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All Journal Infotech Journal Journal of Information Technology and Computer Science (JOINTECS) JITTER (Jurnal Ilmiah Teknologi Informasi Terapan)

Erwin Hermawan

Unknown Affiliation

Author-ID : 3035489

Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering

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Articles

Sistem Pendukung Keputusan Pemilihan Pupuk Untuk Tanaman Padi Menggunakan Metode Fuzzy Erwin Hermawan; Rudi Hariyanto; Sultoni -
JOINTECS (Journal of Information Technology and Computer Science) Vol 2, No 1 (2017)
Publisher : Universitas Widyagama Malang

Kebutuhan pupuk bersubsidi terus mengalami peningkatanmeskipun lahan pertanian semakin sempit, membuat petani mengalami kesulitan dalam hal mendapatkan pupuk yang berpengaruh langsung terhadap produktivitas padi menjadi persoalan para petani. Sehingga dengan adanya sebuah sistem informasi ini memberikan kemudahan pemakaian pupuk yang akan datang secara komputerisasi dalam pengambilan keputusan. Sistem pendukung keputusan diperlukan untuk mendapatkan pengetahuan kepakaran dari ahlinya dalam diagnosa kebutuhan padi, sedangkan inferensi fuzzy Mamdani digunakan untuk pengolahan pengetahuan agar diperoleh konsekuensi atau kesimpulan.

PEMETAAN ZONASI TINGKAT RISIKO COVID-19 MENGGUNAKAN METODE K-MEANS CLUSTER BERBASIS WEBGIS DI KOTA BOGOR Andi Irawan; Erwin Hermawan; Freza Riana
Jurnal Ilmiah Teknologi Infomasi Terapan Vol. 8 No. 2 (2022)
Publisher : Universitas Widyatama

Coronaviruses, also known as COVID-19, is a virus that attacks the respiratory system. This virus is growing very rapidly in transmission from human to human. The distribution rate in Indonesia is quite high, one of the areas exposed to COVID-19 is Bogor City. The city of Bogor occupies a moderately dangerous status, where from March 2020 to August 2021 the number of confirmed positive cases was 35,583 cases, while for patients who were confirmed positive recovered reached 35,062 people, and patients who were confirmed positive died as many as 521 people. From data obtained from the Bogor City Health Office, the daily dynamics of the COVID-19 virus continues to show an increase. The COVID-19 zoning distribution map for the Bogor City area at the kelurahan level is still not available. Therefore, this study utilizes a geographic information system (GIS) within the COVID-19 zone by applying the Kmeans Cluster method to cluster the distribution areas of the COVID-19 virus. The grouping is done based on the parameters of the number of positive cases and patients who died. This study produced a COVID-19 zoning map. Based on the test, the definite number of clusters is 3 clusters. Where the zoning division based on the COVID-19 Task Force is divided into red for the high zone, orange for the medium zone, yellow for the low zone, and areas that are not exposed to COVID-19 cases are in the green category or there are no cases. The result of this study is a COVID-19 zoning map that is displayed in WEBGIS form.

WEBGIS PRIORITAS PENGEMBANGAN POTENSI DESA WISATA DI WILAYAH GEOPARK NASIONAL PONGKOR muhamad iqbal; Budi Susetyo; Erwin Hermawan
Jurnal Ilmiah Teknologi Infomasi Terapan (JITTER) Vol. 9 No. 2 (2023)
Publisher : Universitas Widyatama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33197/jitter.vol9.iss2.2023.1013

Bogor Regency has the potential to progress and develop, because it has natural resources and human resources that are very supportive. To consider the geographical conditions of the Bogor Regency government to prioritize the development of tourist villages. The Pongkor National Geopark area includes 15 sub-districts namely Ciseeng, Jasinga, Nanggung, Tenjo, Cigudeg, Sukajaya, Leuwiliang, Leuwisadeng, Ciampea, Tenjolaya, Cibungbulang, Pamijahan, Rumpin, Tamansari, and Parung. Because this tourism emphasizes the active involvement of the local community and the role of control over the development of tourist villages in their respective regions. the WebGIS process prioritizes the development of potential tourism villages in the Pongkor National Geopark area, so this arrangement needs to be packaged in a geographic information system using the Composite Performance Index (CPI) method displayed in a WebGIS.

KLASIFIKASI KESEHATAN PADA TANAMAN PADI MENGGUNAKAN CITRA UNMANED AERIAL VEHICLE (UAV) DENGAN METODE CONVOLUTIONAL NEURAL NETWORKS (CNN) Dimas Mulya Saputra; Erwin Hermawan; Sahid Agustian2
Jurnal Ilmiah Teknologi Infomasi Terapan (JITTER) Vol. 9 No. 3 (2023)
Publisher : Universitas Widyatama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33197/jitter.vol9.iss3.2023.1044

Indonesia is a country with a majority of the population making rice the main food. With an increasing population, of course, it is necessary to maintain the quality of rice to reduce the risk of crop failure. In 2019, it was stated that nearly 40% of the world's crop was lost due to disease and pest infestation. Unmanned Aerial Vehicle (UAV) is a technology that has been widely used for the observation and mapping of rice plants. The UAV's small size allows it to maneuver more, making shooting land easier and faster. These diseases and pest attacks can be detected by looking at the plant parts. The easiest part to detect is on the leaves because the signs of the disease can be seen clearly. However, it is not easy to recognize these diseases, it requires experts to identify diseases through a more accurate UAV image. Convolutional Neural Network (CNN) is a deep learning method that is often used in digital image recognition. This is because CNN is trying to imitate the image recognition method in the human visual cortex. The CNN method in this study was used to classify healthy rice plants and diseased rice plants through UAV imagery

ANALISIS PERHITUNGAN INDIVIDU PADA POHON PINUS MENGGUNAKAN METODE LOCAL MAXIMA DARI CITRA UAV (UNMANNED AERIAL VEHICLE) Sinta Lestari; Erwin Hermawan; Sahid Agustian Hudjimartsu
INFOTECH journal Vol. 9 No. 2 (2023)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/infotech.v9i2.7101

Salah satu sentra utama populasi hutan pinus Jawa Barat berada di Sukabumi yang terletak di beberapa kecamatan, diantaranya: Kec. Sagaranten, Kec. Bojong lopang, Kec. Jampang dan Kec. Pelabuhan Ratu yang pengelolaannya dilakukan di sejumlah kawasan hutan produksi. Teknologi yang efektif untuk melakukan monitoring pada sektor pekebunan adalah teknologi penginderaan jauh (remote sensing), seperti pesawat tanpa awak/drone atau UAV. Tujuan dari penelitian ini adalah mengidentifikasi hasil perhitungan pohon pinus dari citra UAV menggunakan metode local maxima dan ratiogreen, serta menganalisa akurasi dari hasil perhitungan pohon pinus. Hasil penelitian pada kelas minimum 4 meter identifikasi jumlah pohon dengan metode local maxima terdapat 4.166 pohon. Sedangkan dengan mengkombinasi antara local maxima dan ratiogreen menghasilkan identifikasi sebanyak 4.011 pohon. Pada kelas minimum 3 meter, identifikasi jumlah pohon dengan metode local maximaterdapat 4.731 pohon, sedangkan dengan mengkombinasi antara local maxima dan teknik ratiogreen menghasilkan identifikasi sebanyak 4.540 pohon.

Co-Authors Andi Irawan Budi Susetyo Dimas Mulya Saputra Freza Riana Hudjimartsu, Sahid Agustian muhamad iqbal Rudi Hariyanto Sahid Agustian2 Sinta Lestari Sultoni -

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