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All Journal MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Jurnal Teknologi Sistem Informasi dan Aplikasi Astonjadro Multitek Indonesia : Jurnal Ilmiah Jurnal Riset Informatika Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi BRITech : Jurnal Ilmiah Ilmu Komputer, Sains dan Teknologi Terapan Jurnal Valuasi : Jurnal Ilmiah Ilmu Manajemen dan Kewirausahaan Jurnal Kecerdasan Buatan dan Teknologi Informasi
Hasan Basri
Universitas Terbuka
Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance

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EKSTRAKSI CIRI CITRA KAYU MERBAU DAN KAYU JATI BOJONEGORO MENGGUNAKAN DISCRETE WAVELET TRANSFORM Hasan Basri; Widyastuti, Rifka
BRITech, Jurnal Ilmiah Ilmu Komputer, Sains dan Teknologi Terapan Vol 1 No 2 (2020): Periode Januari
Publisher : Institute Teknologi dan Bisnis Bank Rakyat Indonesia

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Abstract

Keberagaman hasil kayu di indonesia mempunyai keunggulan masing-masing. Untuk mendukung terjaminnya kualitas suatu jenis kayu, maka diperlukan suatu sistem yang dapat mengidentifikasi jenis kayu. Salah satu tahapan identifikasi menggunakan citra digital yaitu proses ekstraksi ciri citra. Ekstraksi ciri citra menggunakan Discrete Wavelet Transform dengan objek penelitian kayu merbau dan kayu jati bojonegoro menghasilkan nilai ciri yang baik pada koefisien LL.
Sistem Pendukung Keputusan Pada Agroindustri Kopi Di Kabupaten Bogor Menggunakan Metode Analytic Hierarchy Process (Ahp) Neneng Rachmalia Feta; Asep Rahmat Ginanjar; Hasan Basri; Michael Sitorus
BRITech, Jurnal Ilmiah Ilmu Komputer, Sains dan Teknologi Terapan Vol 2 No 1 (2020): Periode Juli
Publisher : Institute Teknologi dan Bisnis Bank Rakyat Indonesia

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Abstract

Coffee commodities are agricultural commodities that have highexport value. Indonesia ranks fourth as the most significant coffee exportingcountry in the world. The main problem that occurs is the availability ofabundant crops, not balanced by proper postharvest processing andmarketing and the absence of farmers partnership with the coffeeprocessing industry. This study focuses on the determination of coffeeagroindustry products using the AHP method and the institutionaldetermination of coffee agroindustry using the exponential comparisonmethod. SPK development will use super decision software. The final resultof this study is the calculation of product determination obtained that instantcoffee has the highest weight of 0.3739, while the institution of coffeeagroindustry shows that establishing cooperation with Hulu - Hilir Industryhas the highest weight, namely 389,637
STRATEGI PROMOSI DESA WISATA TANJUNGJAYA KEK TANJUNG LESUNG MELALUI PLATFORM DIGITAL Anang Martoyo; Ninuk Wiliani; Hasan Basri
Valuasi : Jurnal Ilmiah Ilmu Manajemen dan Kewirausahaan Vol. 2 No. 2 (2022): Jurnal Valuasi : Jurnal Ilmiah Ilmu Manajemen dan Kewirausahaan
Publisher : LP2M Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/vls.v2i2.136

Abstract

The COVID-19 pandemic has paralyzed the economy, especially the tourism industry. The government's decision to reopen tourist areas because the spread of the corona has subsided raised the enthusiasm of the tourism village managers. Advances in information technology are utilized by tourism service managers as a medium to communicate superior tourism service products. This study aims to find out how the promotion strategy by utilizing the Digital Platform in increasing the number of visitors in the Tanjungjaya Tourism Village KEK Tanjung Lesung and developing the surrounding area. The research method used is descriptive qualitative with research instruments in the form of primary data derived from observations, interviews from several visitors, and exposure of local officials as well as secondary data from other relevant literacy studies. The data collection technique used triangulation method with inductive analysis referring to positive beliefs, perceptions, certain criteria, and the relationship between variables. Based on the results of observations and analysis of the marketing situation in Tanjungjaya Tourism Village, it can be concluded that the digital platform-based promotion strategy that has been carried out by tourism service managers is 1) Use of the website belonging to the Ministry of Tourism and Creative Economy, the website of the Tourism and Culture Office of Pandeglang Regency, and the website Official CBT Tourism Village Community, 2) Utilization of social media consisting of Facebook, Instagram, and Youtube, 3) Integrated Marketing Communication (IMC) by involving business actors by utilizing marketplaces such as planethotels, traveloka, agoda, en.tiket, and tripadvisor
Texture Feature Extraction of Pathogen Microscopic Image Using Discrete Wavelet Transform Hasan Basri
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.v5i1.488

Abstract

This study used a case study of Jabon leaves, and the pathogen is one of the causes of disease that attack the leaves of jabon, one of the leaf spots and leaf blight. Discovery of leaf spot disease in different pathogens and leaf blight. The pathogen was obtained from the leaf spot of Curvularia sp. 1 and Pestalotia sp., while the pathogen came from Curvularia sp. 2 and Botrytis sp. Identify the pathogen as soon as possible to minimize its effects. Improper handling can lead to increased virulence and resistance to the pathogen. Improper handling also can cause a disease outbreak (disease epidemic) in a region. This study is the first step in identifying the pathogens responsible for Jabon leaf disease. In this study, the Application of Koch's Postulates method to achieve the purification of pathogens and retrieve the microscopic pathogen image as the data acquisition stage. Furthermore, use of the segmentation stage to separate the object pathogen from the background, and one of the methods used is Otsu Thresholding. The extraction process of pathogen microscopic image using Discrete Wavelet Transform (DWT), DWT extraction results can be obtained using energy and entropy information.
Perbandingan Metode GLCM dan DWT Dalam Mengekstraksi Ciri Penyakit pada Daun Tomat (Solanum lycopersicum syn) Tampinongkol, Felliks; Herdian, Cevi; Basri, Hasan; Ginting, Jusia A; Purnomo, Yunianto
Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Vol 8 No 2 (2023): 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.v8i2.5423

Abstract

Penyakit yang disebabkan oleh pathogen dapat menyebabkan terjadinya kematian pada suatu tanaman tertentu yang terjangkit oleh penyakit tersebut. Pathogen memerlukan inang untuk dapat berkembang biak agar dapat menginfeksi bagian tumbuhan yang masih sehat. Bagian daun pada tumbuhan yang menjadi tempat untuk pathogen berkembang biak, sehingga dapat mengakibatkan kematian jaringan pada daun dan membuat tumbuhan tidak dapat berkembang atau mati. Leaf spot dan leaf blight merupakan penyakit yang disebabkan oleh pathogen dan sering ditemukan pada tumbuhan seperti yang ditemukan pada tomat (Solanum lycopersicum syn). Identifikasi penyakit pada tanaman tomat dapat dilakukan dengan pendekatan image processing menggunakan gambar (image) dari daun tomat yang terkena penyakit berak (spot) dan hawar (blight). Gambar yang digunakan dilakukan proses segmentasi terlebih dahulu untuk memisahkan object penyakit dari background yang bukan area penyakit, area penyakit daun tomat berhasil tersegmentasi pada proses pengurangan antar channel warna Green–Red (GR). Sebaliknya invers channel warna tersebut mengsegmentasi area daun berwarna hijau atau area sehat. Setelah berhasil tersegmentasi selanjutnya image GR dilakukan pengenalan ciri menggunakan dua metode yang berbeda Gray Level Co-occurrence Matrix (GLCM) dan Discrete Wavelet Transform (DWT). Kedua metode dapat mengenali ciri penyakit daun dengan baik berdasarkan pada nilai Energy dan Entropy yang diperoleh. Tahapan selanjutnya dapat menambahkan teknik Machine Learning (ML) agar hasil pengenalan ciri penyakit daun dapat diklasifikasikan dan dijadikan model untuk melatih atau mengenali penyakit daun pada varietas tumbuhan yang lain.
ANALISIS SENTIMEN TERHADAP LAYANAN NASABAH BANK MENGGUNAKAN TEKNIK KLASIFIKASI NAIVE BAYES Putri Puspa Wulan; Basri, Hasan
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 3 No. 2 (2024): May 2024
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v3i2.131

Abstract

Pelayanan pelanggan di sektor perbankan berpengaruh besar terhadap kepuasan dan kesetiaan nasabah. Namun, mengukur kepuasan dengan kuesioner tertutup seringkali tidak mencakup semua opini. Untuk mengatasi hal ini, analisis sentimen pada kuesioner terbuka digunakan. Sektor perbankan secara umum mengutamakan pelayanan pelanggan, dengan fokus pada senyum, salam, dan sapa. Penelitian ini bertujuan untuk menganalisis sentimen terhadap pelayanan pelanggan bank menggunakan metode klasifikasi Naive Bayes. Data diperoleh melalui survei kuesioner terbuka, kemudian dianalisis menggunakan metode Naive Bayes untuk mengklasifikasikan sentimen menjadi positif dan negatif. Hasil penelitian menunjukkan bahwa metode Naive Bayes efektif dengan akurasi 76.32%. Model yang terbentuk dapat digunakan untuk menganalisis komentar baru dari nasabah, mengekstrak sentimen positif dan negatif, serta memberikan wawasan mendalam kepada bank tentang penilaian nasabah terhadap pelayanan pelanggan. Dengan demikian, bank dapat mengambil tindakan yang sesuai untuk meningkatkan kepuasan nasabah dan kualitas pelayanan secara keseluruhan.
OPTIMIZING SENTIMENT ANALYSIS FOR USABILITY TESTING: ENHANCING SVM ACCURACY THROUGH KERNEL SELECTION AND TUNING METHODS Basri, Hasan
MULTITEK INDONESIA Vol 18, No 2 (2024): Desember
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/mtkind.v18i2.10615

Abstract

With over 2.4 million apps on the Google Play Store by 2023, app developers face increasing demands to ensure high usability quality to remain competitive. Traditional usability testing methods, including heuristic evaluations and user questionnaires, are often limited by high costs, time constraints, and lack of real-world context. Sentiment analysis presents an alternative approach, leveraging user reviews as a resource for usability insights. This research applies Support Vector Machine (SVM) for sentiment analysis and usability testing on Google Play Store reviews, focusing on five usability criteria. Data collection yielded 2,000 reviews from a banking app, with two annotators conducting multi-label labeling for both sentiment and usability criteria. Through a series of experiments, the Linear Kernel in SVM demonstrated the highest performance, achieving 70.50% accuracy, an F1 Score of 0.8618, and a Hamming Loss of 0.0783. Grid Search was employed to optimize the C parameter for the linear kernel, revealing an optimal C value of 0.01, which resulted in an improved accuracy of 75.20%, F1 Score of 0.8775, and Hamming Loss of 0.0686. Experiments with values above or below 0.01 showed decreased accuracy, underscoring the importance of a balanced C value to enhance model generalization and avoid overfitting. These findings suggest that sentiment analysis via SVM can effectively capture usability feedback from user reviews, providing a scalable, data-driven solution for app usability assessment. This study is part of the Machine Learning for Software Engineering (ML4SE) domain, where machine learning techniques are applied to enhance software engineering practices, specifically in optimizing usability assessment through automated analysis of user feedback.
Analysis and Design of the Web Base Guesthouse Reservation Information System at Universitas Terbuka Using The Prototype Method Kusyadi, Irpan; Junianto, Mochamad Bagoes Satria; Basri, Hasan
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 17, No 1 (2025): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v17i1.32380

Abstract

Efficient guesthouse reservation management is crucial to supporting the accommodation services provided by Universitas Terbuka. Currently, the existing system faces limitations in data management and time efficiency, particularly in the reservation, recording, and reporting processes. This study aims to analyze and design a web-based guesthouse reservation information system that is expected to facilitate the reservation process more effectively and transparently. The design approach used is the prototype method, which allows system development based on early user feedback. The research begins with identifying requirements through the stages of communication, planning, modeling, prototyping, and feedback collection. The results of this analysis are then used as the basis for designing the system model and the initial user interface (UI/UX). The system prototype is then developed and iteratively evaluated by involving potential users, including guesthouse managers and prospective guests, to ensure that the final design meets user needs
Enhancing Usability Testing Through Sentiment Analysis: A Comparative Study Using SVM, Naive Bayes, Decision Trees and Random Forest Basri, Hasan; Junianto, Mochamad Bagoes Satria; Kusyadi, Irpan
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 4 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i4.45117

Abstract

In the digital age, mobile applications have become an integral part of everyday life, making usability testing an essential factor in ensuring a seamless user experience. Traditional usability testing methods often demand considerable resources, including time and cost, which calls for more efficient and automated alternatives. This study explores the use of sentiment analysis as an innovative approach to evaluate the usability of mobile applications. By analyzing user reviews from the Google Play Store, the research compares the effectiveness of four machine learning algorithms—Support Vector Machine (SVM), Naive Bayes, Decision Tree, and Random Forest—in classifying sentiment and evaluating usability. A dataset consisting of 2,000 reviews from a banking app was collected and labeled based on usability criteria, such as efficiency, user satisfaction, learnability, memorability, and error rates. The feature extraction process utilized Term Frequency-Inverse Document Frequency (TF-IDF) to enhance the relevance of the review texts for sentiment analysis. The findings reveal that Random Forest achieved the highest accuracy (68.15%) and demonstrated the best performance in terms of F1 Score, precision, and recall, although it had the longest processing time. In contrast, Naive Bayes, while the fastest, showed lower accuracy and F1 Score, making it suitable for applications with large datasets or limited processing time. Decision Tree and SVM offered a balanced trade-off between speed and accuracy. The study concludes that Random Forest is the preferred choice when high accuracy and prediction performance are crucial, despite its longer processing time. Meanwhile, Naive Bayes is more appropriate for scenarios demanding rapid data processing, and SVM and Decision Tree are recommended when a balance between speed and accuracy is needed.
Sistem Pendukung Keputusan Metode Simple Additive Weighting (SAW) Pemilihan Vendor Jasa Boga Terbaik pada Pusat Bisnis Universitas Terbuka Junianto, Mochamad Bagoes Satria; Basri, Hasan
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 4 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i4.45152

Abstract

The Open University Business Center has duties and functions that focus on the management and development of business units that support the operations and financial sustainability of the Open University. One of the policies handled is the selection of catering vendors used at every event in the Open University environment. Selecting the right catering vendor is a crucial factor in ensuring customer quality and satisfaction. There are 12 catering vendors who are partners of the Open University Business Center which are usually only assessed based on the presentation and quality of the food (Taste). In fact, besides these 2 criteria, there are still several other criteria that must be considered such as Punctuality, interest and vendor experience (administration). The SAW method was chosen because of its ability to carry out multi-criteria assessments simply and efficiently. Of the 12 catering vendors who collaborate with the Open University Business Center, a ranking will be given where the vendor with the highest score is considered most appropriate to the needs of the Open University Business Center. With this Decision Support System, it is hoped that the catering vendor selection process can be carried out objectively, transparently and faster so as to support better decision making at the Open University Business Center.
Co-Authors Anang Martoyo Asep Rahmat Ginanjar Dewi Dyah Maharani, Maya Didik Sugiyanto Felliks Tampinongkol, Felliks Ginting, Jusia A Herdian, Cevi Irpan Kusyadi Istoni, Reza Junianto, Mochamad Bagoes Satria Lestari, Putri Winda Michael Sitorus Mumpuni Ngesti Rahaju, Sri Neneng Rachmalia Feta Ninuk Wiliani Purnomo, Yunianto Putri Puspa Wulan Rifka Widyastuti, Rifka Uci Sulandari