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All Journal Jurnal Informatika dan Teknik Elektro Terapan Jurnal Edik Informatika : Penelitian Bidang Komputer Sains dan Pendidikan Informatika International Journal of Artificial Intelligence Research JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JITK (Jurnal Ilmu Pengetahuan dan Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) METIK JURNAL Vocatech : Vocational Education and Technology Journal Jurnal Computer Science and Information Technology (CoSciTech) International Journal of Engineering, Science and Information Technology TECHSI - Jurnal Teknik Informatika Jurnal Teknologi Terapan and Sains 4.0 Journal of Computer Engineering, Electronics and Information Technology Jurnal Informatika: Jurnal Pengembangan IT Jurnal Malikussaleh Mengabdi
Muhammad Fikry
Teknik Informatika Universitas Malikussaleh
Religion Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Decision Support System (DSS) Determining Credit Customer Pada PT. Bank Rakyat Indonesia (Persero) Tbk Fikry, Muhamamd
Jurnal EDik Informatika Vol 1, No 1 (2014)
Publisher : STKIP PGRI Sumatera Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (399.267 KB) | DOI: 10.22202/ei.2014.v1i1.1437

Abstract

Computer as one advance sintechnology can help people to improve the quality and quantity of work, as well ashelp in getting the information and decision-making to decision making. The concept of decision support systems (decision support system) is one branch of artificial intelligence (artificial intelligence) that is widely used to help makea decision. Many methods can beapplied to decision support system to help providea solutioninaproblemalternaif. One such methodis a method ofdata cleaningand datatransformation. This method will help to process in complete data into acomplete data, then transform the data using theme thods of data transformation.Keywords: decision support system, data cleaning, data transformasi, determining credit
Data Envelopment Analysis with Lower Bound on Input to Measure Efficiency Performance of Department in Universitas Malikussaleh Dahlan Abdullah; Cut Ita Erliana; Muhammad Fikry
International Journal of Artificial Intelligence Research Vol 4, No 1 (2020): June
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (299.606 KB) | DOI: 10.29099/ijair.v4i1.164

Abstract

DEA has become one of the most appropriate methods for comparing the various Decision-Making Units (DMU) associated with public services such as universities.  There are two primary outputs that can be used to measure college performance, namely: the number of graduates and the number of publications.  While the primary input of college efficiency measurement is the number of teaching staff and the number of students.  The higher learning institution is  Universitas Malikussaleh, located in Lhokseumawe, a city in the Aceh province of Indonesia. This paper develops a method to evaluate the efficiency of all departments in Universitas Malikussaleh using DEA with bounded input. The extreme dissimilarity between the weights often found in DEA applications. In this paper, we develop a new DEA model, which can be transformed into a particular case of the bi-level linear program to calculate the lower boundary of input from the pessimistic viewpoints based on the shortcomings of the existing approaches. In the case of having a single input, providing lower bounds for the input weights by imposing the conditions that it uses for the average input level of the DMU being assessed uses per unit of output.  Accordingly, we present some essential differences inefficiency of those departments. Finally, we discuss the effort that should be made by these departments in order to become efficient
Automatic Control System Using Arduino UNO and Web-Based Monitoring For Watering Chili Plants Rizal Tjut Adek; Muhammad Fikry; Helmi Naluri; Risawandi .
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 5, No 2 (2022): Issues January 2022
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v5i2.5495

Abstract

Caring for chili plants in addition to fertilization is proper watering. Watering is sometimes done less regularly in this case is the timeliness other than that the temperature and soil moisture are not paid attention to by the chili plant keepers. Moreover, if the chili plant keeper has other activities, then the watering of the plants will be more irregular, making the production of chili plants not optimal and even chili plants can die. By utilizing Arduino and several supporting sensors, we can determine the right watering time. In this research, data is taken from sensors, such as soil moisture sensors, air humidity sensors, temperature sensors and ultrasonic sensors which then the data will be sent to the website to be displayed to the user. Sensors are devices used to detect changes in physical quantities such as pressure, force, electrical quantities, light, motion, humidity, temperature, speed and other environmental phenomena. The purpose of this study was to measure soil moisture, air humidity, temperature as a determinant of the right watering time for chili plants and make it easier for farmers to monitor and water chili plants. This is evidenced in the Blackbox testing method on the system design, from the test results it is known that this system has been running well and is in accordance with what is expected.
News Opinion Classification Application With Support Vector Machine Algorithm Using Framework Codeigniter Rizal Tjut Adek; Muhammad Fikry; Umar Khalil
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 5, No 1 (2021): EDISI JULY 2021
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v5i1.5189

Abstract

News is an information that contains a lot of data, one of which is data about opinion / sentiment. The opinion / sentiment data of a news can be used for many things. To get the opinion value of a news, it is necessary to do a sentiment analysis technique on the news data that wants to know the level of opinion produced. Sentiment analysis is a technique that uses the data mining method. To see the height of the opinion value of a news item, the Support Vector Machine algorithm is used, which is one of the algorithms in the data mining method that is able to classify data sets into two classes. Using the CodeIgniter framework based on the PHP programming language, an application was developed that can classify the news into two classes, namely the positive class and the negative class. By using 100 pieces of news data from the national news portal, namely detik.com, about 700 sentences and more than 1000 words are generated which are then classified using the SVM algorithm. Applications are able to achieve an accuracy rate of 76%
OPINION MINING ABOUT PARFUM ON E-COMMERCE BUKALAPAK.COM USING THE NAÏVE BAYES ALGORITHM Rizal Rizal; Muhammad Fikry; Annisa Helmina
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 1 (2020): JITK Issue August 2020
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1403.945 KB) | DOI: 10.33480/jitk.v6i1.1448

Abstract

Information plays a very important role in the rapid development of the world. Many people use online media to search for information, one of which is to find out information about the negative or positive of a product in e-commerce based on the comments that exist. To find out the classification of all comments-comet takes quite a long time in reading it. So, to make it easier than that all made a classification system to determine the classification of comments. In this classification process, the Naive Bayes algorithm is used as a solution to the problem. The process with the Naïve Bayes algorithm requires training data which is used as learning material from the system. The training data used is taken from one e-commerce site, Bukalapak.com regarding perfume products. Taking comments from Buakalapak.com used crawling techniques to retrieve comments from the whole product. The training data needed in this system is 1000 comments consisting of 500 positive training comments and 500 negative training comments. To get the accuracy value, it requires 300 test comments consisting of 150 positive test comments and 150 negative test comments. From the results of testing with Naive Bayes, the accuracy rate can be quite good, namely with a precision value of 96.44%, 96.34% recall, and an accuracy of 96.33%.
APLIKASI PERAMALAN KURS BITCOIN-RUPIAH DENGAN MENGGUNAKAN METODE DOUBLE EXPONENTIAL SMOOTHING Hizamrul jaen; Eva Darnila; Muhammad Fikry
TECHSI - Jurnal Teknik Informatika Vol 11, No 1 (2019)
Publisher : Teknik Informatika Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/techsi.v11i1.1295

Abstract

Perkembangan teknologi meghadirkan banyak inovasi. Salah satu inovasi teknologi adalah berkembangnya Cryptocurrency atau mata uang Kripto. Salah satu jenis Cryptocurrency adalah Bitcoin. Karena beberapa faktor, Bitcoin menjadi terkenal di seluruh dunia, sehingga sering diperdagangkan layaknya perdagangan mata uang pada umumya. Namun karena belum adanya regulasi dari pemerintah, membuat harga bitcoin menjadi tidak terkendali sehingga sering terjadi fluktuasi besar besaran. Metode Double Exponential Smoothing adalah sebuah metode yang sering diguakan dalam kebutuhan Forecastng. Metode ini memanfaatka  data historis pada priode tertentu dalam proses prediksi. Untuk metode ini akan diuji dalam sebuah rancangan dan pengembangan system berbasis web, dimana sampel data akan di kalkulasikan dengan Metode Double Exponential Smoothing. Penelitian ini menguji sekitar 5 data setiap harinya selama 10 hari, dengan parameter a (alpha) 0.4035. menghasilkan tingkat akurasi senilai 70%. Hasil peramalan itu akan di sajikan dalam bentuk tabel dan grafik. Key Words : Bitcoin, Forecasting, Double Exponential Smoothing, Kurs, Cryptocurrency
APLIKASI JAVA KRIPTOGRAFI MENGGUNAKAN ALGORITMA VIGENERE Muhammad Fikry
TECHSI - Jurnal Teknik Informatika Vol 8, No 1 (2016)
Publisher : Teknik Informatika Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/techsi.v8i1.112

Abstract

Data merupakan aset yang paling berharga untuk dapat menghasilkan informasi penting. Untuk menjaga keamanan data yang tersimpan, salah satu caranya dengan menggunakan metode kriptografi untuk menyembunyikan data asli tersebut sehingga tidak dapat dilihat oleh pihak yang tidak berhak. Salah satu bagian dari metode kriptografi adalah algoritma Vigenere yang termasuk dalam algoritma Simetrik dengan cara kerja enkripsi dilakukan secara mengalir menggunakan enkripsi dengan kunci yang mengalir juga. Algoritma Vigenere dianalisa dan disimulasikan kinerjanya pada Personal Computer, lalu dibangun aplikasi menggunakan pemrograman Java sebagai user interface.
Sistem Pendeteksi Pola Citra Tajwid Alquran Mad Lazim Mutsaqal Kilmi Menggunakan Metode Algoritma BAM & FAM Muhammad Fikry; Fadlisyah Fadlisyah; Dessayani Putri
TECHSI - Jurnal Teknik Informatika Vol 10, No 2 (2018)
Publisher : Teknik Informatika Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/techsi.v10i2.885

Abstract

Alquran merupakan pedoman umat Islam dan berisikan firman Allah yang diturunkan kepada Nabi Muhammad sebagai penutup para nabi dan rasul dengan perantaraan Malaikat Jibril sebagai penyampai wahyu dan ditulis pada mushaf-mushaf yang kemudian disampaikan kepada manusia secara mutawatir, dimulai dari surat Al-Fatihah sebagai pembuka dan surat An-Nas sebagai penutup. Untuk itu penting mengetahui hukum tajwid agar bacaan Alquran menjadi benar. Pada penelitian akan dibangun sistem untuk mendeteksi tajwid dengan membandingkan keakuratan deteksi pola hukum tajwid Mad Lazim Mutsaqal Kilmi dalam surah Ali Imran dengan menggunakan metode algoritma BAM dan FAM. Dari hasil pendeteksian yang telah dilakukan didapatkan bahwa metode Bidirectionaal Associative Memory (BAM) memiliki tingkat akurasi lebih tinggi dalam melakukan pencarian pola tajwid dibandingkan dengan metode Fuzzy Associative Memory (FAM).
SISTEM PENDUKUNG KEPUTUSAN MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING (SAW) DALAM PEMBERIAN KREDIT Muhammad Fikry
TECHSI - Jurnal Teknik Informatika Vol 9, No 1 (2017)
Publisher : Teknik Informatika Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/techsi.v9i1.206

Abstract

Ada beberapa faktor yang harus dipertimbangkan dalam mengambil keputusan pemberian kredit kepada nasabah, agar tidak terjadi kesalahan yang menyebabkan kerugian. Semakin banyak calon nasabah yang mengajukan kredit dengan kondisi ekonomi yang berbeda-beda, menuntut kejelian dalam pemberian kredit. Sehingga keputusan yang diambil merupakan keputusan yang terbaik bagi pihak bank dan pihak pemohon kredit. Sistem pendukung keputusan pemberian  kredit dibuat dengan tujuan membantu dan mempermudah pihak pengambil keputusan. Sistem pendukung keputusan memberikan alternatif diterima atau tidaknya pengajuan kredit nasabah menggunakan metode Simple Additive Weighting. Konsep dasar metode Simple Additive Weighting adalah mencari penjumlahan terbobot dari rating kinerja pada setiap alternatif attribut. Metode Simple Additive Weighting membutuhkan proses normalisasi matrik keputusan kesuatu skala yang dapat diperbandingkan dengan semua rating alternatif yang ada. Adapun kriteria yang digunakan dalam metode ini ada tujuh kriteria. Dari kriteria tersebut dilakukan proses perhitungan masing-masing kriteria untuk mendapatkan hasil alternatif terbaik nasabah yang layak menerima kredit.
Analysis of Model-Free Reinforcement Learning Algorithm for Target Tracking Muhammad Fikry; Rizal Tjut Adek; Zulfhazli Zulfhazli; Subhan Hartanto; Taufiqurrahman Taufiqurrahman; Dyah Ika Rinawati
Journal of Computer Engineering, Electronics and Information Technology Vol 1, No 1 (2022): COELITE: Volume 1, Issue 1, 2022
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (574.106 KB) | DOI: 10.17509/coelite.v1i1.43795

Abstract

Target tracking is a process that can find points in different domains. In tracking, some places contain prizes (positive or negative values) that the agent does not know at first. Therefore, the agent, which is a system, must learn to get the maximum value with various learning rates. Reinforcement learning is a machine learning technique in which agents learn through interaction with the environment using reward functions and probabilistic dynamics to allow agents to explore and learn about the environment through various iterations. Thus, for each action taken, the agent receives a reward from the environment, which determines positive or negative behavior. The agent's goal is to maximize the total reward received during the interaction. In this case, the agent will study three different modules, namely sidewalk, obstacle, and product, using the Q-learning algorithm. Each module will be training with various learning rates and rewards. Q-learning can work effectively with the highest final reward at a learning rate of 0.8 for 500 rounds with an epsilon of 0.9.
Co-Authors Annisa Helmina Aynun, Nur Azzahra Iskandar, Farah Bustami Bustami Cut Ita Erliana Dahlan Abdullah Dessayani Putri Dyah Ika Rinawati Eva Darnila Fadlisyah Fadlisyah Fajriana, Fajriana Faradilla, Cut Meutia Hasan Tahir Helmi Naluri Herman Fithra Hizamrul jaen Iskandar, Fahra Azzahra Ismail Ismail Kurnia Amanda, Destiara Lidya Rosnita Maharani, Silfa Muhammad Yani, Muhammad Mukhlis Mukhlis NELI SUSANTI, NELI Nura Usrina Nurdin Nurdin Rahma, Mutiara Risawandi, Risawandi Rizal S.Si., M.IT, Rizal Rozzi Kesuma Dinata Safwandi Safwandi Silfa Maharani Br Padang Subhan Hartanto Taufiqurrahman Taufiqurrahman Umar Khalil Yani, Muhamamd Yesy Afrillia Zahratul Fitri Zara Yunizar zulfhazli zulfhazli