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INDONESIA
Jurnal Ilmu Komputer dan Informatika
Published by Global Scients Publisher
ISSN : -     EISSN : 30639026     DOI : https://doi.org/10.62379/jiki
Core Subject : Science, Education, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering Mathematics
Jurnal Ilmu Komputer dan Informatika (E-ISSN : 3063-9026 )adalah jurnal ilmiah yang diterbitkan oleh GLOBAL SCIENTS PUBLISHER. Jurnal Ilmiah Komputer dan Informatika diterbitkan secara berkala yaitu 4 kali dalam setahun (pada bulan januari, april, juli dan oktober) yang bertujuan untuk menyebarluaskan berbagai jenis hasil riset dibidang Komputer dan Informatika kepada publik. Saat ini Jurnal Ilmu Komputer dan Informatika menerima kiriman artikel hasil riset dibidang komputer dan informatika yang ditulis dalam Bahasa Indonesia .
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 64 Documents
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Rancang Bangun Alat Ukur Kadar Protein Pada Makanan Pokok Berbasis Iot Dengan Kendali BOT Telegram Billy Hendrik; Ruri Hartika Zain; Afifah Syahidah Nahda
Jurnal Ilmu Komputer dan Informatika | E-ISSN : 3063-9026 Vol. 2 No. 4 (2026): April - Juni
Publisher : GLOBAL SCIENTS PUBLISHER

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Abstract

Protein is one of the macronutrients that is very important and essential for the human body. This substance functions in various biological processes, including as a builder of muscle tissue, skin, enzymes, hormones, and the body's immune system. Although important, monitoring daily protein consumption is often not carried out accurately by the general public. Most people only rely on rough estimates based on the type of food consumed, or nutritional information printed on the packaging label. This is a challenge, especially for staple foods or home-made foods that do not have nutritional labels. One technology that supports the development of this system is a load cell, which is able to measure the mass or weight of an object precisely and stably. This sensor is widely used in digital scales and industrial systems. In the context of protein measurement, the weight of a food ingredient can be converted to an estimate of its protein constent, based on the average protein content data of each type of food that has been determined. With the help of a microcontroller such as Arduino, ESP32, or other types, this system can regulate the logic flow of the tool's operation, calculate protein levels based on input from the load sensor, and display the measurement results to the user via an output device such as a 20x4 LCD. In addition, the use of infrared (IR) sensors as object presence detectors allows the system to recognize when food has been placed on the device, so that the measurement process can be carried out automatically and responsively.
Implementasi Loker Digital Berbasis Biometrik Untuk Keamanan Barang Pada Tempat GYM Berbasis Website Mardhiah Masril; Hasri Awal; Fitra Rahmadona
Jurnal Ilmu Komputer dan Informatika | E-ISSN : 3063-9026 Vol. 2 No. 4 (2026): April - Juni
Publisher : GLOBAL SCIENTS PUBLISHER

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Abstract

The increasing public awareness of the importance of health and fitness has led to a growing number of gym users. This condition requires the availability of safe and efficient supporting facilities, one of which is a secure locker system for storing personal belongings. Conventional locker systems that rely on physical keys have several weaknesses, such as the risk of lost keys, potential misuse, and difficulties in real-time monitoring. This research aims to design and implement a biometric-based digital locker system for securing belongings in gym facilities using a web-based platform. The proposed system utilizes fingerprint authentication as the main access key, supported by a load cell sensor to measure the weight of stored items, a reed switch sensor to detect forced opening attempts, and a buzzer as a warning alarm. All user data and locker activity records are managed through a website developed using PHP and MySQL, integrated with a microcontroller to enable real-time monitoring by gym administrators. The results of this research indicate that the system is able to improve security, enhance locker management efficiency, and provide greater convenience for users through a modern and centralized authentication mechanism. The implementation of this system is expected to minimize the risk of item loss and increase user trust in gym facilities.
Evaluasi Performa Gaussian Mixture Model dan K-Means terhadap Ketidakseimbangan Data pada Clustering Yuri, Muhammad Farrel Evan; Pasaribu, Farzad Sahnadi; Subuh, Arung Buana; Naibaho, Muhammad Hafif; Piliang, Arnita
Jurnal Ilmu Komputer dan Informatika | E-ISSN : 3063-9026 Vol. 2 No. 4 (2026): April - Juni
Publisher : GLOBAL SCIENTS PUBLISHER

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Abstract

Data imbalance represents a primary challenge in clustering analysis, particularly in datasets with highly disproportionate class distributions such as the Credit Card Fraud Detection dataset from Kaggle. This study aims to evaluate and compare the performance of the Gaussian Mixture Model (GMM) and K-Means algorithms under such conditions through a systematic literature review of nine prior studies. Clustering quality is evaluated using three internal validation metrics: Silhouette Score, Davies-Bouldin Index (DBI), and Calinski-Harabasz Index (CHI). The findings indicate that GMM consistently produces more stable and flexible clusters in data with overlapping distributions, as its probabilistic approach through the Expectation-Maximization (EM) algorithm allows each data point to hold multiple cluster membership probabilities. In contrast, K-Means produces sharper cluster boundaries with lower computational complexity, yet remains sensitive to outliers and the spherical distribution assumption frequently unmet in imbalanced data. The dominance of the majority class risks distorting K-Means centroids, resulting in suboptimal detection of fraudulent transactions, whereas GMM proves more adaptive for this scenario despite its higher computational cost.
Implementasi Algoritma Merge Sort Berbasis Divide and Conquer untuk Pengurutan Data Nilai Akademik Mahasiswa pada Sistem Informasi Akademik Universitas Sahara Lani Lestari; Frengki Alfredo Matondang; Dinda Syafitri; Kayla Amelia Putri; Adidtya Perdana
Jurnal Ilmu Komputer dan Informatika | E-ISSN : 3063-9026 Vol. 2 No. 4 (2026): April - Juni
Publisher : GLOBAL SCIENTS PUBLISHER

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Abstract

This study examines the application of the Merge Sort algorithm in the process of sorting student academic data within an academic information system (SIAKAD). The issue addressed is the suboptimal processing of academic data, which has the potential to cause delays and errors in the presentation of information. The objective of this study is to implement and evaluate the performance of the Merge Sort algorithm by comparing it with Bubble Sort and Insertion Sort. The method used is an experimental approach through testing on various dataset sizes, ranging from small to large scales, as well as under different data conditions, namely random, sorted, and reversed. Implementation was carried out using a Command Line Interface (CLI)-based application and a web interface to simulate real-world usage. The results of the study indicate that Merge Sort performs more efficiently and consistently than other algorithms, particularly on large datasets. Additionally, this algorithm possesses stable sort properties that maintain the relative order of data with the same values, making it more reliable for academic data processing.

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