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Harianto, Kusno
STMIK Widya Cipta Dharma
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Analisis Tingkat Kepuasan Pelanggan Terasko Samarinda Menggunakan Metode Servqual Roffi Maulidi; Salmon Salmon; Kusno Harianto
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 8, No 3 (2025): Juni 2025
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v8i3.9180

Abstract

Abstrak - Kepuasan pelanggan merupakan salah satu indikator utama dalam menilai keberhasilan usaha, khususnya dalam industri kuliner yang semakin kompetitif. Terasko Samarinda perlu menjaga dan meningkatkan kualitas layanan agar tetap mampu memenuhi harapan pelanggan. Penelitian ini bertujuan untuk menganalisis tingkat kepuasan pelanggan Terasko Samarinda menggunakan metode SERVQUAL yang terdiri dari lima dimensi: Tangibles, Reliability, Responsiveness, Assurance, dan Empathy. Metode yang digunakan adalah pendekatan kuantitatif deskriptif dengan penyebaran kuesioner kepada 104 responden. Data dianalisis dengan menghitung selisih antara skor persepsi dan harapan pelanggan pada setiap dimensi. Hasil penelitian menunjukkan bahwa dimensi Tangibles memenuhi harapan pelanggan, sementara empat dimensi lainnya menunjukkan kesenjangan negatif, dengan Reliability sebagai dimensi terendah. Temuan ini dapat menjadi acuan bagi manajemen Terasko Samarinda dalam meningkatkan kualitas layanan untuk meningkatkan kepuasan pelanggan secara menyeluruh.Kata kunci: Kepuasan Pelanggan; Kualitas Layanan; SERVQUAL; Terasko Samarinda Abstract - Customer satisfaction is a key indicator in evaluating the success of a business, particularly in the increasingly competitive culinary industry. Terasko Samarinda must maintain and improve service quality to meet customer expectations. This study aims to analyze customer satisfaction at Terasko Samarinda using the SERVQUAL method, which consists of five dimensions: Tangibles, Reliability, Responsiveness, Assurance, and Empathy. The research employs a descriptive quantitative approach by distributing questionnaires to 104 respondents. Data were analyzed by calculating the gap between customer perception and expectation scores for each dimension. The results show that the Tangibles dimension met customer expectations, while the other four dimensions showed negative gaps, with Reliability being the lowest. These findings can serve as a reference for Terasko Samarinda’s management to enhance service quality and improve overall customer satisfaction.Keywords: Customer Satisfaction; Service Quality; SERVQUAL; Terasko Samarinda
Implementasi Sistem Rekomendasi Makanan Berbasis Web Menggunakan Metode Collaborative Filtering di Mixue Nolan Melambi; Kusno Harianto; Kusnandar Kusnandar
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 8, No 3 (2025): Juni 2025
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v8i3.9194

Abstract

Abstrak - Industri kuliner di Indonesia, khususnya jaringan kedai es krim Mixue, menghadapi tantangan dalam memberikan rekomendasi menu yang tepat kepada pelanggan. Dengan beragamnya pilihan menu dan preferensi individu yang berbeda, sistem rekomendasi yang efektif sangat diperlukan untuk meningkatkan pengalaman pelanggan dan penjualan. Penelitian ini bertujuan untuk mengembangkan sistem rekomendasi makanan di Mixue menggunakan metode collaborative filtering, khususnya pendekatan item-based collaborative filtering, yang memanfaatkan data transaksi pelanggan untuk memberikan saran menu yang relevan. Metodologi yang digunakan mencakup pengumpulan data transaksi pelanggan, perhitungan kesamaan antar item menggunakan metrik cosine similarity, dan pembangunan model rekomendasi berbasis algoritma k-nearest neighbors (k-NN). Sistem ini diintegrasikan dengan aplikasi Mixue,memungkinkan rekomendasi menu ditampilkan secara real-time kepada pengguna.Kata Kunci: Mixue; Sistem rekomendasi; Collaborative filtering; Item-based; k-Nearest Neighbors. Abstract - The culinary industry in Indonesia, particularly the Mixue ice cream shop network, faces challenges in providing the right menu recommendations to customers. With a variety of menu options and different individual preferences, an effective recommendation system is essential to enhance customer experience and sales. This study aims to develop a food recommendation system at Mixue using the collaborative filtering method, specifically an item-based collaborative filtering approach, which utilizes customer transaction data to provide relevant menu suggestions. The methodology used includes collecting customer transaction data, calculating item similarities using the cosine similarity metric, and building a recommendation model based on the k-nearest neighbors (k-NN) algorithm. This system is integrated with the Mixue application database, allowing menu recommendations to be displayed in real-time to users.Keywords: Mixue; Recommendation system; Collaborative filtering; Item-based; k-Nearest Neighbors.
Student Class Grouping in Junior High Schools Based on Academic Performance Using the Fuzzy C-Means Method Tommy Bustomi; Jundro Daud Hasiholan; Kusno Harianto
Building of Informatics, Technology and Science (BITS) Vol 7 No 3 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i3.8585

Abstract

Abstrak−Differences in academic abilities among junior high school students often pose a challenge for schools in conducting class groupings objectively and efficiently. Many educational institutions, including SMP Negeri Y, still rely on manual grouping methods that are subjective and do not accurately reflect the actual conditions of students. Inaccurate grouping may lead to imbalanced learning processes, where students with high and low academic abilities are placed in the same group without considering their performance variations. Therefore, a data-driven approach is needed to represent student characteristics comprehensively and flexibly. This study aims to apply the Fuzzy C-Means (FCM) method to cluster students of SMP Negeri Y based on four main attributes: Academic Average, Attitude Score, Activeness Score, and Attendance. The FCM method was chosen for its ability to handle data uncertainty and assign multiple membership degrees to each student across different clusters. Prior to clustering, the data underwent a preprocessing stage involving data cleaning, normalization using StandardScaler, and scale adjustment across attributes to improve the accuracy of Euclidean distance calculations. The analysis results revealed the formation of two main clusters representing student academic performance levels. Cluster 0 has an average academic score of 78.37 with moderate attitude and activeness levels, while Cluster 1 shows a higher academic average of 82.18 accompanied by better attitude, activeness, and attendance scores. Based on the highest membership degree, 38 students were assigned to Cluster 0 and 26 students to Cluster 1. Model evaluation using Fuzzy Partition Coefficient (FPC), Modified Partition Coefficient (MPC), and Silhouette Score indicated the optimal configuration at a fuzziness level of m = 2, yielding FPC = 0.680, MPC = 0.359, and Silhouette Score = 0.334. These findings demonstrate that FCM is effective in representing variations in student abilities more realistically, while also providing an objective foundation for schools to design adaptive learning strategies and implement data-driven academic policies.
Rancang Bangun Aplikasi Augmented Reality untuk Pembelajaran Teknik Dasar Petanque Bagi Pemula Yosef Lahang; Azahari Azahari; Kusno Harianto
Journal of Informatics and Electronics Engineering Vol. 6 No. 01 (2026): Juni 2026
Publisher : Unit Penelitian dan Pengabdian kepada Masyarakat Politeknik TEDC Bandung Jl. Pesantren Km 2 Cibabat Cimahi Utara – Cimahi 40513 Jawa Barat – Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70428/jiee.v6i01.1589

Abstract

Perkembangan teknologi digital, khususnya Augmented Reality (AR), memberikan peluang besar dalam meningkatkan kualitas pembelajaran interaktif. Penelitian ini bertujuan untuk merancang dan membangun aplikasi AR sebagai media pembelajaran teknik dasar olahraga petanque bagi pemula. Metode yang digunakan adalah Research and Development (R&D) dengan model Luther-Sutopo yang meliputi tahapan konsep, desain, pengumpulan materi, pembuatan, pengujian, dan distribusi. Hasil penelitian menunjukkan bahwa aplikasi AR mampu menampilkan objek 3D teknik dasar petanque seperti pointing dan shooting secara interaktif. Berdasarkan pengujian, aplikasi berjalan dengan baik dan mampu meningkatkan pemahaman pengguna terhadap materi. Hal ini sejalan dengan penelitian sebelumnya yang menyatakan bahwa penggunaan AR dapat meningkatkan hasil belajar, minat, dan keterlibatan peserta didik secara signifikan .Dengan demikian, aplikasi AR ini dapat menjadi alternatif media pembelajaran yang efektif, menarik, dan inovatif bagi pemula dalam memahami teknik dasar petanque.
Sentiment Analysis of Bakso GLG Using the Naive Bayes Method Lingga Wardhana; Ita Arfyanti; Kusno Harianto
TEPIAN Vol. 7 No. 3 (2026): September 2026
Publisher : Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tepian.v7i3.3975

Abstract

Accelerating digital innovations have vastly reshaped the methods individuals use to express their perspectives on the gastronomic industry about culinary services through customer reviews on Google Maps. This study seeks to examine the sentiments conveyed in reviews of Bakso GLG to assist management in understanding customer perceptions objectively by employing the Naïve Bayes algorithm only after undergoing rigorous preprocessing phases, including cleaning, case folding, normalization, tokenization, stopword removal, stemming, and the generation of TF-IDF vectors. The classification results yielded an overall accuracy of 77%. The data distribution is dominated by positive sentiment, comprising 226 reviews, followed by 25 neutral reviews and 13 negative reviews. Although the model demonstrated optimal performance in classifying positive sentiment, it encountered difficulties in classifying the minority classes due to the imbalanced dataset. Overall, the system proved effective in processing large-scale review data as a source of strategic evaluation for improving product and service quality in the culinary sector, particularly at Bakso GLG.
Co-Authors Ahmad Rofiq Hakim Awang H. Kridalaksana Azahari Azahari Bonifasius Candra Dhanny Rindya Pradifta Eddy Kurniawan Saputra Ekawati Yulsilviana Farhan Aufa Azhar Hadi Wiyarno Inka Sandy Taruna Ita Arfyanti Jundro Daud Hasiholan Kusnandar Kusnandar Lingga Wardhana M. Irwan Ukkas Irwan Ukkas Ukkas Mega Jiana Muh. Husain Nooor Hidayat Nolan Melambi Reza Andrea Roffi Maulidi Salmon Salmon Tommy Bustomi Yosef Lahang