengembangan model konseptual pada dasarnya memiliki kelangkaan teori-teori pendukung yang digunakan dan memiliki model yang kompleks. Untuk mengatasi masalah ini dapat menggunakan Partial Least Squares (PLS) Structural Equation Model (SEM). Hasil analisis data mendapatkan temuan bahwa kualitas informasi dan kualitas layanan tidak memiliki pengaruh positif terhadap keberlanjutan penggunaan e-filing dan tingkat korelasi antara kualitas informasi, kualitas system, kualitas layanan, dan kemampuan individual masih kecil terhadap keberlanjutan penggunaan e-filing. Temuan peneliti ini sangat penting bagi pihak KPP Pratama kota Palembang untuk menganalisa keberlanjutan penggunaan e-filing yang telah dibuktikan secara empiris, multidimensional dan konteks yang spesifik. Pengetahuan ini dapat dapat menjadi acuan untuk meningkatkan kualitas secara keseluruhan demi keberlanjutan penggunaan e-filing.Kata kunci : SPT, e-filing, PLS SEM,

Pendampingan Peningkatan Manajemen Mutu ISO 9001:2015 di Badan Pengelola Pajak Daerah Kabupaten Ogan Komering Ilir Leriza Anggraini; Endah Purnamasari; Faradillah Fadhillah; Lastri Astuti; Imelda Saluza
DIKEMAS (Jurnal Pengabdian Kepada Masyarakat) Vol 5 No 2 (2021)
Publisher : Politeknik Negeri Madiun

Show Abstract | Download Original | Original Source | Check in Google Scholar

Badan Pengelola Pajak Daerah (BPPD) merupakan unsur pelaksana urusan penunjang keuangan sub pengelolaan pajak daerah yang melayani pengelolaan penerimaan pajak dan retribusi daerah. BPPD melaksanakan tugas pembantuan dibidang pendapatan daerah. Kabupaten Ogan Komering Ilir (OKI) memiliki potensi yang besar penerimaan pendapatan salah satunya melalui pajak dan retribusi daerah. BPPD OKI sebagai instansi pelayanan yang melayani masyarakat langsung harus memiliki sistem manajemen mutu yang memadai serta dapat diimplementasikan dengan baik guna meningkatkan pelayanan publik yang diharapkan dapat meningkatkan pendapatan daerah Kabupaten OKI. Sistem manajemen mutu memiliki standar dalam implementasinya. Salah satu nya diatur dalam ISO. Implementasi ISO 9001:2015 diharapkan menjadi salah satu cara peningkatan produktivitas. Guna meningkatkan kepercayaan dan jaminan kualitas pelayanan yang diberikan sehingga perlu peningkatan efisiensi proses, biaya, kepuasan konsumen. Pendampingan ini diberikan untuk memberikan pemahaman kepada pegawai beserta staff mengenai implementasi ISO 9001:2015 khususnya sistem manajemen mutu. Pentingnya sistem manajemen mutu dalam pelaksanaan pelayanan maupun non pelayanan pada BPPD dapat meningkatkan pendapatan badan maupun kabupaten.

Co-Authors , Hartati Abdul Aziz Zulfikar Agustina Heryati Ahmad Sanmorino Akbar, Muhamad Hafiz Alie, Muhammad Fadhiel Alpin Herman Saputra Andini Utari Putri Anggraini, Leriza Desitama Anjani, Fia Sakina Antoni, Darius Ariati, Nining Aulia, Beta Bagus Setiawan Bobby Halim Cyndika Dewi Sartika DEWI SARTIKA Dewi Sartika Dewi Sartika Dhamayanti Dhamayanti Dhamayanti Dhamayanti Dhamayanti Dhamayanti, Dhamayanti Eko Nugroho, Muhammad Davidio Endah Dewi Purnamasari Endah Purnamasari Endah Puspita Sari Ensiwi Munarsih, Ensiwi Eva Susanti Evi Yulianti EVI YULIANTI Faradilla Faradilla Faradillah , Faradillah Faradillah Faradillah Faradillah, Faradillah Fattah, Hussein HARTATI Hartati Hartati Hartati Hartati Hatika Hatika, Hatika Heryati , Agustina Heryati*, Agustina Husnawati Husnawati Iisnawati, Iisnawati Indah Permata Sari Indah Permatasari Indah Permatasari Indah Permatasari Indah, Sylvia Uly Kesuma, Hendra Di Lastri Astuti Lastri Widya Astuti Lastri Widya Astuti Lastri Widya Astuti, Lastri Widya Leriza Anggraini M. Fadhiel Alie Marcelina, Dona Marcellina, Dona Maya Amelia Mohammad Taufikurrahman Muhammad Fadhiel Alie Muhammad Haviz Irfani Nazori Suhandi Nining Nova Yanti Maleha Patriansah, Mukhsin Pratiwi, Indah Putri Putri, Hilda Muslia Putri, Indah Pratiwi Ramadhan, Mustafa Rini Yunita, Rini Roswaty Roswaty Roswaty Roswaty Roswaty Roswaty Roswaty Roswaty, Roswaty Rudi Heriansyah Rudi Heriansyah, Rudi Sartika, Dewi Sinta Habibah Sunardi, Hastha Suryati Syachrul Haq, Muhammad Raka Syahrul Haq, Muhammad Raka Teguh Teguh Wulandari, Try Yulianti, Evi Yulius, Yosef Zulfikar, Abdul Aziz

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