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All Journal ComEngApp : Computer Engineering and Applications Journal TEKNIK INFORMATIKA Scientific Journal of Informatics Jurnal Pengabdian Kepada Masyarakat (Indonesian Journal of Community Engagement) Produktif : Jurnal Ilmiah Pendidikan Teknologi Informasi JITK (Jurnal Ilmu Pengetahuan dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Applied Information System and Management Jurnal Sisfokom (Sistem Informasi dan Komputer) J-SAKTI (Jurnal Sains Komputer dan Informatika) IJISTECH (International Journal Of Information System & Technology) Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Jurnal Pendidikan dan Konseling Indonesian Journal of Business Intelligence (IJUBI) ILKOMNIKA: Journal of Computer Science and Applied Informatics Jurnal Berdaya Mandiri Suluah Bendang: Jurnal Ilmiah Pengabdian Kepada Masyarakat Innovation in Research of Informatics (INNOVATICS) IJISTECH International Journal of Engineering, Science and Information Technology Teknik: Jurnal Ilmu Teknik dan Informatika J-SAKTI (Jurnal Sains Komputer dan Informatika) TRIBUTE: JOURNAL OF COMMUNITY SERVICES Parta: Jurnal Pengabdian Kepada Masyarakat PAKDEMAS : Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat As-salam Publikasi Hasil Pengabdian Kepada Masyarakat. Jurnal Karya Abdi Masyarakat Jurnal Pengabdian Pada Masyarakat Jurnal Pengabdian dan Pemberdayaan Masyarakat Indonesia Jurnal Relawan dan Pengabdian Masyarakat REDI TeknoKreatif: Jurnal Pengabdian kepada Masyarakat Inovasi Gagasan Abdimas & Kuliah Kerja Nyata JITEEHA: Journal of Information Technology Applications in Education, Economy, Health and Agriculture International Journal of Informatics and Computing
Praseptiawan, Mugi
Teknik Informatika, Institut Teknologi Sumatera
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Sistem Pantau dan Kontrol Budidaya Ikan Nila Berbasis IoT dengan Bioflok (Studi kasus: Kelompok Budidaya Ikan Sadewa Mandiri, Pringsewu) Ashari, Ilham Firman; Untoro, Meida Cahyo; Praseptiawan, Mugi; Afriansyah, Aidil
Suluah Bendang: Jurnal Ilmiah Pengabdian Kepada Masyarakat Vol 22, No 2 (2022): Suluah Bendang: Jurnal Ilmiah Pengabdian kepada Masyarakat
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/sb.02680

Abstract

Kelompok pembudidaya ikan sadewa muda mandiri saat ini masih mengalami permasalahan dalam pembudidayaan ikan, hal ini dikarenakan control dan monitor mash dilakukan secara manual. Beberapa parameter yang terus dipantau oleh pembudidaya adalah PH, Kadar nutrisi air, dan suhu. Hal ini tentu saja tidak efektif dan memakan waktu. Oleh karena itu perlu system yang dapat melakukan monitoring terhadap parameter PH, kadar nutrisi air, dan suhu air, dan juga dapat melakukan control terhadap kualitas air. Hal ini dikarenakan kualitas air merupakan hal yang penting untuk budidaya ikan dengan teknologi bioflok. Dengan adanya system ini maka monitoring dan control dapat dilakukan dengan mudah lewat aplikasi mobile yang dapat terintegrasi dengan alat di luar, sehingga pembudidaya ikan tidak perlu datang dan melihat kondisi kolam secara berkala. Kegiatan pengabdian dilakukan dengan survei, persiapan pembuatan alat, pembuatan alat, integrasi alat, pengujain system, dan pelaksanaan kegiatan. Sistem ini sudah melakukan berbagai pengujian, seperti pengujian akurasi dan pengujian fungsional. Berdasarkan hasil pengujian akurasi, sensor suhu DS18B20 dan sensor DF Robot PH Meter V 1.1 memilik akurasi yang baik yaitu masing-masing 95,87% dan 98,28%. Sedangkan pada sensor Gravity TDS Meter V 1.0 masih belum cukup baik dimana persentase akurasi yang diperoleh adalah 93,44%.
Sentiment Analysis of Comments on Higher Education Social Media Using Naïve Bayes Algorithm Salisu, Imam Auwal; Ramadhan, Irzal Raisya; Matdoan, Sakina; Arifin, Zainal; Praseptiawan, Mugi
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 1 No. 3 (2024): October
Publisher : Lumina Infinity Academy Foundation

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Abstract

The rapid development of information technology has driven the widespread use of social media across various aspects of life, including the academic environment. Social media platforms, such as Instagram, have become popular channels for disseminating information and fostering interactions between individuals and groups. With the growing number of users, sentiment analysis on social media is essential to understand public perceptions and responses to specific issues. Higher education institutions play a strategic role in creating a positive image through social media. Social media provides opportunities for universities to convey achievements, academic activities, and other information effectively to a broader audience, enhancing their reputation in the public eye. Moreover, Instagram serves not only as a communication tool but also as an educational medium capable of increasing student engagement through relevant and informative content. Technically, the Naïve Bayes algorithm is well-known for its speed and efficiency in sentiment analysis. This probability-based method leverages historical data to predict positive, negative, or neutral sentiments, offering competitive accuracy even when handling large datasets. This study aims to apply the Naïve Bayes algorithm for sentiment analysis of comments on the Instagram account of Widyagama University (@uwg.malang) as a case study. The research is expected to provide valuable insights for developing effective communication strategies and serve as a reference for other higher education institutions or organizations in utilizing analytical technologies for strategic purposes.
SIBOX Smart Loker System with Dynamic Systems Development Method Untoro, Meida Cahyo; Praramadhana, Daffa; Suranta, Akmal Fauzan; Amrulloh, Iqbal; Praseptiawan, Mugi
Teknik: Jurnal Ilmu Teknik dan Informatika Vol. 3 No. 1 (2023): Mei: Teknik: Jurnal Ilmu Teknik dan Informatika
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/teknik.v3i1.302

Abstract

At this time logistics companies have a very important role in everyday life, especially in package delivery. The high level of online shopping is one of the reasons why the role of logistics is very important in our daily lives. Thus, seeing the common problems that occur in the conventional logistics delivery process, we came up with the idea to create an integrated smart locker to be one of the replacements for existing logistics outlets, we hope that with this application we can reduce the company's logistics expenses used in procuring logistics outlets and make it easier for couriers to work in the package delivery process. We created this application using a microservices architecture with the SDLC method used is Agile Dynamic System Development (DSDM). React JS framework as an interface and Express js and Laravel as an application that works behind the interface. The idea that we initiated we raised as a project within the company with the client from the company. In the end, the smart locker program made using the DSDM method has been completed and is ready to be implemented in the company and the client
Digitalisasi Informasi Sebagai Penunjang Efektivitas Pelayanan Administrasi Koperasi Argo Mulyo Lestari Untoro, Meida Cahyo; Kurniawansyah, Apri; Perdana, Agung Mahadi Putra; Praseptiawan, Mugi; Nugroho, Eko Dwi; Afriansyah, Aidil; Yulita, Winda; Verdiana, Miranti
Parta: Jurnal Pengabdian Kepada Masyarakat Vol. 4 No. 2 (2023)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/parta.v4i2.4588

Abstract

Koperasi memiliki peran penting dalam perekonomian Indonesia. Argo Mulyo Lestari, salah satu koperasi yang mengelola dan menyediakan bibit pohon dan buah-buahan serta melakukan pendistribusian keseluruh wilayah Indonesia. Hasil observasi dengan cara wawancara mendapatkan data tentang proses bisnis yang dilakukan koperasi masih tergolong kuno, dengan cara mencatat pada buku, menyimpan pada excel. Proses bisnis yang tidak diimbangi dengan Teknologi informasi dan komunikasi mengakibatka, terjadi duplikasi data dan akses terbatas bagi seluruh anggota koperasi. Tim pengusul membuat usulan untuk menyelesaikan permasalahan dengan cara Teknologi Tepat Guna Digitalisasi Administrasi Koperasi Argo Mulyo Lestari. Tujuan dari digitalisasi, mempermudah, meningkatkan, dan keterbukaan data dalam melaksanakan proses bisnis. Digitalisasi mencangkup proses bisnis administrasi umum, simpan pinjam, keuangan dan pelaporan keuntungan serta kerugian. Teknologi tepat guna akan dievaluasi dengan menggunakan usability test. Hasil dari pengambdian, koperasi Argo Mulyo Lestari sudah menerapkan digitalisasi teknologi yang transparan, dan bertanggung jawab. Digitalisasi administrasi merupakan langkah yang tepat dalam menghadapi perkembangan teknologi informasi yang semakin canggih.
Redesigning UI/UX of A Mobile Application Using Task Centered System Design Approach Praseptiawan, Mugi; Untoro, Meida Cahyo; Fahrianto, Feri; Prabandari, Pungki Resti; Wisnubroto, M. Syamsuddin
Applied Information System and Management (AISM) Vol. 6 No. 1 (2023): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v6i1.24665

Abstract

Digital transformation requires a software system development method to identify and analyze user needs. In this research, software system development uses the Task Centered System Design framework with several stages, including identification, needs analysis, design, and evaluation. The identification stage is carried out by conducting interviews with stakeholders, and then the results of the interviews are analyzed and approved by stakeholders. This study aims to obtain user needs to build an application interface by applying the steps of the Task Centered System Design method and usability evaluation and calculating the weight of the feasibility value by testing the Heuristics method and System Usability Scale on the solution application design. The evaluation phase aims to determine the value of the usability problem in the design that has been designed. The evaluation phase uses the Usability Heuristic method by involving experts in the field of software development and the System Usability Scale method involving end users. After conducting research from the identification to the evaluation stage, the average severity rating of the Heuristic Usability test component scored less than 1 (one) in the second iteration, and the System Usability Scale results scored 70.3 for admin and 73.75 for the customer application. This result is in grade C with an adjective rating of Good.  
ANALISIS MODEL SISTEM REKOMENDASI KURSUS MOOC DENGAN METODE COLLABORATIVE FILTERING DAN INTEGRASI EXPLAINABLE AI Putri, Nabila Muthia; Praseptiawan, Mugi; Untoro, Meida Cahyo
Indonesian Journal of Business Intelligence (IJUBI) Vol 7 No 1 (2024): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v7i1.4274

Abstract

Sistem rekomendasi kursus Massive Open Online Course (MOOC) berperan penting dalam mendukung pembelajaran daring dengan memberikan saran kursus yang sesuai dengan preferensi pengguna. Dalam penelitian ini, kami mengembangkan model sistem rekomendasi kursus MOOC berbasis Collaborative Filtering dengan memanfaatkan dataset Coursera yang telah diproses. Preprocessing meliputi pembersihan data, penghapusan label yang tidak diperlukan, alokasi label, penghapusan data duplikat, dan analisis sentimen untuk memastikan konsistensi antara ulasan dan penilaian. Implementasi Collaborative Filtering melibatkan pembuatan tabel pivot, perhitungan Centered Cosine Similarity, dan prediksi penilaian kursus untuk pengguna yang belum pernah mengambil kursus tertentu. Evaluasi kinerja model dilakukan menggunakan metrik Root Mean Squared Error (RMSE) untuk mengukur tingkat kesalahan prediksi model. Hasil analisis dan evaluasi menunjukkan bahwa model yang dikembangkan berhasil memberikan rekomendasi kursus dengan tingkat kesalahan yang rendah, seperti yang tercermin dari nilai RMSE yang diperoleh yaitu 0.24 untuk sistem rekomendasi kursus MOOC. Integrasi Explainable AI dengan teknik LIME juga membantu dalam menjelaskan dan memahami rekomendasi yang diberikan oleh sistem, meningkatkan penjelasan tambahan terhadap model yang dibuat. Saran untuk pengembangan lebih lanjut termasuk fokus pada peningkatan interpretabilitas model dengan memperdalam integrasi Explainable AI, menggunakan dataset yang lebih besar, serta diversifikasi teknik pemodelan untuk meningkatkan kualitas dan akurasi rekomendasi yang diberikan oleh sistem.
GANS: Genetic Algorithm and Neural Network Integration for Optimal Brain Selection in Snake Game Bambang Pudjoatmodjo; Mugi Praseptiawan; Ulka Chandini Pendit; Rusnida Romli
JICO: International Journal of Informatics and Computing Vol. 1 No. 2 (2025): November 2025
Publisher : IAICO

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

Abstract

Snake games have emerged as an engaging subject in artificial intelligence and optimization research due to the growing interest in developing autonomous agents capable of controlling the snake intelligently. This study presents a hybrid approach by integrating a Genetic Algorithm (GA) with a Neural Network (NN) to enhance the snake game’s performance, effectively forming an adaptive and intelligent control system or “brain.” In this framework, the Snake game is modeled as an optimization problem, where the GA is employed to optimize the parameters of the NN to improve the decision-making process of the snake. The GA operates by evolving a population of individuals each representing a set of strategies through selection, crossover, and mutation. These operations are iteratively applied to discover optimal solutions within the vast parameter space. The integrated neural network enables the snake to make real-time decisions based on environmental stimuli, enhancing its survival and goal-seeking behavior. Fitness evaluation is performed based on everyone’s gameplay performance, where the most successful individuals contribute to the next generation. Experimental results demonstrate that the combination of GA and NN significantly improves snake gameplay performance. The fitness score acts as a performance indicator, showing that higher-generation populations tend to yield better results. For instance, snakes trained over 100 generations achieved scores around 8, while those trained over 500 generations exceeded scores of 15. This confirms the effectiveness of evolutionary optimization in training neural networks for game-based AI tasks.
Purchase Pattern Analysis on Komol Kopi Transaction Data Using Apriori Algorithm Pratama, Dafa Septian Putra; Praseptiawan, Mugi; Paramita, Niken
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 2 No. 3 (2025): October
Publisher : Lumina Infinity Academy Foundation

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Abstract

This research aims to analyze purchasing patterns in Komol Kopi transaction data using the Apriori algorithm. This algorithm enables the discovery of relationships between items in large datasets that can be used to support business decisions, such as bundling promotions and inventory management. The dataset includes 12 transactions with various combinations of items, such as Kopi Hitam, Kopi Tubruk, and Nasi Telur. The analysis results show some significant purchase patterns with high support, confidence, and lift values. An example of an association found is between Kopi Hitam and Es Teh, which provides insights for more effective marketing strategies. This study confirms that the Apriori algorithm is an efficient tool in unearthing purchasing patterns, providing a solid foundation for the development of data-driven business strategies. Further research can integrate this analysis with recommendation systems to improve customer experience.
Supply Chain Optimization in the Retail Industry by Integrating Apriori Algorithms and Time Series Forecasting in Business Intelligence Putra, Gusty Nanda Kharisma; Silviana, Silviana; Riyadi, Agung; Praseptiawan, Mugi
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 3 No. 1 (2026): Vol. 3 No. 1 (2026): February
Publisher : Lumina Infinity Academy Foundation

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Abstract

This study investigates the integration of the Apriori algorithm and time series forecasting within a Business Intelligence (BI) framework to optimize supply chain operations in the retail industry. The Apriori algorithm was utilized to identify significant purchasing patterns, enabling strategic decisions such as product bundling and cross-selling. Concurrently, time series forecasting, with an ARIMA model achieving a mean absolute percentage error (MAPE) of 8%, provided accurate demand predictions, supporting improved inventory management and resource allocation. The integration of these methods into a BI dashboard facilitated real-time monitoring and data-driven decisionmaking, leading to enhanced operational efficiency and reduced costs. While challenges such as data quality, computational resource demands, and user adaptability were observed, this research underscores the transformative potential of analytics in retail supply chain management. Future advancements in machine learning and IoT integration are recommended to further enhance system performance. Overall, this study demonstrates a pathway for retailers to achieve operational excellence and superior customer satisfaction through data-driven strategies.
Co-Authors Abillah, Bintang Adinda Sekar Tanjung Aditya Wahyu Nugraha Afriansyah, Aidil Agung Riyadi Agustinus Noertjahyana Ahmad Naim Bin Che Pee Aidil Afriansya Aidil Afriansyah Aidil Afriasnyah Alam Fathurochman, Alam Alfajar Puja Kusuma Algifari, Muhammad Habib Amirul Iqbal Amrulloh, Iqbal Andika Setiawa Andika Setiawan Andre Febrianto Anggraini , Ade Eka Ardi Gaya Manalu Arre Pangestu Athalla, Muhammad Nadhif Bahri, Samsu Bambang Pudjoatmodjo Baraku, Randi Baskara, Rizandi Agung Che Pee, Ahmad Naim Dadan Sujana Daniel Rinald Dita Alviuni P Drajat, Hilmi Maulana Dyah Ayu Larasati Eka Nur'azmi Yunira Eko Dwi Nugroho Eko Dwi Nugroho Endo Pebri Dani Putra Fauzan Natsir Feri Fahrianto Filiana, Edinia Rosa Firmansyah, Hafiz Budi Gunawan, Rayhan Fatih Hanfiro, Pauline Hersa Dwi Yanuarso Ilham Firman Ashari Ilham Firman Ashari Jati Fatmawiyati Khusnul Khotimah Kurniawansyah, Apri Laisya, Nashwa Putri Leo Viranda Millennium Lisdayana, Nurmalisa M. Syamsuddin Wisnubroto M. Yafi Fahmi Madi Madi Marbun, Rustian Afencius Maria Oktarise Natania Gultom Marsista Buana Putri, Marsista Buana Mastuti Widianingsih, Mastuti Matdoan, Sakina Meida Cahyo Untoro Miranti Verdiana Muhamad Djuanda Muhammad Affandi Muhammad Iqbal Muhammad Nadhif Athalla Muhammad Yusuf Naufal Raki Nela Agustin Kurnianingsih Niken Paramita Nuk Ghurroh Setyoningrum Nur'azmi, Eka Oriza Zativalen, Oriza Perdana, Agung Mahadi Putra Prabandari, Pungki Resti Praramadhana, Daffa Pratama, Dafa Septian Putra Pratama, Djourdi Amrida Pungki Resti Prabandari Putra, Gusty Nanda Kharisma Putri, Nabila Muthia Putri, Nabila Muthia Putty Yunesti Radhinka Bagaskara Rahman Indra Kesuma Rahmat Setiawan Raidah Hanifah Raidah Hanifah Ramadhan, Irzal Raisya Revangga, Dwi Arthur Rinaldi, Daniel Risfihan Rafi Rusnida Romli Salisu, Imam Auwal Samsu Bahri Sianturi, Elsa Elisa Yohana Silviana Silviana Sinaga, Nydia Renli Siregar, Abu Bakar Siddiq Sisilia Juli A Solly Aryza Sophia Nouriska Sudiarjo, Aso Suranta, Akmal Fauzan Ulka Chandini Pendit Untoro, Meida Cahyo Untoro, Meida Cahyo Utoro, Meida Cahyo Vebera Maslami Verdiana, Miranti Wafiqah Azhar , Afra Wafiqah Azhar, Afra Winda Yulita Winda Yulita Wisnubroto, M. Syamsuddin Yulita, Winda Yunira, Eka Nur'azmi Zainal Arifin Zakaria, Mohd Hafiz