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All Journal Agromet Jurnal Teknologi Informasi dan Ilmu Komputer CESS (Journal of Computer Engineering, System and Science) Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Jurnal Ilmiah FIFO Faktor Exacta Petir Kilat Jurnal Manajemen Informatika JURNAL TEKNIK TERANG : Jurnal Pengabdian Pada Masyarakat Menerangi Negeri
Haris, Abdul
Institut Teknologi PLN
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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Pembangunan Aplikasi Kepegawaian untuk SD Islam Terpadu Yasir Di Cipondoh Tangerang Karina Djunaidi; Rosida Nur Aziza; Abdul Haris; Renaldi Bagas P.
Terang Vol 3 No 1 (2020): TERANG : Jurnal Pengabdian Pada Masyarakat Menerangi Negeri
Publisher : Sekolah Tinggi Teknik - PLN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33322/terang.v3i1.1020

Abstract

SDIT Yasir is one of the schools under the management of the Ibnu Rusydi Islamic Education Foundation in Cipondoh, Tangerang. The school that aspires to create Indonesian young generations that resemble Ibnu Rusydi has several obstacles in carrying out daily teaching and learning activities. One of the issues is the teacher and staff data management. Therefore, the PKM team from the Informatics Engineering Department IT PLN intends to help the Yasir SDIT school by designing a web-based application for handling the employees. The application can be used to manage teacher and employee data, monitor teacher and employee attendances, and provide teacher performance assessments. Keywords: SDIT Yasir, PKM, Employee Information System
Teknologi Irigasi Cerdas pada Sistem Irigasi Drip dengan Algoritma Ant Colony Optimization Abdul Haris; Nabilla Anggraini; Hengki Sikumbang
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 9 No 6: Desember 2022
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2022955871

Abstract

Rendahnya penggunaan sistem irigasi modern di Indonesia menyebabkan produktivitas lahan yang rendah, terlebih di musim kemarau hal ini dapat menyebabkan banyak lahan yang tidak produktif. Sementara di sisi lain, perkembangan teknologi komputasi sudah masuk dalam berbagai bidang kehidupan, termasuk pertanian.  Contoh penerapan teknologi di bidang pertanian adalah diperkenalkannya sistem irigasi drip. Banyak peneliti yang telah melakukan kajian dan inovasi di bidang ini untuk menghasilkan irigasi yang baik dan optimal, antara lain dengan mengimplementasikan gabungan Internet of Things (IoT) sebagai infrastruktur, Fuzzy Logic dan Artificial Neural Network (ANN) sebagai algoritma untuk menentukan waktu buka tutup dari Solenoid Valve dalam pengaturan distribusi air.  Penelitian yang ada hanya berfokus pada Open/Close solenoid valve. Penelitian ini menggunakan algoritma Ant Colony Optimiation (ACO) untuk mengendalikan katup tersebut, sekaligus melakukan tracking lokasi lahan yang menjadi prioritas irigasi. Algoritma ini dapat bekerja secara dinamis dan adaptif, sehingga mampu menyesuaikan dengan kondisi lahan yang ada  dan  dapat dimonitor secara realtime. Uji coba dilakukan dengan menggunakan 3 sensor, sebagai representasi 3 kondisi lahan yakni lahan basah, lahan normal dan lahan kering.  Hal ini dilakukan untuk memastikan model yang dibuat dapat bekerja sesuai dengan kondisi lahan yang ada.  Dari hasil pengujian yang dilakukan selama 10 hari,  tingkat persentasi error model mencapai 26%  dan  nilai akurasi model adalah 74%. Dari hasil yang diperolah, dapat disimpulkan bahwa hasil penelitian ini bekerja dengan baik untuk sistem irigasi drip  skala kecil yang dinamis. AbstractThe low use of modern irrigation systems in Indonesia leads to low land productivity, especially in the dry season this can result to many areas of unproductive land.  At the same time, the development of computing technology has entered various areas of life, including agriculture.   An example of the application of technology in agriculture is the introduction of drip irrigation systems.  Many researchers have conducted studies and innovations in this matter to produce a better and more optimal irrigation, for example, by implementing a combination of Internet of Things (IoT) for the infrastructure, Fuzzy Logic and Artificial Neural Network (ANN) as algorithms to determine when the lid of the Solenoid Valve is open or closed.   Existing research only focuses on the Open / Close solenoid valve, meanwhile this research   uses the Ant Colony Optimiation (ACO) algorithm to control the valve and provide the tracking ability to determine the area that needs irrigation the most. This algorithm can work dynamically and adaptively, so it is able to adjust to the land conditions and can be monitored in real time.  The testing is conduvted using 3 sensors, as a representation of 3 land conditions, namely wetlands, normal land, and dry land.  This is done to ensure the prototype can work in accordance with existing land conditions.   From the results of the test conducted for 10 days, the model error percentage rate reached 26% and the model accuracy value was 74%.  Thus, it can be concluded that the result of this study work well for dynamic small-scale drip irrigation systems.
Klasifikasi Citra Penyakit Daun Cabai Menggunakan Algoritma Learning Vector Quantization Puji Catur Catur Siswipraptini; Abdul Haris; Winda Novita Sari
Faktor Exacta Vol 16, No 2 (2023)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v16i2.15900

Abstract

The problem often occurs in chili leaves is organisms that interfere with chili plants which can reduce chili production. There are chili plant diseases that are difficult for farmers to recognize by using their eyes and without using tools. The purpose of this study was to produce a model capable of identifying chili leaf diseases based on leaf colour in order to make it easier for farmers to identify chili leaf diseases, especially  Phytophthora, Anthracnose, and Cercospora diseases, using the Learning Vector Quantization (LVQ) classification algorithm. Data was collected in the form of digital images of 30 chili leaves which were processed by resizing and transforming RGB to HSV which then proceeded to Canny Edge detection process with the aim of getting patterns from images of chili leaves. The result of testing LVQ algorithm using a confusion matrix get an accuracy of 80%, the precision value of 80%, recall value of 82%, and f-1 score of 81%. 
Otomatisasi Pada Sistem Penerimaan Siswa Baru (PSB) MAS Annida Al Islamy Duri Kosambi Jakarta Barat Rahma Farah Ningrum; Efy Yosrita; Rosida Nur Aziza; Puji Catur Siswipraptini; Abdul Haris; Karina Djunaidi; Riki Ruli A. Siregar
Terang Vol 5 No 2 (2023): TERANG : Jurnal Pengabdian Pada Masyarakat Menerangi Negeri
Publisher : Sekolah Tinggi Teknik - PLN

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Perkembangan TI menuntut setiap orang untuk merubah kebiasaan lama dalam beraktivitas menjadi lebih inovatif. Dunia Pendidikan salah satunya, yang memiliki jenjang dalam pembelajaran harus bisa mengakomodir tuntutan zaman yang semakin cepat. MAS Annida Al Islamy yang berlokasi di Duri Kosambi, Cengkareng Jakarta Barat merupakan sekolah yang mengimplementasikan konsep pendidikan Islam berlandaskan Al-Qur’an dan As Sunnah. Penerapan teknologi informasi dalam bentuk Sistem Informasi Penerimaan Siswa Didik Baru diharapkan menjadi nilai lebih bagi sekolah MAS Annida Al Islamy ini dan dapat meningkatkan kemudahan bagi MAS Annida Al Islamy dari segi pengelolaan administrasi sekolah. Kegiatan pengabdian pada masyarakat akan dilaksanakan oleh Tim dari Fakultas Telematika Energi Institut Teknologi PLN ini merupakan program lanjutan dari kegiatan Pengabdian sebelumnya. Selain menyempurnakan Sistem Informasi yang telah dibangun, kegiatan pengabdian kali ini juga akan menyelenggarakan pelatihan bagi guru/staf dalam hal pengelolaan sistem informasi berbasis web. Pemberian pelatihan, pendampingan, manajemen sistem dan bantuan pembuatan sistem yang dibutuhkan mitra akan dilaksanakan selama 10 bulan.
The Use of Artificial Neural Networks to Estimate Reference Evapotranspiration Haris, Abdul; Marimin; Wahjuni, Sri; Setiawan, Budi Indra
Agromet Vol. 39 No. 1 (2025): JUNE 2025
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.39.1.1-7

Abstract

Evapotranspiration is defined as the loss of water from soil and vegetation to the atmosphere, driven by weather conditions. It reduces the availability of water for agricultural purposes, which affects the amount of irrigation water, particularly during the dry season. The objective of this paper is to present a comparative analysis of the estimated reference evapotranspiration value based on artificial neural networks (ANN) with backpropagation bias 1 (BP-1) and backpropagation bias 0 (BP-0) architectures. The model was fed with data of air temperature, relative humidity, and solar radiation. The model is utilized to calculate the evapotranspiration using the Hargreaves method as the training data. The performance of ANN model was evaluated using the mean square error (MSE), root mean square error (RMSE), and coefficient determination (R2). Our results showed that both ANN models performed well as indicated by low error (MSE < 0.01) and high R2 (>0.99). Also, we found that air temperature and relative humidity determine the optimal prediction. Further, this proposed model can serve as a reference for other models seeking to determine the most appropriate computational model for evapotranspiration value estimation.
Co-Authors Abdurrasyid Abdurrasyid Abdurrasyid Abdurrasyid, Abdurrasyid Abdurrasyid, Abdurrasyid Alan Burhan Aminuyati Budi Indra Setiawan Edwin Hendrian Efy Yosrita Efy Yosrita Hengki Sikumbang Hengki Sikumbang Hengki Sikumbang Herman Bedi Agtriadi Indrianto Indrianto Karina Djunaidi Karina Djunaidi L.M Syahrul Anwar Luqman Luqman Luqman Luqman Luqman, Luqman Marimin , Monica Sianturi Muhammad Jafar Elly Nabilla Anggraini Nina Nirmaya Ningrum, Rahma Farah Puji Catur Catur Siswipraptini Puji Catur Siswipraptini Puji Catur Siswipraptini Puji Puji Rahma Farah Ningrum Rahma Farah Ningrum Randi Adrika Putra Renaldi Bagas P. Riki Ruli A. Siregar, Riki Ruli A. Rizqia Cahyaningtyas Rosida Nur Aziza Rosida Nur Aziza Rosida Nur Aziza Rosida Nur Aziza Rosida Nur Aziza Sri Wahjuni Trisma Juwita Winda Novita Sari