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Analisis Sentimen Layanan J&T Express pada Sosial Media X Menggunakan Algoritma Naïve Bayes Clasifier dan K-Nearest Neighbor Muhamad Ilham Priady; M. Afdal; Inggih Permana; Zarnelly Zarnelly
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7721

Abstract

The demand for goods delivery services is increasing along with the widespread use of e-commerce platforms for buying and selling. One of the popular and frequently used delivery service providers is J&T Express. Until now, J&T has had a wide service coverage. However, various customers also have complaints that are often conveyed through social media X. For this reason, this study conducted a sentiment analysis of J&T Express user opinions on social media X using the Naïve Bayes Classifier (NBC) and K-Nearest Neighbor (KNN) algorithms. Data collection was carried out through scraping over a time span from January 1, 2023 to December 1, 2024, resulting in a total of 1,000 data points. The modeling results show that the NBC algorithm outperforms KNN, achieving an accuracy of 72.30%, a precision of 74.76%, and a recall of 72.30%. Meanwhile, the KNN algorithm with the best parameters (K = 9) only has an accuracy of 67.29%, precision of 69.46%, and recall of 67.29%. Then the results of the analysis show that J&T user opinions are dominated by negative sentiment (42.20%), followed by positive sentiment (38.70%) and neutral sentiment (19.10%). Further analysis based on five variables was also conducted and an understanding of J&T's weaknesses, namely in the service aspect, with the highest negative sentiment (21.0%). On the other hand, the user experience aspect is an advantage with the most positive sentiment (16.8%). The data visualization results also indicate that there are dominant customer complaints about the delay in the delivery process. However, customers also appreciate the speed and security of the delivery of goods. These findings provide valuable insights for J&T Express to conduct evaluations and improvements, especially in the service aspect, to improve overall customer satisfaction and experience.
Development Disparity Analysis: Clustering Regencies and Cities in Riau Province Based on Socio-Economic Indicators Using K-Means and Hierarchical Algorithms Yogi Hariadi; Inggih Permana; Febi Nur Salisah; M. Afdal
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 5 No. 2 (2026): September 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v5i2.1454

Abstract

Inter-regional socio-economic disparity remains a persistent challenge in regional development across Indonesia, including Riau Province. Differences in economic capacity, human development quality, poverty levels, and labor absorption indicate that development characteristics across regencies and cities are not yet uniform. This study aims to classify regencies and cities in Riau Province based on socio-economic indicators for the 2019–2023 period using K-Means and Hierarchical Clustering algorithms, as well as to compare the most suitable method for representing the data structure. Secondary data utilized in this study consist of five main macro-indicators: Gross Regional Domestic Product (GRDP) per capita, poverty rate, open unemployment rate, Human Development Index (HDI), and mean years of schooling. The research stages involve data preprocessing, Min-Max normalization, outlier detection, clustering algorithm implementation, and evaluation using the Silhouette Coefficient, Davies-Bouldin Index, and Calinski-Harabasz Score. The results demonstrate that the optimal number of clusters is two, where both algorithms yield identical evaluation values: a Silhouette Coefficient of 0.55, a Calinski-Harabasz Score of 34.45, and a Davies-Bouldin Index of 0.47. The clustering results reveal that Pekanbaru City forms a distinct, solitary cluster due to its superior macro-indicators, while the other eleven regencies and cities are grouped into the same cluster. This finding confirms a sharp socio-economic division between the provincial capital and its peripheral regions, which can simultaneously be utilized by the regional government as an empirical baseline evaluation to accelerate the achievement of SDGs Goal 1, Goal 4, and Goal 8 targets at the local level.
Evaluasi Efisiensi Pemanfaatan Struktur Data dalam Bahasa Pemrograman Python untuk Operasi Pencarian dan Penyimpanan Eka Pandu Cynthia; Inggih Permana; Febi Nursalisah; Aprijon
Jurnal Ilmu Komputer dan Teknik Informatika Vol. 1 No. 1 (2025): Januari 2025
Publisher : CV. Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/juikti.v1i1.41

Abstract

Penelitian ini bertujuan untuk mengevaluasi efisiensi berbagai struktur data yang tersedia dalam bahasa pemrograman Python, khususnya dalam konteks operasi pencarian (searching) dan penyimpanan (storing). Struktur data seperti list, tuple, set, dan dictionary memiliki karakteristik dan kompleksitas waktu yang berbeda, sehingga pemilihan yang tepat sangat berpengaruh terhadap performa program, terutama pada skenario dengan data berukuran besar. Metodologi penelitian ini menggunakan pendekatan kuantitatif melalui serangkaian pengujian eksperimental terhadap masing-masing struktur data. Pengujian dilakukan dengan mengukur waktu eksekusi dan penggunaan memori dalam operasi pencarian dan penyimpanan terhadap sejumlah data dengan variasi ukuran dari kecil hingga sangat besar. Hasil pengujian menunjukkan bahwa dictionary memiliki performa terbaik dalam hal kecepatan pencarian dan penyimpanan karena memanfaatkan teknik hashing, sementara set juga menunjukkan efisiensi yang tinggi dalam pencarian tetapi lebih terbatas dalam hal penyimpanan data kompleks. Sebaliknya, list dan tuple menunjukkan efisiensi yang lebih rendah dalam pencarian karena memerlukan pencarian linear, meskipun penggunaan memori tuple lebih hemat dibanding list. Kesimpulan dari penelitian ini menekankan pentingnya pemahaman terhadap karakteristik struktur data dalam Python untuk mengoptimalkan efisiensi program, khususnya dalam sistem atau aplikasi yang mengandalkan pemrosesan data dalam jumlah besar. Implikasi dari studi ini dapat digunakan sebagai acuan bagi pengembang perangkat lunak dalam memilih struktur data yang paling sesuai berdasarkan kebutuhan spesifik dari aplikasi yang dikembangkan.
Co-Authors Aditya Nugraha Yesa Agus Buono Al Kiramy, Razanul Alabbas Hussein Saeed Alfakhri, Rezky Andi Darlianto Andriyani, Dwi Ratna Anggi Widya Atma Nugraha Anggia Anfina Anisah Fitri Anjani, Yulia Merry Annisa Ramadhani Aprijon Aprijon Arif Marsal Arif Marsal Arif Marsal Arifah Fadhila Andaranti Aufa Zahrani Putri Aulia Dina Bib Paruhum Silalahi Chinthia, Maulidania Mediawati Dedi Pramana Dessi Cahyanti Detha Yurisna Detha Yurisna Dzul Asfi Warraihan Eka Pandu Cynthia Eka Pandu Cynthia Eki Saputra Eki Saputra Endah Purnamasari Esis Srikanti Fadhilah Syafria Fadil Rahmat Andini Farahdina Risky Ramadani Febi Nur Salisah Febi Nur Salisah Febi Nursalisah Febi Yanto Fiki Fikri, M. Hayatul Fitriah, Ma’idatul Fitriah, Ma’idatul Fitriani Muttakin Fitriani Muttakin Fitriani Muttakin Gathot Hanyokro Kusuma Gurning, Umairah Rizkya Hafiz Aryan Siregar Hasbi Sidiq Arfajsyah Hendri, Desvita Hilda Mutiara Nasution Husaini, Fahri Idria Maita Idria Idriani R, Nova Ikhsani, Yulia Imam Muttaqin Intan, Sofia Fulvi Ismail Marzuki Jazman , Muhammad Jazman, Muhammad Kusuma, Gathot Hanyokro M Afdal M Afdal M Zaky Ramadhan Z M. Afdal M. Afdal M. Afdal M. Afdal M. Afdal M. Afdal Maulana, Rizki Azli Megawati Megawati - Mona Fronita, Mona Muhamad Ilham Priady Muhammad Afdal Muhammad Fikry Muhammad Jazman Muhammad Jazman Muhammad Jazman Muhammad Jazman Muhammad Naufal, Muhammad Muhammad Zacky Raditya Mukmin Siregar Mundzir, Mediantiwi Rahmawita Munzir, Medyantiwi Rahmawita Mustakim Mustakim Mustakim Mustakim Mustakim Mustakim Mutia, Risma Muttakin, Fitriani Nabillah, Putri Nardialis Nardialis Nasution, Nur Shabrina Naufal Fikri, R. Adlian Negara, Benny Sukma Nesdi Evrilyan Rozanda Nesdi Evrilyan Rozanda Nisa', Sayyidatun Norhavina Norhavina Nunik Noviana Kurniawati Nurainun Nurainun Nuraisyah Nuraisyah Nurfadilla, Nadia Nurkholis Nurkholis nursalisah, febi Octavia, Sania Fitri Pratama, Arya Yendri Pristiawati, Andani Putri Puput Iswandi Putra, Moh Azlan Shah Putra, Tandra Adiyatma Rahma Aliya Rahma Devi Rahman, Eman Rahmawita M, Medyantiwi Rangga Arief Putra Rayean, Rival Valentino Restu Ramadhan Ria Agustina Rice Novita Rice Novita Rice Novita Rizka Fitri Yansi Rizki Pratama Putra Agri Rozanda, Nesdi Evrilyan Sabillah, Dian Ayu Salisah, Pebi Nur Sania Fitri Octavia Sanusi Shir Li Wang Siti Monalisa Sofia Fulvi Intan Susanti, Pingki Muliya Suzani Mohamad Samuri Tasya Marzuqah Tengku Khairil Ahsyar Triningsih, Elsa Tshamaroh, Muthia Uci Indah Sari Ula, Walid Alma Vicky Salsadilla Wang Shir Li Wenda, Alex Wido Purnama Winda Wahyuti Windy Amelia Putri Wira Mulia, M. Roid Yogi Hariadi Yusmar Yusmar Zarnelly Zarnelly Zarnelly Zarnelly Zarnelly Zarnelly Zarnelly Zarnelly Zarnelly