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All Journal JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Paradigma Journal of Information Technology and Computer Science (JOINTECS) JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL TEKNOLOGI DAN OPEN SOURCE Informatika : Jurnal Informatika, Manajemen dan Komputer JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal ICT : Information Communication & Technology JSAI (Journal Scientific and Applied Informatics) INTI Nusa Mandiri Generation Journal JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Reswara: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika (JUTIF) Yayasan Cita Cendikiawan Al Khwarizmi Jurnal J-PEMAS Edu Cendikia: Jurnal Ilmiah Kependidikan Jurnal Pendidikan Sains dan Komputer Aptekmas : Jurnal Pengabdian Kepada Masyarakat Jurnal Puan Indonesia Jurnal Pengabdian Inovasi dan Teknologi Kepada Masyarakat Journal of Information Systems and Technology Research Internet of Things and Artificial Intelligence Journal Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Bulletin of Informatics and Data Science The Indonesian Journal of Computer Science
Budy Satria
Universitas Andalas
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PROTOTIPE KERAN AIR TANPA SENTUH DAN PENGUKUR SUHU TUBUH OTOMATIS BERBASIS MIKROKONTROLLER ARDUINO UNO Firma, Firma; Satria, Budy; Surya, Candra; Sepriano, Sepriano; Ashari, Muhammad Al; Iqbal, Muhammad
INTI Nusa Mandiri Vol. 19 No. 2 (2025): INTI Periode Februari 2025
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v19i2.6417

Abstract

The global pandemic requires the development of technological solutions to minimize physical contact, especially in public facilities such as water taps, which can function as a medium for transmitting infectious diseases. This study aims to design and develop a prototype of an automatic water tap integrated with an Arduino Uno microcontroller-based body temperature meter. This system was created to support health protocol efforts when carrying out activities, increasing efficiency and reducing the risk of disease transmission. The research method includes problem identification, literature study, hardware and software component design, prototyping, and functionality testing. The test results obtained show that all components work according to their functions with a high level of accuracy, such as the HC-SR04 ultrasonic sensor, which is able to detect objects at a distance between the object and the sensor <12cm, then the Relay will be active and the Mini Water Pump will pump water automatically, and the Valve on the Solenoid Valve will open, and water will flow automatically through the water tap. The test results on the MLX-90614 temperature sensor also obtained an average difference of only 0.28 ° C compared to the thermometer gun as a comparison.
Segmentasi Pasien Rumah Sakit Berdasarkan Pola Kunjungan Menggunakan Algoritma K-Means Clustering untuk Optimasi Layanan Medis Nengsih, Yeyi Gusla; Samosir, Khairunnisa; Satria, Budy
Jurnal Pendidikan Sains dan Komputer Vol. 5 No. 01 (2025): Call for Papers February 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jpsk.v5i01.5492

Abstract

Rumah sakit menghadapi tantangan dalam mengelola arus pasien yang beragam, baik dari segi waktu kunjungan, frekuensi kedatangan, hingga jenis layanan yang dibutuhkan. Penelitian ini bertujuan untuk melakukan segmentasi pasien berdasarkan pola kunjungan menggunakan algoritma K-Means, guna mengoptimalkan layanan medis dan meningkatkan efisiensi operasional rumah sakit. Data yang digunakan mencakup informasi Umur, Jenis Kelamin, Jumlah Kunjungan (per tahun), Durasi Kunjungan, Jenis Perawatan, Diagnosa Utama. Dalam penelitian ini penulis menggunakan K-Means Clustering. Metode K-Means Clustering adalah salah satu teknik dalam analisis data yang digunakan untuk mengelompokkan data ke dalam beberapa kelompok atau cluster berdasarkan kesamaan atau kedekatan atribut atau karakteristik data tersebut. Sedangkan untuk membantu pengolahan data agar lebih cepat dan efesien penulis menggunakan aplikasi Rapidminer. Hasil penelitian menunjukkan bahwa pasien dapat dikategorikan ke dalam 3 (Tiga) cluster, seperti penyakit kronis yaitu cluster_2 yang terdapat 4 variabel data, pasien dengan dengan kunjungan secara rutin yaitu cluster_1 yang terdapat 6 variabel data, dan pasien dengan kategori isidental yaitu cluster_2 terdapat 10 variabel data. Dari hasil segmentasi ini, rumah sakit dapat mengambil langkah strategis, seperti penjadwalan dokter yang lebih efektif, optimalisasi sumber daya medis, serta pengelolaan antrian yang lebih baik. Dengan pendekatan ini, rumah sakit dapat meningkatkan kepuasan pasien, mengurangi waktu tunggu, serta mengalokasikan tenaga medis dan fasilitas dengan lebih efisien.
DESIGN OF FIRE EXTINGUISHER ROBOT USING IOT WITH ANDROID APPLICATION CONTROL Budy Satria; Syarif Hidayatullah; Fitra Yuda; Leonard Tambunan; Siti Sahara Lubis; Irzon Meiditra
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 3 (2025): JITK Issue February 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i3.6135

Abstract

Fire is an unsupervised incidental disaster. This disaster has a detrimental impact on living and non-living things in the surrounding environment. This study was conducted to design an intelligent firefighting robot using Arduino Mega 2560 and Android-based IoT technology. This firefighting robot uses several Node MCU ESP8266 components as additional devices to connect to wifi. The L298N module regulates the speed and direction of the DC motor rotation, followed by the L9110 fan as hardware to extinguish the fire. The mobile robot prototype uses a DC motor as its driver. In addition, an Android application has been programmed to control the firefighting robot. This application has features that allow the robot to move in various directions and adjust the fan speed when extinguishing fires, all through an internet network connection. The study results showed that the application can be connected within a distance of 1-8 meters with good network quality. The test results showed that at a distance of 1-28 cm, the fan worked very well according to its function, and the Android application also worked optimally. In that range, the fan can extinguish the simulated fire source. The results of this study obtained a new approach to autonomous fire detection and extinguishing using IoT and robotic technology. In addition, it is able to integrate an Android-based IoT controller to enable remote control with real-time monitoring to overcome problems in previous research.
INTELLIGENT SYSTEM TO DETERMINE THE BEST LECTURER USING ADDITIVE RATIO ASSESSMENT ALGORITHM Wahyudi Wahyudi; Budy Satria; Lutfil Khairi
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 3 (2025): JITK Issue February 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i3.6281

Abstract

The quality of a lecturer's performance is one of the keys to institutional success that must be continuously improved. The performance assessment of lecturers in the Informatics study program of the Faculty of Information Technology, Andalas University faces obstacles in processing quantitative and qualitative data so that it is vulnerable to subjectivity including research productivity, teaching effectiveness, contributions to community service and additional activities. In addition, limitations in a systematic evaluation system result in unfairness and lack of transparency in the decision-making process. The research objective is to create a technology-based approach by applying the Additive Ratio Assessment method based on a Decision Support System. The ARAS method was chosen because it is able to determine effective final results based on multiple criteria that have been determined. The application of the ARAS method consists of 5 stages, namely determining the decision matrix, normalizing the decision matrix, weighting the normalization results, determining the optimum function value and ranking results. The results obtained are alternative data consisting of A1,A2,A3,A4,A5,A6,A7,A8,A9,A10,A11 and 8 criteria and weighting, namely the last education (10%), functional position (15%), certification (20%), number of publications (15%), author order (15%), publication index quality (10%), research grants (10%) and PkM (5%). The ranking results with the highest value in order 1-5 are 0.113875, 0.109785, 0.104235, 0.099005, 0.094715. The final conclusion of this research is that the ARAS method is able to prove the best lecturer assessment to be more efficient, transparent and subjective to be applied in the Andalas University Informatics study program.
Optimalisasi Penilaian Kinerja Pegawai Baznas Kota Padang Melalui Aplikasi SPK Metode TOPSIS Berbasis Web Budy Satria; Wahyudi, Wahyudi; Rahman, Arifan; Hadi Wijaya, Anggi; Dinilhak, Afdhal; Nurfiah, Nurfiah; Khairi, Luthfil; Dwi Asti, Ajeng; Eka Putri, Rahmi; Derisma, Derisma; Sakinah, Putri; Zamora, Sasya; Azizah, Tiara
JDISTIRA - Jurnal Pengabdian Inovasi dan Teknologi Kepada Masyarakat Vol. 5 No. 2 (2025)
Publisher : Yayasan Rahmatan Fidunya Wal Akhirah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58794/jdt.v5i2.1534

Abstract

Baznas Kota Padang memiliki peran strategis dalam pengelolaan zakat, infak, dan sedekah yang menuntut kinerja pegawai yang profesional dan akuntabel. Namun, sistem penilaian kinerja yang digunakan saat ini masih manual belum terintegrasi secara digital. Kegiatan PkM ini bertujuan untuk membuat aplikasi penilaian kinerja pegawai berbasis web. Aplikasi dibuat menggunakan model Sistem Pendukung Keputusan metode TOPSIS dengan beberapa tahapan yaitu Mengumpulkan data alternatif, data kriteria yang diberi nilai bobot, data sub kriteria, data penilaian seluruh alternatif, data perhitungan dan hasil akhir. Kegiatan ini dilakukan dalam beberapa tahap: pra-persiapan, persiapan, pelaksanaan, dan evaluasi.  Hasil kegiatan yang diperoleh adalah Mitra PkM menjadi lebih mudah melakukan penilaian dan aplikasi mendukung pencapaian target kinerja lembaga dengan adanya aplikasi berbasis web didukung dengan hasil evaluasi melalui pengisian kuesioner bahwa responden memberikan nilai 77,8%. Kesimpulan akhir adalah diharapkan program PkM ini dapat terus berkelanjutan, sehingga Baznas Kota Padang bisa bertransformasi menuju evaluasi kinerja pegawai yang lebih terstruktur dengan dukungan aplikasi.
Comparative Analysis of Weighted-KNN, Random Forest, and Support Vector Machine Models for Beef and Pork Image Classification Using Machine Learning Satria, Budy; Afrianto, Nurdi; Ningsih, Lidya; Sakinah, Putri; Sidauruk, Acihmah; Mayola, Liga
JOIV : International Journal on Informatics Visualization Vol 9, No 4 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.4.3736

Abstract

The actual problem that occurs in the sale of meat by some conventional market traders is mixing beef with pork because of the high selling price. The difference between pork and beef lies in the color and texture of the meat. However, many people do not understand this difference. This study aims to provide a solution to distinguish the two types of beef through a classification process by obtaining the best accuracy using the W-KNN, RF, and SVM models based on machine learning. This study compares the model's performance based on the number of datasets, comprising 400 original images (200 beef and 200 pork images), using a 80:20 ratio for training and test data. The extraction process uses two algorithms: HSV (Hue, Saturation, Value) and RGB (Red, Green, Blue). The model evaluation uses a confusion matrix that includes accuracy, Precision, Recall, and F1-score. Based on the results of the model testing, it was found that the random forest algorithm gave the best overall results, with the highest accuracy of 98.75%, Precision of 97%, F1-score of 98%, and recall of 99% on the number of decision trees of 400. This shows the stability and generalization of the superior model. The random forest algorithm is the most effective for classifying beef and pork data with minimal errors. Implications for further research include using a deep learning approach, especially for image processing, to detect differences in each meat characteristic and increase accuracy.
Weighted Multi-Criteria Assessment of Rice Quality Using The TOPSIS Method Satria, Budy; Fadilah, Sandi
Bulletin of Informatics and Data Science Vol 4, No 2 (2025): November 2025
Publisher : PDSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61944/bids.v4i2.145

Abstract

Rice is a staple food for the Indonesian people, and its availability must be guaranteed by the government. The background of this research is based on the increasing demand for high-quality rice from consumers, thus challenging producers to set optimal rice quality standards. The process of selecting quality rice is still carried out using conventional methods in Bulog warehouses, namely by checking every rice data received by the quality control team tasked with assessing the quality of incoming rice. To overcome this problem, a decision support system is needed that can provide fair, objective, and efficient decisions. This study aims to evaluate the quality of rice from 10 alternatives using five criteria: milling degree, head grain, moisture content, broken grain, and grit grain, with a total weight of 100%. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is applied. This research was conducted by following a series of steps, including building a Decision Matrix, Normalizing the Decision Matrix, Calculating the Weighted Normalized Decision Matrix, Determining the Ideal Positive and Negative Solutions, Calculating the Distance to the Ideal Positive and Negative Solutions, and Calculating the Preference Score. The results of the study showed that from 10 alternative data, 5 types of rice were obtained with the highest preference values, namely Harum Solok Rice (0.8363), Anak Daro Rice (0.7955), Kuruik Kusuik Rice (0.7210), Ampek Angkek Rice (0.6919), and Saganggam Panuah Rice (0.6727). The conclusion of this study is that the application of the TOPSIS method is effective in objectively assessing rice quality. In further research, it is recommended to utilize a combination of other decision support methods to acquire new knowledge and refine preference values, as well as to develop these methods into user-friendly interfaces
Penerapan Model Support Vector Machine dalam Prediksi Keberhasilan Belajar Pemrograman: Application of Support Vector Machine Model in Predicting Programming Learning Success Sarah Astiti; Budy Satria; Yeyi Gusla Nengsih; Sandi Fadilah; Darmansah Darmansah
Edu Cendikia: Jurnal Ilmiah Kependidikan Vol. 6 No. 01 (2026): Call for Papers April 2026
Publisher : ITScience (Information Technology and Science)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/educendikia.v6i01.8061

Abstract

Programming learning success is an important indicator in information technology education; many students still struggle to understand algorithmic concepts, logic, and code implementation. This problem indicates that a data-driven approach is needed to identify students' initial successes and failures in programming learning. The purpose of this study is to develop and validate a predictive model for programming learning success using Support Vector Machine (SVM), a classification algorithm. This research method includes steps such as data collection and preprocessing, feature selection, splitting the dataset into training and test sets, training the SVM model with parameter optimization, and evaluating performance using the test set. The results show that the SVM model achieves good classification performance with an accuracy of 87.5%, precision of 85.7%, F1 score of 87.8%, and AUC of 0.91, placing it in the excellent category. These findings indicate that the model has strong discriminatory power in distinguishing between successful and unsuccessful students. Therefore, the SVM method has been proven effective as a data-driven prediction system. This also allows for the development of more targeted and adaptive learning intervention strategies and academic decision-making.
SEGMENTASI PELANGGAN LAYANAN AIR BERSIH DI KAWASAN PEDESAAN MENGGUNAKAN K-MEANS CLUSTERING BERDASARKAN METRIK DURASI, KONSUMSI RATA-RATA, DAN TOTAL VOLUME (DCV) Nurfiah, Nurfiah; Satria, Budy; Al Hafiz, Muhammad
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 4 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i4.9371

Abstract

Layanan air bersih di kawasan pedesaan menghadapi tantangan terkait keterbatasan infrastruktur dan kesulitan memahami pola konsumsi pelanggan. Memahami karakteristik pelanggan sangat penting untuk efisiensi operasional, perencanaan, dan keberlanjutan layanan. Penelitian ini bertujuan melakukan segmentasi pelanggan layanan air pedesaan untuk mendukung pengambilan keputusan strategis. Metode yang digunakan adalah Data Mining dengan algoritma K-Means Clustering dengan data riil historis pemakaian air pelangga selama 27 bulan. Segmentasi dilakukan menggunakan matrik Durasi (D), Konsumsi Rata-Rata (C), dan Total Volume (V), atau DCV. Penentuan jumlah cluster optimal dilakukan menggunakan Metode Elbow dan Silhouette. Hasil penelitian berhasil mengelompokkan pelanggan menjadi 3 cluster yaitu Cluster 0 atau Pelanggan Reguler sebanyak 202 pelanggan dengan karakteristi Durasi Tinggi namun Konsumsi dan Volume Sedang, kelompok ini stabil dan mendominasi basis pelanggan. Cluster 1 atau Pelanggan Baru/Minimalis, sebanyak 109 pelanggan memiliki karakteristik Durasi, Konsumsi, dan Volume Paling Rendah, kelompok ini diidentifikasi sebagai pengguna minimalis atau pelanggan baru. Cluster 2 atau Pelanggan Premium sebanyak 78 pelanggan memiliki karakteristik Durasi, Konsumsi, dan Volume Paling Tinggi, kelompok ini adalah penyumbang volume pemakaian air dan pendapatan terbesar. Kesimpulan dari segmentasi ini memberikan rekomendasi strategis spesifik di bidang operasional, pemasaran, dan tarif. Rekomendasi ini dapat digunakan oleh pengelola layanan air pedesaan sebagai pendukung kebijakan yang tersegmen dan tepat sasaran.
Digitalization of Rural Water Management: Android-Based Billing for Community Systems using the ADDIE model Nurfiah Nurfiah; Afdhal Dinilhak; Luthfil Khairi; Budy Satria; Anggi Hadi Wijaya; Ajeng Dwi Asti; Arifan Rahman
Journal of Information Systems and Technology Research Vol. 4 No. 2 (2025): May 2025
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v4i02.1135

Abstract

The integration of information technology in everyday life has changed the way people work, learn, socialize, make transactions, and make decisions. The use of Android-based smartphones is a real example of the use of technology. Android, which is open-source, has encouraged the development of applications widely according to need. Access to water is a fundamental human right. PAMSIMAS is a flagship program of the regional and central governments that seeks to meet water needs through the provision of clean water services in line with the Sustainable Development Goals (SDGs). In Durian Seribu Village, PAMSIMAS is a service to meet the water needs of the community and become a solution for rural communities to get clean water at low cost, but its management is still manual, such as recording water usage and billing, so it is inefficient, time-consuming, and prone to errors. From these problems, this study proposes the development and implementation of an Android application designed to simplify the recording and billing process for the PAMSIMAS program in Durian Seribu Village. This application aims to simplify management, increase data transparency, and simplify reporting. The results of tests that have been carried out using the black box method show that this application can facilitate officers in recording and billing payments for PAMSIMAS water usage. Officers only need to enter the total water usage, and the application will automatically calculate and print a receipt as proof of payment. Officers also do not need to calculate manually when reporting the total payment to the administrator. For administrators, this application makes it easier to monitor and evaluate the performance of recording officers. After the application was used for recording and billing, PAMSIMAS's revenue increased by around 30% from the revenue before using the application.
Co-Authors Anggi Hadi Wijaya Abda Abda Abdullah Al Ramadhani Abdur Rohim Abdussalam Al Akbar Acihmah Sidauruk Adi Prastya Adinda Raudhatul Jannah Afdhal Dinilhak Afifah Nur Latifah Afrianto, Nurdi Ajeng Dwi Asti Al Hafiz, Muhammad Aldo Eko Syaputra Anggi Hadi Wijaya Arifan Rahman Arkan Ubaidillah Warman Ashari, Muhammad Al Azizah, Tiara Bima Prakasa Bister Purba Budi Permana Putra Candra Surya Chairil, Slamet Darmansah Darmansah Darmansah Darmansah Darmansah Darmansah Dedi Lesmana Devina Amanda Putri Dori Gusti Alex Candra Dwi Asti, Ajeng Efendi, Irman Efitra Efitra Efitra Fadilah, Sandi FAJAR, LM Firma Firma Fitra Yuda Gusla Nengsih, Yeyi Hafiz Mursalan Hendra, Yomei Karimah Irsyadiyah Khairi, Luthfil Khelvin Ovela Putra Leonard Tambunan Liga Mayola LM Fajar Israwan, LM Fajar Luthfil Khairi Maulana, Fajar Meiditra, Irzon Muhammad Iqbal Mulia Sulistiyono Murni, Aprilia Mutamassikin Mutamassikin Ningsih, Lidya Nurcholis, Muhammad Tofa Nurfiah Qori Islami Aris Radillah, Teuku Raditya Wardhana Rahman, Arifan Rahman, Zumardi Rahmi Eka Putri Resad Setyadi SAKINAH, PUTRI Samosir, Khairunnisa Sandi Fadilah Sandi Fadilah Saputra, Alex Rizky Sarah Astiti Sarah Astiti S.Kom., M.MT Saskia Alifah Sepriano Sepriano Siti Sahara Lubis Sri Wulandari Supriatin Supriatin, Supriatin Syamsul Arifin Syarif Hidayatullah Tomy Nanda Putra Vita Amelia, Vita Wahyudi Willi Novrian Willi Novrian Yessi Ratna Sari Yessi Ratna Sari Yessi Ratna Sari Yeyi Gusla Nengsih Zamora, Sasya