Haerani, Kiki
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Analisis Kepuasan Pengguna Aplikasi Sidawai Menggunakan End User Computing Statisfaction (EUCS) DAn Importance Performance Analysis (IPA) Haerani, Kiki; Imtihan, Khairul; Murniati, Wafiah
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 11 No 4: Agustus 2024
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.1148906

Abstract

Aplikasi Sistem Pendataan Data Pegawai (SIDAWAI) merupakan sebuah aplikasi yang di dirancang sebagai solusi data kepegawaian seperti biodata pegawai, riwayat mutasi jabatan, riwayat kepangkatan, riwayat cuti dan lain sebagainya. Proses penyimpanan, pemusatan data dan pelaporan data kepegawaian yang dapat memudahkan dalam meningkatkan administrasi kepegawaian pada Kabupaten Lombok Tengah sejak tahun 2018. Kualitas informasi pada suatu sistem dapat memberikan pengaruh besar terhadap tingkat kepuasan pengguna, serta tujuan dari penggunaan sistem dapat tercapai ketika sistem digunakan. Penelitian dilakukan untuk mengetahui tingkat kepuasan pengguna dan tingkat kesenjangan antara harapan dan kinerja aplikasi. Dalam membuat instrument kuesioner tingkat kepuasan pengguna mengunakan model End-User Computing Statisfanction (EUCS). EUCS menggunakan 5 indikator penliaian, diantaranya Content, Format, Accurancy, Ease of use dan Timelines. Untuk mengukur ke akuratan instrument kusioner dilakukan uji validitas dan reabilitas dengan melibatkan para pakar yang memahami terkait dengan Aplikasi SIDAWAI. Untuk mengetahui jarak kesenjangan antara harapan dan kinerja, serta mengukur kepuasan pengguna pada Aplikasi SIDAWAI dengan metode IPA (Importance Performance Analysis) berdasarkan hasil dari pengolahan data kuesioner dari model End-User Computing Statisfanction (EUCS). Dari hasil perhitungan kepuasan pengguna mendapatkan hasil 82,66% yang berarti sangat memuskan. Kemudian tingkat kesenjangan antara harapan dan kinerja pada Aplikasi SIDAWAI mendapatkan nilai rata-rata sebesar -0,17 dimana harapan lebih besar dari pada kinerja. Berdasarkan diagram kartesius instrumen perlu dipertahankan kualitasnya yaitu C1, C3, A3, E1, E2, E3, E4, dan T1, dan instrumen yang sangat memerlukan perbaikan yaitu F2 san U2.   Abstract   The Employee Data Collection System Application (SIDAWAI) is an application designed as a staffing data solution such as employee biodata, position mutation history, rank history, leave history and so on. The process of storing, centralizing data and reporting personnel data which can facilitate the improvement of personnel administration in Central Lombok Regency since 2018. The quality of information on a system can have a big influence on the level of user satisfaction, and the objectives of using the system can be achieved when the system is used. Research was conducted to determine the level of user satisfaction and the level of gap between expectations and application performance. In making a questionnaire instrument the level of user satisfaction uses the End-User Computing Statisfanction (EUCS) model. EUCS uses 5 assessment indicators, including Content, Format, Accurancy, Ease of use and Timelines. To measure the accuracy of the questionnaire instrument, validity and reliability tests were carried out by involving experts who understand related to the SIDAWAI Application. To determine the gap between expectations and performance, and measure user satisfaction with the SIDAWAI Application using the IPA (Importance Performance Analysis) method based on the results of processing questionnaire data from the End-User Computing Statisfanction (EUCS) model. From the results of the calculation of user satisfaction, the results obtained are 82.66% which means very satisfied. Then the level of the gap between expectations and performance on the SIDAWAI Application gets an average value of -0.17 where expectations are greater than performance. Based on the Cartesian diagram, the instruments need to maintain their quality, namely C1, C3, A3, E1, E2, E3, E4, and T1, and the instruments that really need improvement are F2 san U2.
UI/UX Design on the DISPERKIM Lombok Tengah Website Using the Design Thinking Method Ashari, Maulana; Haerani, Kiki; Zaen, Mohammad Taufan Asri
Journal of Informatics Management and Information Technology Vol. 4 No. 4 (2024): October 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v4i4.416

Abstract

DISPERKIM Lombok Tengah is in an effort to improve services to the community by utilizing existing information technology, one of which is using the website. Bad user interface and user experience design from a website will make users uncomfortable and leave the website. However, the current website has not maximized the utilization of user interface and user experience. As for the results of the questionnaire conducted on 30 respondents, 5% felt bad, 43% of respondents felt it was enough, 33% felt it was quite bad, 18% felt it was quite good and 1% felt good, for the appearance and the availability of information on the DISPERKIM Lombok Tengah website right now. The method used in designing UI/UX on the DISPERKIM Lombok Tengah website uses the Design Thinking method. The Design Thinking method has five stages, namely empathize, define, ideate, prototype and test. The wireframe and prototypes are designed by using the Figma application. The Prototype results have passed the testing process to users with good results. So that the proposed design has met the needs of users and can be continued to be implemented. The prototype design is expected to increase interaction satisfaction between the user and the DISPERKIM Lombok Tengah website
Pelabelan Sentimen Otomatis Hybrid untuk Analisis Respons Publik Terhadap Program Makan Bergizi Gratis di Twitter/X Haerani, Kiki; Kusrini
Jurnal Teknologi Informasi dan Ilmu Komputer Vol. 13 No. 5: Oktober 2026
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2026135

Abstract

Keterbatasan data berlabel manual menjadi tantangan dalam analisis sentimen berbasis media sosial, khususnya pada data berskala besar seperti Twitter/X. Penelitian ini mengusulkan pendekatan pelabelan sentimen otomatis berbasis hybrid yang mengombinasikan metode lexicon-based menggunakan Indonesian Sentiment Lexicon (INSET) dan metode transformer-based menggunakan IndoBERTweet untuk menganalisis sentimen publik terhadap Program Makan Bergizi Gratis (MBG). Evaluasi dilakukan menggunakan algoritma klasifikasi Naïve Bayes dan Support Vector Machine (SVM) sebagai probe classifier untuk menganalisis pengaruh strategi pelabelan terhadap pola hasil klasifikasi. Data Twitter/X diproses melalui tahap preprocessing dan representasi fitur menggunakan TF-IDF, kemudian dianalisis melalui tiga skenario pelabelan, yaitu INSET, IndoBERTweet, dan hybrid. Hasil penelitian menunjukkan bahwa pelabelan berbasis INSET menghasilkan dominasi sentimen positif sebesar 97.50%, sedangkan IndoBERTweet menghasilkan distribusi sentimen yang lebih banyak pada kategori netral sebesar 47.13%. Pendekatan hybrid menghasilkan distribusi sentimen yang lebih moderat dengan 39.50% positif, 24.51% negatif, dan 39.99% netral. Analisis konsistensi menggunakan Cohen’s Kappa menunjukkan kesepakatan yang sangat rendah antara INSET dan IndoBERTweet (κ = 0.0097), namun kesepakatan yang lebih tinggi antara IndoBERTweet dan hybrid (κ = 0.7595). Selain itu, pengujian Wilcoxon Signed-Rank Test menunjukkan adanya perbedaan yang signifikan secara statistik (p < 0.05) antar skenario pelabelan. Secara keseluruhan, pendekatan hybrid menghasilkan pola klasifikasi sentimen yang lebih seimbang, konsisten, dan stabil dibandingkan pendekatan pelabelan otomatis tunggal, sehingga berpotensi menjadi alternatif metodologis yang lebih adaptif dalam analisis sentimen berbasis media sosial pada kondisi keterbatasan data berlabel manual.   Abstract The limited availability of manually labeled data remains a major challenge in social media–based sentiment analysis, particularly for large-scale data sources such as Twitter/X. This study proposes a hybrid automatic sentiment labeling approach that combines a lexicon-based method using the Indonesian Sentiment Lexicon (INSET) and a transformer-based method using IndoBERTweet to analyze public sentiment toward the Free Nutritious Meals Program (MBG). The evaluation was conducted using Naïve Bayes and Support Vector Machine (SVM) classification algorithms as probe classifiers to examine the influence of labeling strategies on classification outcome patterns. Twitter/X data were processed through preprocessing stages and feature representation using TF-IDF, and subsequently analyzed using three labeling scenarios: INSET, IndoBERTweet, and hybrid. The results show that INSET-based labeling produced a strong dominance of positive sentiment at 97.50%, whereas IndoBERTweet produced a distribution with a higher proportion of neutral sentiment at 47.13%. The hybrid approach generated a more moderate sentiment distribution consisting of 39.50% positive, 24.51% negative, and 39.99% neutral sentiments. Consistency analysis using Cohen’s Kappa indicated very low agreement between INSET and IndoBERTweet (κ = 0.0097), while higher agreement was observed between IndoBERTweet and the hybrid approach (κ = 0.7595). In addition, the Wilcoxon Signed-Rank Test revealed statistically significant differences (p < 0.05) among the labeling scenarios. Overall, the hybrid labeling approach produced a more balanced, consistent, and stable sentiment classification pattern compared to single automatic labeling methods, suggesting that it can serve as a more adaptive methodological alternative for social media sentiment analysis under conditions of limited manually labeled data.