Article Per Year (5 Year)
p-Index From 2020 - 2025
1.452
P-Index
This Author published in this journals
All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Teknologi dan Sistem Komputer JOIV : International Journal on Informatics Visualization Jurnal SITECH : Sistem Informasi dan Teknologi Journal of Computer Networks, Architecture and High Performance Computing Jurnal Hilirisasi Technology kepada Masyarakat (SITECHMAS) Jurnal INFOTEL
Afandi Nur Aziz Thohari, Afandi Nur Aziz
Unknown Affiliation
Computer Science & IT Education Electrical & Electronics Engineering Engineering Social Sciences

Published : 7 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 7 Documents
Search

 1 
Implementasi Test Driven Development Dalam Pengembangan Aplikasi Berbasis Web Thohari, Afandi Nur Aziz; Amalia, Andika Elok
Jurnal SITECH : Sistem Informasi dan Teknologi Vol 1, No 1 (2018): JURNAL SITECH VOLUME 1 NO 1 TAHUN 2018
Publisher : Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (667.133 KB) | DOI: 10.24176/sitech.v1i1.2255

Abstract

Sebuah perangkat lunak dikatakan siap untuk dipakai apabila sudah melalui tahap pengujian. Pada era pengembangan perangkat lunak dengan metodologi tradisional, pengujian dilakukan dengan cara mencoba satu persatu menu aplikasi ketika aplikasi yang dikembangkan sudah jadi. Cara pengujian tersebut akan membutuhkan waktu yang lama apabila developer mengerjakan proyek perangkat lunak dalam skala besar. Selain itu, cara tersebut juga tidak dapat menguji logika dan method dari suatu kelas. Salah satu metode pengembangan perangkat lunak yang dapat menghemat waktu pengujian, namun fungsionalitasnya tetap terjaga adalah test driven development (TDD). Pada metode TDD, pengembangan perangkat lunak dilakukan dengan membuat test case terlebih dahulu baru kemudian melakukan producing code. Pada penelitian ini, dikembangkan sebuah aplikasi web menggunakan TDD. Aplikasi web yang dikembangkan adalah berupa sistem informasi mengenai ulasan film lokal indonesia atau disebut Indonesia Movie Database (IMDB). Bahasa pemrograman web yang dipakai adalah ruby dengan menggunakan framework rails. Sedangkan alat yang dipakai untuk pengujian adalah Rspec. Hasil implementasi TDD membuktikan bahwa fungsi-fungsi dari aplikasi web yang dibangun dapat berkerja dengan baik. Selain itu kode program yang dihasilkan juga menjadi rapi dan mudah dibaca oleh pengembang lain karena menerapkan refactoring. Pengujian unit test menggunakan Rspec membantu pengembang dalam menangani kesalahan dan memudahkan menambah fitur baru dari aplikasi web.
Sistem Penghitung Jumlah Orang Menggunakan Metode SSD-MobileNet dan Centroid Tracking Thohari, Afandi Nur Aziz; Karima, Aisyatul; Wibowo, Angga Wahyu; Santoso, Kuwat
Jurnal Teknologi dan Sistem Komputer Volume 10, Issue 2, Year 2022 (April 2022)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2022.14213

Abstract

Salah satu penerapan kecerdasan buatan untuk mencegah penyebaran virus corona adalah dengan membuat sistem penghitung jumlah orang otomatis untuk mencegah kerumunan di dalam ruangan. Penelitian ini membahas mengenai pembuatan prototipe sistem penghitung jumlah orang menggunakan algoritma deep learning pada single board computer. Tujuan dari penelitian ini adalah untuk menghitung jumlah orang dalam suatu ruangan agar okupansi ruangan dapat ditekan. Kontribusi dari penelitian ini adalah mengkombinasikan dua metode visi komputer yaitu SSD-MobileNet untuk identifikasi objek orang dan centroid tracking untuk menghitung jumlah orang. Berdasarkan pengujian yang telah dilakukan menunjukan bahwa sistem telah dapat menghitung objek orang dengan akurasi 100% apabila jumlah orang yang memasuki ruangan berjumlah satu, dua, atau tiga secara bersama-sama. Kemudian sistem dapat mendeteksi objek dengan jarak maksimal 10 meter dan intensitas cahaya redup atau kurang dari 100 lux. Pada pengujian komputasi menunjukan bahwa sistem dapat memproses video dengan jumlah frame 30 fps dan kualitas video high definition (HD).
Performance Comparison Supervised Machine Learning Models to Predict Customer Transaction Through Social Media Ads Thohari, Afandi Nur Aziz; Ramadhani, Rima Dias
Journal of Computer Networks, Architecture and High Performance Computing Vol. 4 No. 2 (2022): Article Research Volume 4 Number 2, July 2022
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v4i2.1488

Abstract

The application of machine learning has been used in various sectors, one of which is digital marketing. This research compares the performance of six machine learning algorithms to predict customer transaction decisions. The six algorithms used for comparison are Perceptron, Linear Regression, K-Nearest Neighbors, Naïve Bayes, Decision Tree, and Random Forest. The dataset is obtained from Facebook ads transaction data in 2020. The goal is to get a model that has the best performance so that it can be deployed to the web. The method that is used to compare the results is a confusion matrix and also uses visualization of the model to get the prediction error that occurred. Based on the test results, the random forest algorithm has the highest accuracy, recall, and f1-score values, with scores of 96.35%, 95.45%, and 93.32%. The highest precision value was generated by the logistic regression algorithm, which was 94.44%. Based on the data visualization presented by the random forest algorithm, it has the least prediction errors, there are four data. Therefore, it can be concluded that the random forest algorithm has the best performance because it has the highest value in the three confusion matrix measurements and the smallest data prediction error. The model of the random forest algorithm is deployed to the web platform and can be accessed at the link iklan-sosmed.herokuapp.com.
SCALE UP NILAI JUAL MARKETING UMKM MASYARAKAT KEBAKKRAMAT, KABUPATEN KARANGANYAR JAWA TENGAH MELALUI SMART BOOTH PORTABLE, PENDAMPINGAN HPP DAN DIGITAL MARKETING Rahmawati, Roselina; Ratna K, Dianita; Makom, Maharani Rona; Thohari, Afandi Nur Aziz
Jurnal Hilirisasi Technology kepada Masyarakat (SITECHMAS) Vol. 6 No. 2 (2025): Vol. 6 No. 2 Oktober 2025
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/sitechmas.v6i2.6222

Abstract

Usaha Mikro Kecil Menengah (UMKM) berperan penting sebagai penggerak perekonomian Indonesia. Pengelolaan UMKM di Indonesia ini memiliki masalah keterbatasan pengetahuan untuk menghitung harga pokok penjualan yang tepat karena tidak memahami konsep Harga Pokok Penjualan (HPP). Untuk menghadapi permasalahan tersebut, para pelaku UMKM perlu memahami konsep HPP guna mengoptimalkan keuntungan dan meninimalisir kerugian usaha. Metode penelitian ini adalah deskriptif dengan pendekatan kualitatif. Teknik pengumpulan data yang digunakan ini adalah studi kepustakaan dan studi lapangan. Sedangkan teknik analisispengabdian masyarakat terdiri atas tahap persiapan, tahap pelaksanaan dan tahap evaluasi. Hasil penelitian dari pengabdian masyarakat ini adalah untuk memberikan pengetahuan yang relevan kepada masyarakat tentang urgensi dari adanya pencatatan keuangan dalam berwirausaha. Melalui kegiatan ini, pemahaman masyarakat tentang konsep HPP dalam mengoptimalkan usaha UMKM meningkat
Sistem Pakar Diagnosis Penyakit Ikan Gurami (Osphronemus Goramy) Menggunakan Case Based Reasoning Saraswati, Adinda Rahmi; Saintika, Yudha; Thohari, Afandi Nur Aziz; Iskandar, Ade Rahmat
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 4: Agustus 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020701953

Abstract

Ikan Gurami (Osphronemus Goramy) merupakan ikan yang banyak dibudidayakan dan dikomsumsi masyarakat ini menjadi sektor unggulan di beberapa wilayah kabupaten Banyumas. Ikan gurami yang dibudidayakan oleh masyarakat Banyumas, sebenarnya bukan tanpa hambatan. Salah satu hambatan bagi peternak gurami adalah penyakit yang disebabkan oleh bakteri. Pada penelitian ini penulis membuat sistem pakar untuk mendiagnosis penyakit ikan Gurami yang disebabkan bakteri. Penelitian ini menggunakan metode Case Based Reasoning dan Similarity Nearest Neighbor untuk mendapatkan solusi yang terbaik dari kasus yang di identifikasi. Metode tersebut membandingkan antara kasus lama dengan kasus baru dan menghitung suatu nilai similarity kasus. Nilai similarity tertinggi dapat dijadikan kesimpulan untuk kasus yang paling mirip dengan diagnosa pakar. Sehingga dari kedua metode tersebut dapat dihasilkan sistem pakar yang dapat mendiagnosis dan menganalisis sesuai dengan nilai kemiripan gejala terhadap penyakit, serta menampilkan solusi penanganan dari penyakit yang didiagnosis. Hasil pengujian antar kasus dan sistem menggunakan perhitungan similarity mencapai nilai terbaik yaitu 100%. Hasil pengujian akurasi sistem untuk diagnosis yang sesuai dengan pikiran pakar, memperoleh hasil sebesar 93,33% dari 30 kasus yang diuji dengan sistem. Kesimpulan dari hasil tersebut adalah sistem dapat dikatakan layak untuk mendiagnosis penyakit Gurami yang disebabkan bakteri sesuai dengan yang dipikirkan pakar. AbstractGurami (Osphronemus Goramy) is a fish that is widely cultivated and consumed by the community. This fish is a leading sector in several regions of Banyumas district. Gouramy which is cultivated by the Banyumas people, is actually not without obstacles. One obstacle for gouramy breeders is a disease caused by bacteria. Reporting from the online news portal, circulating in February 2018 circulated that news about Gurami farmers was losing money because thousands of broodstock fish that had been raised to death were attacked by bacterial diseases, namely Aeromoniasis. Experts who handle this are limited, namely only 2 people in the Banyumas Regency. In this study the authors made an expert system to diagnose Gurami fish disease caused by bacteria. This study uses the Case Based Reasoning (CBR) and Nearest Neighbor methods used to get the best solution from the identified case. The CBR method compares the old case with the new case and calculates a case similarity value. The system was built with 13 symptoms and 3 Gurami diseases caused by bacteria. Each symptom each has a weight of 5, 3, and 1. The highest similarity value can be used as a conclusion for the case most similar to the expert diagnosis. So that from these two methods an expert system can be produced that can diagnose and analyze according to the similarity of symptoms to the disease, as well as display solutions to the treatment of diagnosed diseases. The test results are between cases and the system uses the similarity calculation to achieve the best value of 100%. The results of the system accuracy test for diagnoses that are in accordance with the expert's mind, obtained results of 93.33% from 30 cases tested with the system. The conclusion of these results is that the system can be said to be feasible to diagnose Gurami disease caused by bacteria according to what experts think.
Brain Tumor Detection Through Image Enhancement Methods and Transfer Learning Techniques Thohari, Afandi Nur Aziz; Mountaines, Patricia Evericho; Mohd Isa, Mohd Rizal
JURNAL INFOTEL Vol 17 No 1 (2025): February 2025
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i1.1262

Abstract

A brain tumor is dangerous and must be treated immediately to prevent worsening. The identification of brain tumors can be performed by a more in-depth examination by specialists or by using artificial intelligence technology through MRI datasets. Several studies have examined how artificial intelligence could be used to find brain cancer in MRI images. The algorithm usually used is CNN with the addition of transfer learning. Previous studies have produced very high accuracy, but the accuracy value can still be improved. In this study, MRI image quality is improved as a new input for modeling. The test results show that the proposed CNN Model produces an accuracy of 98.50% on the test data. This result is higher than the baseline method of 98.45%. Analysis of other metrics, such as precision, recall, and F1-score, indicates consistent performance across classes. These findings suggest that using preprocessing to improve image quality can improve Model performance. Using CLAHE and median blur to improve image quality can improve accuracy by 14.5%. This study contributes to identifying an effective combination of Model optimization techniques for image classification tasks.
(PANDEMIC Covid-19): A Shooter Game for Education - the Impact Measurement of War Games on Virus Eradication Lessons for Students Wibowo, Angga Wahyu; Karima, Aisyatul; Thohari, Afandi Nur Aziz; Santoso, Kuwat; Sato-Shimokawara, Eri
JOIV : International Journal on Informatics Visualization Vol 7, No 2 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.2.1167

Abstract

(PANDEMIC Covid-19) is an educational shooter game inspired by the Covid-19 pandemic which occurred from the end of 2019 until early 2022. There are 2 game modes, namely Third-Person Shooter, or TPS, and First-Person Shooter, or FPS. This study was carried out to highlight the absence of a shooter genre game used in the student learning process. The research methodology in the development of this game applied the pressman method, and the stages include planning, analysis, game development and artificial intelligence, implementation, as well as  evaluation. Furthermore, the testing phase used software testing techniques based on the ISO 9126 standard and involved a total of 100 participants. The age range was between 17 and 20 years, while the participants' gender percentages were 55% male and 45% female. Some of the factors tested include functionality, reliability, portability, usability, efficiency, and maintainability. There were 2 choices only in this test, i.e. agree and disagree. The functionality factor had an agreed rate of 85%; reliability 79%, portability 86%, usability 83%, efficiency 79%, and maintainability 87%. Therefore, it was concluded that this game is suitable for use in student learning in the shooter genre. Furthermore, this research was inspired because shooter games have not been developed for the student learning process. This game genre is currently used for hobbies and for profit by developers and professional players. Further research should develop game levels, enable features to play online together with other users, and should be extended to Android and IOS. 
Co-Authors Ade Rahmat Iskandar Airlangga, Gregorius Aisyatul Karima Amalia, Andika Elok Amalia, Andika Elok Makom, Maharani Rona Mohd Isa, Mohd Rizal Patricia Evericho Mountaines Ramadhani, Rima Dias Ratna K, Dianita Rifki Adhitama, Rifki Roselina Rahmawati Santoso, Kuwat Saraswati, Adinda Rahmi Sato-Shimokawara, Eri Wibowo, Angga Wahyu Yudha Saintika