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All Journal CogITo Smart Journal SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal ICT : Information Communication & Technology SKANIKA: Sistem Komputer dan Teknik Informatika Jurnal Abdimas Sangkabira Abditeknika - Jurnal Pengabdian Kepada Masyarakat Kresna: Jurnal Riset dan Pengabdian Masyarakat Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Academic Journal of Computer Science Research (AJCSR) Jurnal Ticom: Technology of Information and Communication JAMAIKA: Jurnal Abdi Masyarakat Telematika MKOM Artinara Jurnal Ticom: Technology of Information and Communication
Pudoli, Ahmad
Program Studi Teknik Informatika, Fakultas Teknologi Informasi, Universitas Budi Luhur
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Prototipe Alat Pendeteksi Api dan Kebocoran Gas menggunakan Mikrokontroller Nodemcu ESP8266, Flame Sensor dan MQ-135 Estu, Maulana Alzura; Kusumaningsih, Dewi; Pudoli, Ahmad
Academic Journal of Computer Science Research Vol 6, No 2 (2024): Academic Journal of Computer Science Research (AJCSR)
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/ajcsr.v6i2.15663

Abstract

Kebakaran bisa terjadi di berbagai tempat, seperti rumah makan, pabrik, tempat tinggal atau kantor. Penggunaan mikrokontroller dan sensor memungkinkan kita untuk membuat alat yang dapat melakukan pemantauan terhadap kondisi lingkungan. Pemanfaatan Internet of Things pada alat juga memudahkan proses pengendalian dan pemantauan terhadap perangkat dengan memanfaatkan akses internet. Penulis merancang sebuah alat prototipe untuk mendeteksi api dan gas menggunakan mikrokontroller NodeMCU esp8266, buzzer, sensor flame sebagai pendeteksi api dan sensor MQ-135 sebagai pendeteksi gas yang dapat mendeteksi keberadaan gas seperti karbondioksida, amonia, dan alkoholSetelah dilakukan pengujian prototipe bekerja dengan baik sesuai dengan yang diharapkan yaitu dapat mendeteksi api dan kebocoran gas alkohol, amonia, dan karbondioksida. Komponen yang berfungsi sebagai output juga dapat bekerja ketika sensor mendeteksi api atau gas. Flame sensor dapat mendeteksi api dengan jarak efektif deteksi sekitar 80 cm. Kemudian sensor gas MQ-135 berhasil mendeteksi keberadaan gas setelah diuji dengan alkohol 96%, amonia 25%, dan asap dengan nilai bacaan dari sensor melampaui 500 ketika mendeteksi gas dari bahan-bahan kimia tersebut. Website monitoring yang telah dihosting juga berhasil diintegrasikan dengan prototipe dengan rata-rata delay pengiriman data 0.378 detik.
Peningkatan Kualitas Guru dengan Pelatihan Google Classroom sebagai Media Alternatif School From Home pada SMK Puspita Persada Jakarta Selatan Pudoli, Ahmad; Hardjianto, Mardi; Setiono, Devit
Abditeknika Jurnal Pengabdian Masyarakat Vol. 1 No. 1 (2021): April 2021
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/abditeknika.v1i1.235

Abstract

The COVID-19 pandemic in early 2020 is causing major changes in community activities today. Starting from trade, economy, jobs as well as in the world of education. Schools must participate in preventing the spread of the COVID-19 virus by changing teaching patterns in accordance with the instructions of the Ministry of Education and Culture of the Republic of Indonesia, where teaching and learning activities are carried out from home. Puspita Persada Vocational High School participated in the success of the government program by changing the teaching pattern from home. However, because this instruction was given quickly, SMK Puspita persada has not prepared technically thoroughly in teaching and learning. Currently the teaching method is done using WhatsApp Group and email. Of course, this method still needs to be developed so that the delivery of teaching materials is more perfect. The purpose of this activity is to provide training using Google's facility, Google ClassRoom, to improve the ability of teachers to deliver and deliver materials to the maximum and based on better technology. The method that will be done in this activity is face-to-face training (if possible) but still apply physical distancing in the presentation of the material. This method will be adjusted at the time of implementation in accordance with existing conditions. Based on Abdimas activities, it can be concluded that google classroom training provides tremendous benefits for teachers. Teachers are very enthusiastic and interested in using google classroom, teachers know applications that can be used as a learning medium, teachers can be easier to manage classes, save time, and give examples to students to maintain the environment by reducing paper use.
Predictive Linear Regression Model for Premature Birth Risk Assessment System Kusumaningsih, Dewi; Kadir, Abdul; Pudoli, Ahmad
CogITo Smart Journal Vol. 11 No. 2 (2025): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v11i2.924.402-413

Abstract

Preterm birth is a major cause of neonatal mortality in Indonesia and is influenced by multiple maternal factors. Early prediction models are crucial for supporting timely clinical decision-making and reducing adverse maternal–infant outcomes. The method of this study developed a linear regression–based predictive model using 915 pregnancy medical records from Dr. H. M. Ansari Saleh Regional Hospital, Banjarmasin (2020–2022). The workflow included data preprocessing, feature selection, Min-Max normalization, and experimentation with various train–test split ratios (90:10 to 50:50). Model performance was evaluated using R², Adjusted R², MAE, MSE, RMSE, and MAPE metrics. As the results, the 70:30 split ratio achieved the best accuracy of 89.05% and AUC of 98.10%, with low prediction errors. Optimizations with Adamax and Nadam enhanced stability and reduced MAPE to 1.95%. The optimized linear regression model reliably predicts preterm birth risk and is suitable for clinical decision support, particularly in resource-limited settings.
Co-Authors Abdul Kadir Amri Wicahyo Arinda Hana Syafira Aryabima, Muhammad Iqbal Aryasanti, Agnes Baehaqi Batu Bara, Muhamad Aldi Mudin Brury Triya Sartana Devit Setiono Dewi Kusumaningsih Elizabeth Yohanes Estu, Maulana Alzura Hardjianto, Mardi Iis Torisa Utami Iqbal Suwandi Khalid, Zulvia Kusumaningsih, Dewi M. Bucci Ryando Mohammad Syafrullah Noripansyah . Noripansyah, Noripansyah Novia Rana Fadhila Nugroho, Radityo Nurmaesah, Nunung Pradana, Rizky Purwanto Purwanto Raharja, Rian Umbara Maulana Ririt Roeswidiah Roeswidiah, Ririt Rusdah Rusdah Ruwirohi, Jan Everhard Septian Apriyanto Triana Anggraini Wicahyo, Amri Yulianawati Yulianawati Yulianawati Yulianawati Yulianawati Yulianawati