Prediction of Patients' Illness Based on Average Temperature and Rainfall In Az-Zainiyah Clinic Using Backpropagation Method

The purpose of this study is to predict the type of disease in students based on the average temperature and rainfall at the Az-Zainiyah clinic using the backpropagation method. With this research, we hope that the prediction/estimation process on the type of patient's disease using the backpropagation artificial neural network method provides a solution with precise and accurate prediction results based on data on many patients, average temperature, and previous rainfall. This research is carried out through a process of predicting the type of disease by collecting time-series data from patient visit reports. The raw data obtained are examined for completeness and quality of the data. Then, the data was analyzed and applied to an artificial neural network method to predict the type of patient's disease based on many patients, average temperature, and rainfall. Furthermore, the artificial neural network will be optimized by the backpropagation algorithm. From this study, we find that the percentage of precision obtained in the experimental type of pharyngitis/sore throat disease in November 2020 with an average precision percentage is 68.92%, the best precision percentage is 90.25%, and the worst precision percentage 47.59%. In December 2020, the average precision percentage is 41.46%, with the best precision percentage being 65.55%, and the worst precision percentage 4.92%. In the type of dermatitis/itching disease in November 2020, the best precision percentage is 98.81%, the average precision percentage is 68.31%, and the worst precision percentage is -21.57 %. For December 2020, the average precision percentage is -63.27%, the best precision percentage is 48.37%, and the worst precision percentage is -183.85%

PkM Peningkatan Literasi, Numerasi dan Adaptasi Teknologi melalui Program Kampus Mengajar di SMP Negeri 3 Pakuniran Satu Atap

Pandemi COVID-19 membuat banyak perubahan di dunia pendidikan, termasuk di antaranya adalah pembelajaran jarak jauh menjadi solusi altenatif. Meski menjadi solusi, pembelajaran jarak jauh pada kanyataannya tidak dapat memastikan bahwa siswa dapat belajar dengan efektif. Situasi ini membuat motivasi peserta didik menurun, guru mengeluhkan beban kerja administratif yang ribet, dan harus cepat beradaptasi menggunakan teknologi. Artikel ini merupakan luaran dari program  PkM Kampus Mengajar Kemdikbud tahun 2022 di SMP Negeri 3 Pakuniran Satu Atap yang akan menggambarkan tentang pelaksanaan kegiatan penguatan literasi, numerasi, dan adaptasi teknologi bagi peserta didik. Dengan menggunakan pendekatan Participatory Action Research, PkM ini berupaya untuk mengatasi ketertinggalan materi siswa SMP Negeri 3 Pakuniran yang disebabkan keterbatasan sarana belajar mengajar dan ketertinggalan teknologi saat pembelajaran jarak jauh berlangsung. Hasil PkM yang telah dicapai adalah meningkatnya kemampuan literasi dan numerasi siswa serta kemampuan pemanfaatan teknologi dalam pembelajaran. PkM ini juga berhasil menciptakan tata kelola administrasi berbasis SOP dan database online yang baik di SMP Negeri 3 Pakuniran Satu Ata

Comparison of C4.5 and Naive Bayes for Predicting Student Graduation Using Machine Learning Algorithms

Student graduation is a very important element for universities because it relates to college accreditation assessment. One of them is at the Faculty of Engineering Nurul Jadid University, which has problems completing the study period within a predetermined time. So that it can be detrimental because accreditation is less than optimal, and the number of active students makes it less ideal in teaching and learning activities. This study aimed to compare the level of accuracy using the C4.5 algorithm and Naïve Bayes method in predicting graduation on time. The C4.5 and Naïve Bayes algorithms are one of the methods in the algorithm for classifying. Tests were carried out using the C4.5 and Naïve Bayes algorithms using Google Colab with Python programming language, then validated using 10-fold cross-validation. The results of this study indicate that the Naïve Bayes method has a higher accuracy value with an accuracy rate of 96.12%, while the C4.5 algorithm method is 93.82%

Perancangan Sistem Monitoring Surat Perintah Perjalanan Dinas dengan Mobile App Android untuk Biro Kepegawaian Universitas Nurul Jadid

An official travel warrant is a letter made for employee who has been assigned for an official trip to a certain area. The application process of The official travel warrant (surat perintah perjalanan dinas/SPPD) at Nurul Jadid University involves the Faculty Administration by submitting it to Head of Administration and the one who who has a right for approval, such as Representative Rector. The current process is still based on the old system and has an impact on long synchronization between employees due to lack of coordination and time-delays in the process of submitting service processes. Therefore, this study is intended to offer a system design for monitoring official travel orders with the Android Mobile App at Nurul Jadid University. The method used in this research is the waterfall method, whose stages or paths run from top to bottom. The target of this research is the monitoring of official trips which will make it easier for all parties. The results of this study are 96.9% of employees said that this system really helps the process of official travel effectively and efficiently

PKM Peningkatan Pengetahuan Keluarga Penerima Manfaat Program Keluarga Harapan Tentang Stunting Di Desa Sidodadi Kecamatan Paiton Kabupaten Probolinggo

Di Indonesia terdapat 1,2 juta bayi lahir dalam keadaan stunting. Untuk itulah pada awal tahun 2021, Pemerintah Indonesia menargetkan angka Stunting turun menjadi 14% di tahun 2024. Kabupaten Probolinggo kasus stunting di tahun 2021 dari jumlah balita sebanyak 79,356 anak penderita stunting mencapai 12,769 anak atau 16,01%. Jumlah ini menjadikan Kabupaten Probolinggo berada di posisi 5 daerah terbanyak penderita stunting Provinsi Jawa Timur. Dari jumlah sebaran penderita sunting Kabupaten Probolinggo, di Kecamatan Paiton jumlah penderita stunting tahun 2021 tercatat  sebanyak 745 anak atau 14% dari jumlah balita 5,276 anak. Dari 20 desa yang ada di Kecamatan Paiton, desa terbanyak penderita stunting adalah Desa Sidodadi dengan jumlah 145 anak dari 390 balita atau sebanyak 37%. Tujuan PKM ini adalah memberikan penyuluhan dan pendampingan untuk meningkatkan wawasan dan kesadaran masyarakat Desa Sidodadi Kecamatan Paiton Kabupaten Probolinggo dalam mencegah dan mencegah penderita stunting. Hasil yang dicapai dalam PKM ini adalah telah meningkatnya pengetahuan peserta tentang penanganan dan pencegahan stunting. Dimana dari hasil pre-test dengan tingkat pengetahuan baik sekali mencapai 53%, tingkat pengetahuan baik 27% dan tingkat pengetahuan kurang menurun menjadi 20%