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All Journal MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) JAM : Jurnal Aplikasi Manajemen Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Jurnal Sistem Informasi, Teknologi Informasi, dan Edukasi Sistem Informasi (JUST-SI) Jurnal Pengabdian Masyarakat Teknologi Informasi dan Informatika
Yusi Tyroni Mursityo
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering

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Analisis Sentimen Kebijakan Penerapan Kurikulum Merdeka Sekolah Dasar dan Sekolah Menengah pada Media Sosial Twitter dengan Menggunakan Metode Word Embedding dan Long Short Term Memory Networks (LSTM) Maulana, Alif Rizal; Wijoyo, Satrio Hadi; Mursityo, Yusi Tyroni
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 3: Juni 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2023106977

Abstract

Pandemi COVID-19 memberikan banyak kendala terhadap seluruh aspek kehidupan manusia tidak terlepas aspek Pendidikan. Merujuk kondisi selama COVID-19 kegiatan pendidikan mengalami learning loss yang membuat Kemendikbudristek mengeluarkan sebuah kebijakan baru yaitu implementasi kurikulum merdeka. Kebijakan baru ini tentu mendatangkan banyak opini dari berbagai pihak salah satunya siswa yang terkena dampak langsung dari kurikulum ini. Salah satu media sosial yang sering digunakan untuk menyampaikan opini oleh masyarakat Indonesia adalah Twitter. Analisis sentimen dilakukan pada opini siswa yang diutarakan di media sosial Twitter dengan menggunakan pendekatan machine learning. Arsitektur yang digunakan adalah Long Short-Term Memory Networks (LSTM). Metode yang digunakan untuk mempersiapkan data adalah word embedding dengan menggunakan layers embedding dari library TensorFlow. Dataset dkumpulkan dengan teknik text mining yang menggunakan bahasa pemrograman Python dan Twitter API. Hasil pengumpulan data sebanyak 455 opini terbagi dalam tiga kelas sentimen yaitu Negatif, Netral, dan Positif. Model dievaluasi menggunakan classification report yang menghasilkan empat nilai metrics yaitu, accuracy, recall, precision, dan f1-score. Hasil dari metrics tersebut didapatkan sebesar 81%, 81%, 80%, dan 79%. Selain itu, hasil dari penelitian ini ditujukan kepada pihak sekolah dan dinas pendidikan kota batu yang mana dari hasil wawancaranya pihak sekolah dan dinas menyetujui output penelitian ini adalah sebuah visualisasi dashboard hasil analisis sentimen. Hasil dashboard tersebut juga diuji menggunakan kuisioner System Usability Scale (SUS) yang dilakukan oleh perwakilan dari dinas dan sekolah sebanyak 6 orang, hasil dari kuesioner tersebut adalah SUS Score sebesar 62,5 yang menunjukkan hasil cukup baik namun dapat dikembangkan lebih lanjut. Visualisasi Dashboard juga digunakan pihak sekolah dan dinas pendidikan kota batu sebagai ukuran manfaat dan refleksi dari penerapan kurikulum merdeka dan juga melakukan evaluasi untuk lebih baik kedepannya. AbstractThe COVID-19 pandemic has created many obstacles to all aspects of human life, including education. Referring to the conditions during COVID-19, educational activities experienced a learning loss which prompted the Ministry of Education and Culture to issue a new policy, namely the implementation of an independent curriculum. This new policy certainly brings in many opinions from various parties, one of which is students who are directly affected by this curriculum. One of the social media that is often used to convey opinions by the people of Indonesia is Twitter. Sentiment analysis was carried out on student opinions expressed on social media Twitter using a machine learning approach. The architecture used is Long Short-Term Memory Networks (LSTM). The method used to prepare the data is word embedding using layers embedding from the TensorFlow library. The dataset was collected using text mining techniques using the Python programming language and the Twitter API. The results of data collection were 455 opinions divided into three sentiment classes, namely Negative, Neutral and Positive. The model is evaluated using a classification report which produces four metrics values, namely, accuracy, recall, precision, and f1-score. The results of these metrics were 81%, 81%, 80%, and 79%. In addition, the results of this study were addressed to the Batu City school and education office where, from the results of interviews, the school and service agreed that the output of this research was a dashboard visualization of sentiment analysis results. The results of the dashboard were also tested using the System Usability Scale (SUS) questionnaire which was carried out by representatives from offices and schools as many as 6 people, the result of the questionnaire was a SUS Score of 62.5 which showed quite good results but could be developed further. Dashboard visualization is also used by schools and the Batu City Education Office as a measure of the benefits and reflections of implementing the Independent Curriculum and also conducting evaluations to make it better in the future.
Evaluation of User Acceptance of Enterprise Resource Planning System at Material Resource Planning Division of PT. Xacti Indonesia Rahmadan, Fakhri; Mursityo, Yusi Tyroni; Wardani, Niken Hendrakusma
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 5 No 1 (2021): February 2021
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (796.35 KB) | DOI: 10.29407/intensif.v5i1.14590

Abstract

The purpose of this evaluation is to evaluate user acceptance of the Glovia ERP system, whichever embedded in PC to assist operator staffs to record material stocks. The research methodology used in this study is the UTAUT model adjusted for the research problem's conditions. The issue happens because the Staff feel more comfortable with the old procedure and think it has supported their performance well. The respondents, as the sample in this study, are the staff operator from the MRP division. Data analysis is done using Partial Least Squares—the result of the research state that the Performance Expectancy variable has a significant effect on the Behavioral Intention variable. On the contrary, the other variables do not significantly affect the Behavioral Intention variable. The behavioral Intention variable has an R square value of 0.352 percent, which states that four independent variables can explain 35.2% of the Behavioral Intention variable. From the test results, it is suggested that the MRP division of PT can use the recommendations. Xacti Indonesia, as a consideration that can be used to improve the system currently applied.
Penyuluhan Pemanfaatan Search Engine Optimization (SEO) Pada Komunitas Digital Desa Gamping Kabupaten Trenggalek Mursityo, Yusi Tyroni; Brata, Dwija Wisnu; Wardani, Niken Hendrakusma
DIMASLOKA: Jurnal Pengabdian Masyarakat Teknologi Informasi dan Informatika Vol 4 No 2 (2025): Juli
Publisher : Fakultas Ilmu Komputer Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/dimasloka.v4i2.49

Abstract

Smart Village (Desa Cerdas) adalah desa yang mampu meningkatkan kualitas hidup masyarakat desa melalui pemanfaatan teknologi dalam berbagai aspek pembangunan desa. Kementerian Desa Pembangunan Daerah Tertinggal dan Transmigrasi (Kemendesa PDTT) melalui Program Desa Cerdas mendorong pemanfaatan teknologi informasi dan komunikasi menjadi salah satu sektor prioritas dalam penggunaan dana desa yang diprioritaskan untuk pencapaian SDGs Desa. Program smart village punya enam pilar yaitu warga cerdas (smart people), mobilitas cerdas (smart mobility), ekonomi cerdas (smart economic), pemerintahan cerdas (smart government), pola hidup cerdas (smart living),  dan lingkungan cerdas (smart environment). Bentuk konkret dari program Smart Village adalah pelatihan kader-kader digital desa, pembangunan jaringan desa cerdas Indonesia, dan pembentukan desa percontohan. Dalam hal ini Duta digital Kemendesa PDTT adalah mitra dari Tim UB dalam melaksanakan kegiatan pengabdian masyarakat Fakultas Ilmu Komputer di tahun 2024. Berdasarkan kebutuhan yang infokan oleh mitra, salah satu usulan kegiatan peningkatan kapasitas kader digital yang diajukan adalah memanfaatkan Search Engine Optimization (SEO). Karena Search Engine Optimization (SEO) dapat membantu dalam mengoptimasi informasi terkait web, produk UMKM, serta terdata dan terkenal di mesin pencari. Kemampuan optimalisasi informasi di dunia maya, menjadi hal yang penting dalam peningkatan dan pengenalan bisnis UMKM lebih luas, misalnya menciptakan konten baru, meningkatkan efektivitas pengelolaan media sosial, efektif keyword dalam mesin pencari dari produk atau bisnis yang dipasarkan, meningkatkan efektivitas iklan, mengukur sentimen konsumen, hingga menganalisis kompetitor. Pada praktiknya, peserta antusias mencoba teknik SEO dalam mengoptimasi produk mereka di sosial media. Fokus utama pada tahap awal memasarkan di blog dengan mengoptimasi keyword dengan tools dan memanfaatkan pembuatan konten dengan chatGPT. Antusias dan bermanfaatnya dari pelatihan yang dilakukan dengan terlihat hasil kuesioner yang diisi oleh peserta, hasil survei menunjukkan bahwa mayoritas responden sebanyak 91.2% merasa puas dengan pelaksanaan pelatihan.   Abstract Smart Village is a village that can improve the quality of life of village communities through the use of technology in various aspects. The Ministry of Villages, Development of Disadvantaged Regions and Transmigration (Kemendesa PDTT) through the Smart Village Program encourages the use of information and communication technology to become one of the priority sectors in the use of village funds prioritized for achieving Village SDGs. The smart village program has six pillars, namely smart people, smart mobility, smart economy, smart government, smart living, and smart environment. The concrete form of the Smart Village program is the training of digital village cadres, the development of the Indonesian smart village network, and the formation of pilot villages. In this case, the Kemendesa PDTT digital ambassador is a partner of the UB Team in implementing community service activities under the Faculty of Computer Science in 2024. Based on the needs informed by the partner, one of the proposed activities to increase the capacity of digital cadres submitted is to utilize Search Engine Optimization (SEO). SEO can help optimize information related to the web and MSME products and is recorded and well-known in search engines. The ability to optimize information in cyberspace is important in improving and introducing MSME businesses more widely, for example creating new content, increasing the effectiveness of social media management, effective keywords in search engines from marketed products or businesses, increasing advertising effectiveness, measuring consumer sentiment, and analyzing competitors. In practice, participants enthusiastically tried SEO techniques to optimize their products on social media. The main focus in the early stages of marketing on blogs is by optimizing keywords with tools and utilizing content creation with chatGPT. The enthusiasm and usefulness of the training carried out can be seen from the results of the questionnaire filled out by the participants, the survey results showed that the majority of respondents as much as 91.2% were satisfied with the implementation of the training.
Co-Authors 'Aisy, Rihadatul A'ini, Farah Nur Aditya Rachmadi Aditya Rachmadi, Aditya Ahmad Afif Supianto Alfi Nur Rusydi Alghiffari, Farrell Arrazi Amrani, Andi Ahyar Almuhajir Andisela, Yossy Risco Asiyah, Noor Leona Az- Zahra, Hanifah Muslimah Azzahra, Hafia Candra Dewi Dany Primanita Kartikasari Dwi Cahya Astriya Nugraha Dwija Wisnu Brata Endang Siti Astuti Fadhiilah, Muhammad Althaaf Fathurino, Audi Kresna Ferliamo, Aqila Fayyadh Ghiffari, Muhammad Halimah, Roshidah Nur Hanggara, Buce Trias Hanif, Muhammad Irvan Hanifah Muslimah Az-Zahra, Hanifah Muslimah Idota, Patrick Jore Ikhsawiyanthi, Anisah Intan Sartika Eris Maghfiroh Iriandi, Maria Nicole Natasha Putri Isadora, Fara Regina Ivandi, Reyhan Lestari, Adhinda Dinar Maulana, Alif Rizal Mochamad Chandra Saputra, Mochamad Chandra Mumtaz, Muhammad Rafly Mutiarahma, Pradya Nanang Yudi Setiawan Niken Hendrakusma Wardani Novitasari, Shandranuur Fauziah Nugraha, Dwi Cahya Astriya Nugroho, Alief Nugroho, Darryl Dwi Nur A'ini, Farah Nurfidausyi, Muhammad Zidan Tifanno Parengga, Restian Pradana, Yustinus Radityo Prakoso, Bondan Sapta Prima Zulvarina, Prima Purnama, Farid Yoga Rachman, AA Muhammad Itqany Rahmadan, Fakhri Rahmadhani, Via Salsabila Rahmah, Safira Nur Rahmatuliza, Dwi Yuniar Restian Parengga Retno Indah Rokhmawati, Retno Indah Rifky, Muhamad Riswan Septriayadi Sianturi Safira, Salma Nada Santoso, Dzikry Aji Satrio Hadi Wijoyo Setyorini, Luthfia Rahmi Shandranuur Fauziah Novitasari Sidin, Siti Huwaena Maulidiah Suharsono, Eko Ganis Suprapto Suprapto Uun Hariyanti, Uun Wicaksono, Muhammad Adi Widhy Hayuhardhika Nugraha Putra Wong, Vinncent Alexander Zacharias, Andrei Hansel Zaidan, Muhammad Irfan