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All Journal Jurnal Ilmiah Matrik Aksi Kita: Jurnal Pengabdian Kepada Masyarakat Jurnal Informatika Dan Tekonologi Komputer
Wydyanto Wydyanto
Universitas Bina Darma
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Environmental Science Social Sciences Other

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RANCANG BANGUN ALAT DETEKSI KEHADIRAN ORANG Deni Erlansyah; Wydyanto Wydyanto
Jurnal Ilmiah Matrik Vol 18 No 2 (2016): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (539.909 KB) | DOI: 10.33557/jurnalmatrik.v18i2.408

Abstract

Currently criminality condition has been greatly improved. This is due to lack of employment and the high prices of daily necessities that impact on increasing crime rate. Crime is not just happening on the streets, but also in housing. Many homes are visited by people who are not responsible, who then takes the valuables. This situation requires us to be more careful so as reduce the level of crime that occurs in housing projects. The solution is that we can create a tool that can detect the presence of people who do not want. How the tool works based microcontroller are as follows: 1) If there is a presence of people, then the sensor the presence of people going to work, 2) the sensor will send writing (text) to mobile phones via Bluetooth, 3) the sensor will also enable the system alarms.
Pelatihan Perancangan Prototipe UI/UX Pengelolaan Data pada Dinas PU PSDA Sumatera Selatan Maria Ulfa; Evi Yulianingsih; Wydyanto Wydyanto; Dinny Komalasari; Dio Ramadani
Aksi Kita: Jurnal Pengabdian kepada Masyarakat Vol. 2 No. 3 (2026): MEI-JUNI
Publisher : Indo Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63822/vc2yw558

Abstract

Sumatera Selatan masih mengandalkan berkas fisik, lembar kerja, dokumen perkantoran, dan folder komputer yang belum terhubung. Kondisi tersebut mempersulit pencarian, pembaruan, pengendalian versi, pengarsipan, serta penyusunan laporan. Kegiatan pengabdian melalui program magang MBKM ini bertujuan menghasilkan prototipe UI/UX website pengelolaan data yang berpusat pada kebutuhan pengguna. Pelaksanaan berlangsung pada 13 April–19 Juni 2026 dengan pendekatan Design Thinking yang mencakup empathize, define, ideate, prototype, dan testing. Data kebutuhan diperoleh melalui observasi proses kerja, wawancara informal dengan staf, pemetaan peran, serta identifikasi kebutuhan fungsional. Rancangan dikembangkan menggunakan Figma dan ditinjau secara formatif bersama pihak instansi. Kegiatan menghasilkan pemetaan empat peran pengguna, sepuluh kebutuhan fungsional, dan empat belas layar utama yang mencakup login, dashboard, pengelolaan data infrastruktur, peta persebaran aset, arsip dokumen, rekapitulasi, pelaporan, manajemen pengguna, dan profil akun. Peninjauan awal menunjukkan bahwa struktur menu dan alur informasi dapat dipahami oleh staf, meskipun pengujian usability kuantitatif belum dilakukan. Prototipe ini menjadi acuan visual dan fungsional bagi pengembangan sistem terintegrasi serta mendukung penataan data sektoral yang lebih konsisten, mudah ditelusuri, dan sesuai pembagian kewenangan.
Penerapan Algoritma Logistic Regression Untuk Memprediksi Penyakit Jantung Muhammad Fitra Rhomadon; Wydyanto Wydyanto; A. Haidar Mirza; Nurul Huda
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 5 No. 3 (2025): November : Jurnal Informatika dan Tekonologi Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v5i3.8105

Abstract

Heart disease is one of the leading causes of death worldwide, including in Indonesia. Early detection of heart disease risk is crucial to prevent more severe complications and improve patients' quality of life. This study aims to apply the Logistic Regression algorithm to build a data-driven heart disease prediction model. The dataset used is from Kaggle, with 1,025 patient data and 14 attributes covering risk factors such as age, gender, blood pressure, cholesterol, maximum heart rate, and others. The research process was conducted using the CRISP-DM approach, which includes business understanding, data exploration, preprocessing, modeling, evaluation, and model testing. The preprocessing stage includes data cleaning, encoding categorical variables, standardizing numeric data, and dividing the data into training and test data. The model was developed using the Python programming language and the scikit-learn library, then evaluated using metrics such as accuracy, precision, recall, F1-score, confusion matrix, and ROC-AUC. The evaluation results showed that the Logistic Regression model was able to provide good prediction results, with an accuracy of 0.93, a precision of 0.93, a recall of 0.96, and an F1-score of 0.95. With this performance, this model can be used as a tool for medical personnel in early detection of heart disease risk and supporting more effective and efficient decision-making.
Sistem Pendukung Keputusan Rekomendasi Organisasi Untuk Mahasiswa di Universitas Bina Darma Menggunakan Metode Simple Additive Weighting (SAW) M. Denny Tri Lisandi; M. Soekarno Putra; Syahril Rizal; Wydyanto Wydyanto
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 5 No. 3 (2025): November : Jurnal Informatika dan Tekonologi Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v5i3.8361

Abstract

This research was conducted to develop a web-based Decision Support System (DSS) to provide student organization recommendations at Universitas Bina Darma. The Simple Additive Weighting (SAW) method was used to evaluate compatibility based on students’ interests, talents, and preferences. The K-Nearest Neighbor (KNN) algorithm was applied to classify the SAW score results in order to determine the final recommendation. In line with its domain, the system was developed using an Agile Feature-Driven Development (FDD) approach in a gradual and iterative manner, utilizing the Laravel 12 framework. The research results showed that the system was capable of accurately recommending Student Activity Units (UKM) for first- to fourthsemester students. The recommendation process was carried out by combining the SAW method to obtain the top three UKM and the KNN algorithm for final classification when students chose to participate in only one UKM that best matched their historical answer patterns.
Co-Authors A. Haidar Mirza Deni Erlansyah DINNY KOMALASARI Dio Ramadani Evi Yulianingsih M. Denny Tri Lisandi M. Soekarno Putra Maria Ulfa Muhammad Fitra Rhomadon Nurul Huda Syahril Rizal