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All Journal Jurnal Pilar Nusa Mandiri JOURNAL OF APPLIED INFORMATICS AND COMPUTING Unram Journal of Community Service (UJCS) Jurnal Rekayasa Sistem Informasi dan Teknologi Journal of Computer Science and Information Technology Journal of Data Analytics, Information, and Computer Science (JDAICS) Jurnal Computer and Technology
Akbar, Ardiyallah
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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EARLY WARNING SYSTEM FOR FLOOD IN GUNUNGSARI DISTRICT BASED ON IOT WITH TELEGRAM BOT AS A WARNING MESSAGE SENDER Hambali, Hambali; Akbar, Ardiyallah; Yani, Ahmad
Jurnal Pilar Nusa Mandiri Vol 18 No 2 (2022): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v18i2.3711

Abstract

Entering the rainy season with a high level of rainfall will have an impact on vulnerability to floods that will hit a number of areas in various parts of Indonesia. As is often the case in the Gunungsari Sub-district, West Lombok Regency, heavy rains that come early with high intensity for several days often occur, which causes flood disasters and the absence of an automatic system or tool that can detect flooding in the area so that people around the difficulty of detecting floods that come early and cause many people to lose their homes and property due to the flood disaster. The purpose of this study is to provide information related to signs before a flood disaster using the Raspberry Pi 4 as the main tool and the Hc-SR04 ultrasonic sensor as a tool for measuring the distance of an object, where this system can monitor the water level of the river, then disseminate information. related to the water level periodically via Telegram. The test results of the detection sensor system show that the level of accuracy in reading the water level with an average error of 0.48%, indicates that this IoT system has good accuracy.
Design and Implementation of IoT Based Smart Lecture Attendance System at Mataram University of Technology Akbar, Ardiyallah; Zaenudin, Zaenudin; Yani, Ahmad; Muslim, Rudi
Jurnal Pilar Nusa Mandiri Vol 19 No 2 (2023): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v19i2.4608

Abstract

Student attendance is one of the reporting activities that exist in educational institutions. The problem that occurs in educational institutions is that when entering the lecture, many students are late and often absent, which can cause discipline where students often do absenteeism, so lecturers cannot know the number of students who attend accurately. From these problems, a solution is needed to help lecturers recapitulate attendance data. This system uses ESP32 as a data manager, RFID for data reading, and ESP32 to validate student attendance by taking pictures of faces. The data is stored on the web server using ESP32CAM to cover the shortcomings of RFID, which is still card-based, so that it can emphasize the flaws. To simplify the attendance in this study, utilizing the website as an interface to facilitate lecturers in knowing the number of students who are present, late, or absent more efficiently and accurately
Disease Detection of Rice and Chili Based on Image Classification Using Convolutional Neural Network Android-Based Muslim, Rudi; Zaeniah, Zaeniah; Akbar, Ardiyallah; Imran, Bahtiar; Zaenudin, Zaenudin
Jurnal Pilar Nusa Mandiri Vol 19 No 2 (2023): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v19i2.4669

Abstract

The current development of machine learning makes it easier for humans to obtain information, especially from images. The presence of processing assistance from machines can increase the accuracy of the information provided to further convince the recipient of the information. Rice and chili farmers in Indonesia have experienced many disease attacks from several types of plant diseases. Not many farmers understand and are good at guessing the diseases that attack their rice and chili plants. So many rice and chili farmers experienced crop failure. This research aims to build a disease-detection system for rice and chili plants based on Android-based image classification. The machine learning method used is Convolutional Neural Network (CNN) with the Mobile Net version one model combined with the Sequential CNN and Tensor Flow Lite models. The results of the transfer learning evaluation on the Mobile Net version 1 model and the sequential CNN model obtained training accuracy of 0.88% with a loss of 0.34%, validation accuracy of 0.84% with a loss of 0.40%, and testing accuracy of 86% with a loss of 43%. Each uses batch 69 of the total training data stopping at epoch 30 from epoch 100. The results of field testing on the application of rice and chili disease detection on 20 images of rice and chili plants can detect Rice Neck Blast disease with a probability of 75% to 100% and Rice Hispa with a probability of 97% to 100%. It can also detect chili plant diseases such as Chili Yellowish with a probability of 83%, Chili Leaf Spot with a probability of 99%, Chili Whitefly with a probability of 91% to 95, Chili Healthy with a probability of 78% to 99%, and Chili Leaf Curl with a probability 75 to 76%. The probability obtained varies according to how likely damage is to rice and chili plants. CNN with the Mobile Net version one model and the Sequential model can extract and classify images so that it has maximum information processing capabilities. This research can make it easier to help farmers identify diseases that attack their rice and chili plants.
DESIGN AND DEVELOPMENT OF AN INTERNAL QUALITY AUDIT INFORMATION SYSTEM BASED PPEPP CYCLE Yani, Ahmad; Bakti, Lalu Darmawan; Akbar, Ardiyallah; Imran, Bahtiar
Jurnal Pilar Nusa Mandiri Vol. 20 No. 1 (2024): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v20i1.4729

Abstract

The Mataram University of Technology Quality Assurance Institute already has and has established national education standards plus the standards set by universities following Permendikbud number 3 of 2020. However, there are problems with the implementation of Internal Quality Audits, where the implementation of internal quality audits is very less effective and efficient, good in terms of time, cost, and energy. This is because the Mataram University of Technology Quality Assurance Institute only has 3 auditors to audit 12 study programs in one year and even spends two months in a row. This is an important concern for researchers to build and produce an internal quality audit information system application program that can help implement the internal quality audit process carried out by the Mataram University of Technology Quality Assurance Institute. The design of the internal quality audit information system was carried out using the prototyping method. The application of the prototyping method in system design will make information system builders better and more structured. The internal quality audit information system was built using the PHP programming language with the CodeIgniter framework and MySQL as the database and implementing Code-View-Controller (MVC). The main objective of this research is to produce an internal quality audit information system so that it can assist the Mataram University of Technology Quality Assurance Institute in documenting and optimizing higher education quality management in a planned and sustainable manner following the PPEPP cycle
RANCANG BANGUN SMART TRASH BERBASIS IOT (INTERNET OF THINGS) MENGGUNAKAN METODE PROTOTIPYNG MODEL DI DESA BERIRIJARAK Jaelani, Lalu Rizki; Lalu Delsi Samsumar; Zaenudin, Zaenudin; Akbar, Ardiyallah
Journal of Computer Science and Information Technology Vol. 1 No. 4 (2024): September
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70248/jcsit.v1i4.1231

Abstract

Penelitian ini bertujuan untuk mengembangkan sistem smart trash atau tempat sampah pintar yang terintegrasi dengan jaringan Internet of Things (IoT) dan dapat diakses melalui aplikasi Telegram, guna memudahkan petugas dalam memonitor kondisi sampah. Metode penelitian yang digunakan adalah metode Prototyping dan kualitatif. Metode Prototyping digunakan untuk membangun prototipe sebelum mengembangkan sistem secara keseluruhan, sementara metode kualitatif mendukung proses pengumpulan data dan analisis. Sistem ini dirancang untuk merespons secara cepat dan akurat terhadap deteksi kapasitas sampah, yang kemudian ditampilkan dalam bentuk notifikasi melalui aplikasi Telegram dan platform web. Hasil penelitian menunjukkan bahwa sistem smart trash berbasis IoT ini efektif dalam mendeteksi volume sampah menggunakan sensor ultrasonik HCSR04. Informasi tentang kapasitas sampah disajikan dalam bentuk visualisasi yang informatif dan dapat diakses dari jarak jauh. Sistem ini juga dilengkapi dengan fitur otomatis yang memungkinkan penutup tempat sampah terbuka dan tertutup, serta pemberian notifikasi saat sampah penuh. Selain itu, sistem dapat memonitor pengambilan sampah dan mengeluarkan suara saat penutup tempat sampah bergerak, dengan dukungan output LCD, DFPlayer Mini MP3, dan bot Telegram. Penelitian ini memberikan kontribusi penting dalam pengembangan sistem smart trash yang handal, terintegrasi dengan IoT, dan memudahkan proses monitoring sampah di desa. Sistem ini berpotensi meningkatkan kebersihan lingkungan dan memudahkan petugas dalam pengelolaan sampah secara efisien. Kata Kunci: Smart Trash, IoT, sensor ultrasonik HCSR04, Aplikasi Telegram, Notifikasi, Web  
RANCANG BANGUN ALAT PEMISAH SAMPAH CERDAS BERBASIS INTERNET OF THINGS Gunawan, Tony; Subki, Ahmad; Akbar, Ardiyallah; Samsumar, Lalu Delsi; Supardianto, Supardianto
Journal of Computer Science and Information Technology Vol. 1 No. 4 (2024): September
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70248/jcsit.v1i4.1279

Abstract

Jumlah sampah yang meningkat di kota-kota menimbulkan tantangan yang signifikan bagi sistem pengelolaan sampah. Sampah yang dipisahkan secara manual biasanya kurang efisien dan membutuhkan banyak tenaga kerja. Dengan merancang dan mengembangkan sebuah model alat pemisah sampah cerdas yang berbasis Internet of Things (IoT), penelitian ini berusaha mengatasi masalah ini. Dengan menggunakan mikrokontroler Arduino Uno dan NodeMCU ESP8266, alat ini dilengkapi dengan sensor infrared untuk mendeteksi sampah, sensor proximity induktif untuk menentukan jenis sampah, dan sensor ultrasonik untuk memantau kapasitas tempat sampah. Kompartemen tempat sampah digerakkan oleh servo motor. Untuk pemantauan jarak jauh, data sensor diproses dan dikirim melalui aplikasi Blynk dan Telegram. Hasil penelitian menunjukkan bahwa sistem ini memiliki kemampuan untuk membedakan sampah logam dan non-logam secara otomatis dan untuk memberikan notifikasi ketika tempat sampah penuh. Penggunaan teknologi Internet of Things (IoT) dalam pengelolaan sampah diharapkan dapat mempercepat proses daur ulang secara lebih efisien serta mendorong peningkatan kesadaran masyarakat akan pentingnya pengelolaan sampah yang lebih baik.
SISTEM PAKAR DIAGNOSIS PENYAKIT PADA TANAMAN KACANG HIJAU BERBASIS WEB MENGGUNAKAN METODE DEMPSTER SHAFER Hamim, Lutfi; Imran, Bahtiar; Akbar, Ardiyallah
Journal Computer and Technology Vol. 1 No. 1 (2023): Juli 2023
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/comtechno.v1i1.77

Abstract

Kacang hijau merupakan salah satu tanaman kacang-kacangan yang penting di Indonesia karena memiliki banyak gizi dan sebagai sumber pangan berprotein nabati tinggi. Namun dalam perkembangannya banyak pula tanaman kacang hijau yang terserang berbagai macam penyakit apalagi pada saat musim penghujan. Ketersediaan Waktu penyuluhan pun minim disebabkan banyaknya lokasi yang harus dikunjungi.Oleh karena itu perlu adanya sistem pakar yang mampu memberikan informasi tentang penyakit penyakit tanaman kacang hijau dan solusi permasalahannya. Penelitian ini bertujuan untuk membangun sistem pakar yang dapat mendiagnosa 3 jenis penyakit pada tanaman Kacang Hijau dari 17 gejala dengan menggunakan metode Dempster-Shafer berbasis website. Hasil uji coba menunjukkan bahwa sistem pakar ini memiliki tingkat akurasi diagnosa sebesar 80%, yang menunjukkan efektivitasnya dalam membantu mengidentifikasi jenis penyakit yang menyerang tanaman kacang hijau. Metode Dempster-Shafer yang digunakan dalam sistem ini memungkinkan penggabungan informasi dari berbagai gejala penyakit, sehingga memberikan hasil diagnosa yang lebih tepat dan akurat.
CYBER BULLYING SENTIMENT ANALYSIS BASED ON SOCIAL CATEGORIES USING THE CHI-SQUARE TEST Hadi, Zulpan; Suryadi, Emi; Akbar, Ardiyallah; Zaenudin; Muslim, Rudi
Journal Computer and Technology Vol. 2 No. 1 (2024): Juli 2024
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/comtechno.v2i1.144

Abstract

This research evaluates various machine learning models in classifying sentiment in cyberbullying data across six categories: not_cyberbullying, gender, religion, other_cyberbullying, age, and ethnicity. Using a Bag of Words approach combined with Chi-Square feature selection (1000 features), models tested include SVM, Logistic Regression, Naïve Bayes, KNN, and Random Forest. Results show SVM and Logistic Regression achieving the highest accuracy at 83%, indicating their effectiveness in prediction. Naïve Bayes performed the poorest with 62% accuracy, suggesting a mismatch with the data or need for further tuning. KNN and Random Forest showed good performance with 75% and 81% accuracy respectively, though not as high as SVM and Logistic Regression. This multi-algorithm approach provides insights into each model's effectiveness and behavior on diverse data characteristics, essential for understanding the unique nuances of each cyberbullying category. Model selection should consider accuracy, interpretability, computational cost, and suitability to specific problem characteristics. This research aims to deepen understanding of cyberbullying to support more effective mitigation strategies.
A PERANCANGAN DAN IMPLEMETASI SISTEM KONTROL SEPEDA MOTOR BERBASIS SIDIK JARI DAN MOBILE UNTUK KEAMANAN KENDARAAN Wadi, Hamzan; Suryadi, Emi; Akbar, Ardiyallah; Samsumar, Lalu Delsi
Jurnal Rekayasa Sistem Informasi dan Teknologi Vol. 2 No. 2 (2024): November
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70248/jrsit.v2i2.1415

Abstract

Angka pencurian kendaraan bermotor yang tinggi menuntut sistem keamanan yang lebih canggih. Penelitian ini merancang sistem kontrol sepeda motor berbasis sidik jari dan aplikasi mobile untuk meningkatkan keamanan kendaraan. Masalah yang diangkat adalah kelemahan sistem konvensional berbasis kunci fisik yang rentan hilang atau dicuri. Tujuan penelitian ini adalah mengembangkan sistem yang hanya bisa diakses oleh pemilik sah melalui sensor sidik jari dan aplikasi Blynk. Metode penelitian yang digunakan adalah prototipe dengan pendekatan kualitatif untuk memahami kebutuhan pengguna dan menguji efektivitas sistem keamanan. Alat utama yang digunakan mencakup NodeMCU ESP32, sensor sidik jari AS608, dan aplikasi Blynk, dengan tahapan penelitian meliputi perancangan, pengujian, dan evaluasi sistem. Hasil pengujian menunjukkan bahwa sistem ini mampu mendeteksi sidik jari pemilik yang sudah terdaftar secara akurat, dengan respons cepat dalam mengaktifkan mesin dan kelistrikan motor baik secara otomatis maupun melalui aplikasi blynk. Sistem terbukti efektif dalam mencegah akses tidak sah tidak dapat mengaktifkan mesin dan kelistrikan motor dan memungkinkan kontrol jarak jauh melalui aplikasi blynk. Solusi ini memberikan keamanan yang lebih baik dan efisien bagi pemilik sepeda motor di era digital. Kata Kunci: Keamanan Motor, Sidik jari, Blynk,NodeMCU, IoT
RANCANG BANGUN PINTU GARASI OTOMATIS BERBASIS INTERNET OF THINGS(IoT) DENGAN NODEMCU DAN APLIKASI BLYNK Buchtami, Lalu Reza; Suryadi, Emi; Akbar, Ardiyallah; Zaenudin, Zaenudin; i Samsumar, Lalu Delsi
Journal of Data Analytics, Information, and Computer Science Vol. 1 No. 4 (2024): Oktober
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70248/jdaics.v1i4.1327

Abstract

Penggunaan Internet of Things (IoT) dalam aplikasi pintu garasi otomatis semakin populer untuk meningkatkan keamanan dan kenyamanan. Skripsi ini mengimplementasikan pintu garasi otomatis yang terhubung online dengan NodeMCU sebagai kontrol utama, sensor ultrasonik untuk deteksi objek di sekitar pintu garasi, dan sensor infrared di dalam garasi untuk mendeteksi kendaraan yang masuk. Aplikasi Blynk digunakan sebagai antarmuka pengguna untuk mengelola status pintu garasi dari jarak jauh melalui perangkat mobile. Fitur utama sistem ini adalah Telegram Bot yang mengirimkan notifikasi langsung saat sensor infrared mendeteksi keberadaan kendaraan di dalam garasi. Ini memberikan pengawasan realtime yang responsif terhadap aktivitas garasi. Metode penelitian mencakup pengembangan perangkat keras menggunakan NodeMCU, konfigurasi aplikasi Blynk, dan integrasi Telegram Bot untuk notifikasi. Hasil Penelitian menunjukkan bahwa sistem dapat berfungsi dengan baik dalam mengotomatisasi akses pintu garasi dan meningkatkan keamanan dengan notifikasi langsung via Telegram. Penelitian ini menegaskan bahwa IoT dapat memberikan solusi efektif dalam mengoptimalkan teknologi rumah pintar yang lebih terhubung dan aman.
Co-Authors ahmad yani Amiruddin Kalbuadi Buchtami, Lalu Reza Hambali Hambali Hamim, Lutfi Hamzan Wadi Imran, Bahtiar Jaelani, Lalu Rizki Juniyardi, Lalu Karim, Muh Nasirudin Kembang, Lale Puspita Lalu Darmawan Bakti, Lalu Darmawan Lalu Delsi Samsumar, M.Eng. Rudi Muslim Sriasih, Sriasih Subki, Ahmad Supardianto Supardianto Suryadi, Emi Tony Gunawan Zaeniah Zaeniah Zaenudin Zaenudin Zaenudin Zulpan Hadi