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Tri A. Sundara
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The Indonesian Journal of Computer Science
Published by STMIK Indonesia Padang
ISSN : 25497286     EISSN : 25497286     DOI : https://doi.org/10.33022
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering
The Indonesian Journal of Computer Science (IJCS) is a bimonthly peer-reviewed journal published by AI Society and STMIK Indonesia. IJCS editions will be published at the end of February, April, June, August, October and December. The scope of IJCS includes general computer science, information system, information technology, artificial intelligence, big data, industrial revolution 4.0, and general engineering. The articles will be published in English and Bahasa Indonesia.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 22 Documents
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Search results for , issue "Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science" : 22 Documents clear
Analisa Pengaruh Jalur Penerimaan Mahasiswa Baru Terhadap Hasil Akademik Mahasiswa Menggunakan Metode Clustering K-Means Yang, Agita Rindri; Rollastin, Boy; Riyadi, Muhammad
The Indonesian Journal of Computer Science Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i1.3103

Abstract

Setiap tahun perguruan tinggi melakukan penerimaan mahasiswa baru untuk menyaring calon mahasiswa baru yang berkualitas. Data penerimaan mahasiswa baru tersebut semakin bertambah setiap tahunnya dan hanya tersimpan sebagai arsip dalam basis data perguruan tinggi. Padahal data-data tersebut dapat diolah dengan menggunakan teknik data mining untuk mendapatkan informasi tertentu yang bermanfaat bagi perguruan tinggi. Penelitian ini bertujuan memanfaatkan data penerimaan mahasiswa baru untuk mengetahui pengaruh jalur penerimaan mahasiswa baru terhadap hasil akademik mahasiswa selama mengikuti perkuliahan dengan menggunakan algoritma K-Means Clustering. Data yang digunakan adalah data penerimaan mahasiswa baru pada Program Studi Sarjana Terapan Teknik Elektro, Program Studi Sarjana Terapan Teknologi Rekayasa Perangkat Lunak, dan Program Studi Sarjana Terapan Teknik Mesin dan Manufaktur Polman Negeri Babel Tahun Akademik 2021/2022 dan data nilai semester ganjil TA 2021/2022. Jumlah data yang digunakan sebanyak 179 data dari Program Studi Sarjana Terapan Teknik Elektro, Program Studi Sarjana Terapan Teknologi Rekayasa Perangkat Lunak, dan Program Studi Sarjana Terapan Teknik Mesin dan Manufaktur. Hasil dari penelitian menunjukkan bahwa K-Means Clustering mengelompokkan data menjadi 3 cluster di setiap kategori jalur penerimaan mahasiswa baru. Hasil cluster tersebut menunjukkan bahwa jalur SNMPTN menghasilkan 48% mahasiswa memiliki hasil akademik 10 terbaik di kelasnya, sementara itu 60% mahasiswa dari jalur MANDIRI menempati peringkat 21-30 di kelasnya.
Sistem Kontrol Menghidupkan Lampu Otomatis Menggunakan Sensor Suara FC-04 Berbasis Arduino Uno Chairil, Slamet; Teuku Radillah; Satria, Budy
The Indonesian Journal of Computer Science Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i1.3121

Abstract

The problem that often occurs is forgetting to turn off the lights when you want to leave because you are in a hurry, as a result the lights stay on and there is a waste of electricity. This research was conducted with the aim of designing an Automatic Light Turning Control System Using the FC-04 Sound Sensor Based on Arduino Uno. When the Sound Sensor FC-04 detects the input of two hands clapping, the relay will give current to the light object so that it turns on automatically. The results of the tests that have been carried out are that the Arduino Uno Microcontroller works well for processing data. Testing the FC-04 Sound Sensor with a distance of 50-200 cm from the input in the form of the sound of applause causes the light to turn on as an output that the sensor functions to detect vibration frequency waves. In addition, the relay device also works well as a regulator of the electric power supply for the lamp so that the lamp can turn on or on. So that this tool can help humans turn off the lights so they no longer have to move closer to the lights and press existing buttons to be able to turn on or turn off the lights, but can be controlled through voice commands of applause.
Jaringan Syaraf Tiruan Mendeteksi Penyakit Pneumonia Infeksi Saluran Pernafasan Akut Dengan Algoritma Backpropagation Yulia; Rendy; Arnomo, Sasa Ani
The Indonesian Journal of Computer Science Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i1.3129

Abstract

Acute Respiratory Infections (ARI) are a health problem that often affects children and adults. For adults, acute respiratory infections are mild or common, but in children under five, this disease is a threat that can cause death. One of the causes of death due to acute respiratory infections is incorrect diagnosis. This study aims to determine the level of accuracy and optimal neural network architecture in detecting ARI using the backpropagation method. This research was implemented using MATLAB software with several forms of network architecture. Symptoms of ARI that were used as input for detection of the disease consisted of 13 variables targeting non-pneumonia and pneumonia ARDs. Based on the research results, the architecture with the best configuration consists of 13 input layer neurons, 20 hidden layer neurons, and two output layer neurons with a binary sigmoid activation function (logs), a learning rate value of 0.5, an error tolerance value of 0.001, a maximum of the epoch of 216 and MSE 0.000997. Artificial neural networks with the backpropagation method used for weight adjustment can respond to training data and testing data well, marked by the resulting network accuracy of 100% in accordance with the desired target.
Transfer learning pada Network VGG16 dan ResNet50 Fauzan Muhammad; Aniati Murni Arimurthy; Dina Chahyati
The Indonesian Journal of Computer Science Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i1.3130

Abstract

Transfer Learning adalah prinsip yang digunakan pada neural network dengan tujuan membantu pelatihan pada data yang sedikit, mempercepat waktu dan meningkatkan performa pelatihan. Salah satu metode transfer learning adlaah fine tuning. Pada metode tersebut, melakukan pembekuan pada sejumlah layer pada model network yang dilatih sebelumnya dan melakukan pelatihan pada lapisan yang lainnya dan pada lapisan feature extractor. Pada penelitian ini akan dilihat salah satu metode transfer learning pada model network VGG6 dan ResNet50, yaitu fine tuning, dengan melakukan pembekuan dengan jumlah yang lapisan berbeda pada masng-masing model. Kemudian pada kedua model tersebut dilihat kinerja dan akurasinya pada saat pelatihan dan pengujian
Online Terrain Classification Using Neural Network for Disaster Robot Application Sanusi, Muhammad Anwar; Dewantara, Bima Sena Bayu; Setiawardhana; Sigit, Riyanto
The Indonesian Journal of Computer Science Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i1.3132

Abstract

A disaster robot is used for crucial rescue, observation, and exploration missions. In the case of implementing disaster robots in bad environmental situations, the robot must be equipped with appropriate sensors and good algorithms to carry out the expected movements. In this study, a neural network-based terrain classification that is applied to Raspberry using the IMU sensor as input is developed. Relatively low computational requirements can reduce the power needed to run terrain classification. By comparing data from the Accelerometer, Gyroscope, and combined Accelero-Gyro using the same neural network architecture, the tests were carried out in a not moving position, indoors, on asphalt, loose gravel, grass, and hard ground. In its implementation, the mobile robot runs over the field at a speed of about 0,5 m/s and produces predictive data every 1,12s. The prediction results for online terrain classification are above 93% for each input tested.
Reduksi Dimensi pada Klasifikasi Data Microarray Menggunakan Minimum Redundancy Maximum Relevance dan Random Forest : The Dimensional Reduction in Microarray Data Classification Using Minimum Redundancy Maximum Relevance and Random Forest Harahap, Lailan; Nababan, Erna Budhiarti; Efendi, Syahril
The Indonesian Journal of Computer Science Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i1.3133

Abstract

Di Indonesia prevalensi kanker pada data Riskesdes tahun 2018 terdapat 1,79 per 1.000 penduduk mengidap penyakit kanker. Akibat tingginya prevalensi kanker maka diperlukan pendeteksian kanker sejak dini. Salah satu cara mendeteksi kanker yaitu dengan teknologi microarray dimana teknologi ini dapat memantau ribuan ekpresi gen secara bersamaan dalam satu percobaan. Namun, data microarray memiliki dimensi yang besar sehingga diperlukan proses reduksi dimensi data microarray pada penyakit prostate cancer da gastric cancer agar dapat menghilangkan atribut yang redundansi dan meningkatkan akurasi pada klasifikasi. Reduksi dilakukan menggunakan MRMR (FCQ dan FCD) dengan k 10,20,30,40,50,60,70,80,90 dan 100. Klasifikasi dilakukan menggunakan RF dengan membentuk 100 tree. Hasil akurasi terbaik pada klasifikasi data prostate cancer yaitu dengan FCQ 100% pada k=10, tanpa reduksi 95% dan akurasi terendah dengan FCD 52% pada k=90. Sedangkan hasil akurasi terbaik klasifikasi data gastric cancer yaitu dengan FCQ dan FCD 100% pada semua k dan akurasi terendah yaitu tanpa reduksi 83%.
Sistem Lokalisasi Mobile-Robot Pertanian Otonom Berbasis Ultra-Wideband (UWB) dan Sensor Inersia Bagus Muliawan, Nobby; Sulistijono, Indra Adji
The Indonesian Journal of Computer Science Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i1.3135

Abstract

Sitem kendali pergerakan kendaraan pertanian otonom membutuhkan sistem lokalisasi yang akurat. Pada penelitian ini, penentuan posisi robot otonom berbasis DWM1000 dan sensor inersia diusulkan. Algoritma Trilaterasi digunakan untuk mendapatkan posisi berdasarkan 3 titik anchor terhadap robot. Sistem UWB (Ultra-Wideband) menghitung jarak dengan menggunakan TDOA (Time Difference of Arrival) dengan perhitungan SDS-TWR (Symetrical Double Sided-Two Way Ranging) untuk menentukan jarak. Data posisi yang didapatkan kemudian disaring dengan Kalman-filter pada aksis X dan Y. Berdasarkan pengujian experimen sensor UWB pada mobile robot pertanian otonom, didapatkan hasil akurasi yang cukup baik dengan nilai eror simpangan rata-rata sebesar 0,33m
Manajemen Pembelajaran Online Menggunakan Adobe Flash pada Mata Kuliah Pattiserie Terhadap Capaian Kompetensi Angraini, Ezi; Giatman, M; Maksum, Hasan
The Indonesian Journal of Computer Science Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i1.3136

Abstract

Learning media is an instrument that greatly determines the success of the teaching and learning process. Because its existence can directly provide its own dynamics to students. After the spread of the Covid-19 outbreak had an effect on the world of education, changes to the learning system were directed to an online home study policy. This study aims to determine the effectiveness of Adobe Flash CS6 media in online learning towards competency achievement in the Pattiserie course. This research method uses a quantitative method by comparing student learning outcomes online during the pandemic with before the pandemic in the Pattiserie course at the IKK FPP UNP department. Based on data obtained from the 2017 and 2019 batch of Pattiserie semester scores, the average grade for the experimental class was 73.01 and the average grade for the control class was 88.53. From the results above, it can be concluded that a valid and practical media has not been able to replace the effectiveness of Pattiserie learning, in other words, this Pattiserie course is more competent if it is carried out practically in a laboratory because the hierarchy of practical courses must be carried out in a laboratory/workshop.
Analisis Kontras Densitas Lapisan Batuan Di Bawah Permukaan Tanah Dengan Metode Gravitasi Maulidina, Miftakhul
The Indonesian Journal of Computer Science Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i1.3139

Abstract

Metode gravitasi merupakan salah satu metode dalam survei geofisika yang bermanfaat untuk menentukan struktur batuan di bawah permukaan berdasarkan perbedaan nilai massa jenis batuan penyusunnya. Perbedaan massa jenis atau densitas tersebut ditandai dengan adanya anomali gravitasi di permukaan bumi. Obyek penelitian kontras densitas dengan metode gravitasi kali ini adalah area Gunung Kelud yang terletak di Kabupaten Kediri Provinsi Jawa Timur. Hasil perekaman data gravitasi di lapangan diolah menggunakan beberapa software, yaitu Surfer 9, MagPick, dan GRAV2DC. Pemodelan data gravitasi dengan menggunakan GRAV2DC untuk anomali lokal area Gunung Kelud di Kediri, Jawa Timur menghasilkan layer sebanyak 4 bodies dengan kontras densitas dan kedalaman masing-masing adalah -0,005 gr/cm3 – 13,5 km, 0,015 gr/cm3 – 3,19 km, 0,005 gr/cm3 – 7,178 km, dan 0,005 gr/cm3 – 14 km, dengan misfit sebesar 0,37. Dengan mengambil densitas awal 2,6 gr/cm3, lapisan tersebut terdiri dari lapisan syenite dan granitc.
Pengembangan Sistem Manajemen Bank Sampah berbasis Web untuk mewujudkan keberhasilan Ekonomi Sirkular di Masyarakat Utami, Kery; Sandya Prasvita, Desta; Widiastiwi, Yuni
The Indonesian Journal of Computer Science Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i1.3140

Abstract

This research will be conducted at the Solusi Hijau Main Garbage Bank in the Gunung Sindur District, Bogor Regency. The Solusi Hijau Waste Bank still uses a manual recording system that is easily lost, inefficient, and not dynamic. Therefore it is necessary to make a Web-based Waste Savings Application that can become the main activity facility for the Green Solutions Main Garbage Bank. This application will be used as an interactive interface for Customers and Unit Waste Banks as well as the general public as Prospective Customers or Prospective Management Unit Waste Banks so that they can maximize the performance of the Waste Bank in its development. The Web-based Waste Savings application is a continuation of basic research that has been done before, namely to create digital applications that are utilized by waste banks and the community so that waste banks can become a forum for public education in terms of waste handling and environmental management as well as generating community economic resources. Systems Development Life Cycle (SDLC) is implemented as an Application development method. SDLC is a system development cycle in making waste bank applications by applying the waterfall method. The results of this research in the future are directed to be developed into a standard for Waste Saving System Applications in the community.

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