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PELATIHAN PEMBUATAN VIDEO PEMBELAJARAN DENGAN MENGGUNAKAN POWERPOINT DI MI MUHAMMADIYAH WANGON Ikhsan, Ali Nur; Hidayat, Muslimin; Suhaman, Jali
SELAPARANG Jurnal Pengabdian Masyarakat Berkemajuan Vol 4, No 3 (2021): Agustus
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v4i3.4526

Abstract

ABSTRAKMI Muhammadiyah Wangon merupakan salah satu sekolah yang mempunyai tenaga pendidik atau guru dengan rentang usia yang variatif, dalam menyajikan bahan ajar para guru mempunyai cara yang variatif juga. Di masa pandemi Covid-19 ini para guru dalam menyajikan bahan ajar masih merasa kesulitan untuk membuat video pembelajaran yang komunikatif dan interaktif. Tim pengabdian kepada Masyarakat (PkM) memberikan pelatihan pembuatan video pembelajaran dengan menggunakan PowerPoint. Metode yang digunakan dalam pelatihan ini yaitu berupa workshop. Tim PkM melakukan pelatihan secara langsung dengan 1 narasumber sebagai pemateri workshop dan 2 pendamping untuk mendampingi peserta dalam pelaksanaan workshop. Pelatihan ini dapat menambah pengetahuan dan kemampuan peserta dalam membuat video pembelajaran yang komunikatif dan interaktif. Kata kunci: pelatihan; video; interaktif; powerpoint; workshop. ABSTRACTMI Muhammadiyah Wangon is one of the schools that has mentors or teachers with various age ranges, and has various way of presenting teaching materials as well. During the Covid-19 pandemic, teachers in presenting teaching materials still found it difficult to make communicative and interactive learning videos. The community service team (PkM) provides training on making learning videos using PowerPoint. The method used in this training is a workshop. The PkM team conducts direct training with 1 person as a speaker and 2 assistants to assist participants in the implementation of the workshop. This training can increase the knowledge and abilities of participants in making communicative and interactive learning videos. Keywords: training; video; interactive; power point; workshop.
PREDIKSI POTENSI SISWA PUTUS SEKOLAH AKIBAT PANDEMI COVID-19 MENGGUNAKAN ALGORITME K-NEAREST NEIGHBOR Darmayanti, Irma; Subarkah, Pungkas; Anunggilarso, Luky Rafi; Suhaman, Jali
JST (Jurnal Sains dan Teknologi) Vol 10, No 2 (2021)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jst-undiksha.v10i2.39151

Abstract

The implementation of the PSBB has an impact on all sectors, one of which is education, namely the threat of children dropping out of school. Dropouts explain that every student or student who leaves school or other educational institutions for any reason before finishing school without moving to another school. Early prediction must be done, to prevent many students dropping out of school. The dataset used in this study was taken from students in Junior High School (SMP) in Banyumas Regency. The method used in this study is the confusion matrix and 10-fold cross validation on the K-Nearest Neighbors (KNN) algorithm. The results obtained on the KNN algorithm in predicting the potential for dropout students are 87.4214%, with a precision value of 88.2%, recall 87.4% and F-Measure 87%. Then the results of the accuracy value on the KNN algorithm are categorized as Good Classification
Smart Plant: A Mobile Application for Plant Disease Detection Suhaman, Jali; Sari, Tia; Kamandanu, Kamandanu; Aulianti, Dwy; Adhi, Muhammad; Amartiwi, Utih
GMPI Conference Series Vol 2 (2023): 4th International Conference of Integrated Intellectual Community (ICONIC)
Publisher : Gemilang Maju Publikasi Ilmiah (GMPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (184.526 KB) | DOI: 10.53889/gmpics.v2.173

Abstract

Indonesia is one of the big producers of agricultural products in the world. Agriculture sector plays an important role in the national economic development structure. However, the proportion of young farmers (ages 20 to 30 years old) is only 8% of the farmer population (BPS, 2019). Majority proportion comes from old people with age interval from 50 to 60 years old. (Taufik Leoni, 2020). Based on our case study in Purwokerto, the problem that is often found by old age farmers is the reduced ability to see and recognize plant diseases. Furthermore, they also face the difficulty to follow the development of agricultural science so that some of their knowledge is outdated. That encourages us to make a mobile application to identify plant disease and connect them with scientists. Since the majority of farmers in Purwokerto plant tomatoes, we limit this research for tomato disease only. After studying some related previous research, we found most of them used a deep structure of Convolutional Neural Network (CNN) to reach a high accuracy. However, since our aim is to make daily use technology for old people, a high complexity model does not fit for this case. Therefore, we proposed our own CNN model with less complexity but got 89% accuracy. For future works, we plan to develop it for the other plants and hope it will help all farmers to do quality control, especially for the old age farmers.
PREDIKSI POTENSI SISWA PUTUS SEKOLAH AKIBAT PANDEMI COVID-19 MENGGUNAKAN ALGORITME K-NEAREST NEIGHBOR Darmayanti, Irma; Subarkah, Pungkas; Anunggilarso, Luky Rafi; Suhaman, Jali
JST (Jurnal Sains dan Teknologi) Vol. 10 No. 2 (2021)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (282.104 KB) | DOI: 10.23887/jstundiksha.v10i2.39151

Abstract

The implementation of the PSBB has an impact on all sectors, one of which is education, namely the threat of children dropping out of school. Dropouts explain that every student or student who leaves school or other educational institutions for any reason before finishing school without moving to another school. Early prediction must be done, to prevent many students dropping out of school. The dataset used in this study was taken from students in Junior High School (SMP) in Banyumas Regency. The method used in this study is the confusion matrix and 10-fold cross validation on the K-Nearest Neighbors (KNN) algorithm. The results obtained on the KNN algorithm in predicting the potential for dropout students are 87.4214%, with a precision value of 88.2%, recall 87.4% and F-Measure 87%. Then the results of the accuracy value on the KNN algorithm are categorized as Good Classification
Komparasi Model Prediksi Kurs Pada Masa Pandemi Covid-19 Menggunakan Neural Network Berbasis Genetic Algorithm dan Particle Swarm Optimization Nur Ikhsan, Ali; Arsi, Primandani; Suhaman, Jali
Infotekmesin Vol 13 No 1 (2022): Infotekmesin: Januari, 2022
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v13i1.938

Abstract

Data from Bank Indonesia shows that the rupiah exchange rate against dollar weakened at the beginning of the Covid-19 pandemic. This exchange rate volatility is an important problem in the Indonesian economy. Therefore, the prediction model for the exchange rate against the dollar is needed during the Covid-19 pandemic to predict the exchange rate during the Covid-19 Pandemic. This study is proposed to compare the prediction of the rupiah exchange rate against the dollar using the GA-based Neural Network algorithm and the PSO-based Neural Network algorithm. Initially the data was collected in the period 2019 to 2021, then the data is preprocessed. Validation used the k-fold validation technique with a ratio of 70:30, while the evaluation is carried out with the output of RMSE. The results showed that the performance of PSO and GA was the same, namely 0.020 +/- 0.006.