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J I M P - Jurnal Informatika Merdeka Pasuruan
Published by Universitas Merdeka Pasuruan
ISSN : 25025716     EISSN : 25031945     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal Informatika Merdeka Pasuruan (JIMP) terbit 3 kali dalam satu tahun yaitu dibulan maret, agustus dan desember. Memuat tulisan ilmiah yang berhubungan dengan bidang teknologi informasi serta aplikasi teknik informatika. Jurnal JIMP terbitan berkala ini adalah hasil penelitian dari tugas akhir penelitian dari dalam dan luar Departemen Fakultas Teknologi Informasi Universitas Merdeka Pasuruan.
Arjuna Subject : -
Articles 146 Documents
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Pencarian Perangkat Alat Produksi Telekomunikasi Berbasis Webgis Menggunakan Metode Dijkstra Danang Tisma Amijaya; Anang Aris Widodo; Muhammad Misdram
J I M P - Jurnal Informatika Merdeka Pasuruan Vol 5, No 3 (2020): DESEMBER
Publisher : Fakultas Teknologi Informasi Universitas Merdeka Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37438/jimp.v5i3.318

Abstract

Optical Distribution Cabinet (ODC)  adalah   salah      satu   alat   produksi yang  dimiliki PT.Telkom untuk mendistribusikan internet kesetiap daerah demi pelanggan supaya dapat menikmati jaringan internet.  Hampir disetiap kota bahkan setiap pelosok pedalaman ada perangkat milik PT. Telekomunikasi Indonesia. Pada penelitian ini penulis mengimplementasikan metode Dijkstra yang digunakan untuk mencari rute terpendek. Algoritma yang cukup popular yang  ditemukan  oleh  Edsger  Wybe  Dijkstra.  Dijkstra  akan  berperan  dalam  menentukan  rute terpendek  menuju  ke perangkat yang lokasinya sudah di dapatkan dari PT.Telkom Pasuruan. Djikstra merupakan salah satu varian bentuk algoritma popular dalam pemecahan persoalan terkait masalah optimasi pencarian lintasan terpendek sebuah lintasan yang mempunyai panjang minimum dari verteks a ke j dalam graph berbobot, bobot tersebut adalah bilangan positif jadi tidak dapat dilalui oleh node negatif. Namun jika terjadi demikian, maka penyelesaian yang diberikan adalah infiniti (Tak Hingga). Pada algoritma Dijkstra, node digunakan karena algoritma Dijkstra menggunakan graph berarah untuk penentuan rute listasan terpendek. Dari hasil penelitian yang telah di lakukan   penulis dapat mengambil kesimpulan menerapkan metode dijkstra dilakukan pada titik (A) yaitu lokasi awal dengan tujuan titik (J). kemudian didapakan beberapa pilihan rute yang yang berjumlah 4 rute dengan satuan Kilometer. untuk rute pertama mendapatkan hasil (0,67),   kedua (0,7),   ketiga (0,9), keempat  (0,69).  rute  yang diambil  berdasarkan  rute  yang  memiliki  nilai  paling  kecil  yaitu  rute  pertama  (0,67). Kemudian dapat disimpulkan bahwa rute pertama adalah rute terpendekk untuk menuju ke tujuan (J).Kata kunci : Dijkstra, Edsger Wybe Dijkstra, ODC,  rute terpendek
APLIKASI PENCARIAN BAHAN PUSTAKA DI PERPUSTAKAAN MENGGUNAKAN METODE VECTOR SPACE MODEL Syaiful Bahri
J I M P - Jurnal Informatika Merdeka Pasuruan Vol 5, No 2 (2020): AGUSTUS
Publisher : Fakultas Teknologi Informasi Universitas Merdeka Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37438/jimp.v5i2.265

Abstract

ABSTRAKBahan pustaka dapat ditemukan dengan melakukan pencarian secara manual, namun hal itu selain kemungkinan hasil yang relevan terlewatkan dan cara tersebut juga tidak efisien. Mahasiswa juga kesulitan untuk mencari bahan Pustaka yang sesuai kebutuhannya. Sehingga mesin pencarian merupakan salah satu solusinyaPenelitian ini memanfaatkan metode Vektor Space Model  (VSM) dengan pembobotan TF/IDF pada 10 dokumen teratas sebagai cara perangkingan dokumen.. Terdapat 150 jurnal yang di input dengan menggunakan 4 Query terpilih dengan melakukan tiga tahap proses yaitu proses dokumen, proses Query dan yang terahir adalah proses penerapan metode Vektor Space Model  (VSM).Pada tahapan selanjutnya penelitian ini menghitung recall, Presisi dan Akurasi. Hasil penghitungan pada presisi dari masing-masing Query dengan nilai maksimal yaitu 100% dan nilai terendah 83%. Meskipun terdapat selisih namun tidak jauh. Nilai recall yang didapatkan dari semua Query adalah 100%. Kemudian pada hasil akurasi uji semua Query dengan nilai maksimal 100% dan 96% minimal. Hasil tersebut mengindikasikan bahwa system IR dengan metode VSM  efektif dan relevan untuk digunakan untuk pencarian bahan Pustaka, juga memiliki performa yang baik dan stabil sesuai dengan database uji coba
Sistem Pakar untuk Mendiagnosis Gangguan Tidur Menggunakan Metode Dempster Shafer Ivo Dwi Ananda; Rahmad Kurniawan; Novi Yanti; Fitri Insani
J I M P - Jurnal Informatika Merdeka Pasuruan Vol 6, No 3 (2021): DESEMBER
Publisher : Fakultas Teknologi Informasi Universitas Merdeka Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37438/jimp.v6i3.354

Abstract

Poor quality of sleep can cause psychological and physiological health problems. Estimated from 238,452 million people in Indonesia every year, about 67% elderly people reported having trouble sleeping. With a prevalence of 10% or about 28 million people suffering from sleep disorders. This makes Indonesia has the highest number of sleep disorders in Asia. The cases of sleep disorders increased during the Covid-19 pandemic by 23.87% in general public and by 36.53%  in medical personnel. This study aims to build a system that can diagnose sleep disorders like an expert. This study employed the Dempster Shafer method with 25 symptoms and four types of sleep disorders. The Dempster Shafer method is a commonly applied technique which is combining evidence in uncertainty cases. The experimental testing based on the validation of the results of the system diagnosis with expert diagnosis, the percentage of test accuracy is 90%. It can be concluded that the system potentially be used for early sleep disorder diagnosis.Keywords—expert system, dempster shafer, sleep disorders, sleep quality, uncertainty.
Pengelompokkan Judul Buku dengan Menggunakan Algoritma K-Nearest Neighbor (K-NN) dan Term Frequency – Inverse Document Frequency (TF-IDF) Fahrur Rozi; Farid Sukmana; Muhammad Nabil Adani
J I M P - Jurnal Informatika Merdeka Pasuruan Vol 6, No 3 (2021): DESEMBER
Publisher : Fakultas Teknologi Informasi Universitas Merdeka Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37438/jimp.v6i3.346

Abstract

Universitas Bhinneka PGRI Library has many collections in both printed and digital forms, which collections will increase over time. Thus the number of collections of books in the library will be more and more diverse, it will make the process of grouping existing collections difficult. The method used in this study is data mining with the K-Nearest Neighbors (K-NN) algorithm approach by combining TF-IDF as word frequency weighting. The stages of working on the K-NN method in this study went through 4 stages, namely: (1) text preprocessing by applying the tokenization method, case folding, stopword removal and stemming, (2) Word weighting using the TF-IDF method (3). Modeling the k value from a minimum limit of 1 to a maximum limit of 30. (4) Classification of data using the most optimal k value based on k value modeling. (5) discussion of classification results. Data collection techniques using literature studies and datasets. With this classification system, it is expected to provide useful information for users. In addition, this study also aims to implement the K-NN method by combining it with TF-IDF while at the same time knowing the accuracy of the sales prediction system. The results of this study are based on the highest accuracy value for the classification of book titles of 66.67% and the lowest accuracy value of 60% with an average accuracy value of 63.33%.Kata kunci— Data Mining, K-Nearest Neighbor (K-NN), TF-IDF
Prototipe Monitoring Daya Listrik dan Pengendalian Perangkat Elektronik Skala Industri Berbasis IoT di CV. Wellracom Nusantara Surabaya Samsul Huda; Trio Bekti Imansah; Elvianto Dwi Hartono
J I M P - Jurnal Informatika Merdeka Pasuruan Vol 6, No 3 (2021): DESEMBER
Publisher : Fakultas Teknologi Informasi Universitas Merdeka Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37438/jimp.v6i3.340

Abstract

The electricity bill accounts for a considerable amount of the full operating costs of industries. CV. Wellracom Nusantara has a lot of electronic equipment and industrial machines for production. Here, the company does not really know the electricity usage each month. They only know the significant amount of bill payments and over-budget when the electricity bill comes. Therefore, it is crucial for companies to accurately estimate future electricity costs as a strategy to reduce over-budget and uncontrolled costs. To overcome the problems, we propose a prototype monitoring system to make it more comfortable to monitor the use of electrical power in the company. This solution allows the electricity consumption from all devices to be monitored and controlled. The prototype monitors the use of electrical energy from each device and controls the electronic devices. The proposed solution adopts IoT technology using industrial-scale devices. This can monitor electricity consumption data from each device in real-time, record historical data from daily to monthly, send notifications, and control on/off devices. This prototype has an accuracy of 98% of the reading measurement results compared to the digital AVOmeter. Through a simple experiment using electric power loads of two light bulbs and two laptop chargers for 24 hours, we confirmed that the implemented prototype runs correctly.Keywords— electricity usage management, electricity bill, IIoT, IoT
The Technology of Educational Games for Support Science Learning: A Preliminary Study Suritno Fayanto; Dwi Sulisworo; Wa Ode Alkamalia; Wa Ode Indrawati; Hunaidah Hunaidah
J I M P - Jurnal Informatika Merdeka Pasuruan Vol 6, No 1 (2021): MARET
Publisher : Fakultas Teknologi Informasi Universitas Merdeka Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51213/jimp.v6i1.348

Abstract

Many learning technologies have emerged in education, often called educational games, along with technological development. Educational games are one of the learning technology instruments to support student interest. Educational games have exciting features that make students more interested in learning, especially science. Educational games in science learning give a different nuance to the learning process—this distinction is formed in a system that can attract students' interest and attention. This paper is here to provide an overview of the importance of educational games in science learning. Students usually consider learning science unattractive because it involves thinking and counting processes. Learning science by presenting a new system in educational games turns out to have its nuances. In science learning, educational games are presented in quizzes or games. This study uses qualitative research on review articles sourced from journals and books. Researchers use journals, both national and international journals, as the main reference source in conducting research. The analysis results found that each student can raise the level of the game if they can solve the given scientific problem. Therefore, educational games support learning in the classroom so that the learning process is more fun.Keyword— educational games, kahoot, quizizi, quizlet,  games-based learning
PENGUKURAN TINGKAT KEMATANGAN KOPI ARABIKA MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR Anastasia L Maukar; fitri marisa; Ahmad Farhan; Erdian Ari Widodo; Ilhamsyah I; Inayati Sa'adah; Rivaldo Tito L Dasilva
J I M P - Jurnal Informatika Merdeka Pasuruan Vol 6, No 3 (2021): DESEMBER
Publisher : Fakultas Teknologi Informasi Universitas Merdeka Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37438/jimp.v6i3.280

Abstract

Coffee has an important role in improving the national economy. Coffee is also one of the fourth major export commodities in foreign countries. Assessing the level of ripeness of a good coffee can be seen depending on the type of coffee itself. Arabika coffee will start to ripen on days 310 to 350 and for Arabica coffee types it will start to look ripe at the age of 210 to 250 days. In classifying coffee maturity, the K-Nearest Neighbor (KNN) method can be used. By taking a sample image of 3 arabika coffee grains with different levels of maturity twice. The existing data will be processed using the HSV feature to assess the RGB of the coffee bean image data. Based on the test results that have been determined. An accuracy calculation has been used to measure KNN and HSV's performance in determining the ripeness of arabika coffee. The calculation results show the performance of KNN at K=1 is outstanding,, 93.33%.Keywords— Arabica Coffee, ripeness level, K-Nearest Neighbor, HSV, accuracy
Autoregressive Integrated Moving Average Untuk Memprediksi Kebutuhan Daya Listrik Kabupaten Lumajang Fery Agung Prastyo; Moh Ahsan; Danang Aditya Nugraha
J I M P - Jurnal Informatika Merdeka Pasuruan Vol 6, No 2 (2021): AGUSTUS
Publisher : Fakultas Teknologi Informasi Universitas Merdeka Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37438/jimp.v6i2.323

Abstract

The electricity consumption of PLN in Lumajang Regency consists of several types of customers including external customers, internal customers and intermediate customers. Prediction or forecasting in research to forecast the electricity consumption of each type of customer uses the Autoregressive Integrated Moving Average (ARIMA) technique. The research was carried out with data collection, data analysis using Autoregressive Integrated Moving Average. The results of forcasting with the ARIMA technique are based on the results of the smallest MSE and MAPE values. The results of the parameter significance test using the ARIMA model (1,1,0) obtained MSE 23236091976 and MAPE 5.52278%, while for the ARIMA model (0,1,1) MSE 24588319865 and MAPE 6.0376302% and for the ARIMA model (1,1 ,1) obtained MSE 139049864555 and MAPE 14.021832% so that it can be concluded that the ARIMA parameter model (1,1,0).Keyword — Forcasting, ARIMA, electric power, PLN Lumajang Regency
Penerapan Algoritma K-Means Clustering dan Correlation Matrix Untuk Menganalisis Risiko Penyebaran Demam Berdarah di Kota Pekanbaru m azwan; Rahmad Kurniawan; Pizaini Pizaini; Fitri Insani
J I M P - Jurnal Informatika Merdeka Pasuruan Vol 6, No 3 (2021): DESEMBER
Publisher : Fakultas Teknologi Informasi Universitas Merdeka Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37438/jimp.v6i3.353

Abstract

Dengue cases in Pekanbaru in November 2020 reached 2,788 cases and 33 deaths. The government has carried out socialization to eradicate mosquito nests and provided vector control tools and materials. However, the government's efforts were not practical because the applied method has not been able to refer to vector data and information. Machine learning can be used to analyze specific problems such as Dengue. Therefore this study employed a Machine Learning algorithm, i.e., k-means clustering and correlation matrix for dengue risk analysis in Pekanbaru. This study obtained 12 sub-districts and 50 dengue attributes and weather data in 2020. K-means automatically searches for unknown clusters from dengue cases data quickly, which cluster results C1 (Sukajadi, Senapelan), C2 (Tenayan Raya, Tampan), and C3 (Rumbai Pesisir, Rumbai). Based on experimental testing, this study produced a silhouette score is 0.6. Meanwhile, the correlation matrix looks for relevant relationships hidden in the data. The correlation matrix obtained a strong linear relationship between the population (JP) and sufferers (P) of 0.73 for January and 0.93 for February 2020.Keywords— Dengue Fever, K-means, Correlation matrix, Machine learning.
Sistem Pendukung Keputusan Pemilihan Tempat Wisata Belanja di Kota Batam Menggunakan Metode Simple Additive Weighting (SAW) Novitia Chinoi; Allsela Meiriza
J I M P - Jurnal Informatika Merdeka Pasuruan Vol 6, No 1 (2021): MARET
Publisher : Fakultas Teknologi Informasi Universitas Merdeka Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37438/jimp.v6i1.330

Abstract

Batam city is one of the areas that are often visiting as a shopping destination by tourists because of the many attractions offered. However, the number of shopping tourism scattered is not in line with information about related tourist attractions. In addition, the number of shopping destinations often makes tourists confused in choosing shopping tourism. Therefore, the importance of a decision support system supports tourists in choose the desired shopping tourist attractions. It takes a method in its application so the desired decision support system can be achieving where one of the methods is the Simple Additive Weighting (SAW). This research uses the Simple Additive Weighting (SAW) method because it can complete multi-criteria decision-making. There are five criteria used in the selection of shopping tourism in this research, namely transportation (C1), atmosphere (C2), security (C3), product variation (C4), and facilities (C5). Based on calculations using the Simple Additive Weighting (SAW) method obtained shopping tourism attractions A4 (Alternative 4), namely Nagoya Hill, holds the highest rank value with a value of 1.00000 and makes it the most recommended shopping tourism attraction.Keywords— decision support system; DSS; shopping tour; simple additive weighting; SAW

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