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All Journal InfoTekJar (Jurnal Nasional Informatika dan Teknologi Jaringan) Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Indonesian Journal on Software Engineering (IJSE) Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Riset Informatika Jurnal Infortech Reputasi: Jurnal Rekayasa Perangkat Lunak Jurnal Pengabdian Literasi Digital Indonesia
Wahyutama Fitri Hidayat
Universitas Bina Sarana Informatika
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Library & Information Science

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Deteksi Penyakit Daun pada Tanaman Padi Menggunakan Algoritma Decision Tree, Random Forest, Naïve Bayes, SVM dan KNN Annida Purnamawati; Wawan Nugroho; Destiana Putri; Wahyutama Fitri Hidayat
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 5, No 1 (2020): InfoTekJar September
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/infotekjar.v5i1.2934

Abstract

Pertanian sebagai salah satu sektor industri menjadi bagian pekerjaan yang menunjang pemenuhan kebutuhan makanan pokok masyarakat seperti tanaman pangan. Tanaman padi merupakan tanaman pangan yang rentan terserang hama. Pengenalan terhadap jenis hama yang menyerang merupakan langkah awal yang sangat penting untuk menunjang keberhasilan dalam usaha pengendaliannya. Hama tanaman padi tersebut dapat menjadi kendala bagi petani untuk bisa meningkatkan produksi. karena hama tersebut dapat merusak tanaman padi hingga membuat gagal panen. Oleh sebab itu perlu dilakukan deteksi klasifikasi pada hama daun padi untuk mencari akurasi dengan menggunakan perbandingan berbagai macam metode algoritma yaitu dengan Decision Tree, Random Forest, Naïve Bayes, SVM dan KNN. Sehingga diharapkan mampu menangani hama secara tepat, agar tidak terjadi kerusakan dan gagal panen. Dengan menggunakan dataset Rice Leaf Diseases Detection untuk Deteksi dan Klasifikasi Penyakit Padi. Dataset ini memiliki tiga kelas/penyakit yang diantaranya yaitu: Bakteri daun busuk, bercak coklat, dan daun api, masing-masing memiliki 40 gambar dengan format gambar jpg. Dari perbandingan ke lima metode algoritma tersebut dapat dihasilkan 3 macam model yaitu Model Overfit (Random Forest, Decission Tree dan Naive Bayes), Model Underfit (SVM) dan Good Models (KNN). Jadi metode terbaik diantara kelima tersebut yaitu metode KNN dengan nilai akurasi 87%, karna model ini konsisten baik pada kedua evaluasi. KNN tidak terbukti memiliki masalah overfiting karena secra konsisten berkinerja baik pada data train dan data test.Agriculture as one of the industrial sectors has become a part of the work that supplies people's basic food needs, such as food crops, rice is a food that is susceptible to pests. Identifying the host of pests is a vital first step toward promoting success in its control. The pest of the rice plant can pose a challenge for farmers to increase production. Because such pests can damage the crops to the point of failure. It is therefore necessary to assess the classification of rice leaf pests for accuracy by using a variety of algorithm-based methods of decision tree, random forest, naive bayes, SVM and KNN in the hope that farmers will soon discover the type of rice pests and their ferocity levels. And so it is expected to be able to handle eve properly, lest the damage and failure of the harvest, by using datassets Rice leaf diseases diseases diseases to detect and classification rice diseases. This datasset has three classes The underlying diseases: leaf rot, chocolate patches, and fire leaves produce 40 images each with JPG in their format. In comparison to the five possible methods of the algorithm, the three types of models are the overfit models (Random Forest, Decission Tree dan Naive Bayes), Model Underfit (SVM) dan Good Models (KNN). So the fifth prime method, however, is the KNN method with an accuracy of 87%, because it is consistent with both evaluations. KNN has no evidence of overfiting problems because it consistently performs well on train data and test data.
COMPARATION OF DECISION TREE MODEL AND SUPPORT VERCTOR MACHINE IN SENTIMENT ANALYSIS OF REVIEW DATASET SAMSUNG SSD 850 EVO AT NEW EGG SHOP Muhammad Fahmi Julianto; Yesni Malau; Wahyutama Fitri Hidayat; Wawan Nugroho; Fintri Indriyani
Jurnal Riset Informatika Vol 3 No 4 (2021): Period of September 2021
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (704.421 KB) | DOI: 10.34288/jri.v3i4.278

Abstract

The development of information technology is currently growing very rapidly, including the impact on the hardware used. This can be exemplified in the use of hard drives that are starting to switch to SSDs. The process of selecting an SSD product to be used cannot be separated from the sources of information found on the internet. Through the internet, every user can provide reviews, both positive and negative reviews. With the many reviews regarding the review of the Samsung 850 Evo SSD on the NewEgg Store, the author uses it to be processed into information, which will have new knowledge. Based on that, the author makes research, in the form of opinion classification by analyzing sentiment through a text mining approach. In this study, two classification models were used, namely Decision Tree and Support Vector Machine. The results of this study are in the form of a comparison of the 2 models used based on the accuracy and AUC values. Based on research, the Support Vector Machine model is better than the Decision Tree model. This conclusion can be proven by the accuracy value of the Support Vector Machine model resulting in a value of 0.87 or 87% while the accuracy value of the Decision Tree model produces a value of 0.82 or 82%. In addition, the AUC value of the Support Vector Machine model produces a value of 0.87 and the Decision Tree mode produces a value of 0.82 or it can be said that the AUC value of the Support Vector Machine model is better than the Decision Tree model.
Perancangan Website Desa Wisata Wukirsari Bantul Sebagai Media Promosi dan Pemesanan Wahyutama Fitri Hidayat; Paulus Tofan Rapiyanta; Fajar Shidiq
Jurnal Infortech Vol 2, No 1 (2020): Juni 2020
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (281.114 KB) | DOI: 10.31294/infortech.v2i1.7472

Abstract

Desa Wukirsari Bantul merupakan salah satu objek wisata yang mempunyai potensi alam dan budaya yang menarik untuk di kembangkan. Namun sampai saat ini untuk melakukan promosi dan pemesanan, pengelola desa wisata hanya mengandalkan media konvensional. Dalam era teknologi sekarang ini cara seperti itu terbilang sederhana karena orang lebih memilih cara instan menemukan informasi melalui internet. Perancangan website merupakan solusi terbaik untuk mempromosikan sekaligus sebagai media pemesanan secara online dengan tujuan mempermudah wisatawan memperoleh informasi, dan memberi kemudahan pengelola dalam kegiatan promosi dan pencatatan pesanan. Metode penelitian yang digunakan dalam pengumpulan data adalah metode pengamatan, metode studi pustaka, dan metode wawancara. Pengembangan software yang digunakan dalam perancangan ini yaitu dengan metode waterfall yang meliputi analisa kebutuhan perangkat lunak, desain, pembuatan kode program, pengujian, pendukung dan pemeliharaan. Penulis menganalisis kebutuhan dalam pembuatan database, membuat Entity Relationship Diagram, membuat Logical Relationship Structure kemudian membuat struktur navigasi user, member dan admin. Dalam pengujian website, penulis melakukan dengan menggunakan Black Box Testing agar sistem berjalan sesuai dengan lingkungan yang diinginkan. Kesimpulan yang dapat di ambil bahwa website ini memudahkan pengelola dalam kegiatan promosi dan pencatatan pesanan. Terutama dengan website ini wisatawan dapat dengan mudah memperoleh informasi dan  pemesanan.
Analisis Niat Pembelian Pada Instagram Online Shopping Menggunakan Information Acceptance Model (IACM) Wahyutama Fitri Hidayat; Rangga Sanjaya; Ali Mustopa
Bianglala Informatika Vol 8, No 1 (2020): Bianglala Informatika 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (308.472 KB) | DOI: 10.31294/bi.v8i1.7837

Abstract

Along with the development of technology and information, it also has an impact on the product sales media, one of which is through Instagram online shopping. The results of the surf show that comments (electronic word of mount) are on Instagram online shopping. This study aims to analyze the effect of the electronic word of month (EWOM) on purchase intentions using the Information Acceptance Model (IACM) model. The method used in this research is descriptive quantitative to find out the cause and effect relationship of IACM variables. The population in this research is Instagram users who have seen product promotions through Instagram. The sampling technique used is incidental sampling by distributing questionnaires online. The data analysis technique used is multiple linear regression analysis. Based on the results of the research, it can be concluded that the electronic word of mount found on Instagram online shopping has a significant partial effect on purchase intention. This can be seen from the results of the calculation of all the t-count variables 0.191 and the  significance level 0.05. Based on the results of the calculation of the determination coefficient (R2), the magnitude of the effect on the benefits of information is information quality 19.5%, information credibility 41.3%, information needs 13.9%, and attitudes towards information 28.6%. The results of information adoption are affected by 11.2% of the benefits of information. Other lts show that 24.9% of information adoption affects purchase intentions. While attitudes toward information affect 38.9% of purchase intentions.
IMPLEMENTATION OF THE SCRUM MODEL IN THE DEVELOPMENT OF ONLINE SALES SYSTEMS OF MSMEs DURING THE COVID-19 PANDEMIC Wahyutama Fitri Hidayat; Annida Purnamawati; Fajar Sarasati
Techno Nusa Mandiri: Journal of Computing and Information Technology Vol 18 No 1 (2021): TECHNO Period of March 2021
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/techno.v18i1.1896

Abstract

A global pandemic or epidemic indicates a covid-19 infection that is very fast spreading throughout the world, including Indonesia. This has an impact on several sectors, one of which is the economic sector. There are various things that have caused the economic sector to be touched by the impact of the covid-19 virus, including government policies at both the central and regional levels that issued several regulations relating to restrictions on community mobility. Indirectly, things related to mobility restrictions or what is currently known as Pembatasan Sosial Berskala Besar (PSBB) have an impact on consumer behavior to switch to making purchases online. To address this, the online sales system is considered to be a solution for MSMEs to continue the buying and selling process. Using the Scrum model as a more efficient system development, feedback between users and developers who can work better to create a more interactive system. The results of this study are a website that can be used by UMKM as a means of selling their business products amid the Covid-19 pandemic.
Prototype Aplikasi Edukasi Anak Berbasis Mobile Wahyutama Fitri Hidayat; Yesni Malau; Muhammad Fahmi Julianto
Reputasi: Jurnal Rekayasa Perangkat Lunak Vol. 3 No. 1 (2022): Mei 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Teknologi informasi dunia dimana saat ini sedang berkembang dengan pesat telah menyasar berbagai aspek di masyarakat yaitu ekonomi, kebudayaan, seni, politik, dan tak terkecuali dunia pendidikan. Tujuan dari penelitian yag dilakukan yaitu menghasilkan prototype aplikasi yang berberbasiskan mobile application dengan diberikan nama Aplikasi Edukasi Anak. Batasan yang digunakan di penelitian ini yaitu hanya akan dibahas mengenai merancangan aplikasi berdasarkan model prototype. Hasil dari penelitian ini berupa rancangan Aplikasi Edukasi Anak berbasis mobile yang dirancang menggunakan aplikasi Justinmind. Hasil rancangan yang dilakukan pengujian dengan digunakannya metode BlackBox dapat menghasilkan fitur aplikasi prototype yang dirancang dapat berjalan sesuai dengan rancangan dan diterima.
Sentiment Analysis of Twitter's Opinion on The Russia and Ukraine War Using Bert Muhammad Fahmi Julianto; Yesni Malau; Wahyutama Fitri Hidayat
Jurnal Riset Informatika Vol 5 No 1 (2022): Priode of December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.452

Abstract

News about the war that took place between Russia and Ukraine can not be denied affecting various aspects of life in the world. This affects the writings of every citizen of the world on various social media platforms, one of which is Twitter. Sentiment analysis is a process of identifying and making sentiment categories which is done computationally. Sentiment analysis process is also intended to make computers understand the meaning of sentences written by humans by processing using algorithms. This study uses a deep learning method using a language model, namely BERT (Bidirectional Encoder Representation Form Transformers) as a process of analyzing the sentiments that exist in tweets written about the war in Russia and Ukraine by twetter social media users. These sentiments will be divided into three parts, namely positive, neutral and negative. In this study, the hyperparameters used were 10 epochs, learning rate 2e-5, and batch size 16. The sentiment analysis test used the BERTbase Multilingual-cased-model model and the accuracy value obtained was 97%.
Pelatihan Pembuatan Video Reel Instagram Menggunakan Canva Pada Yayasan Widya Kapuas Kalbar Eri Bayu Pratama; Wahyutama Fitri Hidayat; Hermanto Hermanto; Muhamad Syarif; Ade Hendini
Jurnal Pengabdian Literasi Digital Indonesia Vol. 1 No. 2 (2022): December
Publisher : Puslitbang Akademi Relawan TIK Indonesia (ARTIKA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (629.589 KB) | DOI: 10.57119/abdimas.v1i2.11

Abstract

The development of information and communication technology today has changed the way humans interact with each other. Social media is one of the media that allows humans to interact without being limited by space and time. The positive impact of using social media can be used as a medium of information. However, this positive impact must be accompanied by an increase in digital literacy, especially in designing information that will be conveyed to the public, one of which is through the Instagram application rails. This service has the main goal of providing training in the form of making Instagram reels using the Canva application. The target of community service activity partners is in the form of non-formal institutions, the Yayasan YAWIKA Kota Pontianak. The method of implementation is done offline by coming directly at the location of community service. The results of this activity showed satisfactory results from the participants as well as increasing digital literacy, especially in optimizing social media as a medium of information and using the Canva application.
Klasifikasi Penyakit Daun Kentang Menggunakan Model Logistic Regression Wahyutama Fitri Hidayat; Taufik Asra; Ahmad Setiadi
Indonesian Journal on Software Engineering (IJSE) Vol 8, No 2 (2022): IJSE 2022
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/ijse.v8i2.14624

Abstract

Tanaman kentang merupakan salah satu jenis umbi-umbian yang ditanam di Indonesia. Budidaya kentang dapat dikatakan tidak selalu sesuai yang diharapkan, serangan hama dan penyakit menjadi salah satu faktor penyebabnya. Sebagai upaya indentifikasi penyakit pada tanaman kentang dilakukan penelitian berdasarkan klasifikasi penyakit daun pada tumbuhan kentang. Penelitian ini berisi tentang membuat suatu sistem untuk identifikasi berdasarkan citra daun pada tanaman kentang menggunakan metode klasifikasi Logistic Regression sedangkan untuk ekstraksi fitur digunakan Resnet50. Tahap perancangan sistem diawali dnegan menggumpulkan data berupa data sekunder mengenai penyakit pada daun tanaman kentang, setelah itu dilakukan fitur ekstraksi, data test dan train (pembagian data), serta menghitung nilai akurasi dan prediksi. Model ini dapat mengidentifikasi berdasarkan citra dimana sehingga menghasilkan luaran berupa nilai akurasi dari penerapan model Logistic Regression dan fitur ekstrasi Resnet50. Berdasarkan percobaan yang telah  dilakukan, menggunakan data latih menghasilkan nilai akurasi sebesar 98%, sedangkan menggunakan seluruh data dengan jumlah 405 citra menghasilkan nilai akurasi sebesar 80%.               Kata kunci: Pemrosesan Gambar, Klasifikasi, Resnet50, Logistic Regression
Konfigurasi dan Implementasi OwnCloud Sebagai Cloud Storage Wahyutama Fitri Hidayat; Yesni Malau; Ahmad Setiadi; Muhammad Fahmi Julianto
Jurnal Infortech Vol 5, No 1 (2023): JUNI 2023
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/infortech.v5i1.15836

Abstract

Penelitian bertujuan mengkonfigurasi dan implementasi penyimpanan cloud sehingga dapat memberikan kemudahan dalam proses bisnis organisasi karang taruna Gemamikow. Metode penelitian yang digunakan merupakan prototype model, dimana dilakukan identifikasi kebutuhan, mendesain logika jaringan komputer, konfigurasi jaringan komputer, dan implementasi. Hasil penelitian ini berupa cloud storage yang dapat digunakan sebagai penyimpanan file dalam bentuk dokumen, gambar, maupun video. Keamanan data digunakan akses login, hal ini dilakukan sebagai upaya pencegahan terhadap pencurian informasi oleh pihak yang tidak seharusnya mengakses informasi tersebut. Hasil akhir dari pembuatan cloud storage, batas maksimal file ditentukan berdasarkan identifikasi kebutuhan masing-masing divisi, kemudian untuk penyimpanan cloud storage digunakan XAMPP yang memiliki paket Apache sebagai server lokal dan MySQL sebagai database. Konfigurasi jaringan komputer difungsikan untuk membuat akses server yang tadinya hanya dapat diakses secara lokal setelah dikonfigurasi dapat diakses menggunakan jaringan internet.
Co-Authors Ade Hendini Ahmad Setiadi Ali Mustopa, Ali Annida Purnamawati Destiana Putri Eri Bayu Pratama Fajar Sarasati Fajar Shidiq Fintri Indriyani Hermanto Hermanto Muhamad Syarif Muhammad Fahmi Julianto Paulus Tofan Rapiyanta Rangga Sanjaya Taufik Asra Wawan Nugroho Yesni Malau