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All Journal Voteteknika (Vocational Teknik Elektronika dan Informatika) Syntax Jurnal Informatika KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Faktor Exacta Systematics Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Pengabdian Masyarakat Nasional
Baihaqi, Kiki Ahmad
Universitas Buana Perjuangan Karawang
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Library & Information Science

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Penerapan Haar Cascade Classification Model Untuk Deteksi Wajah, Hidung, Mulut, dan Mata Menggunakan Algoritma Viola-Jones Nono Heryana; Rini Mayasari; Kiki Ahmad Baihaqi
Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Vol 5 No 1 (2020): Techno Xplore: Jurnal Ilmu Komputer dan Teknologi Informasi
Publisher : Teknik Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/technoxplore.v5i1.1064

Abstract

Penelitian ini dilakukan untuk melakukan deteksi fitur yang ada pada wajah manusia, pendekatan yang digunakn dalam penelitian ini adalah Penerapan Haar Cascade Classification Model Untuk Deteksi Wajah, Hidung, Mulut, Mata Menggunakan Algoritma Viola-Jones sehingga sistem yang dihasilkan mampu untuk melakukan deteksi terhadap fitur-fitur yang ada pada wajah manusia yang meliputi Wajah, Hidung, Mulut, dan Mata. Dalam penerapan deteksi wajah, hidung, mulut dan mata ini dibangun menggunakan metode viola-jones yang terdiri dari metode haar-like feature, citra integral, adaboost, dan cascade of classifier. Teknologi pengenalan wajah, Deteksi wajah, hidung dan mulut juga menjadi hal yang penting dalam teknologi pengenalan wajah.
Penerapan Metode Machine Learning untuk Prediksi Nasabah Potensial menggunakan Algoritma Klasifikasi Naïve Bayes Devi Fitrianah; Saruni Dwiasnati; Hanny Hikmayanti H; Kiki Ahmad Baihaqi
Faktor Exacta Vol 14, No 2 (2021)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v14i2.9297

Abstract

Customers are people who trust the management of their money in a bank or other financial service party to be used in banking business operations, thereby expecting a return in the form of money for their savings. To reach information to increase company profits, a method is needed to be able to provide knowledge in supporting the data that the company has. The model can be obtained by using predictive data processing of customer data that is categorized as potential or not potential. Data processing can be done using Machine Learning, namely classification techniques. This technique will produce a churn prediction model for determining the category of customers who fall into the Potential or Not Potential category and find out what accuracy value will be generated by applying the classification technique using the Naïve Bayes Algorithm. The parameters used in this study are Gender, Age, Marital Status, Dependent, Occupation, Region, Information. The data used are 150 data from customers who have participated in the savings program to find out whether the customer is in the Potential or Non-Potential category. The accuracy results generated using this data are 86.17% of the tools used by Rapidminner.
Artikel Implementasi Algoritma Best First Search untuk Pencarian Rute Terpendek pada Aplikasi Cerdas Pendaftaran Santri Baru: Aplikasi Cerdas Pendaftaran Santri Baru Herfandi Herfandi; Ulfatus Soleha; Agung Susilo Yuda Irawan; Kiki Ahmad Baihaqi; Reza Maulana
SYNTAX Jurnal Informatika Vol 11 No 01 (2022): Mei 2022
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/syji.v11i01.6398

Abstract

Pesantren in Indonesia is a traditional Islamic educational institution that is able to exist until now. A less structured registration process allows errors and delays in the new santri registration process will be easy to occur. Pondok Pesantren Manbaul Ulum in carrying out the education administration process still uses conventional means this causes the service system used has not been efficient and the problem of dormitory limitations, registration regulations must be made in accordance with the distance zone of residence that has been determined. Therefore this study conducted the implementation of the best first search algorithm for the search of the shortest route on the new registration intelligent application. This research resulted in a new santri registration intelligent application by applying the best first search algorithm. The development method uses waterfall. Testing software with black box testing method with test case equivalence partitioning technique gets successful conclusions from various types of testing. With features for santri namely estimation data, home, instructions, contact us, register, login, fill out registration form, see verification, print proof of pass, and see the shortest tute, for admin setting school year, see registration, see registration accepted and rejected and see reports. As for the superadmin, crud admin data and see the report. This application is expected to help pesantren administration and prospective students see the route and support education in the Industrial 4.0 era.
Analisis Vulnerability pada Website Universitas Singaperbangsa Karawang menggunakan Acunetix Vulnerability Rini Mayasari; Azhari Ali Ridha; Didi Juardi; Kiki Ahmad Baihaqi
SYSTEMATICS Vol 2 No 1 (2020): April 2020
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/sys.v2i1.3450

Abstract

Isu keamanan website merupakan hal yang sangat krusial pada masa sekarang, sehingga masalah keamanan dan kerentanan website menjadi sangat penting dalam mengembangkan aplikasi website. Dalam mendeteksi kerentanan dalam penelitian ini digunakan metode kualitatif dengan memanfaatkan perangkat lunak Acunetix Vulnerability Scanner, yang dimulai dari tahap inisiasi, investigasi, pengujian dan verifikasi. Hasil dari penelitian ini, tingkt kerentanan website Universitas Singaperbangsa Karawang berada pada level 2 yaitu Medium, sehingga kemungkinan untuk mengakses dan mengumpulkan informasi sensitif, karena dengan infromasi tersebut penyusup bisa dengan mudah mengeksploitasi kelemahan yang ada.
Securing the Website Login System with the SHA256 Generating Method and Time-based One-time Password (TOTP) Iman Permana; Mardi Hardjianto; Kiki Ahmad Baihaqi
SYSTEMATICS Vol 2 No 2 (2020): August 2020
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/sys.v2i2.3756

Abstract

Security to enter a system has a very important role because as the main entrance to access data sources. But often lack the attention of the owners and managers of information systems. To reduce these weaknesses, one method that is widely used today is to use One-Time password, which is where the password we have becomes dynamic, meaning that at a certain time the password is always changing, the positive side is that it makes it difficult for others to steal our passwords because besides representative passwords that are difficult to understand and passwords are always changing. This study discusses One-Time Password installed on a mobile device where the password is randomized using a combination of two algorithms, namely SHA256 and Time-based One Time Password. The development of this login method can reduce the level of theft of passwords owned by users who are entitled to access information sources.
Application of Convolution Neural Network Algorithm for Rice Type Detection Using Yolo v3: Penerapan Algoritma Convolution Neural Network untuk Deteksi Jenis Padi Menggunakan Yolo v3 Kiki Ahmad Baihaqi; Yana Cahyana
SYSTEMATICS Vol 3 No 2 (2021): August 2021
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/sys.v3i2.5874

Abstract

Rice is a staple food that contains a lot of energy for human life. There are several types of rice that are often sold in rice shops in general, namely IR42 rice, Pera rice, glutinous rice and Pandan fragrant rice. For now, there are still many people who do not recognize the 4 types of rice, especially millennials, for this reason, research is carried out on the introduction of rice types. The purpose of this study is to make it easier for buyers to identify the type of rice that is in the rice shop so as to minimize fraud by rice traders. The method used in this study is the YOLO (You Only Look Once) v3 method for detecting rice types. The implementation of the image detection process using YOLO (You Only Look Once) v3 has been tested for 12 samples. Based on the results of testing 12 detection experiments on digital image objects, it was obtained 100% where in the picture there were 4 types of rice, 4 grains of rice and 3 types of rice shapes.
Rancang Bangun Alat Pendeteksi Kebocoran Liquefied Petroleum Gas Berbasis Mikrokontroler Wemos D1 R1 Dengan Notifikasi Calling Herfandi Herfandi; Eko Purwirawansyah; Agung Susilo Yuda irawan; Kiki Ahmad Baihaqi
Voteteknika (Vocational Teknik Elektronika dan Informatika) Vol 10, No 2 (2022): Vol. 10, No 2, Juni 2022
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/voteteknika.v10i2.118061

Abstract

Penggunaan LPG (Liquefied Petroleum Gas) mengalami peningkatan pesat. LPG rawan menimbulkan kebakaran dikarenakan tekanan yang tinggi saat di udara. Alat berbasis mikrokontroler sudah banyak digunakan untuk mengatasi permasalahan kebocoran LPG. Sistem keamanan LPG di Desa Boak   menggunakan alat bawaan dari regulator konvensional dimana diputar secara manual untuk penutup aliran LPG, ini kurang efektif karena pengguna tidak bisa mengetahui kondisi LPG saat berada diluar rumah. Penelitian ini melakukan rancang bangun alat pendeteksi kebocoran LPG berbasis mikrokontroler wemos D1 R1 dengan fitur notifikasi calling. Hasil penelitian adalah 95% responden setuju alat perlu dibuat, dengan temuan tegangan Step down LM2596 tidak stabil dengan 4.12V ke 3.5V. Revisi produk menambahkan kapasitor sebesar 1000mF dan LED sebagai indikator kebocoran, serta resistor sebagai penghambat tegangan LED. Alat ini sudah berfungsi maksimal dikarenakan sudah dilakukan pengujian dan penyempurnaan berdasarkan temuan. Diharapkan alat ini sebagai sistem peringatan dini terjadinya kebocoran LPG.Kata kunci : Alat Deteksi, Liquefied Petroleum Gas, Mikrokontroler, Notifikasi Calling, Wemos D1 R1 The use of LPG (Liquefied Petroleum Gas) has increased rapidly. LPG is prone to fire due to the high pressure in the air. Microcontroller-based tools have been widely used to solve the problem of LPG leakage. The LPG safety system in Boak Village uses a built-in device from a conventional regulator which is manually rotated to shut off the LPG flow, this is less effective because users cannot know the condition of LPG when outside the house. This study designs an LPG leak detector based on the Wemos D1 R1 microcontroller with a calling notification feature. The result of the research is 95% of respondents agree that the tool needs to be made, with the finding that the LM2596 Step down voltage is unstable from 4.12V to 3.5V. The product revision added a 1000mF capacitor and an LED as a leakage indicator, as well as a resistor as an LED voltage blocker. This tool has been functioning optimally because it has been tested and refined based on the findings. It is hoped that this tool will serve as an early warning system for LPG leaks.Keywords: Detection Tool, Liquefied Petroleum Gas, Microcontroller, Call Notification, Wemos D1 R1
Perancangan Sistem Penerimaan Siswa Baru Berbasis Web Pada Sekolah Dasar Islam Plus Baitul Maal Herfandi Herfandi; Saruni Dwiasnati; Kiki Ahmad Baihaqi; reza Avrizal
Faktor Exacta Vol 15, No 2 (2022)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v15i2.12894

Abstract

Islamic-based education in Indonesia is an educational institution that focuses on forming the character and knowledge of Islamic religious values. Islamic Elementary School Education Institute Plus Baitul Maal in carrying out educational administration procedures still uses the conventional system. The procedure that took place has not been efficient because prospective students are required to complete the registration form sheet by manual means and still stored in the folder. The implementation of information system technology in the education sector is able to provide convenience, especially in terms of efficientness, accuracy and novelty of information. Therefore, the design and creation of a website-based new student admission information system is expected to be able to solve the problem. This research resulted in a website-based new student admission information system with the main Page having Home, About Us, How to Apply, and Contact functionality. The student dashboard page has Home, Student Profile, Document functionality. The admin dashboard page has the functionality of Home, Website Content, Management, Document Completeness, and Settings as an admin user management serves to set up admin accounts (Create, Record, Update and Delete (CRUD) for admin accounts), development methods using waterfalls, research methods using qualitative and information system testing using black box testing that gets conclusions according to various functionality tests. This system is expected to ease the work of new student admission administrators as well as adjustments to education in the Industrial 4.0 era.
KOMPARASI ALGORITMA NAïVE BAYES, SUPPORT VECTOR MACHINE, DAN LOGISTIC REGRESSION PADA ANALISIS SENTIMEN PENGGUNA APLIKASI TRANSPORTASI ONLINE Krisna Perdana Jaya Sitompul; Adi Rizky Pratama; Kiki Ahmad Baihaqi
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 10, No 1 (2023)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v10i1.616

Abstract

Online transportation is one of the transportation that is increasingly in demand by the public at this time. Grab is an online transportation application that has many users in Indonesia. However, this system certainly has many shortcomings that are felt by users. One way to find out user satisfaction and disappointment with the application is to do sentiment analysis. By analyzing the deficiencies of the application, the company can find out the shortcomings of the application and how to fix it. The purpose of this study is to compare the accuracy between the Support Vector Machine, Naive Bayes, and Logistic Regression algorithms by conducting sentiment analysis on Grab application review data. The results of the comparative test found that the Naive Bayes algorithm has the best performance compared to other classification algorithms with an accuracy obtained by the Naive Bayes algorithm of 88.5%, while the Support Vector Machine algorithm has the lowest accuracy with an accuracy of 85.5%. So it can be concluded that the Naive Bayes algorithm has a better value than the Logistic Regression and Support Vector Machine algorithms. Keywords: Grab, Support Vector Machine, Naive Bayes, Logistic Regression Transportasi online adalah salah satu transportasi yang semakin diminati masyarakat pada saat ini. Grab adalah alah  satu  aplikasi  trasportasi online  yang  memiliki  pengguna  bisa  dikatakan  banyak  di  Indonesia. Namun  dalam  system  ini  pasti  memiliki banyak  kekurangan  yang  dirasakan  penggunanya. Salah satu cara untuk mengetahui kepuasan dan kekecewaan pengguna terhadap aplikasi tersebut yaitu melakukan analisis sentimen.  Dengan  menganalisis  kekurangan  dari  aplikasi  perusahaan dapat mengetahui kekurangan dari aplikasi dan bagaimana cara memperbaikinya. Tujuan penelitian ini untuk mengetahui perbandingan keakurasian antara algoritma Support Vector Machine, Naive Bayes, dan Logistic Regression dengan melakukan analisis sentimen pada data ulasan aplikasi Grab . Hasil pengujian komparasi ditemukan bahwa algoritma Naive bayes memiliki kinerja terbaik dibandingkan algoritma klasifikasi lainnya dengan akurasi yang di dapat algoritma Naive bayes sebesar 88.5%, sedangkan algoritma Support Vector Machine memiliki akurasi terendah dengan akurasi sebesar 85.5%. Sehingga dapat disimpulkan bahwa algoritma Naive bayes memiliki nilai yang lebih baik dibandingkan algoritma Logistic Regression dan Support Vector Machine.Kata kunci: Grab, Support Vector Machine, Naive Bayes, Logistic Regression
Implementasi Algoritma Logistic Regression Untuk Klasifikasi Penyakit Stroke suhliyyah; Hanny Hikmayanti Handayani; Kiki Ahmad Baihaqi
SYNTAX Jurnal Informatika Vol 12 No 01 (2023): Mei 2023
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/syji.v12i01.8329

Abstract

Stroke menyebabkan kerusakan pada bagian otak yang muncul secara mendadak akibat dari gangguan peredaran darah non traumatik. Gangguan tersebut dapat menimbulkan gejala antara lain kelumpuhan seisi wajah atau anggota badan, bicara tidak jelas, bicara tidak lancar, gangguan penglihatan dan perubahan kesadaran. Penyakit stroke merupakan penyakit yang menjadi penyebab kematian nomor tiga tertinggi di indonesia setelah penyakit kanker dan jantung. Di indonesia, jumlah kasus dan prevalensi stroke belum diketahui secara jelas. Diperkirakan 500.000 penduduk terkena stroke setiap tahunnya, sekitar 2,5% atau 12.500 orang meninggal dunia dan sisanya mengalami cacat ringan. Hampir setiap hari, atau minimal rata-rata tiga hari sekali ada seseorang penduduk indonesia baik tua maupun muda meninggal dunia karena serangan penyakit stroke. Penelitian ini dibuat menggunakan metode Confusion matrix dan pengujian menggunakan algoritma Logistic Regression, penelitian ini dilakukan dengan pengumpulan data dan hasil analisis untuk meningkatkan akurasi, berdasarkan variabel berpengaruh meliputi jenis kelamin, hipertensi, penyakit jantung, kadar gula darah, berat badan dan status merokok. Berdasarkan hasil pengumpulan data yang telah dilakukan sebanyak 4981 data diperoleh hasil akurasi sebesar 94%.
Co-Authors Adi Rizky Pratama Agung Susilo Yuda Irawan Ahmad Fauzi Azhari Ali Ridha Bambang Sukowo Devi Fitrianah Didi Juardi Eko Purwirawansyah Hanny Hikmayanti H Hanny Hikmayanti Handayani Hardjianto, Mardi Herfandi Herfandi Heryana, Nono Iman Permana Indra, Jamaludin Krisna Perdana Jaya Sitompul Reza Avrizal Reza Maulana Rini Mayasari Saruni Dwiasnati suhliyyah Ulfatus Soleha Yudo Devianto