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All Journal Jurnal Komtika (Komputasi dan Informatika) Infotek : Jurnal Informatika dan Teknologi Jurnal PRINTER : Jurnal Pengembangan Rekayasa Informatika dan Komputer Jurnal Teknologi Informasi untuk Masyarakat (Jurnal Teknokrat)
Fathurrahman, Imam
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Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science

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Identifikasi Kematangan Buah Mentimun Berbasis Citra Digital Menggunakan Jaringan Syaraf Tiruan Backpropagation fathurrahman, imam; Nur, Amri Muliawan; Farhurrahman, Fathurrahman
Infotek : Jurnal Informatika dan Teknologi Vol 2, No 1 (2019): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (492.156 KB)

Abstract

Cucumber, cucumber, or cucumber (Cucumis sativus L) are plants that produce edible fruit. Especially in NTB cucumber production in 2015 reached 5,224 tons with a harvest area of 326 hectares. It is at number five after onions, chili, tomatoes and cabbage [2]. There are several parameters that can affect the quality of cucumbers, one of which is the shape, level of planting age and maturity [5]. Maturity of cucumbers can be recognized physically in terms of skin texture and color. The identification process of physical properties conventionally still has many disadvantages including the time needed is relatively long and produces a variety of products due to the limitations of human visuals. This becomes an obstacle so that it requires the application of computer image processing technology, especially in agriculture. Because of this, the researchers proposed using GLCM as feature extraction and using Backpropagation artificial neural networks for testing and training so that the research resulted in an accuracy of 89.6%.DOI : 10.29408/jit.v2i1.976
Identifikasi Kematangan Buah Mentimun Berbasis Citra Digital Menggunakan Jaringan Syaraf Tiruan Backpropagation fathurrahman, imam; Nur, Amri Muliawan; Farhurrahman, Fathurrahman
Infotek : Jurnal Informatika dan Teknologi Vol 2, No 1 (2019): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (492.156 KB)

Abstract

Cucumber, cucumber, or cucumber (Cucumis sativus L) are plants that produce edible fruit. Especially in NTB cucumber production in 2015 reached 5,224 tons with a harvest area of 326 hectares. It is at number five after onions, chili, tomatoes and cabbage [2]. There are several parameters that can affect the quality of cucumbers, one of which is the shape, level of planting age and maturity [5]. Maturity of cucumbers can be recognized physically in terms of skin texture and color. The identification process of physical properties conventionally still has many disadvantages including the time needed is relatively long and produces a variety of products due to the limitations of human visuals. This becomes an obstacle so that it requires the application of computer image processing technology, especially in agriculture. Because of this, the researchers proposed using GLCM as feature extraction and using Backpropagation artificial neural networks for testing and training so that the research resulted in an accuracy of 89.6%.DOI : 10.29408/jit.v2i1.976
KLASIFIKASI PENENTUAN PENERIMA PROGRAM KELUARGA HARAPAN (PKH) MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) PADA KANTOR DINAS SOSIAL LOMBOK TIMUR fathurrahman, imam; fathurrahman, fathurrahman
Infotek : Jurnal Informatika dan Teknologi Vol 3, No 1 (2020): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (53.666 KB)

Abstract

The Family of Hope Program (PKH) is a program of giving cash to Very Poor Households (RTSM) based on established terms and conditions. Where PKH was implemented in Indonesia in 2007, but in East Lombok PKH was only implemented in 2011. However, judging from the data of PKH recipient members, there are still many RTSM who do not get the PKH assistance. This situation identified the data collection method and the determination of priorities that were not yet on target. From these problems, it is necessary to utilize data mining techniques using the support vector machine (SVM) algorithm in determining PKH recipients. After testing 4 times using different K-Fold Validation on the cross validation operator. K-Fold Validation functions to divide the amount of training data and testing data on the data being tested. Then the accuracy results that have been tested are 95.41%.DOI : 10.29408/jit.v3i1.1802
KLASIFIKASI PENENTUAN PENERIMA PROGRAM KELUARGA HARAPAN (PKH) MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) PADA KANTOR DINAS SOSIAL LOMBOK TIMUR fathurrahman, imam; fathurrahman, fathurrahman
Infotek : Jurnal Informatika dan Teknologi Vol 3, No 1 (2020): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (53.666 KB)

Abstract

The Family of Hope Program (PKH) is a program of giving cash to Very Poor Households (RTSM) based on established terms and conditions. Where PKH was implemented in Indonesia in 2007, but in East Lombok PKH was only implemented in 2011. However, judging from the data of PKH recipient members, there are still many RTSM who do not get the PKH assistance. This situation identified the data collection method and the determination of priorities that were not yet on target. From these problems, it is necessary to utilize data mining techniques using the support vector machine (SVM) algorithm in determining PKH recipients. After testing 4 times using different K-Fold Validation on the cross validation operator. K-Fold Validation functions to divide the amount of training data and testing data on the data being tested. Then the accuracy results that have been tested are 95.41%.DOI : 10.29408/jit.v3i1.1802
Identifikasi Kematangan Buah Mentimun Berbasis Citra Digital Menggunakan Jaringan Syaraf Tiruan Backpropagation imam fathurrahman; Amri Muliawan Nur; Fathurrahman Farhurrahman
Infotek: Jurnal Informatika dan Teknologi Vol 2, No 1 (2019): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (492.156 KB) | DOI: 10.29408/jit.v2i1.976

Abstract

Cucumber, cucumber, or cucumber (Cucumis sativus L) are plants that produce edible fruit. Especially in NTB cucumber production in 2015 reached 5,224 tons with a harvest area of 326 hectares. It is at number five after onions, chili, tomatoes and cabbage [2]. There are several parameters that can affect the quality of cucumbers, one of which is the shape, level of planting age and maturity [5]. Maturity of cucumbers can be recognized physically in terms of skin texture and color. The identification process of physical properties conventionally still has many disadvantages including the time needed is relatively long and produces a variety of products due to the limitations of human visuals. This becomes an obstacle so that it requires the application of computer image processing technology, especially in agriculture. Because of this, the researchers proposed using GLCM as feature extraction and using Backpropagation artificial neural networks for testing and training so that the research resulted in an accuracy of 89.6%.DOI : 10.29408/jit.v2i1.976
Identifikasi Kematangan Buah Mentimun Berbasis Citra Digital Menggunakan Jaringan Syaraf Tiruan Backpropagation imam fathurrahman; Amri Muliawan Nur; Fathurrahman Farhurrahman
Infotek: Jurnal Informatika dan Teknologi Vol 2, No 1 (2019): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (492.156 KB) | DOI: 10.29408/jit.v2i1.976

Abstract

Cucumber, cucumber, or cucumber (Cucumis sativus L) are plants that produce edible fruit. Especially in NTB cucumber production in 2015 reached 5,224 tons with a harvest area of 326 hectares. It is at number five after onions, chili, tomatoes and cabbage [2]. There are several parameters that can affect the quality of cucumbers, one of which is the shape, level of planting age and maturity [5]. Maturity of cucumbers can be recognized physically in terms of skin texture and color. The identification process of physical properties conventionally still has many disadvantages including the time needed is relatively long and produces a variety of products due to the limitations of human visuals. This becomes an obstacle so that it requires the application of computer image processing technology, especially in agriculture. Because of this, the researchers proposed using GLCM as feature extraction and using Backpropagation artificial neural networks for testing and training so that the research resulted in an accuracy of 89.6%.DOI : 10.29408/jit.v2i1.976
KLASIFIKASI PENENTUAN PENERIMA PROGRAM KELUARGA HARAPAN (PKH) MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) PADA KANTOR DINAS SOSIAL LOMBOK TIMUR imam fathurrahman; fathurrahman fathurrahman
Infotek: Jurnal Informatika dan Teknologi Vol 3, No 1 (2020): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (53.666 KB) | DOI: 10.29408/jit.v3i1.1802

Abstract

The Family of Hope Program (PKH) is a program of giving cash to Very Poor Households (RTSM) based on established terms and conditions. Where PKH was implemented in Indonesia in 2007, but in East Lombok PKH was only implemented in 2011. However, judging from the data of PKH recipient members, there are still many RTSM who do not get the PKH assistance. This situation identified the data collection method and the determination of priorities that were not yet on target. From these problems, it is necessary to utilize data mining techniques using the support vector machine (SVM) algorithm in determining PKH recipients. After testing 4 times using different K-Fold Validation on the cross validation operator. K-Fold Validation functions to divide the amount of training data and testing data on the data being tested. Then the accuracy results that have been tested are 95.41%.DOI : 10.29408/jit.v3i1.1802
KLASIFIKASI PENENTUAN PENERIMA PROGRAM KELUARGA HARAPAN (PKH) MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) PADA KANTOR DINAS SOSIAL LOMBOK TIMUR imam fathurrahman; fathurrahman fathurrahman
Infotek: Jurnal Informatika dan Teknologi Vol 3, No 1 (2020): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (53.666 KB) | DOI: 10.29408/jit.v3i1.1802

Abstract

The Family of Hope Program (PKH) is a program of giving cash to Very Poor Households (RTSM) based on established terms and conditions. Where PKH was implemented in Indonesia in 2007, but in East Lombok PKH was only implemented in 2011. However, judging from the data of PKH recipient members, there are still many RTSM who do not get the PKH assistance. This situation identified the data collection method and the determination of priorities that were not yet on target. From these problems, it is necessary to utilize data mining techniques using the support vector machine (SVM) algorithm in determining PKH recipients. After testing 4 times using different K-Fold Validation on the cross validation operator. K-Fold Validation functions to divide the amount of training data and testing data on the data being tested. Then the accuracy results that have been tested are 95.41%.DOI : 10.29408/jit.v3i1.1802
Sistem Informasi Geografis Pemetaan Lokasi Stunting Di Desa Gereneng Timur Berbasis Web Imam Fathurrahman; Suhartini Suhartini; Hamzan Ahmadi; Fathurrahman Fathurrahman
Jurnal Komtika (Komputasi dan Informatika) Vol 6 No 2 (2022)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v6i2.8157

Abstract

Cases of malnutrition often occur every year, one of them is in Gereneng Timur Village. Because the community's understanding of stunting is still lacking and it is difficult to obtain information quickly, it is a weakness for local governments to be able to identify locations affected by malnutrition. Case handling has also not been effective because data collection is still being carried out manually by the Village Maternity Boarding School (POLINDES) or the village government. The results of this researcher designed web-based software using the waterfall model in the development process and utilized the Geographic Information System (GIS) in mapping stunting locations in East Gereneng Village which aims to display location points along with the number of toddlers affected by stunting and information on how parents prevent stunting from an early age accessed by the community and village government.
Sistem Informasi Geografis Pemetaan Lokasi Stunting Di Desa Gereneng Timur Berbasis Web Imam Fathurrahman; Suhartini Suhartini; Hamzan Ahmadi; Fathurrahman Fathurrahman
Jurnal Komtika (Komputasi dan Informatika) Vol 6 No 2 (2022)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v6i2.8157

Abstract

Cases of malnutrition often occur every year, one of them is in Gereneng Timur Village. Because the community's understanding of stunting is still lacking and it is difficult to obtain information quickly, it is a weakness for local governments to be able to identify locations affected by malnutrition. Case handling has also not been effective because data collection is still being carried out manually by the Village Maternity Boarding School (POLINDES) or the village government. The results of this researcher designed web-based software using the waterfall model in the development process and utilized the Geographic Information System (GIS) in mapping stunting locations in East Gereneng Village which aims to display location points along with the number of toddlers affected by stunting and information on how parents prevent stunting from an early age accessed by the community and village government.
Co-Authors Arnila Sandi Hamzan Ahmadi Ira Ayu Sekar Dadu L M Samsu M.Yazid Muh. Fathin Kautsar Muhammad Djamaluddin Muhammad, Saiful Nur, Amri Muliawan nurhidayati, nur ida Siti Quthrotunnada Suhartini, Suhartini Yahya, Yahya