Article Per Year (5 Year)
p-Index From 2020 - 2025
0.659
P-Index
This Author published in this journals
All Journal YUME : Journal of Management JURNAL MANAJEMEN Jurnal Teknik Informatika (JUTIF)
Lilik Hariyanto
Culinary Art, Faculty Of Hospitality And Tourism, Universitas Pradita, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Health Professions Social Sciences

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Pengaruh Kualitas Produk Terhadap Loyalitas Pelanggan di Dim Sum Inc., Kemang Lilik Hariyanto
YUME : Journal of Management Vol 5, No 3 (2022)
Publisher : Pascasarjana STIE Amkop Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37531/yum.v5i3.1939

Abstract

Perkembangan bisnis di Indonesia semakin berkembang pesat belakangan ini. Salah satu bisnis yang berkembang sangat pesat adalah bisnis food and beverage (makanan dan minuman). Berdasarkan fenomena diatas, penelitian ini bertujuan untuk mengetahui pengaruh kualitas produk terhadap loyalitas pelanggan di Dim Sum Inc., Kemang. Populasi dalam penelitian ini adalah seluruh pelanggan yang berkunjung ke Dim Sum Inc., Kemang. Jumlah sampel yang diambil dalam penelitian sebanyak 148 sampel. Metode yang digunakan adalah metode deskriptif dengan pendekatan kuantitatif. Teknik pengamblan sampel menggunakan accidental sampling. Hasil pengujian pada penelitian ini menunjukan bahwa kualitas produk berpengaruh signifikan  terhadap loyalitas pelanggan adalah positif, dengan kata lain yaitu semakin baik atau tinggi kualitas produk maka semakin tinggi loyalitas pelanggan di Dimsum Inc Kemang.Kata Kunci: Kualitas Produk, Loyalitas Pelanggan
THE INFLUENCE OF FOOD QUALITY, BRAND IMAGE AND PRICE ON PURCHASE DECISIONS OF BOGOR'S ASINAN AHAUW TRADITIONAL FOOD Candra Hidayat; Christin Setiawan; Lilik Hariyanto
JPIM (Jurnal Penelitian Ilmu Manajemen) Vol 8 No 1 (2023): JPIM (JURNAL PENELITIAN ILMU MANAJEMEN)
Publisher : Universitas Islam Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to determine the effect of food quality, brand image and price on purchasing decisions for culinary Asinan Ahauw Traditional Food from Bogor. This type of quantitative descriptive research. The population in this study were consumers who bought Asinan Ahauw culinary, Bogor's traditional food, while the sample consisted of 100 respondents. The sampling technique uses accidental sampling. The data collection technique is by distributing questionnaires with a Likert scale from 1 to 5. The results of the study partially show that food quality and brand image have a significant effect on purchasing decisions, while partially they do not have a significant effect on purchasing decisions. the producers of Asinan Ahauw Traditional Food from Bogor to always maintain product quality and build a positive brand image in order to win the competition between Asinan Ahauw producers.
A COMPARISON OF THE NAIVE BAYES AND K-NN ALGORITHMS IN PREDICTING THE FRESHNESS OF MILKFISH AT FISH AUCTIONS Harlis Setiyowati; Hendra Mayatopani; Lilik Hariyanto; Muhammad Alfathan Harriz
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2277

Abstract

This research aims to compare the performance of two machine learning algorithms, Naive Bayes and K-Nearest Neighbors (K-NN), in predicting the freshness of milkfish (Chanos chanos) at fish auctions. Predicting fish freshness is an important aspect to ensure product quality and customer satisfaction. The Naive Bayes algorithm, which is based on Bayes' Theorem with the assumption of independence between features, as well as the K-NN algorithm, which uses an instance-based approach to classify data based on proximity to k nearest neighbors, were implemented and tested. Evaluation is carried out using accuracy and Kappa metrics. The results show that Naive Bayes achieved an accuracy of 73.44% with a Kappa value of 0.594, indicating good performance in predicting the freshness of milkfish. In contrast, K-NN shows an accuracy of 68.75% and a Kappa value of 0.461, which means its performance is lower compared to Naive Bayes. Further analysis revealed that Naive Bayes is more computationally efficient and faster at making predictions, making it better suited for real-time applications at fish auctions. However, Naive Bayes has limitations in assuming feature independence which may not always be true in real-world situations. On the other hand, K-NN although more flexible and capable of capturing complex patterns in data, tends to be slow and requires optimization of parameters such as k values ​​to improve its performance. In conclusion, Naive Bayes is recommended for predicting the freshness of milkfish at fish auctions because of its higher accuracy and reliability. Further research is needed to optimize these two algorithms through parameter adjustments and the use of ensemble methods to improve overall prediction performance.
Co-Authors Candra Hidayat Christin Setiawan Harlis Setiyowati Mayatopani, Hendra Muhammad Alfathan Harriz