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All Journal Jurnal Minfo Polgan (JMP) Jurnal Informatika dan Komputer (JIK) Jurnal Sistem Informasi Mahakarya (JSIM) Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer
Rusidi
Universitas Mahakarya Asia
Computer Science & IT Library & Information Science Mathematics Social Sciences

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Membangun Alat Deteksi Penggunaan Masker Menggunakan Arduino Pada Layanan Penerimaan Mahasiswa Baru Universitas Mahakarya Asia Rusidi; Ristu; Defi
Jurnal Informatika dan Komputer (JIK) Vol 13 No 2 (2022): Jurnal Informatika dan Komputer (JIK)
Publisher : Universitas Mahakarya Asia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1058.623 KB)

Abstract

The Covid-19 outbreak became a global pandemic after it was announced by the WHO or the World Health Organization and with its rapid spread, Covid-19 became a major topic around the world. Indonesia is no exception because the number of people infected with the Covid-19 or corona virus is increasing day by day. The central government, entering the new normal era, has begun to open activities at schools and universities by tightening the implementation of the recommended 5M health protocol, namely washing hands with soap, wearing masks, maintaining distance, avoiding crowds and limiting mobility. This is important for the government to oblige all Indonesians to wear masks when they are outside, because the spread of Covid-19 is influenced by the high mobility of the people. Build a mask detection tool using Arduino in the new student admission service of Mahakarya Asia University. The design of this mask detection device is one of the efforts to reduce the spread of the Covid-19 virus
SISTEM INFORMASI PENDUDUK DESA TANJUNG BARU KECAMATAN BATURAJA TIMUR KABUPATEN OKU MENGGUNAKAN EMBARCADERO XE2 BERBASIS CLIENT SERVER Satria Novari; Rusidi
JSIM : Jurnal Sistem Informasi Mahakarya Vol 5 No 1 (2022): Jurnal Sistem Informasi Mahakarya (JSIM)
Publisher : LPPM universitas Mahakarya Asia

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Abstract

Kantor Desa tanjung baru merupakan salah satu instansi Pelayanan Data kependudukan yang terletak di Kabupaten Ogan Komering Ulu Kecamatan Baturaja Timur. Didalam proses pengelolahan Data Kependudukan Memiliki beberapa permasalahan yaitu, petugas data kependudukan mengalami kesulitan dalam pengolahan data kependudukan yang dimana proses pengelolahan data yang tidak mungkin lagi menggunakan cara tertulis yaitu dengan cara mencatat dalam buku besar, hal tersebut dianggap kurang efektif dan efisien. Dalam hal ini memberikan ide bagi penulis untuk membuat sistem informasi data kependudukan. Pengumpulan data dilakukan dengan cara mendatangi langsung ketempat tersebut dengan cara Interview, Observasi dan Reverensi. Software pendukung dalam pembuatan aplikasi ini adalah sistem operasi Windows 10, Microsoft Office Word 2007, XMAPP,ODBC,Embarcadero XE2 dan Database MySql. Penelitian ini menghasilkan sebuah Sistem Informasi penduduk Desa Tanjung Baru Kecamatan Baturaja Timur Kabupaten Ogan Komering Ulu berbasis Client Server menggunakan Embarcadero XE2 yang mempermudah proses pengelolahan data penduduk, data kelahiran, data kartu keluarga, data penduduk datang, data penduduk pindah, data sementara, data usaha dan beserta laporannya. Sehingga mempermudah kepala desa dan petugas kependudukan dalam pengecekan laporan dan juga menginputkan data kependudukan.
Implementasi Virtual Tour 360 sebagai Media Promosi Penjualan Properti (Studi Kasus Rumah Sehat Property Baturaja) Defi Puji Anto; Kadarsih; Rusidi
Jurnal Minfo Polgan Vol. 12 No. 1 (2023): Artikel Penelitian Juni 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v12i1.12573

Abstract

Di era teknologi yang semakin berkembang saat ini, implementasi virtual tour 360 menjadi salah satu solusi yang dapat digunakan dalam proses promosi penjualan properti. Virtual tour 360 merupakan teknologi yang memungkinkan pengguna untuk melihat tampilan 360 derajat, sehingga calon pembeli dapat melihat detail properti tersebut dari berbagai sudut tanpa harus datang langsung ke lokasi. Website ini dibuat sebagai alternatif untuk mempromosikan produk perumahan, serta untuk membantu pemasaran perumahan Rumah Sehat Baturaja dengan menggunakan teknologi Virtual Tour. Penelitian ini menggunakan Metode Multimedia Development Life Cycle (MDLC), dimana website yang dikembangkan secara bertahap sampai dihasilkan sebuah aplikasi berbasis website dengan teknologi virtual tour 360. Aplikasi Berbasis website virtual tour 360 dapat memberikan keuntungan bagi pemilik properti dalam proses pemasaran dan penjualan. Dengan adanya virtual tour, calon pembeli dapat melihat detail properti secara jelas dan lengkap tanpa harus melakukan kunjungan fisik ke lokasi. Kondisi seperti ini dapat menghemat waktu dan biaya yang dikeluarkan oleh calon pembeli dan pemilik properti. Implementasi virtual tour 360 juga dapat membantu dalam proses pemasaran dengan cara menarik perhatian calon pembeli. Berdasarkan hasil implementasi website, hasil kuesioner menunjukan bahwa, 77,5%. aplikasi berbasis website ini dapat dikategorikan sebagai media promosi yang baik. Properti Baturaja. Aplikasi berbasis web Perumahan rumah Sehat Properti Baturaja telah berhasil divisualisasikan melalui Virtual Tour 360 derajat, dan dapat diakses melalui website.
Evaluasi Komparatif Ridge, SVR, Extratrees Untuk Prediksi Konsumsi Energi Iot Smarthome Dengan lag-1 Sri Hartati; Rusidi; Erlita Sulistiati
BETRIK Vol. 16 No. 02 (2025): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/hvqebr82

Abstract

This study presents a comparative evaluation of Ridge Regression, Support Vector Regression (SVR, RBF), and ExtraTrees Regressor against a lag-1 (persistence) baseline for short-term load forecasting (STLF) of IoT smart-home energy consumption at an hourly resolution. The research is motivated by the need for accurate forecasts to enable operational efficiency, peak shaving, and residential demand response. The workflow emphasizes reproducibility: hourly resampling, short-gap imputation, minimalist feature engineering (calendar and lag features), and a time-based split of 70%/15%/15% (train/validation/test). Models are compared using MAE, RMSE, and R², prioritizing RMSE due to its sensitivity to spikes. Results show that on validation ExtraTrees performs best (RMSE 1.012, R² 0.854) and surpasses the lag-1 baseline (RMSE 1.507, R² 0.677). However, on the test set the lag-1 baseline is most accurate (RMSE 1.457, R² 0.808, MAE 0.900), while ExtraTrees is the closest yet does not surpass it (RMSE 1.482, R² 0.802, MAE 1.119). SVR and Ridge degrade markedly on test (RMSE > 2.0; R² < 0.65). These findings highlight the strength of persistence at a one-hour horizon and the need for seasonal/exogenous features and hyperparameter tuning to reduce large errors. Our practical contribution is a concise, Colab-based pipeline. Future work includes walk-forward validation, residual modeling over lag-1, adding daily/weekly lags and weather variables, and significance testing of error differences.
Explainable Predictive Analytics untuk Prediksi Pengunduran Diri Karyawan pada Data Human Resource Analytics Sri Hartati; Rusidi; Dodi Herryanto
BETRIK Vol. 17 No. 02 (2026): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/gcx9tn49

Abstract

Digital transformation has encouraged organizations to adopt Human Resource Analytics and Artificial Intelligence to support data-driven decision-making, including employee attrition prediction. Although numerous predictive models have been developed, most of them still suffer from limited interpretability, making their predictions difficult for Human Resource practitioners to understand and utilize. This study aims to develop an Explainable Predictive Analytics model for employee attrition prediction by integrating Information Gain, Random Forest, RandomizedSearchCV, and SHapley Additive exPlanations (SHAP). The study employs the IBM HR Analytics Employee Attrition & Performance dataset consisting of 1,470 employee records. The research workflow includes data preprocessing, feature selection using Information Gain, Random Forest model development, hyperparameter optimization using RandomizedSearchCV, model evaluation using Accuracy, Precision, Recall, F1-Score, and ROC-AUC, followed by model interpretation through SHAP Summary Plot and SHAP Feature Importance. The experimental results indicate that the model achieved 82.54% Accuracy, 37.50% Precision, 12.68% Recall, 18.95% F1-Score, and a ROC-AUC of 0.7439. Feature selection results indicate that OverTime has the highest Information Gain value, while MonthlyIncome is identified as the most influential feature according to Random Forest Feature Importance. The main contribution of this study is the integration of Information Gain-based feature selection, Random Forest optimization, and SHAP-based Explainable Artificial Intelligence into a unified Explainable Predictive Analytics framework, providing a more transparent and interpretable predictive model to support decision-making in Human Resource Management
ANALISIS PERILAKU PENGGUNA ATAS LAYANAN SISTEM PPDB ONLINE DI SMK NEGERI 1 TANJUNG AGUNG MENGGUNAKAN WEBQUAL 4.0 Della Hadi Sugesti; Yuanita Sinatrya; Rusidi
JSIM : Jurnal Sistem Informasi Mahakarya Vol 9 No 1 (2026): Jurnal Sistem Informasi Mahakarya (JSIM)
Publisher : LPPM universitas Mahakarya Asia

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Abstract

This study aims to analyze user behavior toward the Online Student Admission System (PPDB Online) service at SMK Negeri 1 Tanjung Agung using the WebQual 4.0 method. WebQual 4.0 is a website quality measurement instrument consisting of six dimensions: functionality, security, usability, efficiency, maintainability, and portability. This research employed a quantitative approach using a survey method by distributing questionnaires to 80 respondents comprising prospective students, current students, and parents. Sampling used Slovin's formula with simple random sampling. Data were analyzed using descriptive statistics via SPSS. Results indicate that the system falls into the good-to-very-good category overall. However, the visual appearance aspect of usability still requires improvement, as 66.3% of respondents strongly disagreed that the site looks attractive and professional. Other dimensions—functionality, security, efficiency, maintainability, and portability—received positive ratings from more than 91% of respondents. Keywords: User Behavior, PPDB Online, WebQual 4.0, Website Quality, Information System.
Co-Authors Defi Defi Puji Anto Della Hadi Sugesti Dodi Herryanto Erlita Sulistiati Kadarsih Ristu Satria Novari sri hartati Yuanita Sinatrya