Article Per Year (5 Year)
p-Index From 2021 - 2026
4.699
P-Index
This Author published in this journals
All Journal Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Jurnal Teknik Komputer AMIK BSI JURNAL MEDIA INFORMATIKA BUDIDARMA JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Sisfokom (Sistem Informasi dan Komputer) JSiI (Jurnal Sistem Informasi) Krea-TIF: Jurnal Teknik Informatika IJISTECH (International Journal Of Information System & Technology) Jurnal ICT : Information Communication & Technology Health Sciences and Pharmacy Journal Building of Informatics, Technology and Science Madani : Indonesian Journal of Civil Society Jurnal Pengabdian kepada Masyarakat Nusantara Teknika IJISTECH Journal of Soft Computing Exploration Batara Wisnu : Indonesian Journal of Community Services The Indonesian Journal of Computer Science Research SmartComp The Indonesian Journal of Computer Science
Acihmah Sidauruk
Universitas AMIKOM Yogyakarta
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Library & Information Science Medicine & Pharmacology Nursing Public Health Social Sciences

Published : 32 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 32 Documents
Search

 1   2   3   4 
Prediksi Curah Hujan Menggunakan Algoritma Regresi Linear Berganda Afifah Nur Latifah; Acihmah Sidauruk; Mulia Sulistiyono; Budy Satria; Muhammad Tofa Nurcholis
Jurnal ICT: Information Communication & Technology Vol. 23 No. 1 (2023): JICT-IKMI, Juli 2023
Publisher : LPPM STMIK IKMI Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Abstrak- Negara Indonesia merupakan wilayah tropis dengan perubahan cuaca yang selalu berubah. Perlu dilakukan sebuah penelitian tentang prediksi cuaca sebagai pengambilan keputusan terhadap informasi cuaca yang akan terjadi dikemudian hari. Curah hujan merupakan salah satu factor yang menyebabkan perubahan cuaca di suatu wilayah. Penelitian ini dilakukan terhadap iklim di wilayah Yogyakarta yang berupa pegunungan dan dataran rendah menyebabkan terjadinya perbedaan curah hujan. Variable yang dijadikan untuk melakukan prediksi adalah beberapa parameter yang berpengaruh terhadap curah hujan yaitu suhu, kelembaban, kecepatan angina dan lama penyinaran matahari. 5 variabel tersebut diolah melalui data yang diperoleh kemudian dilakukan penelitian dan perbandingan terhadap data yang sebelumnya. Penelitian dilakukan menggunakan algoritma regresi linear berganda dengan menjadikan data curah hujan sebagai variabel dependen serta parameter lain sebagai variabel independen. Penelitian ini menggunakan data iklim yogyakarta tahun 2010-2022 Hasil yang diperoleh yaitu R2 score sebesar 12,99%. Prediksi curah hujan pada diperoleh sebesar 14.41778516. Kemudian evaluasi RMSE menghasilkan penympangan antara prediksi curah hujan dengan curah hujan sebenarnya sebesar 14.78316110508722.
THE DECISION MAKING METHOD FOR AWARDING SCHOLARSHIPS TO STUDENTS USING COMPOSITE PERFORMANCE INDEX ALGORITHM Budy Satria; Acihmah Sidauruk; Muhammad Tofa Nurcholis; Raditya Wardhana; Bister Purba
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 8 No. 2 (2023): JITK Issue February 2023
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (387.268 KB) | DOI: 10.33480/jitk.v8i2.3335

Abstract

Higher education in Indonesia has several programs to help reduce the burden on students, one of which is through a scholarship program. Scholarships given can be obtained with the terms and conditions that apply at each university. Mitra Gama Institute of Technology is one of the private universities in the province of Riau which always runs a scholarship aid program. The problem that has been happening so far is that the procedures carried out are still using a document checking system without involving a weighting system and the right criteria and time constraints have always been an obstacle in determining scholarship recipients. This research was conducted as a solution to create an innovation in the form of making a computerized decision support system using criteria and weight values ​​so that scholarship recipients are on target. Composite performance index is the method used in this study. The purpose of this research is to create a decision support system for the selection of scholarship recipients to be more systematic and time efficient in the process. There are 5 alternatives used and 4 criteria, namely parents' income, GPA, electricity consumption and semester. The results of the research carried out were obtained the 5 highest composite index values, namely MHS4 with a value of 200.00, MHS1 with a value of 134.14, MHS5 with a value of 120.00, MHS3 with a value of 87.00 and MHS2 with a value of 85.71.
RAINFALL PREDICTION USING MULTIPLE LINEAR REGRESSION ALGORITHM Mulia Sulistiyono; Acihmah Sidauruk; Budy Satria; Raditya Wardhana
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 9 No. 1 (2023): JITK Issue August 2023
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v9i1.4203

Abstract

Indonesia is a tropical region with ever-changing weather changes. It is necessary to conduct a research on weather prediction as a decision making regarding weather information that will occur in the future. Rainfall is one of the factors that cause changes in weather in an area. This research was conducted on the climate in the Yogyakarta region in the form of mountains and lowlands causing differences in rainfall. The variables that are used to make predictions are several parameters that affect rainfall, namely temperature, humidity, wind speed and duration of solar radiation. These 5 variables are processed through the data obtained then carried out research and comparisons with the previous data. Multiple linear regression is the algorithm used. This algorithm is one of the machine learning techniques by making rainfall data as the dependent variable and other parameters as independent variables. This study uses Yogyakarta City, Central Java climate data for 2010-2020. The results obtained are an R2 score of 12.99%. Prediction of rainfall is obtained at 14.41778516. Then the RMSE evaluation resulted in a deviation between predicted rainfall and actual rainfall of 14.78316110508722. Based on these results, it shows that there is light rain because it is in the intensity category of 5 mm – 20 mm/day.
Upaya Peningkatan Manajemen Proyek Pada CV Nabila Zafira Mahalia Melalui Aplikasi Clickup Norhikmah Norhikmah; Wiji Nurastuti; Rumini Rumini; Acihmah Sidauruk
Madani : Indonesian Journal of Civil Society Vol. 5 No. 2 (2023): Madani, Agustus 2023
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/madani.v5i2.1889

Abstract

At CV. Nabila Zafira Mahali (Nazma) the daily recap of the work of the creative team still uses Google Excel which is prone to data manipulation by people who are irresponsible and don't have a good history of data records, if someone makes a mistake. Recap for monthly reports takes quite a long time, if there is an error in awarding honorarium or there is data that is not appropriate then it is not immediately known by management, the creative team's daily work report has an indirect relationship to the finance department, or the part that regulates awarding honorarium, if the data entered is unclear or inappropriate, there will be a delay in awarding honorarium. Therefore training is needed in using the clickup application which can help the creative team's daily work recap. The process of implementing the training stages begins with an interview with director Nazma and documentation of the required data, followed by determining and creating training materials, and finally, continuing online training using Google Meet, with material using the click-up application, one of the template features, namely CRM (company management profile) in the template there is todo (work list), in progress (under construction), Ready (ready) and complete (finished) features, so that management can monitor the work of the creative team more clearly. In the results of the training evaluation, a score of 70% was obtained on the value of the questions on the benefits of training and project management control.
Expert System for Pineapple Fruit Diseases Using Bayes' Theorem Ade Pujianto; Raditya Wardhana; Acihmah Sidauruk; Ria Andriani
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6432

Abstract

Expert systems are a branch of artificial intelligence that utilizes specialized knowledge to solve problems at the level of an expert. In the field of agriculture, expert systems are used for diagnosing plant diseases. In this research, an expert system was designed and developed with the aim of assisting pineapple farmers in determining the diagnosis of diseases based on the main symptoms observed in the plants. To overcome knowledge uncertainty, the Bayesian probability method was employed in this expert system. The diagnostic process begins with a consultation session, where the system asks relevant questions to the farmers based on the observed symptoms in the pineapple plants. The ultimate outcome of this study is an expert system capable of diagnosing diseases in pineapple plants and providing effective solutions with an accuracy rate of 93.34%. Additionally, the system provides probability values for each diagnosed disease, indicating the system's confidence level in the identified diseases, and offers treatment recommendations or solutions to the pineapple farmers.
PELATIHAN PENGGUNAAN APLIKASI PENGARSIPAN SURAT PERTANAHAN PADA DINAS PERTAHANAN DAN TATA RUANG DAERAH ISTEMEWA YOGYAKARTA Elsafira Budi Dewantari; Trisa Ayunanda Saputri; Shofi Putri Ekadewi; Rabiatul Adawiyah; Yuli Astuti; Acihmah Sidauruk; Erni Seniwati
Batara Wisnu : Indonesian Journal of Community Services Vol. 3 No. 3 (2023): Batara Wisnu | September - Desember 2023
Publisher : Gapenas Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53363/bw.v3i3.218

Abstract

A website-based archiving information system is an application that allows users to manage digital documents in a structured and easily accessible manner via the internet. In today's digital era, the use of digital documents is increasing and requires a filing system that can store, manage, and provide document access easily and quickly. Therefore, the use of a website-based archiving information system is becoming increasingly popular because it makes it easy to manage digital documents. A web-based archiving information system consists of several features that allow users to manage documents easily. These features include document search, document upload, and document categories. In the document search feature, users can easily search for documents by entering specific keywords. The document upload feature allows users to upload documents to the system easily and quickly. The document categories feature allows users to group documents according to specific types or categories. The design of this archiving information system website is created using Laravel. The result of this research is the Surat Dinas Archiving Information System at the Land and Regional Planning Agency of the Special Region of Yogyakarta.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN SUPPLIER KAIN DENGAN METODE MOORA Proboningrum, Sandyea; Acihmah Sidauruk
Jurnal Sistem Informasi Vol 8 No 1 (2021)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v8i1.3073

Abstract

Abstrak - Sistem pendukung merupakan cara yang dapat digunakan untuk membantu seseorang maupun perusahaan dalam mengambil keputusan. Salah satunya yaitu pengambilan keputusan dalam pemilihan supplier kain. Pemilihan supplier merupakan salah satu bagian terpenting dalam suatu usaha. Untuk mendapatkan hasil yang maksimal, dibutuhkan supplier yang terbaik dan berkualitas. Karena banyaknya supplier kain, Yani kain kesulitan dalam memilih supplier dengan kelebihannya masing-masing. Metode yang digunakan dalam pengambilan keputusan supplier kain pada Yani kain adalah dengan menggunakan metode Multi-Objective Optimazion on the basis of Ratio Analysisi (MOORA). Pada penelitian ini terdapat 5 kriteria yang ada, yaitu desain, harga, kualitas, pengiriman dan pelayanan. Setelah dilakukan perhitungan terhadap 30 sample data supplier, dilakukan pengujian menggunakan confusion matrix dengan hasil akurasi sebesar 80%. Untuk implementasi aplikasi dibangun berbasis web. Kata kunci : MOORA, Sistem Pendukung Keputusan, Supplier, Web, Confusion Matrix.
Object Recognition with SSD MobileNet Pre-Trained Model in the Cashier Application Burhanudin, Nazil Ilham; Laksito, Arif Dwi; Sidauruk, Acihmah; Yudianto, Muhammad Resa Arif; Rahmi, Alfie Nur
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 12, No 2 (2023): JULI
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v12i2.1659

Abstract

Object recognition is a type of image processing technique that is frequently employed in current applications such as facial identification, vehicle detection, and automated cashiers. One issue with barcode and RFID cashier apps is that they cannot scan several products at the same time. The cashier application employing object identification using picture images is believed to be able to distinguish more than one object in order to speed up the transaction process. The usage of SSD pre-trained models with MobileNet architecture to detect items in automatic cashier applications is discussed in this paper. This study put the model to the test on three types of soft drink objects: coca-cola, floridina, and good day. A smartphone camera was used to collect the data, which totaled 203 images. The findings indicated that the product object identification method was 82.9% accurate, 97.5% precise, and 84.7% recall. The object recognition process takes between 365 and 827 milliseconds, with an average time of 695 milliseconds (0.69 seconds).
Clustering Performance Between K-means and Bisecting K-means for Students Interest in Senior High School Seniwati, Erni; Sidauruk, Acihmah; Haryoko, Haryoko; Lukman, Achmad
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): June 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3624

Abstract

The interest of high school students is an important thing to do to see the talents of each student based on the academic scores obtained in the first and second semesters. There are two majors of interest in this case study, namely natural and social studies with criteria for natural studies scores including mathematics, chemistry, biology and physics. Meanwhile, the social studies criteria include history, economics, geography and sociology. This research propose comparing of clustering time and accuracy based on manual data from school as a reference of clustering in SMAN 1 Wonosari for 2011/2012 academic year using two clustering methods namely K-means and Bisecting K-Means. The results of this research compare to manual results interest from class teacher, so this work can demonstrate the run time comparison and accuracy of this study. The accuracy result shows 87.5% for both methods but different run times. For bisecting k-means got 0.0229849 seconds to complete the clustering process faster than k-means only got 0.0929448 seconds
Robusta Coffee Plant Disease Identification using Dempster Shafer Method in Expert Systems Sidauruk, Acihmah; Miftakhurrokhmat, Miftakhurrokhmat; Pujianto, Ade; Salmuasih, Salmuasih
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6272

Abstract

Robusta coffee is one type of coffee that can grow well in Indonesia. Robusta coffee has 2.2% more caffeine and less sugar than Arabica coffee. This coffee may be a more interesting coffee variety from different levels of taste and thickness. In addition, Robusta coffee is very accommodating to the economy of several coffee-producing countries around the world, including Indonesia. A number of factors, especially pests and diseases, can reduce the productivity and quality of coffee plants. This is also confirmed by coffee experts who conducted research on pests and diseases in Robusta coffee plants. This study aims to develop an expert-based system that can identify problems and diseases in Robusta coffee plants using the Dempster Shafer method, and developed in a web-based platform. From the data collected from literature studies, dialogue with farmers, and consultation with an expert, 13 types of pests and diseases were obtained, and 27 symptoms of the disease. The results of this study are the development of a web-based expert system that can diagnose pests or diseases from several symptom inputs filled in by users or coffee farmers. The results of the trial of 13 test cases on the diagnosis of pests and diseases of Robusta coffee plants obtained an average accuracy value of 94%. This shows that this expert system can analyze the types of pests or diseases in Robusta coffee plants very well using the Dempster Shafer method.
Co-Authors Abdullah Abdullah Abdussalam Al Akbar Achmad Lukman, Achmad Ade Pujianto Ade Pujianto, Ade Afifah Nur Latifah Afrianto, Nurdi Afrig Aminuddin Alvy Chasanatussalma Anggita, Sharazita Dyah Arif Dwi Laksito Asro Nasiri Atik Nurmasani Bernadhed, Bernadhed Bister Purba Budy Satria Burhanudin, Nazil Ilham Danang Wijayanto Darmawan, Briga Dwi Rahayu Elsafira Budi Dewantari Erni Seniwati Febri Liantoni, Febri Gita Cahyani Gunawan, Puguh Hasta Hairul Januar Haryoko, Haryoko Hasyim, Jaka Wardana Hendra Kurniawan Ihsan, M. Arinal Ikmah Ikmah Ilyas Ferry Ceasar Widayanto Jamroni Jamroni Khoiruddin, Lukman Liga Mayola M. Arinal Ihsan Miftakhurrokhmat Miftakhurrokhmat, Miftakhurrokhmat Muhammad Iqbal Kusrachmansyah Muhammad Resa Arif Yudianto Mulia Sulistiyono Mulyatun, Sri Ningsih, Lidya Norhikmah Norhikmah Norhikmah, - Nurcholis, Muhammad Tofa Panggih Suseno Pirmansah, Imam Ainudin Proboningrum, Sandyea Rabiatul Adawiyah Raditya Wardhana Raditya Wardhana Rahmi, Alfie Nur Ria Andriani Riza Yulina Amry Robert Marco, Robert Rumini Rumini SAKINAH, PUTRI Salmuasih, Salmuasih Sarni Anggoro Satria, Dhimas Adi Seniwati, Erni Shofi Putri Ekadewi Sutarni, Sutarni Tri Widayanti Trisa Ayunanda Saputri Wardhana, Raditya Waskito, Bimo Wiji Nurastuti Wiji Nurastuti, Wiji Wiwi Widayani Wulandari, Evita Sekar Yoga Pristyanto Yudiyanto, Muhammad Resa Arif Yuli Astuti Yuli Astuti