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Tri A. Sundara
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tri.sundara@stmikindonesia.ac.id
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+628116606456
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ijcs@stmikindonesia.ac.id
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Jalan Khatib Sulaiman Dalam 1, Padang, Indonesia
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INDONESIA
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 96 Documents
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Search results for , issue "Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)" : 96 Documents clear
Analisis dan Pengembangan Sistem Informasi Kemahasiswaan Berbasis E-Letter dengan Menggunakan User Centered Design Karunia, Reiza Dwi; Hidayati, Nurtriana
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.3755

Abstract

SISKA adalah sebuah sistem informasi yang memuat mengenai informasi dan kegitan Kemahasiswaan Universitas Semarang. SISKA Sudah berjalan 2 tahun, berdasarkan pengguna SISKA masih memiliki kekurangan danbelum sesuai kebutuhan. Untuk mengetahui ketepatan tersebut sesuai atau tidak, maka disebarlah kuisioner terhadap 26 Responden yang mana terdiri dari Admin dan Mahasiswa yang memiliki hak akses SISKA pada Organisasi Mahasiswa. Dalam organisasi mahsiswa SISKA sebagai tempat mengupload surat menyurat, proposal kegiatan maupun Laporan Pertanggung jawaban kegiatan. Proposal ini dibuat untuk menganalisis serta mengembangkan SISKA agar sesuai dengan Kebutuhan. Pada proses pengembangan sistem ini menggunakan metode User Centered Design (UCD) serta untuk Analisis sistemnya menggunakan perhitungan Kuisioner SUS.
Analisis Topic Modelling Pariwisata Yogyakarta Menggunakan Latent Dirichlet Allocation (LDA) Uray Nur Khadijah; Nuri Cahyono
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.3816

Abstract

Pariwisata Yogyakarta sebagai destinasi yang kaya akan budaya dan sejarah, sering menjadi fokus diskusi di media sosial. Tujuan dari Penelitian ini adalah menelaah topik pariwisata Yogyakarta dari Twitter. Dataset yang diperoleh dalam penelitian ini dari crawling data menggunakan API key Twitter. Penelitian ini menggunakan tahapan dari pengumpulan data, text preprocessing, dan menerapkan metode Topic Modelling, khususnya Latent Dirichlet Allocation (LDA). Hasil penelitian ini pengujian kinerja pemodelan topik dengan metode LDA dapat dilihat dari nilai coherence score, semakin tinggi nilai coherence suatu topik, semakin mudah diinterprestasikan oleh manusia dan Perplexity merupakan salah satu standar pengukuran yang dapat digunakan untuk menilai kinerja model yang baik dari model tersebut ditunjukkan dengan nilai perplexity yang lebih rendah. Nilai coherence score yang ditunjukkan pada num topic ke-1 sebesar 0.331047, untuk nilai perplexity ditunjukkan dengan nilai yang tinggi terletak pada num topic ke-3 sebesar -8.830172565520245. diharapkan dapat memberikan wawasan mendalam tentang topik-topik yang sering dibahas dan berkonsentrasi pada penerapan sistem pemodelan topik untuk membangun sistem keputusan topik berita yang menggunakan metode Latent Dirichlet Allocation (LDA). Pada Penelitian ini efektif dalam menggunakan metode LDA untuk menentukan topik berita yang mencakup tiga kategori topik yang sering dibicarakan pada masing-masing kelas.
Predictive Analytics for Water Safety: Data Mining and Supervised Learning in Potability Classification Nanda Aulia Sofiah; Fanny Olivia; Jambak, Muhammad Ihsan
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.3884

Abstract

Water is crucial for survival, especially for consumption, yet its quality is under threat due to human-caused pollution. Contaminated water poses serious health risks, including the transfer of diseases transmitted by water. Therefore, assessing water quality is critical for ensuring its safety for consumption. Data mining and supervised machine learning algorithms can help classify water potability, revealing hidden patterns and correlations between water parameters. This study evaluates the effectiveness of K-Nearest Neighbors (KNN), Naïve Bayes, Support Vector Machine (SVM), and Neural Network methods in categorizing a water quality dataset. The evaluation is aimed at selecting the most accurate procedure, as indicated by the highest accuracy rate. Results show that Neural Network exceeds KNN (81%), Naïve Bayes (63%), and SVM (73%), with a 85% accuracy rate. Keywords : Classification, Data Mining, Supervised Machine Learning, Water Potability
Sistem Informasi Harga Bahan Pokok Dinas Perdagangan dan Perindustrian Kota Palu Nursalim, Moh. Agung; Chairunnisa Ar Lamasitudju; Miftah; Wirdayanti; Mohammad Yazdi Pusadan; Rahmah Laila
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.3937

Abstract

Pasar tradisional Indonesia sangat penting bagi perekonomian, terutama bagi pedagang kecil dan komunitas yang bergantung pada perdagangan sebagai sumber pendapatan mereka. Namun, masalah seperti pergeseran demografi, kemajuan teknologi, dan kurangnya transparansi harga telah mengganggu stabilitas pasar tradisional. Artikel ini menunjukkan betapa pentingnya sistem informasi harga bahan pokok untuk mengelola harga dan mencegah inflasi. Studi ini bertujuan untuk membangun sistem informasi yang disebut GadeMart yang akan melacak perubahan harga di dua pasar tradisional terbesar Kota Palu: Pasar Inpres Manonda dan Pasar Masomba. Diharapkan bahwa penelitian ini akan menawarkan solusi untuk meningkatkan stabilitas ekonomi dan transparansi harga di pasar tradisional.
PERBANDINGAN AKURASI LINEAR REGRESSION DAN SUPPORT VECTOR REGRESSION DALAM PREDIKSI SUHU RATA-RATA Lesnusa, Gideon Namlea; Dwi Shinta Angreni; Ardiansyah, Rizka
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.3944

Abstract

The weather in Indonesia varies significantly and is influenced by geographical location, topography, and regional climate. Weather patterns differ between the western and eastern parts of Indonesia. This study explores time series models to predict weather data in Palu City, a region that is complex due to various weather factors. The focus is on the unique weather patterns reflected by the geography and topography of Palu City. Evaluation was conducted on time series models, including Linear Regression and Support Vector Regression (SVR), to estimate weather conditions in Palu City. The evaluation results show that the SVR model has an RMSE of 0.6302, while linear regression has an RMSE of 0.6328. This research has the potential to improve early warning and decision-making regarding extreme weather
Diagnosis Penyakit Tanaman Kopi Robusta Menggunakan Metode Dempster Shafer Berbasis Sistem Pakar Acihmah Sidauruk; Panggih Suseno; Budy Satria; Mulia Sulistiyono
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.3953

Abstract

Robusta coffee is a coffee variety that has unique characteristics, a strong taste and a different level of bitterness from Arabica coffee because Robusta coffee contains lower sugar and 2.2% more caffeine than Arabica coffee so that Robusta coffee production is quite helpful for the economy. several coffee producing countries in the world. The quality and productivity of coffee plants can decrease due to several factors such as pests and disease. However, the limitations of experts regarding coffee plant diseases are a factor and obstacle. The aim of this research is to create an expert-based intelligent system to identify pests and diseases in robusta coffee plants. The method that will be applied is Dempster Shafer. Data on disease names amounted to 13 and data on symptoms amounted to 27. The final result was that Robusta coffee plants were tested for expertise on the system with an average accuracy of diagnosis results of 94% from 13 test cases on pests and diseases of coffee plants, so it can be concluded that the system Experts can diagnose coffee plant pests and diseases very well using the Dempster Shafer method
Comparative Study Of Android-Based Learning Media With Web-Based Learning Media Monica Fransisca; Renny Permata Saputri
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4008

Abstract

Many choices of learning media were available, so it’s necessary to research which learning media are appropriate and suit the needs. Learning media are now technology-based, for example android-based and web-based learning media. The use of these two media was similar and widely used, so it’s necessary to examine the comparison of effectiveness. To conduct this research, a comparative analysis method with a literature study approach was used. Through the analysis, a comparison was carried out by comparing several research relevant with the themes. The research focuses on the level of effectiveness. The comparison of this research that comes from the research team itself, and several other studies. Based on comparison, the results showed that android-based learning media had a higher effectiveness percentage, 87.67%, while web-based learning media had average 80.39%. The conclusion of the research was that android-based learning media has a higher effectiveness compared to web-based learning media.
Implementation Of Naïve Bayes Classifier And Support Vector Machine For Stunting Classification Azani, Nilam Wahdiaz; M. Afdal
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4040

Abstract

Stunting is a condition when a child's physical growth and development are stunted or delayed due to a lack of adequate nutritional intake over a long period of time, especially during the early years of life. Indonesia still has a stunting prevalence rate above the WHO standard, which is at 21.6%. 2020 UN statistics recorded more than 149 million (22%) toddlers worldwide were stunted, of which 6.3 million were early childhood or stunted toddlers were Indonesian toddlers. This study aims to create a classification model using Data Mining Algorithms NBC and SVM to analyze and describe the class of a total of 2018 toddler nutritional status data in Lima Puluh Kota Regency. The results of this study are expected to be an evaluation of whether the stunting prevention program implemented has been successful, and can be the basis for creating the next program.
Perancangan Perancangan Evaluasi Proses Pembelajaran Untuk Kurikulum Merdeka Fitri Rahmadani, Ade; Yudhi Diputra
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4054

Abstract

This study aims to produce a learning evaluation system on the independent curriculum for State Junior High School 5 Pelepat. This system can help schools in the process of capturing and processing value data that still uses tools and uses manual processing methods. In the development of this learning evaluation system, the SDLC (System Development Lifecycle) method is used with a prototype model. Field study methods and literature studies are used for data collection. This information system is created using Microsoft Excel. System testing is carried out by testing aspects of functionality and usability using the black box testing test method. The results of the information system test developed obtained a functionality value of 1 (Very Good), and usability aspect testing obtained results with a percentage of 85% (Very Decent). So it can be concluded that the system built has succeeded in helping schools overcome manual problems in processing independent and feasible curriculum values and ready to use based on the results of the tests carried out.
Perbandingan Algoritma Naïve bayes Dan Support Vektor Machine Untuk Klasifikasi Status Stunting Pada Balita Muh. Faried Muchtar; Rahma Laila; Dwi Shinta; H. M. Yazdi Pusadan
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4055

Abstract

Penelitian ini bertujuan untuk membandingkan efektivitas algoritma Naïve Bayes dan Support Vector Machine (SVM) dalam klasifikasi status stunting pada balita. Stunting merupakan kondisi pertumbuhan terhambat pada balita akibat kekurangan gizi yang memiliki dampak serius terhadap kesehatan dan perkembangan anak. Dengan menggunakan data dari Puskesmas Tawaeli Kecamatan Tawaeli, penelitian ini mengimplementasikan kedua algoritma untuk mengidentifikasi balita yang mengalami stunting. Metode penelitian meliputi pengumpulan data, preprocessing, dan pengujian menggunakan metrik evaluasi yang sesuai. Hasil penelitian diharapkan dapat memberikan kontribusi dalam pengembangan metode klasifikasi stunting pada balita serta memberikan wawasan baru dalam penanganan masalah stunting pada tingkat populasi. Diharapkan penelitian ini dapat menjadi referensi bagi peneliti selanjutnya dalam pengembangan sistem informasi serupa.

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