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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal Pengabdian Kepada Masyarakat (Indonesian Journal of Community Engagement) Sistemasi: Jurnal Sistem Informasi Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control
Rachman, Fika Hastarita
Universitas Trunojoyo Madura
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering

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Rencana Strategi Teknologi Informasi pada Perguruan Tinggi di Indonesia: Sebuah Tinjauan Pustaka Wahyudi Agustiono; Mutiara Cahyani Fajrin; Fika Hastarita Rachman
Sistemasi: Jurnal Sistem Informasi Vol 10, No 1 (2021): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (761.959 KB) | DOI: 10.32520/stmsi.v10i1.1145

Abstract

AbstrakTeknologi Informasi (TI) salah satu bagian penting dalam sebuah organisasi. Terutama pada era disrupsi dan lingkungan yang dinamis saat ini, TI telah menjadi sarana utama bagi organsisasi untuk mencapai efisiensi dalam operasional dan mendapatkan keunggulan kompetitif. Oleh karena itu, perencanaan strategis TI yang efektif sangat diperlukan guna memastikan bahwa proses pembangunannya sejalan dengan nilai, visi, misi dan tujuan dari organisasi. Hal ini tanpa perkecualian bagi universitas sebagai salah satu organisasi pendidikan yang saat ini semakin mengandalkan TI untuk memfasilitasi penyelenggaraan kegiatan akademis yang berkualitas serta memberikan layanan terbaik bagi para pemangku kepentingan. Dalam penelitian ini dilakukan kajian pustaka terhadap 34 artikel yang berkaitan dengan perencanaan strategi TI pada perguruan tinggi di Indonesia. Dari 34 artikel dibagi menjadi 2 sub topik perencanaan strategi TI. Dari hasil kajian pada 34 artikel diperoleh temuan yang mendominasi penelitian, yaitu terdapat sebanyak 30 artikel yang membahas topik penelitian mengenai kegiatan perencanaan strategi TI, 17 artikel yang menggunakan framework Ward And Peppard, 22 perguruan tinggi swasta yang dijadikan objek penelitian, 34 artikel yang melakukan perencanaan strategi TI sebagai aspek penelitian, dan kurangnya jumlah penelitian mengenai tingkat keselarasan antara perencanaan strategi TI dan strategi bisnis, serta kurangnya penelitian mengenai perencanaan strategi TI pada perguruan tinggi negeri di Indonesia.Kata Kunci: Tinjauan Pustaka, Perencanaan Strategis TI, Teknologi Informasi, Perguruan tinggi AbstractInformation Technology (IT) is an essential part for many organisations. Especially in the current disruptive and dynamic environment, IT has been the main tool for achieving operational efficiencies and gain competitive advantage. Indeed, an effective IT strategic plan is required to ensure the development is inline with the organisations' value, vision, mission and goals. This is no exception for university as a learning organisation which is becoming more reliant on IT in facilitating a quality academic activites and providing excellent servics to its stakeholders. In this study, a review was conducted of 34 articles related to the strategic planning of information technology in Indonesian universities. From 34 articles divided into 2 sub topics information technology strategic planning. From the results of the study on 34 articles, it was found that the findings dominated the research, namely 30 articles that discussed research topics regarding IT strategic planning activities, 17 articles using the Ward And Peppard framework, 22 private universities that were used as research objects, 34 articles that carried out planning IT strategy as an aspect of research, and the lack of research on the level of alignment between IT strategy planning and business strategy, as well as a lack of research on IT strategy planning in state universities in Indonesia.Keywords:  literature review,  IT strategic plan, information technology
Pembekalan Pemrograman Dasar Komputer bagi Guru TIK dan Siswa Terpilih di Tiga Mitra SMA Kabupaten Bangkalan Sri Wahyuni; Fika Hastarita Rachman; Yonathan Ferry Hendrawan
Jurnal Pengabdian kepada Masyarakat (Indonesian Journal of Community Engagement) Vol 2, No 1 (2016): September
Publisher : Direktorat Pengabdian kepada Masyarakat Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (309.747 KB) | DOI: 10.22146/jpkm.22234

Abstract

Programming is a basic skill in computing (Teknologi Informasi dan Komunikasi–TIK) feld. In our school partners located at Bangkalan, the teachers of computing course have non-computing background (physics, mathematics, biology). Tis condition means that their programming skill is not good enough. Tis is certainly a suboptimal circumstance since teacher’s mastery of a subject has a lot to do with the success of the teaching-learning process. Computer olympics (olimpiade komputer) is a programming competition for high school students. It has two kinds of tests. Tey were mathematical logic and programming problem solving. Because of the lacking in teacher’s programming skill, the preparation event focused only on mathematical logic. Tis approach had led the students to pass through frst/city selection, but it was not enough to pass the second/provincial selection. In this community service, we gave programming learning modules to the school partners and also train them about pascal programming. Te initial targets were TIK teachers who were also the preparation event coaches. Afer several considerations, we asked the schools to also send their best students as participants for the training. Te purpose were to not only prepare the current participant team, but also to support the regeneration of future teams. By the end of this activity, our partners’ teachers and students have had a better pascal programming skills. Tis result is shown in the increasing scores they get in their pre, mid, and fnal training evaluations.
Deep Convolutional Neural Network AlexNet and Squeezenet for Maize Leaf Diseases Image Classification Wahyudi Setiawan; Abdul Ghofur; Fika Hastarita Rachman; Riries Rulaningtyas
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 6, No. 4, November 2021
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v6i4.1335

Abstract

Maize productivity growth is expected to increase by the year. However, there are obstacles to achieving it. One of the causes is diseases attack. Generally, maize plant diseases are easily detected through the leaves. This article discusses maize leaf disease classification using computer vision with a convolutional neural network (CNN). It aims to compare the deep convolutional neural network (CNN) AlexNet and Squeezenet. The network also used optimization, stochastic gradient descent with momentum (SGDM). The dataset for this experiment was taken from PlantVillage with 3852 images with 4 classes i.e healthy, blight, spot, and rust. The data is divided into 3 parts: training, validation, and testing. Training and validation are 80%, the rest for testing. The results of training with cross-validation produce the best accuracy of 100% for AlexNet and Squeezenet. Furthermore, the best weights and biases are stored in the model for testing data classification. The recognition results using AlexNet showed 97.69% accuracy. While the results of Squeezenet 44.49% accuracy. From this experiment environment, it can be concluded that AlexNet is better than Squeezenet for maize leaf diseases classification.
Pendekatan Data Science untuk Mengukur Empati Masyarakat terhadap Pandemi Menggunakan Analisis Sentimen dan Seleksi Fitur Fika Hastarita Rachman; Imamah Imamah
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 8, No 3 (2022): Volume 8 No 3
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v8i3.56655

Abstract

Empati merupakan kemampuan seseorang untuk turut merasakan penderitaan orang lain. Pandemi covid yang melanda dunia, telah menyisakan banyak kehilangan dan keterpurukan. Penelitian ini bertujuan untuk mengetahui emosi masyarakat terhadap penderitaan sesama menggunakan pendekatan sentimen analisis. Dataset yang digunakan adalah komentar masyarakat di Twitter tentang pandemi Covid dalam rentang waktu November-Desember 2020. Data diambil dengan teknik crawling menggunakan library twint, didapatkan data sebanyak 2386 komentar, namun komentar yang mengandung empati hanya sebanyak 984 data. Dataset empati kemudian dilabeli oleh tiga orang menggunakan teknik majority voting. Hasil pengukuran dataset empati menunjukkan 55,7% komentar masyarakat indonesia mengandung empati positif (berempati), 37,4% empati negatif (tidak berempati), dan 6,9% netral. Untuk membentuk model yang dapat mendeteksi empati secara otomatis, maka digunakan  dataset empati sebanyak 400, dengan 200 kelas positif dan 200 kelas negatif, kelas netral tidak digunakan pada penelitian ini karena jumlah data sangat sedikit. Metode machine learning yang digunakan untuk membangun model adalah Support Vector Machine (SVM) dengan metode ekstraksi fitur reliefF. Berdasarkan penelitian yang dilakukan, akurasi sistem dengan metode SVM tanpa seleksi fitur ReliefF adalah 83%. Sedangkan akurasi yang diperoleh sistem dengan seleksi fitur ReliefF mencapai 93% dengan penggunaan 85% fitur dari total keseluruhan fitur.
Co-Authors Abdul Ghofur Imamah Imamah Mutiara Cahyani Fajrin Riries Rulaningtyas Sri Wahyuni Wahyudi Agustiono Wahyudi Setiawan Yonathan Ferry Hendrawan