Garuda - Garba Rujukan Digital

Pengembangan Expert Advisor Berbasis Indikator Moving Average dan Relative Strength Index dalam Trading Kripto Romadhoni, Alvian Nur; Kusanti, Jani; Baradja, Abdillah
Jurnal Pustaka Robot Sister (Jurnal Pusat Akses Kajian Robotika, Sistem Tertanam, dan Sistem Terdistribusi) Vol 3 No 2 (2025): Jurnal Pustaka Robot Sister (Pusat Akses Kajian Robotika, Sistem Tertanam, dan Si
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakarobotsister.v3i2.1036

Perkembangan teknologi dalam dunia digital trading telah mendorong penggunaan Expert Advisor (EA) untuk meningkatkan efisiensi dan objektivitas dalam pengambilan keputusan trading. Penelitian ini bertujuan untuk merancang dan mengembangkan EA berbasis indikator Moving Average (MA) dan Relative Strength Index (RSI) serta mengevaluasi performanya melalui backtesting pada platform TradingView. MA digunakan untuk mengidentifikasi arah tren sementara RSI digunakan untuk mendeteksi kondisi overbought, oversold dan konsolidasi. Pengujian dilakukan pada empat sampel instrumen trading, yaitu dua aset crypto (BTCUSDT dan ETHUSDT) dan dua pasangan mata uang forex (EURUSD dan USDJPY), menggunakan timeframe 1 jam dengan rentang data historis dari tahun 2021 hingga 2025. Strategi trading yang diimplementasikan pada EA ini mengikuti arah tren utama dengan aturan beli memperhatikan konfirmasi dari sinyal MA dan RSI. Penelitian Expert Advisor (EA) berhasil dikembangkan menggunakan bahasa Pine Script v5 di TradingView. Strategi yang digunakan adalah memicu sinyal beli saat RSI melakukan crossover ke atas level 50 dan harga berada di atas garis MA, dengan eksekusi entry yang disertai Take Profit (10%) dan Stop Loss (1%). Backtest menunjukkan performa terbaik pada instrumen crypto (BTCUSDT dan ETHUSDT). BTCUSDT menghasilkan profit bersih 833,01 USD (166,60%) dengan drawdown 34,92%, sementara ETHUSDT mencatat profit bersih 703,26 USD (140,65%) dengan drawdown 37,52%. Hal ini menunjukkan bahwa EA sangat responsif terhadap instrumen dengan volatilitas tinggi.

Identifikasi Kerusakan Dini Otomatis Komponen Elektronika Berbasis Arus Dengan Mikrokontrol Arduino Uno Rianto, Agus; Kusanti, Jani
Jurnal FORTECH Vol. 4 No. 2 (2023): Jurnal FORTECH
Publisher : FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56795/fortech.v4i2.4206

Electric current is the flow of electricity in an electronic circuit where the amount flows through the circuit. The greater the current flowing in the circuit, the greater the value in amperes. The components in electronic circuits always have an electric current flowing through them. The electric current in this component is the basis for knowing whether the component is in good condition or not. On this basis, researchers use current sensors to detect damage to electronic components. In designing DC Current Based Early Damage Identification of Electronic Components with Text Notifications on the LCD using the Arduino UNO microcontroller, the current sensor is used, namely the ACS 712 current sensor. This Electronic Component Early Damage Identification Tool works automatically, the system will provide automatic error information via notifications on the LCD and the system will stop itself if one of the components is damaged. With this tool, Early Damage Identification of Electronic Components Based on DC Current with Text Notification on the LCD using the Arduino UNO microcontroller will make repairs easier and faster if one of the components is damaged. Because the notification on the LCD will notify you of damage to the damaged component

Location Aware Machine Learning Models for Predicting Online Sales of MSMEs: A Case Study from Indonesia Widiastuti, Erni; Kusanti, Jani; Agustiwi, Asri; Susilowardani, Susilowardani
Jurnal Manajemen, Akuntansi, Ekonomi Vol. 4 No. 2 (2025): Jurnal Manajemen, Akuntansi, Ekonomi (September)
Publisher : CV. Era Digital Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59066/jmae.v4i2.1556

The rapid growth of e-commerce in emerging economies presents new opportunities for Micro, Small, and Medium Enterprises (MSMEs). However, the main problem lies in the difficulty of accurately predicting online sales across regions with heterogeneous socioeconomic and infrastructural conditions, which often leads to inefficient resource allocation and missed market potential. This study aims to develop a location-aware predictive framework that integrates spatial intelligence into machine learning models for forecasting MSME online sales in Indonesia. The proposed model adopts a two-stage approach that combines XGBoost regression with spatial lag features, allowing the model to capture both local demand drivers and inter-regional dependencies. The datasets include historical e-commerce transactions, demographic indicators, infrastructure accessibility, and socioeconomic profiles aggregated at the regional level. To ensure robustness, spatial-temporal cross-validation is applied, and model performance is evaluated using RMSE, MAE, and MAPE. The results show that the location-aware model outperforms baseline approaches, reducing forecasting errors by up to 18% and identifying high-potential sales regions more effectively. Explainability analysis further highlights population density, regional income, and proximity to logistics hubs as key predictors. Future work will focus on extending the framework with deep learning and graphbased models to capture dynamic spatio-temporal interactions, as well as integrating real-time data streams for adaptive sales forecasting.

Sistem Informasi Pengawasan Aset di Dinas Pendidikan Kota Surakarta untuk Meningkatkan Efisiensi dan Transparansi Arif Nur Utomo, Dwi; Rianto, Agus; Kusanti, Jani
Nucleus Journal Vol. 3 No. 2 (2024): November
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32492/nucleus.v3i2.3204

Asset monitoring at the Surakarta City Department of Education is still carried out manually by visiting all related institutions that receive financial aid. This activity is conducted daily every year and consumes a significant amount of labor, time, and costs, potentially leading to inefficiencies, data recording errors, and a lack of transparency in the asset reporting and monitoring processes. These issues can hinder decision-making processes related to asset management and reduce the accountability of relevant parties. This research aims to develop a web-based Asset Monitoring Information System using PHP and MySQL to enhance efficiency and transparency in asset management. The system development method used is the System Development Life Cycle (SDLC), which includes the stages of planning, needs analysis, design, implementation, and system testing. The results of this research show that the developed system can accelerate the asset management process, minimize data errors, and improve the accessibility and transparency of asset reporting. The system also facilitates real-time asset monitoring and simplifies the validation process by authorized personnel. The designed system is expected to improve operational efficiency and accountability in asset monitoring at the Surakarta City Department of Education.

Pemanfaatan Teknologi E-Commerce Dalam Memperkuat Orientasi Kewirausahaan Dan Customer Relationship Management Terhadap Kinerja Umkm Di Surakarta Sudalyo, Ramadhian Agus Triono; Prasetyaningrum, Nurita Elfani; Kusanti, Jani
GEMA EKONOMI Vol 11 No 1 (2022): GEMA EKONOMI
Publisher : Fakultas Ekonomi Universitas Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55129/https://doi.org/10.55129/.v12i4.2927

Penelitian bertujuan untuk menganaisis pengaruh pemanfaatan teknologi e-commerce sebagai variabel pemoderasi dalam memperkuat pengaruh orientasi kewirausahaan dan Customer Relationship Management terhadap kinerja UMKM di Surakarta. Penelitian ini menggunakan sampel 127 UMKM di Surakarta yang telah memanfaatkan e-commerce. Metode penelitian adalah deskriptif kuantitatif. Teknik pengumpulan data menggunakan kuesioner tertutup. Teknik analisis data menggunakan analisis regresi linier berganda dan uji selisih mutlak. Hasil penelitian menunjukkan bahwa (1) Orientasi kewirausahaan tidak berpengaruh signifikan terhadap kinerja UMKM di Surakarta. (2) Customer Relationship Management berpengaruh signifikan terhadap kinerja UMKM di Surakarta. (3) Pemanfaatan teknologi e-commerce terbukti sebagai variabel moderating yang dapat memperkuat pengaruh orientasi kewirausahaan dan customer relationship management terhadap kinerja UMKM di Surakarta.

Radio Broadcasting Innovation Management, Digital Technology Enhances Excellence Radio Business Performance Elfani Prasetyaningrum, Nurita; Agus Triono Sudalyo, Ramadhian; Kusanti, Jani
GEMA EKONOMI Vol 12 No 1 (2023): GEMA EKONOMI
Publisher : Fakultas Ekonomi Universitas Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55129/https://doi.org/10.55129/.v12i4.2927

Development is carried out by mapping based on the potential of each district. However, the potential of its natural resources has not been optimally explored for industrial opportunities due to the absence of supporting maintenance. The results show that most of the potential is in its natural resources. Market opportunities usually meet the interests of individuals, such as brokers who create the largest profit margins. On the other hand, the craft community collects very minimal profits. In fact, human resources have enormous potential but become a problem when there is no regeneration of the younger generation. In addition, corporate institutional factors are needed to increase the potential bargaining position of the d

Optimasi Klasifikasi Parasit Malaria Dengan Metode LVQ, SVM dan Backpropagation Kusanti, Jani; Irianto Tjendrowarsono, Tri
Infotekmesin Vol 12 No 1 (2021): Infotekmesin: Januari 2021
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v12i1.483

The use of the classification method affects the accuracy of the test results. The accuracy of the classification method is affected by the number of classes in the image. The number of classes and the amount of data should be considered when making decisions in choosing a classification method. This study used 600 data, which were divided into 510 training data and 90 test data. The number of classes tested is 12 classes with the number of initial features used by 22 features. The characteristics used in the test consist of shape characteristics and texture characteristics. The classification methods used in this study are LVQ, Backpropagation, and SVM. The data has 22 features or attributes that are the result of texture and shape feature extraction. Texture features are energy 0o, energy 45o, energy 90o, energy 135o, entropy 0o, entropy 45o, entropy 90o, entropy 135o, contrast 0o, contrast 45o, contrast 90o, contrast 135o, homogeneity 00, homogeneity 45o, homogeneity 90o, homogeneity 135o, correlation 0o, Correlation 45o, correlation 90o, correlation 135o, features of Ã¡rea and perimeter shape. The test results using the Backpropagation method obtained 89.7% results, using the LVQ method obtained 77.78% results, and the SVM method obtained 99.1% results.

Perancangan Monitoring Limbah Air Sungai Bengawan Solo di Kalurahan Sewu Rianto, Agus; Kusanti, Jani; Agus Triono Sudalyo, Ramadhian
Jurnal Pengabdian Masyarakat Universitas Darul Ulum Vol 2 No 2 (2023): DIMAS-UNDAR
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32492/dimas-undar.v2i2.2205

Limbah merupakan bahan pembuangan yang di hasilkan dari suatu proses produksi, baik industri maupun domestik (rumah tangga). Keberadaannya limbah sering tidak dikehendaki dan mengganggu lingkungan, karena limbah dipandang tidak memiliki nilai ekonomis khususnya limbah industri berasal dari kegiatan industri. Air limbah khususnya yang ada sekitar kota solo perlu adanya pemantauan secara dini dan rutin karena di kota solo banyak industri yang banyak menghasilkan limbah air yang langsung dibuang di sungai seperti industri tekstil. Limbah air khususnya yang ada di sungai tidak dikelola dengan baik akan merugikan masyarakat yang tinggal di sekitar sungai. Dalam perancangan alat deteksi dini dan monitoring limbah air sungai sensor yang digunakan yaitu menggunakan modul PH-4502C dengan sensor pH Elektroda BNC E-201C. Sensor ini akan mendeteksi kandungan kadar air sungai berupa nilai pH. Sedangkan untuk memonitor limbah air dengan realtime berbasis IoT pemberitahuan terjadi limbah air yang mengkawatirkan dan informasi limbah air berupa nilai pH dapat dimonitor secara real time yang dapat diaksses secara online. Untuk memonitor nilai pH secara real time menggunakan aplikasi open source Thingspeak. Data nilai pH selama terhubung dengan internet data nya akan tersimpan otomatis di Thingspeak. Tujuan dalam penelitian ini yaitu perancangan alat yang menghasilkan alat deteksi dini dan monitoring limbah air sungai berbasis IoT dengan alat ini maka akan terbantu informasi dini mengenai limbah air yang mengalir di sungai sehingga bisa diantisipasi sejak dini.

Identifikasi Kerusakan Dini Otomatis Komponen Elektronika Berbasis Arus Dengan Mikrokontrol Arduino Uno Rianto, Agus; Kusanti, Jani
Jurnal FORTECH Vol. 4 No. 2 (2023): Jurnal FORTECH
Publisher : FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56795/fortech.v4i2.4206

Electric current is the flow of electricity in an electronic circuit where the amount flows through the circuit. The greater the current flowing in the circuit, the greater the value in amperes. The components in electronic circuits always have an electric current flowing through them. The electric current in this component is the basis for knowing whether the component is in good condition or not. On this basis, researchers use current sensors to detect damage to electronic components. In designing DC Current Based Early Damage Identification of Electronic Components with Text Notifications on the LCD using the Arduino UNO microcontroller, the current sensor is used, namely the ACS 712 current sensor. This Electronic Component Early Damage Identification Tool works automatically, the system will provide automatic error information via notifications on the LCD and the system will stop itself if one of the components is damaged. With this tool, Early Damage Identification of Electronic Components Based on DC Current with Text Notification on the LCD using the Arduino UNO microcontroller will make repairs easier and faster if one of the components is damaged. Because the notification on the LCD will notify you of damage to the damaged component

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