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Ward and Peppard Method Approach for Strategic Planning Information Systems XYZ Training Center Quratul Ain; Norlaila Norlaila; Silvi Agustanti Bambang; Sukoco Sukoco; Dhani Ariatmanto; Adrianto M. Wijaya
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 8 No 4 (2021): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v8i4.1174

Abstract

ELTIBIZ Training Center is one of the training institutions engaged in non-formal education that has used information systems and information technology to make organizational performance more effective, efficient and increase competitiveness. The IS/IT strategy is needed to facilitate the management of information by the organization in winning the competition with competitors. In this study, IS/IT strategic planning uses the Ward and Peppard method starting from the process of analyzing the condition of the external and internal business environment, as well as the external and internal IS/IT environment. The analysis process uses SWOT analysis techniques, Value Chain analysis, Porter's Five Forces analysis, technology trend analysis and Mcfarlan's Strategic Grid matrix. The IS/IT strategic plan produced in this study includes an IS strategy in the form of a portofolio of future applications that can support business processes, an IS/IT management strategy in the form of a proposed system application development. The IS/IT strategic plan is written into an information system development roadmap as an implementation reference for the ELTIBIZ Training Center in the future whose implementation plan will be carried out within the next 5 (five) years. Keyword : Strategic Plan, Information System, Ward and Peppard, SWOT, Value Chain.
Kombinasi Algoritma Sampling dengan Algoritma Klasifikasi untuk Meningkatkan Performa Klasifikasi Dataset Imbalance Gagah Gumelar; Norlaila2; Quratul Ain; Riza Marsuciati; Silvi Agustanti Bambang; Andi Sunyoto; M. Syukri Mustafa
Prosiding SISFOTEK Vol 5 No 1 (2021): SISFOTEK V 2021
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (368.284 KB)

Abstract

A class to be imbalanced when there is a class that has more data than other classes. A comparison between minority classes and the majority class is called Imbalance Ratio (IR). The greater the difference between the minority class and the majority class the value of the Imbalance Ratio (IR) is getting larger. Dataset imbalance in data mining is a serious problem. The application of the classification algorithm regardless of class balance resulted in a good prediction for the majority class and a neglected minority class. Therefore, in this research, the SMOTE algorithm was applied to balance the dataset. The study used 4 datasets with different Imbalance Ratio and used classification algorithms, C45, Naïve Bayes, K-NN, and SVM. Then compared before and after using SMOTE. The research results that have been done accuracy value and value G-mean Naïve Bayes algorithm is consistent with its performance at each level of imbalance ratio, before the implementation has no good performance, whereas after the implemented SMOTE algorithm Naïve Bayes has a consistent increase in accuracy. So it can be concluded that the combination SMOTE + Naïve Bayes most effectively used in the imbalance dataset with different levels in the scheme of 10 fold cross validation and 80% data testing tested as much as 50 times.
ANALISIS SENTIMEN: PREDIKSI RATING TERHADAP REVIEWS WISATAWAN TANJUNG PUTING PADA TRIPADVISOR MENGGUNAKAN SUPPORT VECTOR MACHINE Ain, Quratul; Utami, Ema; Nasiri, Asro
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 3 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i3.5430

Abstract

Di era digital, sebagian besar data di internet berbentuk teks mentah. Data tambang emas ini sangat berharga karena berisi banyak informasi mendasar yang dapat diekstraksi menggunakan natural language processing dengan analisis sentimen. Termasuk data Reviews dan rating online di era digital menjadi hal pertimbangan penting dan terpercaya bagi wisatawan sebelum berkunjung ke sebuah objek wisata, salah satunya situs TripAdvisor. Penelitian ini akan memproses data teks ulasan wisatawan pada TripAdvisor pada objek Taman Nasional Tanjung Puting untuk menentukan sentimen wisatawan  berdasarkan rating 1 hingga 5. Data penelitian yang digunakan adalah sebanyak 390 reviews yang telah di-export dengan TripAdvisor Reviews Scrapper. Penelitian ini menggunakan Metode Support vector machine(SVM)  yang dikombinasikan dengan feature extraction dan Truncate singular-value decomposition (TSVD) pada preprocessing data. Penelitian ini dapat menampilkan visualisasi wordcloud top 10 kata yang paling banyak muncul berdasarkan rating sebagai pengetahuan dan informasi bagi pelaku industri pariwisata.  Berdasarkan pengujian dengan pembagian dataset 30:70 tingkat akurasi memperoleh rata-rata 80%.
Peningkatan Kompetensi Guru SD melalui Pelatihan Koding dan Kecerdasan Artifisial di SD Tahfidz Al-Jamiel Palangka Raya Ain, Quratul; Athaillah, Muhammad
Jurnal Pengabdian Masyarakat Terapan Vol 3 No 1 (2026): JUPITER April 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jupiter.3.1.120

Abstract

Kegiatan pengabdian masyarakat ini bertujuan untuk meningkatkan literasi digital dan kompetensi guru Sekolah Dasar (SD) dalam memahami konsep koding dan kecerdasan artifisial (AI). Kegiatan dilaksanakan di SD Tahfidz Al-Jamiel, Palangka Raya, pada 28 Oktober 2025 dengan 14 peserta guru. Metode pelaksanaan berupa pelatihan interaktif selama satu hari (6 JP) menggunakan pendekatan praktik langsung melalui platform Scratch, Teachable Machine, dan AI PoseBlock. Evaluasi dilakukan melalui pre-test, post-test, serta refleksi kualitatif menggunakan Mentimeter. Hasil analisis menunjukkan peningkatan rata-rata skor guru dari 3,08 pada pre-test menjadi 15,00 pada post-test, dengan peningkatan rata-rata 11,92 poin. Selain itu, respon guru menunjukkan pelatihan dinilai menyenangkan, bermanfaat, dan mudah dipahami. Sebagian besar peserta berminat mendalami topik AI-based learning. Kegiatan ini membuktikan bahwa pelatihan koding dan AI efektif meningkatkan kompetensi guru dalam pembelajaran berbasis teknologi, serta memperkuat implementasi literasi digital di lingkungan sekolah dasar.