cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Dewa Made Sri Arsa
Contact Email
dewamsa@unud.ac.id
Phone
-
Journal Mail Official
jurnal.merpati@unud.ac.id
Editorial Address
Gedung Teknologi Informasi-Fakultas Teknik Jalan Raya Kampus UNUD, Jimbaran, Badung, Bali
Location
Kota denpasar,
Bali
INDONESIA
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi)
Published by Universitas Udayana
ISSN : 22523006     EISSN : 26852411     DOI : https://doi.org/10.24843/JIM
Core Subject : Science,
Computer Science & IT
The journal publishes work from all disciplinary, theoretical and methodological perspectives. It is designed to be read by researchers, scholars, teachers and advanced students in the fields of Information Systems and Information Science, as well as IT developers, consultants, software vendors, and senior IT executives seeking an update on current experience and future prospects in relation to contemporary information and communications technology.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 280 Documents
 20   21   22   23   24 
Prediksi Kecelakaan Lalu Lintas di Bali dengan XGBoost pada Python Ngakan Nyoman Pandika Pinata; I Made Sukarsa; Ni Kadek Dwi Rusjayanthi
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol. 8, No. 3, December 2020
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2020.v08.i03.p04

Abstract

Tingginya pertumbuhan penduduk di Indonesia menyebabkan kepemilikan kendaraan bermotor pribadi semakin tinggi yang mempengaruhi meningkatnya kemacetan dan juga kecelakaan lalu lintas. Peramalan angka kecelelakan lalu lintas dilakukan pada penelitian ini sebagai salah satu upaya yang dapat dimanfaatkan sebagai dasar tindakan antisipasi terkait peningkatan angka kecelelakaan lalu lintas. Penelitian ini bertujuan untuk meramalkan kecelakaan lalu lintas menurut akibatnya menggunakan Xtreme Gradient Boosting (XGBoost) dengan bahasa pemrograman Python. Data yang digunakan dalam penelitian ini yaitu data dari Badan Pusat Statistik Provinsi Bali dengan periode dari Tahun 1996 sampai dengan Tahun 2019 dalam selang waktu tahunan. Hasil peramalan diukur menggunakan RMSE (Root Mean Square Error). Penerapan XGBoost untuk meramalkan data kecelakaan lalu lintas menurut akibatnya, menunjukkan model XGBoost memiliki performa yang sangat baik pada dua kategori yaitu kategori jumlah orang meninggal akibat kecelakaan dengan nilai RMSE 4,92 dan jumlah orang yang mengalami luka berat dengan nilai RMSE 4,11. Nilai RMSE model XGBoost untuk kategori jumlah kejadian kecelakaan lalu lintas yaitu sebesar 21,69 dan kategori orang yang mengalami luka ringan akibat kecelakaan yaitu sebesar 77,24.
Geographic Information System for Mapping and Complaint of Damaged Roads Widiana Putra Winarta; I Nyoman Piarsa; Ni Made Ika Marini Mandenni
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 9 No 3 (2021): Vol. 9, No. 3, December 2021
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2021.v09.i03.p05

Abstract

Indonesia is a massive archipelago of 1.919.400 km², containing roads that span at 542.000 km across various terrain conditions. This diverse geographic environment is a challenge to road constructions and repairs across the country, which has lead to disruption in public service and traffic accidents each year. We propose the Geographic Information System for Mapping and Complaint of Damaged Roads, a solution which can provide users a digital interface to report damaged roads to the transportation department in their area. This research uses Google Maps API to digitize and make a complaint about damaged roads. The result of this research is an android application for the users and a website application for the road managers. The android application is used by the users to make complaints of damaged roads. The web application is used by road managers to draw the road on Google Maps using polyline feature. With this our goal is to systematize the handling of damaged roads information, leading to faster service times and hopefully help reduce the level of traffic accidents in Indonesia. Keywords: Complaint, Damaged road, Geographic Information System, Google Maps, Road digitization.
Cloud-Based Online Tutoring Information System (BIMBELOL) I Gede Sumiarta Adinata; I Made Sukarsa; Dwi Putra Githa
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol. 9, No. 2, August 2021
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2021.v09.i02.p04

Abstract

Tutoring is a guidance activity in terms of finding appropriate learning methods and overcoming learning difficulties. Generally, every tutoring process is carried out at the tutoring place. The general tutoring process can have a less effective and efficient impact during extreme weather and pandemics. Extreme weather and pandemic have resulted in delays to the end of the tutoring process. Problems that arise can be overcome by designing a system that can make the tutoring process more efficient and effective during extreme weather and pandemics. A cloud-based online tutoring information system (BIMBELOL) is a system that can help any tutoring process to be more efficient and effective. The use of cloud technology in making the system can help every tutoring process be carried out online. Testing of 40 respondents and black-box testing carried out on the system shows that each tutoring process has been successfully implemented.
Sistem Monitoring dan Kontrol Berbasis Internet of Things untuk Penghematan Listrik pada Food and Beverage Ali Khumaidi
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol. 8, No. 3, December 2020
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2020.v08.i03.p02

Abstract

Departemen Food and Beverage (F&B) menjadi salah satu sumber penghasilan dari perusahaan. F&B menggunakan berbagai peralatan dan mesin dengan daya yang cukup besar untuk mendukung operasional, jika pemakaiannya tidak dikendalikan maka menyebabakan biaya listrik yang tinggi. Penggunaan peralatan dan mesin harus rutin dikontrol, jika kondisi peralatan tidak normal dapat mengakibatkan pemakaian listrik menjadi berlebih hingga kerusakan. Dalam mengendalikan pemakaian listrik dibutuhkan sebuah sistem yang dapat memonitor dan mengendalikan penggunaan energi listrik. Beberapa publikasi sebelumnya sudah ada yang meneliti terkait monitoring penggunaan listrik berbasis internet of things namun belum ada yang meneliti terkait monitoring dan kontrol peralatan dan mesin pada F&B. Pada penelitian ini untuk mengontrol dan mengendalikan peralatan digunakan arduino mega2560, ethernet shield, sensor suhu, sensor magnet, sensor arus ACS712, fusethermo, dan modul wifi. Hasil pengujian prototipe bahwa sistem yang dibangun bekerja dengan baik dan mampu memonitoring penggunaan energi listrik serta dapat mengendalikan peralatan dari jarak jauh serta pengontrolan segala bentuk kerusakan yang disebabkan kelalaian perawatan terhadap peralatan dapat diminimalisir dengan adanya sensor-sensor yang terpasang pada tiap alat.
Implementasi Algoritma PRNG pada Aplikasi Port Knocking Sebagai Perlindungan Server Made Andika Verdiana; I Made Agus Dwi Suarjaya; Anak Agung Ketut Agung Cahyawan Wiranatha
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol. 8, No. 3, December 2020
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2020.v08.i03.p08

Abstract

Keamanan jaringan harus dipertimbangkan dan dilindungi dengan baik. Masalah yang terjadi jika keamanan jaringan tidak terlindungi akan menyebabkan kerusakan sistem server dan dapat terjadinya akses tidak sah pada sistem server. Penelitian ini bertujuan untuk melakukan proses autentikasi jaringan antara komputer klien dengan komputer server dalam memvalidasi klien yang akan terhubung dengan sistem server. Penelitian dilakukan dengan metode autentikasi port knocking yang telah diimplementasikan algoritma PRNG (pseudo random number generator) dengan acuan seed waktu sistem. Hasil dari penelitian ini yaitu autentikasi port knocking dilakukan menggunakan hasil random sequence port yang berbeda sesuai dengan waktu sistem saat random number dibangkitkan guna untuk memperkuat autentikasi dalam memvalidasi klien yang akan terhubung dengan sistem server.
Game Development of “Prokes” to Socialize the Prevention of Covid-19 Dewa Ayu Indah Cahya Dewi; Ngakan Putu Darma Yasa
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol. 9, No. 2, August 2021
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2021.v09.i02.p08

Abstract

The level of awareness of the Indonesian people to orderly and comply with the implementation of health protocols is still very low. Special touch to young people is needed in socializing health protocols and new normal life. Game of “Prokes” is expected as a means for socialization of covid-19 prevention. The proposed method is agile method that is combined using shuffle random algorithm to randomize question in quiz of this game. The blackbox result was 100% functionality of the game has run well. There was a significant difference between user knowledge before and after playing the game of “Prokes” as indicated by t value of 2.297, t table value of 2.004, and the critical value of ? = 0.05. The proposed method had an GEQ result of 3.04. Therefore, the game feasible as a means of socialization in prevention covid-19 using health protocols and new normal for the young generations.
Implementing kNearest Neighbor Methods to Predict Car Prices Deshiwa Budilaksana; I Made Sukarsa; Anak Agung Ketut Agung Cahyawan Wiranatha
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol. 9, No. 1, April 2021
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2021.v09.i01.p06

Abstract

The demand for automotive in Indonesia has never subsided, considering that the human need for transportation greatly affects people's daily lives. Various attempts are made by manufacturers to produce cars of a quality that is comparable to the costs incurred and following market demand. Prediction is a process that can be done to achieve this goal. One of the prediction methods that can be used in this case is the kNearest Neighbor. The prediction process consists of a preprocessing stage that cleans and filters unnecessary variables, followed by a variable multicollinearity test stage with Variance Inflation Factor (VIF). The multicollinearity test found 4 variables that had a specific influence in predicting the VIF value of these variables, respectively 2.22, 2.08, 1.53, 1.10 for Horse Power, Car Width, Highend, and, Hatchback respectively. The four variables of the VIF test results have a positive correlation with the price variable as the dependent variable. The prediction model is made using 4 variables selected based on the VIF test, to determine the accuracy of the method used, the Linear Regression model and, the kNearest Neighbor through the validation test with Mean Absolute Error (MAE) and R2. The kNearest Neighbor method produces an MAE test of 0.06 and R2 results are 0.843. This can be concluded if the overall kNearest Neighbor method has qualified performance in making predictions with continuous value variables or in other words using the concept of regression.
Design and Development of Android-Based Indoor Wi-Fi Site Survey Application Ida Bagus Kade Taruna; I Made Agus Dwi Suarjaya; I Putu Agus Eka Pratama
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 9 No 3 (2021): Vol. 9, No. 3, December 2021
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2021.v09.i03.p08

Abstract

In the indoor wireless network technology, it is found that there are many disturbances such as interference with LOS (Line of Sight), improper access point position, and low signal strength. To overcome these disturbances, wireless network optimization can be done by conducting a survey or analysis of the coverage area and quality of service. This analysis can be done by using an application, however available applications are mostly desktop applications, which makes surveying the indoor wireless network less efficient. This study discusses the design and development of mobile applications that can be used to analyze Wi-Fi networks in an indoor environment which can provide information about the coverage area of ??a Wi-Fi network. The application development uses the PDR (Pedestrian Dead Reckoning) RSSI (Receive Signal Strength Indicator) classification method. Application testing was carried out using two different scenarios, where in the first scenario the Wi-Fi network source was placed in the living room area, while in the second scenario the Wi-Fi network source was placed in the bedroom area 2. The result of the test carried out is the application can provide information regarding the coverage area of the signal from the two positions of different Wi-Fi network sources in a heatmap format that can be easily understood and can be used to optimize Wi-Fi networks in the future. Keywords : Android Application, Wireless Network, Sensor, Network Survey
A Comparison Between Backpropagation, Holt-Winter, and Polynomial Regression Methods in Forecasting Dog Bites Cases in Bali Gede Eridya Bayu; I Ketut Gede Darma Putra; Ni Kadek Dwi Rusjayanthi
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 9 No 3 (2021): Vol. 9, No. 3, December 2021
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2021.v09.i03.p06

Abstract

Rabies is a zoonotic disease that is usually transmitted to humans through animal bites. It can cause severe damage to the central nervous system and is generally fatal. Dog bite cases are considered the leading cause of rabies transmission in Bali. The government's preventive action is expected to reduce the problem of increasing the number of dog bite cases so that it does not spread quickly and cause casualties. Data mining is an attempt to extract knowledge from a set of data. The use of data mining in this study is to forecast the number of dog bite cases in Bali. Forecasting predicts what will happen in the future based on relevant data in the past and placing it in a mathematical model. Data mining methods used in forecasting dog bite cases are backpropagation, holt-winters, polynomial regression methods. This forecasting aims to help the government predict dog bite cases in the coming period to prepare appropriate countermeasures. Forecasting is done using data on bite cases every month in Bali province for five years, from 2015 to 2019. Dog bite case data is divided into four datasets for each attribute, namely data on the number of dog bite cases, the number of vaccinations, the number of male deaths, the number of female deaths. The four datasets are divided into training data and testing data to share 80% training data and 20% testing data. The results obtained are that the backpropagation method is better at predicting dog bite case data with an average MAPE error rate of 11.59%, while the holt-winters method has an average MAPE error rate of 16.05%, and the polynomial regression method has an average MAPE error rate of 19.91% Keywords : Dog Bites, Rabies, Forecasting, Backpropagation, Holt-Winter, Polynomial Regression
Reengineering of Manufacturing Business Process Utilising the Manufacturing Module of an ERP Application I Putu Agastya Harta Pratama; I Made Sukarsa; Gusti Agung Ayu Putri
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 9 No 3 (2021): Vol. 9, No. 3, December 2021
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2021.v09.i03.p07

Abstract

The significant change in the consumption pattern of Indonesia’s modernising society––further intensified by the Indonesian Government’s plan to push towards the era of the Industrial Revolution 4.0, has fostered the need for manufacturing companies to create newly automated processes and make the transition to become a digitalised business entity. Enterprise Resource Planning is a software that enables the creation of integration and automation of business processes between various departments within a company, thus creating an effective business strategy. The data that has been acquired from research at a poultry processing company are then being mapped into the ERP software of Odoo V12.0, therefore creating new sets of re-engineered business processes. There are seven newly proposed reengineering business processes––in which only concentrate on the production and technical department within the particular company, by utilising the manufacturing and maintenance modules. The re-engineered business processes are assessed using the Technology Acceptance Model theory, to measure its usability and practicality, which generates the score of Likert’s interpretation above the accepted standard of 1340 and 1227, for both the manufacturing and maintenance modules respectively. Keywords: Business Process Reengineering, Enterprise Resource Planning, Manufacturing Process, Odoo, Technology Acceptance Model.

Page 22 of 28 | Total Record : 280

 20   21   22   23   24 

Filter by Year

2013 2025


Reset
Filter By Issues
All Issue Vol 13 No 1 (2025): Vol. 13, No. 1, April 2025 Vol 12 No 3 (2024): Vol. 12, No. 3, December 2024 Vol 12 No 2 (2024): Vol. 12, No. 2, August 2024 Vol 12 No 1 (2024): Vol. 12, No. 1, April 2024 Vol 11 No 3 (2023): Vol. 11, No. 3, December 2023 Vol 11 No 2 (2023): Vol. 11, No. 2, August 2023 Vol 11 No 1 (2023): Vol. 11, No. 1, April 2023 Vol 10 No 3 (2022): Vol. 10, No. 3, December 2022 Vol 10 No 2 (2022): Vol. 10, No. 2, August 2022 Vol 10 No 1 (2022): Vol. 10, No. 1, April 2022 Vol 9 No 3 (2021): Vol. 9, No. 3, December 2021 Vol. 9, No. 2, August 2021 Vol. 9, No. 1, April 2021 Vol. 8, No. 3, December 2020 Vol. 8, No. 2, August 2020 Vol. 8, No. 1, April 2020 Vol. 7, No. 3, Desember 2019 Vol. 7, No. 2, Agustus 2019 Vol. 7, No. 1, April 2019 Vol. 6, No. 3, Desember 2018 Vol. 6, No. 2, Agustus 2018 Vol. 6, No. 1, April 2018 Vol. 5, No. 3, Desember 2017 Vol. 5, No. 2 Agustus 2017 Vol. 5, No. 1 April 2017 Vol. 4, No. 3 Desember 2016 Vol. 4, No. 2 Agustus 2016 Vol. 4, No. 1, April 2016 Vol. 3, No. 3, Desember 2015 Vol. 3, No. 2, Agustus 2015 Vol. 3, No. 1, April 2015 Vol. 2 No. 3, Desember 2014 Vol. 2, No. 2, Agustus 2014 Vol. 2, No. 1, April 2014 Vol. 1, No. 2, Agustus 2013 Vol. 1 No. 1, April 2013 More Issue