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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) Computer & Science Industrial Engineering Journal
Fajrin, Alfannisa Annurullah
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Computer Science & IT Education

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PENERAPAN FUZZY INFERENSI DALAM SELEKSI KAYU MENTAH UNTUK PERABOT BERBASIS METODE MAMDANI Zain, Zabur; Fajrin, Alfannisa Annurullah
Computer Science and Industrial Engineering Vol 3 No 5 (2020): comasie
Publisher : LPPM Universitas Putera Batam

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Abstract

ABSTRACT Technology has become a significant part that cant separated in the modern world, especially in the industrial field where so many manufactures competing to fulfil the end-user expectation. At Industry Revolution 4.0, a common problem that occurs in every industry growth is the adoption technology that needs to integrate into the traditional method so the product generation is much faster because optimized. Furniture manufacture is one from a thousand manufacture field that struggles with this condition. The craftsmen are facing the problem with selecting the appropriate raw wood material for production, so the crafted furniture will maintain good quality and makes the creation much efficient. With fuzzy logic Mamdani method, a system will be built and aim to help the manufacturer to determine the best raw material for producing the furniture. The result found that the fuzzy logic Mamdani method is capable of assisting the manufacturer in determining the right raw material to use and achieving a high-efficiency material consumption for the better production cycle. Keywords: Keywords: Furniture; Fuzzy Logic; Mamdani Method: Wood Raw Material.
EXPERT SYSTEM MENDIAGNOSA TINGKAT DEPRESI SISWA MENGGUNAKAN METODE CERTAINLY FACTOR Yulianti, Nadia; Fajrin, Alfannisa Annurullah
Computer Science and Industrial Engineering Vol 9 No 1 (2023): Comasie
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v9i1.7466

Abstract

Depression is a mood disorder characterized by symptoms such as moodiness, lethargy, lack of passion, feelings of worthlessness, deep frustration, hopelessness, thoughts of death and suicidal thoughts, depression is one of the mental health conditions, many students still have difficulty determining which stage and how severe the depression they are experiencing, Identifying factors that affect the level of depression experienced by students by applying the Certainty Factor (CF) method to the expert system to diagnose the level of student depression, Certainty Factor is a method for dealing with uncertainty in rule-based systems by performing calculations, after the system runs well, the implementation is carried out on students by registering first then logging in after that answering questions from data on symptoms that cause depression based on their respective levels.
SISTEM PAKAR UNTUK MEDIAGNOSA KODE KERUSAKAN PADA SEPEDA MOTOR INJEKSI YAMAHA DENGAN METODE FORWARD CHAINING BERBASIS WEB Situmorang, Jones Parsaoran; Fajrin, Alfannisa Annurullah
Computer Science and Industrial Engineering Vol 9 No 3 (2023): Comasie
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v9i3.7671

Abstract

There are many fault codes on the motor. The general public dose not yet know about these damage codes. Many people ignore the importance of maintenance for motorcylcle. Consumers often use motorbikes unnaturally. This will cause damage codes in the motorbike. Here a expert system is important for diagnosis damage codes for motorcycyes. So that people can learn and know the damage codes. Communities to know the solutions and symptomps that occur.
PENGEMBANGAN APLIKASI DIGITAL LIBRARY MENGGUNAKAN METODE WATERFALL BERBASIS ANDROID MEMORI MANALU, FRIA ANJU; Fajrin, Alfannisa Annurullah
Computer Science and Industrial Engineering Vol 10 No 1 (2024): Comasie
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v10i1.8368

Abstract

SMPN 40 Batam Library implements a library information system. Currently, because library data information management is still very conventional, errors in checking data and difficulties in finding data information still often occur in library data management. Along with the development of library needs, it is important to realize that the data management process, including member data, book data, data borrowing, data returning, and data library are still done manually. The main objective of implementing a library information system is to facilitate the smooth processing of data and information in the library, especially for library staff. This aims to ensure that book borrowers can more easily access various information related to the book collections available in the library. For digital library development, the first is small-scale development. The digital library application was created using Adobe Animate software and Adobe AIR as the programming language. The data collection method uses the waterfall method which is carried out in stages, namely needs analysis, design, implementation, testing and maintenance. Design stages use Unified Modeling Language (UML) such as use case diagrams, activity diagrams, sequence diagrams, and class diagrams. And system testing adopts black box testing. The research results show that the digital library system has succeeded in building Android-based applications that can be run on mobile devices. Digital library applications are more convenient for administrators to use, managing book data and querying book information and making library reports more efficient.
PERANCANGAN ALAT MONITORING KECEPATAN ANGIN MENGGUNAKAN ARDUINO UNO Zahra, Elza Maudy; Fajrin, Alfannisa Annurullah
Computer Science and Industrial Engineering Vol 10 No 1 (2024): Comasie
Publisher : LPPM Universitas Putera Batam

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Abstract

In studying the field of Meteorology and Geophysics, monitoring wind speed is very useful for human activities such as activities related to transportation. Excessive wind speed can hinder fishermen from carrying out their work when they want to catch fish at sea and hinder fish drying activities when there is strong wind. The lack of digital activity or availability of smartphones also makes it difficult for fishermen to find out the current wind speed, such as through wind monitoring applications so that fishermen only see wind speed based on the movement of objects around them that are blown by the wind. In this regard, a tool is needed to measure wind speed called an anemometer along with its monitoring to produce information about how much wind speed is occurring in the surrounding environment. This wind speed monitoring tool can find out how much wind speed is occurring. The design of this wind speed monitoring tool uses an Arduino Uno as a microcontroller, an I2C LCD to display information about the wind speed, an anemometer sensor which functions as a sensor that will measure wind speed, the results of which will be displayed via the I2C LCD in real-time.
PENGEMBANGAN APLIKASI KEAMANAN MOBILE UNTUK MENGAWASI JARINGAN RUMAH DARI JARAK JAUH Winda Syukur, Winda Syukur; Fajrin, Alfannisa Annurullah
Computer Science and Industrial Engineering Vol 10 No 1 (2024): Comasie
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v10i1.8407

Abstract

In the current era of globalization, the use of mobile devices has become an important part of daily life by providing easy internet access to various online service applications. Security is an important aspect to deal with increasing general crime in Indonesia, for this reason innovation is needed to develop a remote home security application to prevent theft. The solutionis to create a home monitoring tool that adopts CCTV cameras. Which uses ESP32-CAM as a microcontroller which can be monitored via the application, there is also a PIR Sensor to detect living objects. The output produced is a buzzer as an alarm sound warning and there is also a notification in the application.
Klasifikasi dan Deteksi Malware Menggunakan Variasi Model Algoritma Machine learning Maslan, Andi; Fajrin, Alfannisa Annurullah; Putri, Anggia Dasa
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 11, No 1 (2025): Volume 11 No 1
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v11i1.87924

Abstract

Serangan Malware merupakan serangan yang dilakukan oleh seorang attacker dengan cara mengirimkan kode-kode berbahaya ke berbagai file atau bahkan banyak paket dan server. Oleh karena itu, operasional jaringan yang handal menjadi faktor yang perlu diperhatikan untuk mencegah terjadinya serangan sedini mungkin agar tidak terjadi kerusakan sistem yang lebih parah. Jenis serangan dapat berupa Ping of Death, flooding, remote-controlled attack, UDP flooding, dan Smurf Attack. Data serangan diperoleh dari dataset ClaMP, selain itu dilakukan penangkapan paket data pada log jaringan dan optimasi ekstraksi fitur yang selanjutnya dianalisa secara statistik dengan algoritma machine learning. Tujuan dari penelitian ini adalah untuk mendeteksi, mengklasifikasi serangan Malware menggunakan berbagai model Algoritma ML seperti SVM, KNN dan Neural Network serta melakukan pengujian kinerja deteksi. Tahapan penelitian dimulai dari proses Pre-Processing, ekstraksi, pemilihan fitur dan klasifikasi serta pengujian kinerja. Data training dan testing pada penelitian ini menggunakan mixed model yaitu data division, split model dan cross validation. Hasil penelitian menyimpulkan bahwa algoritma terbaik untuk mendeteksi paket Malware adalah Neural Network untuk kategori Feature Combination dengan tingkat akurasi sebesar 96,91%, Recall sebesar 97,35% dan Precision sebesar 96,78%. Sehingga penelitian tersebut dapat berimplikasi bagi para ahli siber untuk dapat mencegah serangan Malware sejak dini. Sedangkan penelitian selanjutnya diperlukan algoritma khusus untuk meningkatkan deteksi serangan Malware, selain KNN, SVM dan Neural Network. Penelitian ini dapat dijadikan referensi bagi para peneliti yang sedang melakukan penelitian di bidang yang sama.
Co-Authors Maslan, Andi MEMORI MANALU, FRIA ANJU Putri, M.Kom, Anggia Dasa Situmorang, Jones Parsaoran Winda Syukur, Winda Syukur Yulianti, Nadia Zahra, Elza Maudy Zain, Zabur