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All Journal Jurnal Pendidikan dan Pembelajaran Indonesia (JPPI) Business Management
Andreas Fajar Nugroho
Universitas Airlangga
Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Other

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An Analysis of PT.X (Yogyakarta)'s Development Cycle Based on Adizes and Galbraith's Theories Andreas Fajar Nugroho
Business Management Vol. 4 No. 3 (2025): Business Management Agustus
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Mandala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58258/bisnis.v4i3.9248

Abstract

E-commerce is a business strategy that promotes products and services through digital marketing platforms, one of which is PT.X. PT.X operates in multiple countries, including Indonesia, specifically in Yogyakarta. The Yogyakarta branch of PT.X consistently meets its annual targets and tends to express satisfaction with these achievements, often overlooking the crucial role of employee efficiency in reaching these goals. This study aims to explore the background and organizational culture of PT.X, assess its developmental stage based on the models of Adizes and Galbraith, and examine the challenges and strategies needed to sustain its current development stage. The organizational culture of PT.X (Yogyakarta) has been analyzed using the Organizational Culture Assessment Instrument (OCAI), revealing that the most significant desired cultural change is a reduction in Hierarchy culture by 7.50 points and a notable increase in Adhocracy culture by 6.83 points. According to Ichak Adizes, PT.X is currently in the 'Stable Organization' phase of its development cycle. Meanwhile, Jay Galbraith’s Star Model suggests that PT.X (Yogyakarta) could undergo significant transformation by focusing on the areas of organizational structure and human resources—particularly addressing the issue of high employee turnover. Based on Adizes' (2014) model, PT.X (Yogyakarta) has reached the stability stage in its organizational life cycle. At this point, it is crucial to pay attention to potential factors that may lead to stagnation or organizational decline. As Galbraith (2014) emphasizes, sustaining organizational development requires addressing existing constraints—such as those currently faced by PT.X (Yogyakarta).
Analisis Sentimen Pengguna Google Classroom terhadap Efektivitas Pembelajaran Digital Menggunakan Naive Bayes Andreas Fajar Nugroho; Bambang Suharto
Jurnal Pendidikan dan Pembelajaran Indonesia (JPPI) Vol. 6 No. 3 (2026): Jurnal Pendidikan dan Pembelajaran Indonesia (JPPI), 2026 (3)
Publisher : Yayasan Pendidikan Bima Berilmu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53299/jppi.v6i3.4524

Abstract

Penelitian ini bertujuan untuk menganalisis sentimen pengguna terhadap penggunaan Google Classroom dalam mendukung pembelajaran digital. Peneliti menggunakan metode kuantitatif deskriptif dengan pendekatan analisis sentimen terhadap ulasan pengguna Google Classroom pada Google Play Store periode Januari 2025 hingga Mei 2026. Pengumpulan data dilakukan melalui teknik web scraping dan memperoleh 533 ulasan yang telah melalui tahap pembersihan data. Analisis data pada penelitian ini menggunakan aplikasi RapidMiner dengan algoritma Naive Bayes melalui tahapan preprocessing, tokenisasi, transformasi huruf, penghapusan stopword, klasifikasi sentimen, dan evaluasi model. Hasil penelitian ini menunjukkan bahwa mayoritas ulasan pengguna didominasi oleh sentimen negatif. Kata yang sering muncul dalam ulasan pengguna antara lain tugas, bug, notifikasi, dan aplikasi. Hasil tersebut menunjukkan bahwa masih terdapat kendala dalam penggunaan Google Classroom, terutama pada aspek teknis aplikasi, pengumpulan tugas, dan sistem notifikasi pembelajaran. Kondisi tersebut menunjukkan bahwa kualitas dan stabilitas Learning Management System memiliki pengaruh terhadap efektivitas pembelajaran digital. Peningkatan kualitas layanan platform pembelajaran daring diperlukan agar proses belajar mengajar dapat berlangsung lebih optimal sesuai kebutuhan pengguna. Penelitian berikutnya disarankan untuk memperluas cakupan data ulasan dari berbagai platform pembelajaran digital lainnya serta menggunakan algoritma deep learning lainnya. Hal ini berguna dalam meningkatkan akurasi klasifikasi sentimen. Analisis yang ditemukan dapat dikembangkan dengan mempertimbangkan variabel demografis pengguna seperti jenjang pendidikan dan wilayah geografis yang bertujuan memperoleh gambaran lebih komprehensif terhadap efektivitas pembelajaran digital.
Co-Authors Bambang Suharto