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PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic
Published by Universitas Islam 45 Bekasi
ISSN : 23033304     EISSN : 26203553     DOI : https://doi.org/10.33558/piksel
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Jurnal PIKSEL diterbitkan oleh Universitas Islam 45 Bekasi untuk mewadahi hasil penelitian di bidang komputer dan informatika. Jurnal ini pertama kali diterbitkan pada tahun 2013 dengan masa terbit 2 kali dalam setahun yaitu pada bulan Januari dan September. Mulai tahun 2014, Jurnal PIKSEL mengalami perubahan masa terbit yaitu setiap bulan Maret dan September namun tetap open access tanpa biaya publikasi. p-ISSN: 2303-3304, e-ISSN: 2620-3553. Available Online Since 2018.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 489 Documents
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Optimization of Classification Models for Customer Sentiment on Train Suite Class Compartments Using SMOTE and Particle Swarm Optimization Kiki Setiawan; Miswanto Miswanto; Aditya Zakaria
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 2 (2025): September 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i2.11617

Abstract

This study uses three algorithms, namely Naive Bayes (NB), K-Nearest Neighbour (KNN), and Support Vector Machine (SVM). Then, the three methods are supplemented with the use of SMOTE (Synthetic Minority Oversampling Technique) and Particle Swarm Optimization (PSO), which will later be compared with the three methods to obtain good accuracy results. It is hoped that the use of SMOTE in this study can be a solution in handling imbalanced data, because the influence of imbalanced data is very large on the results of the model obtained, since algorithm processing that does not take into account data imbalance will tend to be dominated by the major class and ignore the minor class. Similarly, the use of Particle Swarm Optimization is expected to increase attribute weights and improve the accuracy of an algorithm and data classification. The model that obtained the best evaluation results was the Support Vector Model using SMOTE and Particle Swarm Optimization, with an accuracy value of 81.15%.
Comparative Study of PCA, t-SNE, and UMAP for CNN Feature Representation of Image Classification Herlawati Herlawati; Rahmadya Trias Handayanto
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 2 (2025): September 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i2.11634

Abstract

Currently, the use of Deep Learning is widespread across various domains, with Convolutional Neural Networks (CNNs) as one of its main pioneers due to the principle of convolution. Recent methods continue to emerge with steadily increasing accuracy, in some cases approaching perfection. However, their implementation is often limited by the lack of sufficient computational resources in many environments. Moreover, the growing demand for explainable AI compels researchers to explore approaches that reveal the inner workings of deep learning models rather than treating them as mere black boxes. In this study, a simple CNN model is employed as a testbed for examining the feature extraction process through convolution, which is subsequently transformed into a user-friendly two-dimensional representation. The dataset used in this study is the Cats and Dogs dataset from Kaggle, which contains 25,000 labeled images equally distributed between the two classes. The dimensionality reduction methods utilized include Principal Component Analysis (PCA), t-distributed Stochastic Neighbor Embedding (t-SNE), and Uniform Manifold Approximation and Projection (UMAP). The results demonstrate that UMAP achieves superior performance compared to PCA and t-SNE, with the highest silhouette score and a lower Davies–Bouldin index, indicating more compact and well-separated feature clusters.
Water Quality Measurement based on Internet of Thing Misbahul Fajri; Yuwan Jumaryadi; Anne Parlina
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 2 (2025): September 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i2.11642

Abstract

Good water quality is crucial for living things, including temperature, pH, and TDS, which are constantly changing due to various factors. These three water parameters are crucial for maintaining water quality within a certain threshold to ensure that an ecosystem meets specified standards. Measuring water quality is essential to anticipate these changes as desired. Internet of Things (IoT) technology allows continuous monitoring of water parameters at any time and can be accessed anywhere with a network connection via computer or smartphone. In this proposed research, an IoT-based system based on ESPHome will be developed for water quality measurement in aquarium water and its ecosystem. The proposed research detects, records, and displays water pH and TDS parameters, including temperature, using an ESP8266 microcontroller. The system utilizes sensors to detect water parameters; the system utilizes an ESP8266 microcontroller and a WiFi connection that sends data to a cloud-based server with a Homeassistant dashboard. The research results are well-functioning in both hardware and software and are easily accessible.
Comparative Study of Logistic Regression, Neural Network, and Deep Learning in Predicting Hypertension Risk Prima Dina Atika
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 2 (2025): September 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i2.11646

Abstract

Hypertension is a major risk factor for cardiovascular diseases, and early detection is crucial for effective management. This study compares the predictive performance of three modeling techniques—Logistic Regression (LR), Neural Network (NN), and Deep Learning (DL)—in estimating the risk of hypertension. The dataset, obtained from Kaggle, consists of demographic and clinical variables with binary labels indicating the presence or absence of hypertension. Each model was trained and evaluated using RapidMiner, with performance assessed through accuracy and Root Mean Squared Error (RMSE). The results indicate that the Neural Network outperformed both Deep Learning and Logistic Regression, achieving the highest accuracy (99.88%) and the lowest RMSE (0.124). These findings suggest that shallow neural networks can provide reliable and efficient predictions for hypertension risk, sometimes even surpassing more complex deep learning architectures.  
ROUTING PROTOKOL EIGRP DAN OSPF PADA JARINGAN PT. INDONESIA COMNETS PLUS JAKARTA Khifli Mulyadi
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 2 No. 1 (2014): Maret 2014
Publisher : LPPM Universitas Islam 45 Bekasi

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Abstract

ABSTRACT In a business, the customer is a very important factor for a service company such as PT Indonesia Comnets Plus engaged in VoIP providers. The increasing number of customers using VoIP services then it needs a routing system that can facilitate customer additions and to facilitate in analyzing the problem.The purposeof this thesisis to create a routing that can facilitate network administrators in handling problems that occur. The method used in the manufacture ofthe authorof this thesisby comparing between using Dynamic Routing Enhanced Interior Gateway Routing Protocol and Open Shortest Path First. after comparing two routing results obtained EIGRP is best to apply in PT.Indonesia Comnets Plus in particular by the Division Unit Bisnis Multimedia because there is no need reconvergence time for performed by EIGRP when a change in route. Keyword : Routing, static , dynamic ,EIGRP,OSPF. ABSTRAK Dalam sebuah bisnis, pelanggan merupakan faktor yang sangat penting bagi sebuah perusahaan jasa seperti PT Indonesia Comnets Plus yang bergerak dibidang penyelenggara VoIP. Semakin banyaknya pelanggan yang menggunakan jasa voip maka dibutuhkannya sebuah system routing yang dapat memudahkan penambahan pelanggan dan dapat mempermudah dalam menganalisa masalah. Tujuan penelitian ini adalah membuat suatu routing yang dapat mempermudah network administrator dalam penanganan –penanganan masalah yang terjadi. Metode yang digunakan adalah Routing Dynamic Enhanced Interior Gateway Routing Protocol dan Open Shortest Path First. Setelah membandingkan kedua routing tersebut didapatkan hasil EIGRP yang terbaik untuk diterapkan di PT.Indonesia Comnets Plus khususnya oleh Divisi Unit Bisnis Multimedia dikarenakan tidak perlunya waktu konvergensi ulang yang dilakukan oleh EIGRP ketika terjadi perubahan route. Kata Kunci : Routing, static , dynamic ,EIGRP,OSPF.
SISTEM PAKAR ANALISA PERMASALAHAN AWAL CLOUD COMPUTING MENGGUNAKAN FORWARD CHAINING Rosyidi Muhtar
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 2 No. 1 (2014): Maret 2014
Publisher : LPPM Universitas Islam 45 Bekasi

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Abstract

ABSTRACT Many customers of PT Lintas Media Danawa (LMD) find it difficult to analyze if there is problem in Cloud computing systems that they rent. If there is a little problem it will immediately call or send an email to customer service PT LMD. By applying expert system then problems start Cloud Computing customers can analyze and identify problems early and not have to call a technician LMD.Dalam develop an expert system using a data research and development system. Expected by the web-based expert system customers will be able to analyze all alone The issue that occurs on systems that they use cloud computing from anywhere and can minimize the time, cost, and effectiveness of the customer PT LMD. Keyword: expert system , first probelms ABSTRAK Banyak pelanggan PT Lintas Media Danawa (LMD) mengalami kesulitan untuk menganalisa jika terjadi permasalahan dalam sistem Cloud computing yang mereka sewa. Jika terjadi masalah sedikit maka akan langsung menelpon atau mengirim email ke layanan pelanggan PT LMD. Dengan menerapkan sistem pakar permasalahan awal Cloud Computing maka pelanggan dapat menganalisa dan mengidentifikasi permasalahan awal dan tidak harus menghubungi teknisi LMD.Dalam mengembangkan sistem pakar menggunakan metode penelitian data dan pengembangan sistem. Diharapkan dengan sistem pakar berbasis web tersebut nantinya pelanggan dapat menganalisa semua permasalahanya sendiri yang terjadi pada sistem cloud computing yang digunakan dari manapun dan dapat meminimalisir waktu, biaya, dan efektifitas dari para pelanggan PT LMD. Kata kunci : sistem pakar, permasalahan awal
APLIKASI MOBILE KAMUS ISTILAH KOMPUTER BERBASIS ANDROID Herlan Mulyana; Maimunah Maimunah
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 2 No. 1 (2014): Maret 2014
Publisher : LPPM Universitas Islam 45 Bekasi

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Abstract

ABSTRACT Dictionary on mobile phones is more practical than conventional dictionaries, because at the moment the user needs a lot of information quickly anywhere without any time restrictions. In addition to the dictionary is able to provide information dictionary can also be used as a container for learning. In scientific writing, the author makes an application using the Android Dictionary of Computer Terms. The author of Android in the making of this application for android based on open source. The design of this application is made by xml code in Eclipse, the Android Java as a programming language and SQLite as database creation. Dictionary of Computer Terms is created because of the need for information is very important and a difficult time if you have to search for the meaning of the word or term using conventional dictionaries. It is expected that with this dictionary the user can search for a computer terms with access directly from their mobile phones without having to look for in conventional dictionaries. Keyword: application,dictionary,computer term , android, eclipse ABSTRAK Kamus pada telepon selular lebih praktis dibandingkan dengan kamus cetak konvensional, karena pada saat ini pengguna membutuhkan banyak informasi dengan cepat dimana saja tanpa adanya batasan waktu. Selain kamus mampu memberikan informasi kamus juga dapat dijadikan wadah untuk belajar. Dalam penulisan ilmiah ini penulis membuat sebuah aplikasi Kamus Istilah Komputer menggunakan Android. Penulis mengangkat Android dalam pembuatan aplikasi ini karena android berbasis open source. Perancangan aplikasi ini dibuat dengan kode xml pada Eclipse, Java Android sebagai bahasa pemrograman dan SQLite sebagai pembuatan database. Kamus Istilah Komputer ini dibuat karena kebutuhan akan informasi sangat penting serta waktu yang sulit jika harus mencari arti kata ataupun istilah menggunakan kamus cetak konvensional. Diharapkan dengan kamus ini pengguna dapat mencari pengertian istilah komputer dengan mengakses langsung dari telepon selular mereka tanpa harus mencari pada kamus cetak konvensional. Kata Kunci : aplikasi, kamus, istilah komputer, android, eclipse.
IMPLEMENTASI NEURAL NETWORK BACKPROPAGATION UNTUK IDENTIFIKASI TINGKAT MANIS BUAH BELIMBING BERDASARKAN CITRA RGB Retno Nugroho Whidhiasih
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 2 No. 1 (2014): Maret 2014
Publisher : LPPM Universitas Islam 45 Bekasi

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Abstract

ABSTRACT Star fruit classification is needed to maintain quality and improve competitiveness. Star fruit-based sweetness can be done destructively and non-destructively. Nondestructive can be done by measuring the correlation value of red, green, blue (RGB) star fruit image with Total Dissolved Solids (TPT) contained in starfruit. This study aims to develop an artificial intelligence system model to classify star fruit non-destructively based on the red-green-blue component using Neural Network (NN). The input parameter used is the red-green-blue component of the star fruit image which has been correlated to the TPT. The amount of sample data used is 99 pieces, which is 33 sweet starfruit image, 33 medium starfruit image and 33 image starfruit acid. A total of 81 data were used as training data and 18 data were used as test data. To obtain the best introductory results experiments were conducted using 6 variations of the number of neurons in the hidden layer. The classification into acid, medium and sweet fruit classes in this study obtained the best NN model using red, green and blue input parameters with 2 neurons in the hidden layer. The NN backpropatation 3-2-1 model provides an accuracy of 66.67% with 2 neurons in the hidden layer, MSE of 4.73e-06 on epoch 1. Keyword : classification, neural network, starfruit, non-destructive grading, pattern recognition. ABSTRAK Pemutuan buah belimbing sangat diperlukan untuk mempertahankan mutu dan meningkatkan daya saing. Pemutuan buah belimbing berdasarkan rasa dapat dilakukan secara destruktif dan nondestruktif. Nondestruktif dapat dilakukan dengan mengukur korelasi nilai red, green, blue (RGB) citra buah belimbing dengan Total Padatan Terlarut (TPT) yang terdapat pada belimbing. Penelitian ini bertujuan untuk mengembangkan model sistem kecerdasan buatan untuk mengklasifikasi buah belimbing secara non-destruktif berdasarkan komponen red-green-blue menggunakan Neural Network (NN). Parameter input yang digunakan adalah komponen red-green-blue dari citra buah belimbing yang telah dikorelasikan terhadapTPT. Jumlah sampel data yang digunakan adalah 99 buah, yaitu 33 citra belimbing manis, 33 citra belimbing sedang dan 33 citra belimbing asam. Sejumlah 81 data digunakan sebagai data pelatihan dan 18 data digunakan sebagai data pengujian. Untuk mendapatkan hasil pengenalan terbaik dilakukan percobaan-percobaan menggunakan 6 variasi jumlah neuron pada lapisan tersembunyi. Klasifikasi menjadi kelas buah asam, sedang dan manis dalam penelitian ini mendapatkan model NN terbaik menggunakan parameter input red, green dan blue dengan 2 neuron pada lapisan tersembunyi. Model NN backpropatation 3-2-1 ini memberikan akurasi sebesar 66.67% dengan 2 neuron pada lapisan tersembunyi, MSE sebesar 4.73e-06 pada epoch ke 1. Keyword : klasifikasi, belimbing, neural network, citra digital, pemutuan non-destruktif
ANIMASI INTERAKTIF PENGENALAN HARDWARE KOMPUTER DENGAN METODE DEMONSTRASI BERBASIS TIGA DIMENSI Andreans Yoshiya; Aziz Setyawan Hidayat
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 2 No. 1 (2014): Maret 2014
Publisher : LPPM Universitas Islam 45 Bekasi

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Abstract

ABSTRACT People who are still learning the system manually by using face-to -face private or group class is less effective . With the cost issues for practice learning in the form of expensive physical examples such as learning computer assembly . Moreover, with limited manpower in general , made ​​public no intention to learn . Facilities and teaching to the learning community is expected to be given to the maximum so that people can implement useful learning for education or employment. Method demonstration become a factor in the response to people quickly learn something like recognition and computer assembly . Interactive animation introduction of computer -based three- dimensional and assisted with the demonstration method allows users to learn and better understand themselves as assisted object - the object three- dimensional look that can be seen as the original . The software used for the creation of interactive animations and this is with Unity 3D Blender for 3D modeling. Keyword : Animation, Introduction to Computer Hardware , Method Demonstration , Three Dimensional. ABSTRAK Sistem pembelajaran masyarakat yang masih menggunakan cara manual yaitu dengan bertatap muka dikelas private maupun berkelompok kurang efektif. Dengan masalah biaya untuk praktek pembelajaran yang berupa fisik yang mahal contohnya seperti belajar perakitan komputer. Terlebih lagi dengan tenaga kerja yang terbatas pada umumnya, membuat masyarakat tidak ada niat untuk belajar. Fasilitas dan pengajaran terhadap masyarakat dalam pembelajaran diharapkan dapat diberikan secara maksimal sehingga masyarakat dapat mengimplementasikan pembelajaran yang berguna untuk pendidikan ataupun pekerjaan. Metode demonstrasi menjadi salah satu acuan agar masyarakat cepat tanggap dalam mempelajari sesuatu seperti pengenalan dan perakitan komputer. Animasi Interaktif pengenalan komputer yang berbasis tiga dimensi dan dibantu dengan metode demonstrasi memungkinkan pengguna dapat belajar dan lebih paham dengan sendirinya karena dibantu objek – objek tiga dimensi yang dapat dilihat seperti terlihat aslinya. Perangkat lunak yang digunakan untuk pembuatan animasi interaktif ini adalah dengan Unity dan Blender 3D untuk modeling 3D. Kata Kunci : Animasi. Pengenalan Hardware Komputer, Metode Demonstrasi, Tiga Dimensi.
PERANCANGAN ALAT PENGENDALI LISTRIK RUMAH BERBASIS MIKROKONTROLER ATMEGA8 Ahmad Rosadi
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 2 No. 2 (2014): September 2014
Publisher : LPPM Universitas Islam 45 Bekasi

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Abstract

ABSTRACT The paper is made with the objective of making simulation or miniature of ATMega8 microcontroller based home electricity controller segmence. This segmence consists of 4 blocks, they are input block as sms (short massage service) character and timer set, control block using ATMega8 microcontroller,output block display as lcd (liquid crystal display) and 4 lamps. This paper is made by way of observing system segmence using the trial electricity control devices, designing mechanical, electrical and programme of devices. Then doing tests of the experiments which have been made, then found that the ATMega8 microcontroller based home electricity controller was successfully tested to save and control home electricity. Keywords: home electricity controller, sms, atmega8. ABSTRAK Perancangan pengendali ini dibuat dengan tujuan untuk membuat simulasi atau miniatur dari rangkaian pengendali listrik rumah berbasis mikrokontroler ATMega8. Rangkaian ini terdiri dari 4 blok yaitu: blok input berupa karakter sms dan set timer, blok kontrol (pengendali) menggunakan mikrokontroller ATMega8, output blok display berupa LCD dan berupa 4 buah lampu. Perancangan alat ini dilakukan dengan cara pengamatan rangkaian sistem dan kerja alat pengendali listrik yang sesungguhnya. Perancangan ini dilakukan dengan melakukan perancangan mekanik, perancangan elektronik dan perancangan program alat. Kemudian dilakukan pengujian pada rangkaian yang telah dibuat. Dari hasil perancangan diperoleh bahwa, alat pengendali listrik rumah berbasis mikrokontroller ATMega8 telah berhasil dibuat dan diuji untuk dapat menghemat energi sekaligus melakukan pengendalian listrik khususnya diperumahan Kata Kunci: pengendali listrik rumah, sms, atmega8.

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