Garuda - Garba Rujukan Digital

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All Journal JOIN (Jurnal Online Informatika) BAREKENG: Jurnal Ilmu Matematika dan Terapan JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Parameter: Journal of Statistics Jurnal Media Computer Science Dedikasi : Jurnal Pengabdian Lentera

Setiawan, Iman

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Author-ID : 1482208

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Articles

Digitalisasi UMKM BatikRin Meningkatkan Daya Saing melalui Konten Digital dan Seminar Pemasaran Digital Husein, Abid; Setiawan, Iman
Dedikasi: Jurnal Pengabdian Lentera Vol. 1 No. 09 (2024): Oktober 2024
Publisher : Lentera Ilmu Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59422/djpl.v1i09.543

Digitalisasi telah menjadi bagian integral dalam pengembangan UMKM untuk meningkatkan daya saing, terutama di era pasar digital. Program ini berfokus pada pengembangan konten digital (foto dan video) untuk produk UMKM Batikrin di Kabupaten Bekasi dan inisiasi seminar bertema "Strategi Efektif dalam Promosi dan Penjualan di Marketplace." Seminar bertujuan memberikan wawasan tentang pemanfaatan marketplace sebagai sarana promosi dan penjualan. Melalui pendekatan pelatihan, pendampingan, dan diskusi interaktif, kegiatan ini meningkatkan keterampilan pelaku UMKM dalam pemasaran digital. Hasil menunjukkan adanya peningkatan pemahaman peserta dan dampak positif pada strategi pemasaran digital mereka.

Comparative Study of MySQL and MongoDB Performance on Node.js REST API Using Chinook Database Setiawan, Iman
Jurnal Media Computer Science Vol 4 No 2 (2025): Juli
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v4i2.8870

Kebutuhan akan sistem manajemen basis data (Database Management System) yang efisien dan optimal semakin penting, terutama dalam pengembangan aplikasi berbasis REST API. Penelitian ini bertujuan untuk mengevaluasi dan membandingkan performa dua jenis DBMS yang umum digunakan, yaitu MySQL (relasional) dan MongoDB (non-relasional), ketika diimplementasikan dalam REST API berbasis Node.js. Pengujian dilakukan di lingkungan server nyata untuk mencerminkan kondisi operasional sesungguhnya, menggunakan alat Apache JMeter dengan empat parameter utama, yaitu processed requests, response time, throughput, dan error rate. Data yang digunakan bersumber dari Chinook Database yang telah diperbanyak hingga mencapai 10.000 entri, dan diuji dengan beban pengguna virtual sebanyak 50 dan 100 pengguna selama 120 detik, dengan skenario yang telah diatur. Hasil penelitian menunjukkan bahwa MySQL unggul pada hampir seluruh parameter, dengan processed requests tertinggi (64.098 permintaan), response time terendah (135 ms), dan throughput terbesar (532 permintaan/detik), serta tanpa error. Sebaliknya, MongoDB mencerminkan karakteristik arsitektur non-relasional yang lebih dinamis, namun menunjukkan performa yang lebih rendah pada skenario pengujian ini. Kesimpulan dari penelitian ini menyatakan bahwa pemilihan DBMS harus disesuaikan dengan kebutuhan aplikasi, di mana MySQL lebih cocok untuk pengolahan data yang terstruktur dan konsisten, sedangkan MongoDB lebih sesuai untuk data semi-terstruktur atau tidak terstruktur yang berkembang secara dinamis.

Intervention Model Analysis The Number of Domestic Passengers at Sultan Hasanuddin Airports Andi Ferosita Sustrisno; Rais; Setiawan, Iman
Parameter: Journal of Statistics Vol. 1 No. 1 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Domestic passengers are objects whose travel / flight transportation services only cover the domestic area. The increase or decrease in the number of domestic passengers is usually influenced by the occurrence of intervention. This research uses the intervention analysis. Intervention analysis is the time series analysis to model data that is determined by the presence of an intervention. Intervention analysis is one of the time series analysis to model data that are affected by the occurrence of a particular event in a short period of time, such as accidents, natural disasters, and promotions. This research is used to establish intervention model with pulse function of passengers of domestic Sultan Hasanuddin Airport. The result of the research were obtained the model Seasonal ARIMA .There were 6 intervention times during 2006 - 2018, by entering the intervention order b = 0, s = 0, and r = 1 based on the smallest AIC value is -303,66 with MAPE value is 6,1023.

EXPERT SYSTEM DESIGN TO DIAGNOSE PESTS AND DISEASES ON LOCAL RED ONION PALU USING BAYESIAN METHOD Junaidi, Junaidi; Fadjryani, Fadjryani; Setiawan, Iman; Batara, Mohammad; Hendra, Syaiful; Ismail, Nurmasita
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Bayesian is a method that can be used to overcome the uncertainty of a situation or data. The information obtained must be continuously updated so that it can foster trust as a result of the uncertainty of those conditions. In this study, the application of the Bayesian method to detect early symptoms of diseases on local red onion Palu plants based on the symptoms that appear will be carried out. Information about pests and diseases that attack local red onion Palu is needed to help farmers. As a result, they can deal with attacked diseases quickly and precisely. This is crucial conducted by considering that this plant is one of the mainstay commodities for farmers in Central Sulawesi Province whose production must continue to be increased. Pests and diseases can be diagnosed through visible symptoms.The sample is local red onion Palu that affected by pests and disesases which planted in the AIAT of Central Sulawesi by experiment. As a result, through these symptoms an expert system can then be created to do a diagnosis. An expert system is a system that seeks to adopt human knowledge to a computer that is built to solve problems like an expert. The created expert system to diagnose diseases uses the Bayesian method to calculate the probability of an event occurring based on the obtained results from observations and experts. An expert system for diagnosis of pests and diseases is built on a web-based basis. This expert system has features and functions including the diagnosis of pests and diseases of the observed plants, viewing the results of the diagnosis and printing the results of the diagnosis. In addition, users can view information on pests and other diseases that attack plants. From the results of system testing that conducted by experts, this shows that the expert system is feasible to use to diagnose local red onion Palu plants which affected by pests and diseases with an accuracy point that has the largest percentage value.

Automatic Plant Watering System for Local Red Onion Palu using Arduino Setiawan, Iman; Junaidi, Junaidi; Fadjryani, Fadjryani; Amaliah, Fika Reski
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.813

Central Sulawesi Province in Indonesia has great potential for horticultural commodities, namely local red onion Palu. In the current climate change, local farmers are still watering plants in the conventional way. The automatic watering system simplifies the work of local farmers. This device uses a soil moisture sensor as a soil moisture detector and Arduino as a program brain. This study aims to determine the position of soil moisture sensor, the optimal length of watering time and analyze the quality of data stored. The experiment was carried out using a Completely Randomized Design (CRD). The position of the soil moisture sensor was analyzed by Profile Analysis. The optimal length of watering time was determined by Analysis of Variance (ANOVA) and Least Significant Difference (LSD). The quality of data stored was determined by a number of missing values and frequency of watering. The results showed that in soil planting media the position of soil moisture sensor had no significant effect, while in others planting media (water and combination of water and soil) the position of the sensor had a significant effect. The optimal watering time was 3 seconds. The stored data has low quality in terms of missing values and lack of consistency.

Internet of Things (IoT) for Soil Moisture Detection Using Time Series Model Setiawan, Iman; Junaidi, Junaidi; Fadjryani, Fadjryani; Amaliah, Fika Reski
JOIN (Jurnal Online Informatika) Vol 7 No 2 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i2.951

Technology in agriculture has been widely and massively applied. One of them is automation technology and the use of big data through the Internet of Things (IoT). The use of IoT allows a process to run automatically without human intervention. Extreme weather changes and narrow land use are one of the main problems in agriculture. The development of IoT devices has been widely developed regarding this subject. One of them is a soil moisture detection system. This study aims to build an IoT soil moisture detection system. The system will use a sensor as input which is then processed in a microcontroller device and the prediction results are sent to the IoT cloud platform. Prediction results are obtained using a time series model and then its performance is evaluated using RMSE. This model was chosen because the structure of the observed soil moisture data is based on time. The results of this study indicate that the soil moisture IoT system can work well. This is supported by the results of the prediction evaluation value of the RMSE = 1.175682x10-5 model which is very small.

Analisis Hasil Ujian Nasional Sekolah Menengah Kejuruan di Kota Makassar Menggunakan Linear Mixed Model Regression Setiawan, Iman; Pannu, Abdullah
Jambura Journal of Probability and Statistics Vol 5, No 1 (2024): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjps.v5i1.21287

Graduates of Vocational High Schools (SMK) in South Sulawesi Province, especially Makassar City, have a higher Open Unemployment Rate (TPT) than other levels of education. In fact, during the 2016-2020 period, various education management policies such as the revitalization of SMKs, the arrangement of study groups and the accreditation of SMK Education Units were held to encourage increased competence of graduates and the quality of SMK Education. The purpose of this study is to see how the pattern of National Examination (UN) results for SMKs in Makassar City in 2018-2020 and whether there are differences in the pattern of UN results for SMK accreditation. Because the analysis was carried out in multi years, the analysis was carried out using the Linear Mixed Model (LMM). Modeling is carried out in stages using 4 model schemes. This research shows that there has been a decrease in the SMK National Exam results in Makassar City in 2018-2020. In 2018, 2019 and 2020 each has an average of 52.26, 50.33 and 46.50. When viewed based on SMK accreditation, it can be seen that the decline in SMK National Examination results only occurs in SMKs that are not accredited A. This shows that policies related to increasing the competence of graduates and the quality of SMK education, especially in Makassar City, have no impact or even cannot be implemented properly for SMKs with accreditation other than A.

Co-Authors Amaliah, Fika Reski Andi Ferosita Sustrisno Batara, Mohammad Fadjryani, Fadjryani Husein, Abid Ismail, Nurmasita Junaidi Junaidi Pannu, Abdullah Rais Syaiful Hendra

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