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All Journal MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Jurnal EECCIS SMARTICS Journal Applied Information System and Management ILKOM Jurnal Ilmiah JISKa (Jurnal Informatika Sunan Kalijaga) Internet of Things and Artificial Intelligence Journal Jurnal ilmiah teknologi informasi Asia
Ajib Hanani
Universitas Islam Negeri Maulana Malik Ibrahim Malang
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science

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Rancang Bangun Sistem Monitoring Environment Area Tempat Tinggal Mahasiswa Berbasis Internet Of Things Karisma, Alfiana Intan; Kurniawan, Fachrul; Hanani, Ajib
MATICS Vol 11, No 2 (2019): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (416.448 KB) | DOI: 10.18860/mat.v11i2.8416

Abstract

Pencemaran udara muncul menjadi masalah di kota-kota besar seperti pada kota Malang. Kota Malang dikenal sebagai kota Pendidikan, banyak mahasiswa dari luar kota yang menimba ilmu di kota ini. Bertambahnya penghuni maka peningkatan aktivitas manusia akan semain banyak dan menjadi salah satu penyebab pencemaran udara. Pencemaran udara mengandung gas-gas berbahaya seperti gas buang kendaraan bermotor dan asap pabrik, sehingga akan berdampak negatif bagi kesehatan manusia. Hal tersebut dapat diminimalisir dengan dibuat sebuah sistem monitoring lingkungan area tempat tinggal mahasiswa berbasis Internet Of Things (IoT) yang berada disekitar kampus UIN Malang.Perancangan sistem ini bertujuan untuk memberi informasi tingkat kualitas udara yang berasal dari gas buang kendaraan bermotor dan aktivitas gerakan yang terekam disekitar lingkungan tempat tinggal mahasiswa dengan menggunakan teknologi IoT. Alat yang digunakan yaitu sensor MQ-7, Mikrokontroller NodeMCU dan kamera web. Sistem database menggunakan database MSQL dan informasi data berupa grafik dalam aplikasi berbasis web. Setiap sensor gas memiliki tingkat akurasi yang berbeda-beda, untuk mengukur keakuratan sensor MQ-7 menggunakan perhitungan dari rumus Mean Absolute Percentage Error (MAPE). Sensor MQ-7 memiliki nilai akurasi sebesar 58,9% dengan nilai kesalahan 41,1%.
Peningkatan Keamanan Grup Chat Menggunakan Kombinasi Metode RSA, Elgamal, Dan Vigenere Chiper Setiawan, Dwi Risky; Crysdian, Cahyo; Hanani, Ajib
MATICS Vol 11, No 2 (2019): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (508.993 KB) | DOI: 10.18860/mat.v11i2.8438

Abstract

Abstrak—Seiring dengan perkembangan teknologi telepon seluler yang pesat dan  banyaknya penggunaan layanan mobile messenger, maka aspek keamanan menjadi sangat penting untuk dipertimbangkan. Keamanan merupakan masalah  terbesar bagi pengguna mobile messenger pada perusahaan atau enterprise. Maka dibutuhkan aplikasi mobile messenger dengan sistem enkripsi menggunakan kombinasi metode RSA, Elgamal, dan Viginere Cipher yang lebih sulit untuk dipecahkan dari pada menggunakan single metode. Penggunaan kombinasi metode akan meningkatkan konsumsi waktu sebanyak 45%, tingkat keberhasilan dideskripsikan kembali menurun sebanyak 46,2%, dan peningkatan size pesan sebanyak 80% namun aspek keamanan jauh lebih penting. Dengan menggunakan kombinasi metode akan meningkatkan usaha perulangan brute force sebesar 73.496.518,7%.
Pemberian Harakat Bahasa Arab Menggunakan Metode N-Gram dan C5.0 Ajib Hanani; Harry Soekotjo Dachlan; Purnomo Budi Santoso
Jurnal EECCIS Vol 9, No 1 (2015)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (662.412 KB)

Abstract

This research is about an Arabic diacritizer using N-Gram (Quad Gram) and C5.0. The input of application is an undiacritized Arabic sentence. Quad Gram and matching word to known patterns are used to diacritize the undiacritized Arabic sentence. C5.0 is used to simplify the rules for diacritizing the final diacritic mark of word. The output of application is a diacritized Arabic sentence based on morphological and syntactic rules. Then, the diacritized Arabic sentence is converted into speech and spoken by talking avatar using text to speech API. The result of N-Gram (Quad Gram) and matching word to known patterns gives an accuracy of 96% based on morphological rules. The result of C5.0 gives an accuracy of 94% based on syntactic rules. Finally, the result of integrating N-Gram (Gram Quad) and C5.0 gives an accuracy of 90% based on morphological and syntactic rules.Index Terms — Arabic Diacritics, C5.0, N-Gram, Text to Speech.
Deteksi Plagiarisme pada Dokumen Jurnal Menggunakan Metode Cosine Similarity Rito Putriwana Pratama; Muhammad Faisal; Ajib Hanani
SMARTICS Journal Vol 5 No 1: SMARTICS Journal (April 2019)
Publisher : Universitas PGRI Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (403.316 KB) | DOI: 10.21067/smartics.v5i1.2848

Abstract

Plagiarisme merupakan tindakan mengambil gagasan, mengambil hasil riset, mengakuisisi hasil riset, dan meringkas suatu tulisan tanpa menyebutkan sumbernya. Metode cosine similarity merupakan salah satu metode yang dapat digunakan untuk menghitung nilai kemiripan antar dokumen. Tahapan yang dilakukan sistem untuk menghasilkan nilai kemiripan antar dokumen yaitu dengan membandingkan dokumen jurnal yang di upload dengan dokumen repository yang diperoleh dari hasil grabbing data DOAJ dan tersimpan di database. Dalam perhitungan metode yang dilakukan akan diperoleh presentase nilai kemiripan antar dokumen. Setelah itu akan dihitung kembali untuk mencari nilai kemiripan dokumen jurnal antar publisher yang ada di dokumen repository. Berdasarkan skenario uji coba yang dilakukan dengan menghitung jumlah dokumen relevan terambil dibagi dengan jumlah dokumen yang ada dalam database kemudian dikali 100%, maka diperoleh nilai recall pada Aplikasi Deteksi Plagiarisme Menggunakan Metode Cosine Similarity yaitu 13%. Sedangkan untuk memperoleh nilai precision dilakukan skenario pengujian dengan menghitung jumlah dokumen relevan terambil dibagi dengan jumlah dokumen relevan dalam pencarian kemudian dikali 100% diperoleh hasil 8%.
Integrasi Sistem Informasi Akademik dan E-Learning UIN Maulana Malik Ibrahim Malang berbasis Web Service REST Ajib Hanani
SMARTICS Journal Vol 6 No 1: SMARTICS Journal (April 2020)
Publisher : Universitas PGRI Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1540.172 KB) | DOI: 10.21067/smartics.v6i1.4155

Abstract

Universitas Islam Negeri (UIN) Maulana Malik Ibrahim of Malang has Academic Information System (SIAKAD) and E-Learning. They are used to manage the entire academic process in UIN of Malang. SIAKAD has been accessible via the internet and always updated. This is different from E-Learning, which is online and has not updated. The existing E-Learning data is entered manually and not scheduled automatically. In addition, the data entry are very complex, so that management becomes difficult. Data integration between SIAKAD and E-Learning should be created to solve the problem. The REST (REpresentational State Transfer) web service is a great choice of method to integrate many systems and databases. The result shows that data integration between SIAKAD and E-Learning in UIN of Malang can be created using REST web service. The SIAKAD data will be the same as the E-Learning data because the data is already synchronized. The data are data of students, lecturers, faculties, departements and courses. REST web services can be executed on a scheduling automatically using crontab application on Linux or FreeBSD operating system, so the data is no longer entered manually.
Sistem Pengukuran Kualitas Media pada Larva BSF (Black Soldier Fly) Berbasis Internet of Things Menggunakan Metode Naive Bayes Mohammad Faisal Fajar Fadilah; Ajib Hanani; Totok Chamidy
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 8 No. 2 (2023): Mei 2023
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2023.8.2.125-139

Abstract

Piles of waste increase in line with population growth and consumption patterns. The concept of bioconversion using black soldier fly larvae can solve the problem of organic waste management. From these problems, an application of Internet of Things technology is needed. The system implemented aims to allow the system to find out how much accuracy, precision, and recall are in making decisions on media quality values using the Naive Bayes method. The main feature of this Naive Bayes Classifier is the very strong assumption of the independence of each condition or event. From the research results, the system has been successfully built according to the research design, as well as the goals that have been fulfilled in completing the development of the smart maggot. Several sensors used in this study were tested so that sensor performance could be determined by finding the average error value. Three parameters are measured; namely, the temperature obtained an average error of 1.6%, air humidity obtained an average error of 2.03%, and soil moisture obtained an average error of 2.7%. By measuring using Python, the Confusion Matrix is obtained so that the test results from the calculation of the Naive Bayes method can find the data in the form of accuracy, precision, and recall. Accuracy percentage results obtained 92%, precision percentage average results obtained 93%, and recall percentage average results obtained 92%. The conclusion shows the results of the system's accuracy obtained have worked well.
Performance Analysis of LoRaWAN Communication Utilizing the RFM96 Module Yassir, Muhammad; Soepandi, Harry; Hanani, Ajib; Prakasa, Johan Ericka Wahyu; Puspitadewi, Ganis Chandra; Wibowo, Sastya Hendri; Adi, Puput Dani Prasetyo; Kitagawa, Akio
ILKOM Jurnal Ilmiah Vol 16, No 3 (2024)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v16i3.2326.255-270

Abstract

This research discusses the utilization of LoRa and LoRaWAN or Low Power Wide Area (LPWA) and Low Power Wide Area Network (LPWAN). In this study, the application server is utilized using Telkom IoT. In its utilization, Telkom IoT can provide comprehensive results regarding LoRa quality of service capabilities such as bit rate, latency, and longitude and latitude data. Terrestrial measurements conduct tests in different areas with different conditions that cause different data obstruction, with several LoRa end-node points transmitting data with low bit-rate. For example, heart rate data. Some other parameters are the spreading factor (SF) and power consumption. Some parameters that determine the quality of transmitting data include the Spreading Factor and the Bandwidth used. From the analysis dan Experiment results, the Delay (ms) generated from measurements using RFM96 LoRa for IoT is around 0.02 seconds or 20 ms to around 0.05 seconds or 50 ms, and sometimes it can reach 0.07 ms to 0.09 ms. RSSI and SNR show the quality of the signal obtained which will provide a Quality of Service (QoS) value. From the measurement results using Telkom IoT in several times of data collection and testing, the average RSSI (-dBm) is at -110 dBm to -115 dBm. While SNR is at -10 dB to -16 dB.
Smart Home Berbasis IoT Menggunakan Suara Pada Google Assistant Ajib Hanani; Mokhamad Amin Hariyadi
Jurnal Ilmiah Teknologi Informasi Asia Vol 14 No 1 (2020): Volume 14 Nomor 1 (8)
Publisher : LP2M INSTITUT TEKNOLOGI DAN BISNIS ASIA MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32815/jitika.v14i1.456

Abstract

This research builds an IoT based Smart Home using voice command on Google Assistant. It is a solution for sick people who are in wheelchairs / beds or people with disabilities but can speak or elderly people who cannot reach the switch in order to turn on / turn off home devices. In addition, we able to control home devices from any where. The system is built using voice command on the Google Assistant application. Google Assistant converts the voice command to the text command. And then, the text command is forwarded from Google Assistant to Webhooks by IFTTT. Webhooks makes a request to the HTTP RESTful API. The text command is published to MQTT Broker by phpMQTT library available on the HTTP RESTful API. ESP32 Dev Kit as an internet connected microcontroller receives text command from MQTT Broker to turn on or turn off the lights in home. The system testing has succeeded in turning on and turning off the lights with voice commands using Google Assistant.
Detection of Bruteforce Attacks on the MQTT Protocol Using Random Forest Algorithm Akbar, Galuh Muhammad Iman; Hariyadi , Mokhamad Amin; Hanani, Ajib
Internet of Things and Artificial Intelligence Journal Vol. 3 No. 3 (2023): Vol. 3 No. 3 (2023): Volume 3 Issue 3, 2023 [August]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v3i3.630

Abstract

Bruteforce is a hacking technique that launches an attack by guessing the username and password of the system that is the target of the attack. The Bruteforce attack on the MQTT protocol is an attack that often occurs on the IoT, so it is necessary to detect attacks on the MQTT protocol to find out normal traffic and brute force traffic. Random Forest was chosen because this method can classify a lot of data in a relatively short time, and the results from Random Forest can improve accuracy and prevent overfitting in the data classification process. This study uses two types of data: primary data from the hacking environment lab and secondary data from the IEEE Data Port MQTT-IOT-IDS2020 dataset. Trials on primary data and the results obtained are accuracy of 99.55%, precision of 100%, recall of 99.54%, and f-measure of 99.77%, the duration needed to get these results with 1796 data lines, i.e., for 0 seconds. As for the secondary data, the researcher obtained an accuracy of 99.77%, a precision of 100%, a recall of 99.43%, and an f-measure of 98.71%, the duration required to obtain these results with 85002 data lines, i.e., for 62 seconds.
Improving Moodle Performance Using HAProxy and MariaDB Galera Cluster Prakasa, Johan Ericka Wahyu; Hanani, Ajib; Hariri, Fajar Rohman; Utama, Shoffin Nahwa
Applied Information System and Management (AISM) Vol. 7 No. 1 (2024): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v7i1.34871

Abstract

Moodle is a widely used Learning Management System in various educational institutions worldwide. However, frequent reports on internet forums indicate performance degradation when massive simultaneous users access Moodle. One of the most resource-intensive components supporting Moodle is the database, as all user-accessed data is stored in it. This study aims to optimize Moodle’s performance through distributed databases. Distributing the database into multiple database servers allows the database load to be distributed across all the database servers, resulting in an overall improvement in Moodle performance. This study compares the performance of Moodle installed on a single server with that installed on multiple database servers. Various testing parameters are employed to get valid results. Namely, course read, course write, and database performance, utilizing the server performance plugin available in Moodle. This research reveals a performance improvement of 384% in course read, 193% in course write, and 260% in the Moodle database in the multi-server scenario compared to the single-server scenario. This result validates that the database is the most crucial part of Moodle.
Co-Authors Adi, Puput Dani Prasetyo Akbar, Galuh Muhammad Iman Cahyo Crysdian Fachrul Kurniawan Fajar Rohman Hariri Ganis Chandra Puspitadewi Harry Soekotjo Dachlan Harry Soepandi Johan Ericka Wahyu Prakasa Karisma, Alfiana Intan Kitagawa, Akio Mohammad Faisal Fajar Fadilah Mokhamad Amin Hariyadi Muhammad Faisal Muhammad Yassir Purnomo Budi Santoso Rito Putriwana Pratama Sastya Hendri Wibowo Setiawan, Dwi Risky Shoffin Nahwa Utama Totok Chamidy