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Web Based Disaster Early Warning System on Pagar Alam City Mukti, Yogi Isro; Puspita, Desi
SENATIK STT Adisutjipto Vol 5 (2019): Peran Teknologi untuk Revitalisasi Bandara dan Transportasi Udara [ISBN 978-602-52742-
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/senatik.v5i0.302

Pemantauan curah hujan yang dilakukan oleh BMKG, merupakan modal sebagai dasar penelitian ini yang bertujuan untuk membuat sistem peringatan dini bencana longsor berbasis web pada Kota Pagar Alam, dengan mendata curah hujan yang terjadi sebagai bahan antisipasi terjadinya tanah longsor di wilayah Pagar Alam. Agar penelitian ini berjalan sesuai dengan yang diharapkan menjadi sistem peringatan dini yang bisa diakses secara daring, maka digunakan metodologi penelitian dan analisa yang mendalam. Dengan metode pengembangan sistem Rapid Aplication Development (RAD), dengan perancangan menggunakan flowchart dan Unified Modelling Language (UML), dengan bahasa pemrograman PHP dan basis data MySQLi. Hasil dari penelitian ini adalah sistem peringgatan dini bencana longsor berbasis web di wilayah Kota Pagar Alam yang merupakan daerah pegunungan, dengan memanfaatkan klasifikasi curah hujan sangat ringan, ringan, sedang, lebat dan sangat lebat.

Pest diagnosis expert system on chili plants using Forward Chaining method in the department of agriculture in Pagar Alam City Septriani, Evy; Mukti, Yogi Isro
SENATIK STT Adisutjipto Vol 6 (2020): Keselamatan Penerbangan di masa Pandemi Covid-19 [ISBN 978-602-52742-2-0]
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/senatik.v6i0.431

This study aims to produce an expert system for diagnosing pests in chilies using the Forward Caining method. Chili is one of the basic needs of the community as a flavoring or flavor, but farmers often experience failure to harvest due to pest attacks on chili plants. The system development method used by Waterfall consists of four stages, namely Analysis, Design, Coding and Testing. Therefore, the researcher created an expert system for diagnosing pests in chilies using the Onlane Forward Chaining method. the benefits of this expert system for the city of Pagar Alam, especially for farmers, make it easy to find out the types of pests that attack and provide solutions to prevent pests from being planted in chilies like an expe

Sistem informasi multimedia untuk meningkatan UMKM pada Kota Pagar alam berbasis web Iskandar, Iskandar; Mukti, Yogi Isro
SENATIK STT Adisutjipto Vol 6 (2020): Keselamatan Penerbangan di masa Pandemi Covid-19 [ISBN 978-602-52742-2-0]
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/senatik.v6i0.418

Pagar Alam in gething the data of improvement of UMKM then use manual system, process of collecting data of number UMKM, kind of UMKM so that of collecting data, reporting data non effective note taking of total UMKM and UMKM activities ar activity routinely done by goverment in getting UMKM data consist of total of UMKM, kinds of industry system developing method which used is Web Engenering method with some steps: Costumers, Comunication, Planning, Modelling, Construction and development. By desingning this system information, get information system, dinamiclay and updating hopely. Beside that this system information can be us one of alternativ media and conveying information with faster for user commonly.

Optimization Of Agricultural Production In South Sumatera Using Multiple Linear Regression Algorithm Setiadi, Dedi; Sasmita, Sasmita; Mukti, Yogi Isro
Knowbase : International Journal of Knowledge in Database Vol. 4 No. 2 (2024): December 2024
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v4i2.8754

Rice is one of the agricultural commodities in South Sumatra whose productivity level still fluctuates. In 2000, rice production reached 1,863,643.00 kg, then increased to 3,272,451.00 kg, in 2010, but decreased again in 2020 to 2,696,877.46 kg. This instability is influenced by various factors such as land area, rainfall, pest attacks, and fertilizer use. This study aims to optimize rice production by applying machine learning using multiple linear regression algorithms, and the CRISP-DM method, with the stages being business understanding, data understanding, data preparation, modeling, evaluation, and implementation. Data of 1,000 records obtained from farmers were analyzed using Google Collaboratory, resulting in an intercept of -3836,2639, and coefficients for land area of 5,7336, rainfall of 1,2710, pests of 6,1153, urea of 1,6226, and phonska of 1,2581. To evaluate the accuracy of rice production predictions based on these independent variables, calculations were made on the RMSE value and analysis of the coefficient of determination. The results were that the RMSE value was recorded at 17065084,9641, and the coefficient of determination (R²) was 0,6487, indicating that around 64,87 % of the variability in rice production can be explained by independent variables such as land area, rainfall, pest attacks, use of urea fertilizer, and phonska, while the remaining 35,13 % was influenced by other factors.

Pemberdayaan Petani Desa Sumber Jaya dalam Menanggulangi Penyakit Kriting Cabai 3T (Trips, Tungau, TMV) dengan Smart Mukti, Yogi Isro; Nasrullah, Abdi; Anggraini, Lesi
Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Vol 7, No 4 (2024): Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstormin
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/japhb.v7i4.7602

Desa Sumber Jaya menghadapi tantangan serius dalam produksi cabai akibat serangan penyakit kriting yang disebabkan oleh Trips, Tungau, dan TMV (3T). Permasalahan ini diperparah oleh harga jual cabai yang fluktuatif, akses pasar yang terbatas, serta kurangnya pengetahuan dan keterampilan petani dalam mengelola usaha tani. Program pengabdian masyarakat ini bertujuan untuk memberdayakan petani melalui penerapan teknologi Smart Farming guna meningkatkan produktivitas, kualitas, dan daya saing cabai. Program ini melibatkan sebanyak 1 kelompok tani yang berjumlah 5 orang petani cabai sebagai sampel utama untuk memastikan implementasi yang komprehensif. Metode dalam pelaksanaan kegiatan meliputi analisis kebutuhan, sosialisasi, penerapan teknologi, pendampingan, serta evaluasi dan keberlanjutan program. Hasil menunjukkan peningkatan signifikan dalam pengetahuan petani (90%), produktivitas dan kualitas panen (75%), serta pendapatan petani (40%). Kolaborasi antara perguruan tinggi, pemerintah, dan masyarakat juga berhasil dibangun, menunjukkan potensi keberlanjutan program ini.

Optimization Of Agricultural Production In South Sumatera Using Multiple Linear Regression Algorithm Setiadi, Dedi; Sasmita, Sasmita; Mukti, Yogi Isro
Knowbase : International Journal of Knowledge in Database Vol. 4 No. 2 (2024): December 2024
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v4i2.8754

Rice is one of the agricultural commodities in South Sumatra whose productivity level still fluctuates. In 2000, rice production reached 1,863,643.00 kg, then increased to 3,272,451.00 kg, in 2010, but decreased again in 2020 to 2,696,877.46 kg. This instability is influenced by various factors such as land area, rainfall, pest attacks, and fertilizer use. This study aims to optimize rice production by applying machine learning using multiple linear regression algorithms, and the CRISP-DM method, with the stages being business understanding, data understanding, data preparation, modeling, evaluation, and implementation. Data of 1,000 records obtained from farmers were analyzed using Google Collaboratory, resulting in an intercept of -3836,2639, and coefficients for land area of 5,7336, rainfall of 1,2710, pests of 6,1153, urea of 1,6226, and phonska of 1,2581. To evaluate the accuracy of rice production predictions based on these independent variables, calculations were made on the RMSE value and analysis of the coefficient of determination. The results were that the RMSE value was recorded at 17065084,9641, and the coefficient of determination (R²) was 0,6487, indicating that around 64,87 % of the variability in rice production can be explained by independent variables such as land area, rainfall, pest attacks, use of urea fertilizer, and phonska, while the remaining 35,13 % was influenced by other factors.

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