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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Reconfigurable and Embedded Systems (IJRES) International Journal of Advances in Applied Sciences IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Lensa: Kajian Kebahasaan, Kesusastraan, dan Budaya Dinamik Jurnal Simetris Abdimas Telematika Jurnal Transformatika KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Abdimas BSI: Jurnal Pengabdian Kepada Masyarakat IJCIT (Indonesian Journal on Computer and Information Technology) Journal of Economic, Bussines and Accounting (COSTING) Voice Of Informatics STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Building of Informatics, Technology and Science Jurnal Teknologi Informasi dan Multimedia Jurnal Teknologi Dan Sistem Informasi Bisnis JATI (Jurnal Mahasiswa Teknik Informatika) Scientific Journal of Informatics Jurnal E-Komtek Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Sistem Komputer dan Informatika (JSON) JITU : Journal Informatic Technology And Communication Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) Jurnal Teknologi Informasi dan Komunikasi Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) International Journal of Quantitative Research and Modeling JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Sistem Informasi Galuh SmartComp Tematik Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Muria Pengabdian Masyarakat Jurnal DIMASTIK Palawa Jurnal Pengabdian Kepada Masyarakat
Susanto Susanto
Universitas Semarang
Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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The Selection of Learning Platforms to Support Learning Using Fuzzy Multiple Attribute Decision Making Vensy Vydia; Susanto Susanto; Sri Handayani; Maulana Bahrul Alam
International Journal of Quantitative Research and Modeling Vol. 3 No. 1 (2022): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v3i1.257

Abstract

The utilization of information technology in learning has functioned as a tool in the teaching and learning process during the Covid-19 pandemic. The need for the availability of a learning platform using LMS (Learning Management System) or free e-learning that is easily obtained from the public network (internet) makes the utilization of the learning platform indispensable for the teaching and learning process. Learning platforms available on the internet can also be used independently by students. However, not all existing learning platforms can be used as the appropriate means to improve the quality of education. The educator policies are needed to utilize the existing learning platforms so that learning objectives can be achieved. This study will analyze how to choose the right learning platform for an educational institution using SAW (Simple Additive Weighting)-based Fuzzy Multiple Attribute Decision Making (FMADM) method. FMADM is a method used to find the optimal alternative from a number of alternatives with certain criteria. The purpose of this study is to assist educators in deciding the most appropriate learning platform that can be used to support the teaching and learning process during the Covid 19 pandemic.
Optuna-Driven Hyperparameter Optimization in Tsukamoto Fuzzy Logic for House Price Estimation Annisa Aurelia Fitriani; Nabilah Putri Wijaya; Susanto Susanto; Nur Wakhidah
Building of Informatics, Technology and Science (BITS) Vol 8 No 1 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v8i1.9573

Abstract

The property sector faces challenges in determining accurate house selling prices due to subjectivity and market uncertainty. The relationship between physical attributes, such as land area and building area, and price is not always linear, making conventional methods often less precise in estimation. This study aims to design a decision support system to objectively estimate house prices in the Plamongan area, Semarang. The method used is Fuzzy Tsukamoto Logic. This preliminary study explores the integration of the Tree-structured Parzen Estimator (TPE) algorithm through the Optuna framework to automatically optimize membership function limits, replacing manual trial and error methods. The dataset was collected via scraping techniques, providing a pilot dataset of 26 data points. Final model performance evaluation showed a Mean Absolute Percentage Error (MAPE) value of 11.39%, which falls into the 'Good Forecast' category. However, given the highly limited sample size, these findings primarily serve as a proof-of-concept that requires further validation with larger, multi-variable datasets. These results prove that integrating the Fuzzy Tsukamoto method with hyperparameter optimization is effective in reducing subjectivity and providing reliable property price estimates. The primary contribution of this research is providing a mathematical proof-of-concept for an automated, objective property valuation system that eliminates human bias in fuzzy parameter configuration, offering a practical baseline tool for localized real estate markets.
Pendekatan Naive Bayes dalam Analisis Sentimen pada Ulasan Pengguna Aplikasi Indodax di Platform Google Play Store Riki Ardi Pranata; Susanto Susanto; Nur Wakhidah
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 15, No 2 (2026): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v15i2.9938

Abstract

Aplikasi investasi digital, seperti Indodax, berperan sebagai sarana transaksi jual beli aset kripto yang mendukung aktivitas pengguna sesuai dengan tujuan dan kebutuhan investasi. Analisis sentimen digunakan untuk mengidentifikasi opini serta kecenderungan sikap pengguna terhadap suatu topik. Penelitian ini bertujuan untuk menganalisis sentimen ulasan pengguna Aplikasi Indodax yang diperoleh dari platform Google Play Store. Metodologi yang diterapkan adalah Knowledge Discovery in Database (KDD), yang meliputi tahapan data selection, preprocessing, pelabelan berbasis lexicon-based, transformation, klasifikasi menggunakan algoritma Naive Bayes, serta evaluasi. Proses klasifikasi dilakukan untuk mengelompokkan ulasan ke dalam dua kategori sentimen, yaitu positif dan negatif. Dataset penelitian berasal dari ulasan pengguna Play Store yang telah melalui tahap prapemrosesan teks. Hasil pengujian menunjukkan algoritma Naive Bayes memberikan performa klasifikasi yang cukup baik. Berdasarkan tiga skenario pembagian data latih dan data uji, yaitu rasio 60:40, 70:30, dan 80:20, diperoleh rasio 60:40 menghasilkan kinerja optimal dengan nilai akurasi sebesar 82,95% serta nilai presisi, recall, dan F1-score sebesar 83%. Distribusi sentimen menunjukkan 55,45% ulasan bersifat negatif dan 44,55% bersifat positif, menandakan tanggapan pengguna terhadap aplikasi Indodax masih didominasi oleh sentimen negatif. Namun, metode pelabelan berbasis lexicon-based masih kesulitan dalam konteks kalimat seperti sarkasme, bahasa informal, dan ambigu dari sebuah ulasan.
Rancang Bangun Aplikasi Antrian Komunitas Game Arcade Maimai Berbasis Framework Laravel Insannul Imam Rohny Khoirri; Susanto Susanto
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 15, No 2 (2026): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v15i2.10027

Abstract

Meningkatnya popularitas game arcade maimai di kalangan pecinta musik dan komunitas rhythm game menghadirkan permasalahan baru, yakni terbatasnya jumlah mesin arcade yang tersedia dibandingkan dengan banyaknya pemain yang ingin bermain. Kondisi ini sering menyebabkan antrean Panjang dan ketidaknyamanan dalam pengelolaan waktu bermain. Bahkan untuk beberapa game center tidak memperbolehkan memasang papan antrian, jadi akan menyusahkan jika setiap datang harus membawa papan antrian sendiri. Untuk mengatasi hal tersebut, penelitian ini merancang sebuah aplikasi antrian berbasis web menggunakan framework Laravel yang bertujuan untuk mempermudah pengelolaan antrean secara digital, transparan, dan terorganisir. Aplikasi ini dirancang dengan fitur utama seperti pengisian antrean secara real-time dan serta histori antrean. Dengan menerapkan metode pengembangan sistem RAD (Rapid Application Development), aplikasi ini diuji melalui simulasi penggunaan oleh komunitas pemain Maimai. Diharapkan bahwa sistem antrian digital ini mampu meningkatkan efisiensi waktu tunggu dan mengurangi terlewatinya antrian untuk pemain yang pergi untuk makan atau melakukan kegiatan lain . Dengan demikian, aplikasi ini diharapkan dapat menjadi solusi efektif dalam mendukung pengalaman bermain yang lebih tertib dan menyenangkan bagi komunitas game arcade Maimai.
Implementasi Metode SMART Untuk Menentukan Kinerja Pegawai Terbaik Pada CV Swastika Permata Kontruksi Fila Puspita Sari; Susanto Susanto
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 15, No 1 (2026): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v15i1.9827

Abstract

: Evaluasi kinerja pegawai adalah elemen penting dalam pengelolaan sumber daya manusia yang berfungsi untuk menilai seberapa efektif, produktif, dan berkontribusinya individu terhadap sasaran organisasi. CV Swastika Permata Konstruksi, sebagai perusahaan yang bergerak di industri konstruksi, membutuhkan sistem penilaian yang adil, transparan, dan terukur untuk mengidentifikasi pegawai terbaik. Dalam studi ini, metode Simple Multi Attribute Rating Technique (SMART) digunakan sebagai pendekatan penilaian yang berdasarkan pada kriteria. Pemilihan metode SMART dilakukan karena kemampuannya untuk menggabungkan bobot dan nilai guna dari tiap kriteria penilaian, seperti tanggung jawab, skill, presentasi, kerja tim, dan loyalitas. Dengan melalui proses perhitungan yang terstruktur, didapatkan skor akhir yang mempertimbangkan kinerja total setiap pegawai. Temuan penelitian mengindikasikan bahwa pegawai dengan skor tertinggi menunjukkan performa terbaik berdasarkan bobot yang telah ditetapkan. Implementasi metode SMART terbukti meningkatkan objektivitas, efisiensi, dan membantu manajemen dalam pengambilan keputusan
Perancangan Aplikasi Pemantauan Aktivitas Fisik Mobile Berbasis User-Centered Design Purbo Pangestu Satria Jati; Susanto Susanto; Titis Handayani
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 4 (2025): November
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i4.811

Abstract

Physical activity monitoring is an important aspect of maintaining health and fitness. With increasing awareness of the importance of a healthy lifestyle, many people are trying to be more physically active. Although many health apps offer physical activity monitoring features, not all apps are designed with user comfort and needs in mind. This study aims to design and evaluate a prototype of a mobile-based health app user interface that emphasizes comfort in physical activity monitoring, using a User-Centered Design (UCD) approach. This approach places the user at the center of the entire design process, ensuring that the design aligns with users' actual preferences and needs. The research methodology includes stages of understanding the user context, identifying user needs, designing the interface (wireframes and user flow), and evaluating the design through A/B testing conducted internally or preliminarily, without involving external respondents. The results of the study indicate that design version B is superior to version A in terms of ease of use and user engagement, as evidenced by a 67.86% increase in interaction and a 71.43% increase in feature usage, based on quantitative metrics such as task completion count and average interaction time measured through internal task scenario simulations. Version B features a more modern appearance and simple, clear navigation. These findings underscore the importance of applying UCD principles in the development of effective and efficient health application interfaces. A better design can encourage user engagement in monitoring physical activity. The application, once designed, not only meets current user needs but also has a strong foundation for future development requirements.
Implementasi Model Machine Learning untuk Deteksi Phishing dengan Pendekatan Ekstraksi Fitur yang Dioptimalkan Adam Pradana; Susanto Susanto
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 1 (2026): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i1.881

Abstract

Phishing is a common form of cybercrime used by digital criminals to steal sensitive information such as passwords, personal data, and financial details through fake websites designed to re-semble legitimate pages. However, conventional detection methods such as blacklists and manual inspection are currently considered ineffective due to their static nature, often failing to recognize new, evolving and increasingly sophisticated attack patterns. To address this issue, this study developed a machine learning-based phishing detection model focused on improving the accura-cy and efficiency of identifying malicious sites. This model applies an optimized feature extrac-tion technique to enable the system to analyze URL characteristic patterns more comprehensively and targeted. The research dataset was taken from the Kaggle platform, which provides a dataset of phishing and benign URLs with a high reputation. The data was then processed through nor-malization, cleaning, and extraction of important features such as URL structure and domain at-tributes. The classification process was carried out using an ensemble learning approach that combines four popular algorithms: Random Forest, Gradient Boosting, Logistic Regression, and AdaBoost through a soft voting mechanism. The evaluation results show that the proposed model has excellent performance with an accuracy of 98.10%, a precision of 97.81%, a recall of 93.90%, an F1-Score of 95.82%, and a ROC-AUC of 98.62%. These findings confirm that the ensemble ap-proach with optimized features has great potential for application in artificial intelligence-based cybersecurity systems capable of adaptive and real-time phishing detection.
Perancangan dan Implementasi Sistem Pengelolaan Order Barang Berbasis Web dengan Laravel Nabela Yulian Anggraini; Susanto Susanto
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 1 (2026): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i1.890

Abstract

CV. Surya Sarana Dinamika currently faces significant operational inefficiencies due to its man-ual, paper-based order management process. These challenges lead to frequent data recording errors, substantial delays in information flow, and a critical lack of real-time visibility regarding order status, which ultimately hinders effective administrative decision-making. This study aims to address these systemic issues by designing and implementing a web-based order management system utilizing the Laravel Framework. The system was developed using the Agile Development methodology, employing iterative cycles to ensure that the final product remains aligned with dynamic business requirements. The architecture is built upon the Model-View-Controller (MVC) pattern to ensure code scalability and long-term maintenance ease. Functional validation via Black-Box testing confirms that all core features, including order submission and purchasing validation, operate according to specifications. Quantitatively, the implementation resulted in a drastic efficiency increase; the average time for order submission decreased from 20-25 minutes to just 3-5 minutes (an efficiency gain of over 75%), while purchasing validation time was re-duced from 30-60 minutes to 5-10 minutes. These findings demonstrate that digital automation effectively eliminates manual bottlenecks and reduces the risk of human error. By providing cen-tralized data and real-time tracking, the system significantly enhances accountability and trans-parency within the company’s supply chain, providing a replicable model for digital transfor-mation in similar organizational contexts..
Rancang Bangun Sistem Informasi Pendaftaran Siswa Baru Berbasis Web dengan Metode Waterfall pada TK Pertiwi 14 Gilang Akbar Romadhoni; Susanto Susanto; Titis Handayani
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 1 (2026): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i1.895

Abstract

The transformation of information technology in the modern era provides significant opportunities to improve the effectiveness of educational administration, particularly in the new student admission process. One form of implementation is a web-based registration system that can automate the online registration flow and minimize data recording errors. Pertiwi 14 Kindergarten currently still uses the conventional registration method through paper forms that require parents to be present in person at the school, potentially causing verification delays, information duplication, and data input errors. This study aims to design and build a web-based new student registration system using the Laravel framework with Laravel Filament support to display a dynamic interface and structured data management. The system development uses the Waterfall model through the stages of needs analysis, design, implementation, testing, and maintenance. Testing results using Black Box Testing show that all system functions run according to specifications without any errors and are able to reduce input errors by up to 100% compared to manual methods. In addition, the registration data verification process is faster with an increase in time efficiency of 70%. The implementation of this system makes a real contribution to improving ease of access, data accuracy, management transparency, and administrative efficiency in the new student admission process at Pertiwi 14 Kindergarten.
Implementasi Algoritma FP-Growth untuk Sistem Rekomendasi Produk Kebutuhan Pokok pada E-Commerce Mahjid Herlambang; Susanto Susanto
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 1 (2026): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i1.900

Abstract

The rapid development of e-commerce in Indonesia necessitates recommendation systems that can capture user purchasing patterns accurately, adaptively, and in a data-driven manner. This study implements the FP-Growth algorithm to analyze transaction data from a self-developed essential-goods e-commerce platform. The research dataset consists of 60 user accounts with a total of 600 completed transactions, processed using a Python-based analytical module and au-tomatically integrated into a Laravel backend through a dedicated execution script. The FP-Growth algorithm is applied to generate frequent itemsets and association rules using a min-imum support of 0.01, a minimum confidence of 0.1, and a minimum lift of 1.0. The results indi-cate that the most dominant associative patterns occur among kitchen staple products such as in-stant noodles, chicken eggs, and wheat flour, as well as household cleaning products such as de-tergents and fabric softeners. Several rules exhibit confidence values as high as 0.9615 and lift values up to 4.451, indicating strong and statistically significant relationships between products. System performance evaluation using a Top-4 recommendation scheme shows a Hit Rate of 54.35% and a Recall of 54.35%, demonstrating that the system is able to provide relevant recom-mendations for the majority of transactions. This implementation is shown to improve recom-mendation accuracy while strengthening personalization and cross-selling strategies on essen-tial-goods e-commerce platforms. These findings confirm that FP-Growth is an effective and effi-cient method for identifying empirical purchasing patterns and supporting the development of recommendation systems in small- to medium-scale e-commerce environments.
Co-Authors Abriansah, Fausta Rizky Adam Pradana Adellia Hilda Putri Ahmad Maulana Arif Ahmad Syauqi Alauddin Maulana Hirzan Alda Hani Meidina Alfian Nur Fariq Anggi Ratnasari Annisa Aurelia Fitriani Aprih Santoso April Firman Daru Ardi Pramono Ardiyanto, Ilham Aria Hendrawan, Aria Astrid Novita Putri, Astrid Asyira Andhini Luna Atmoko Nugroho Az-Zahra Jasmine Sya'bania Basworo Ardi Pramono Burhan Harminanto Cahyono, Yudi Cholil, Saifur Rohman Dewanti, Tita Risa Dewi Nurdiyah, Dewi Dimas Dwi Budiarjo Dipa Teruna Awaloedin Dlovan Ferdiansyah Edi Widodo, Edi Eka Putri Rachmawati Erica Rahmawati Faranisa Ulya Ashari Febrian Wahyu Christanto Ferdian, Praditya Rendi Fila Puspita Sari Firdaus, Azmi Maulana Gilang Akbar Romadhoni Hafidz Zamzam Albani Hafiq Wardana Handayani, Sri Insannul Imam Rohny Khoirri Irfan Hanafi Jovita Kharisma Ayu Febriana Khoirudin Khoirudin, Khoirudin Kurniawan, Nanda Dwi Kurniawan, Nurdin Laely Syafitri Lila Anggraini Mahjid Herlambang Mar’atuzzulfa, Salma Masithoh, Mauluddiah Maulana Bahrul Alam Mauriski Syahruli Mikael Arvito Kurnia Adi Moch Rafi Dewayanto Moh Harysakti Rahanyamtel Mojang Widhiyani Ashari Muhammad Jauhar Fardani Muhammad Nur Irfan Muhsinin, Muhammad Muhsinin Mukhammad Said Riza Zudi Muzzakin, Muhamad Nabela Yulian Anggraini Nabilah Putri Wijaya Najihatul Faridy Narisa Aulia Nela Soca Putri Ardana Ningrum, Setya Nur Wakhidah Nur Wakhidah Nurtriana Hidayati Nurul Arini Obing Zaid Sobir Patmawati, Putri Pipit Aryani Prind Triajeng Pungkasanti, Prind Triajeng Pulung Nurtantio Andono Purbo Pangestu Satria Jati Putri, Nela Aulina R. Dwi Widi Pratito Sri Nugroho Radhita Amelia Pasha ramadhani, jovita wayan Ramdan Yusuf Rangga Rahmat Prayuda Rastri Prathivi Rastri Prathivi Rati - Riana Rico Cahyono Riki Ardi Pranata Rosidah, Nafiati Sadna Putri Yuliarti Saifur Rohman Cholil Siti Asmiatun, Siti Sri Handayani Teguh Rizki Saputra Titis Handayani Titis Handayani Titis Handayani Titis Handayani Vensy Vydia Victor Gayuh Utomo Whisnumurti Adhiwibowo Widyandayani, Anita Galih Yasiri, Jamilatur Rizqil Yekti Adi Prasetyo Yogi Agus Setiawan Yudi Cahyono Yudi Prayoga Yurista Kumkamdhani, Tirta