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Register: Jurnal Ilmiah Teknologi Sistem Informasi
Published by Universitas Pesantren Tinggi Darul ulum
ISSN : 25030477     EISSN : 25023357     DOI : https://doi.org/10.26594/register
Core Subject : Science,
Computer Science & IT
Register: Scientific Journals of Information System Technology is an international, peer-reviewed journal that publishes the latest research results in Information and Communication Technology (ICT). The journal covers a wide range of topics, including Enterprise Systems, Information Systems Management, Data Acquisition and Information Dissemination, Data Engineering and Business Intelligence, and IT Infrastructure and Security. The journal has been indexed on Scopus (reputated international indexed) and accredited with grade “SINTA 1” by the Director Decree (1438/E5/DT.05.00/2024) as a recognition of its excellent quality in management and publication for international indexed journal.
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Articles 219 Documents
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Use of online applications in maintaining MSMEs performance during the COVID-19 pandemic Nurlinda, Nurlinda; Sinuraya, Junus; Asmalidar, Asmalidar; Hassan, Rahayu; Supriyanto, Supriyanto
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 7, No 2 (2021): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v7i2.2223

Abstract

This study aims to see whether there are differences in sales made by offline/conventional and online MSMEs to discover alternative media transactions to survive and increase sales during the COVID-19 period. This research is an exploratory study on MSMEs players who sell Rujak Sentir at Simpang Jodoh, Percut Sei Tuan, Deli Serdang District, Indonesia. The data source in this research is primary data by collecting data using a questionnaire on 50 samples of Rujak Sentir MSMEs merchants. Data were analyzed using statistical descriptive analysis of the Wilcoxon Signed Rank Test. The final analysis of data shows that the apply of online applications can be an alternative for MSMEs in maintaining and improving performance throughout the COVID-19 pandemic. The usage of this research practice is to give input to related parties regarding other options that can be utilized by enterprises throughout the Coronavirus widespread so that in the future, MSMEs are ready to face uncertainties that arise due to external factors. In addition to this, this research will be a recommendation regarding technical guidance that can be carried out by the local government in fostering MSMEs.
Segmentasi Citra menggunakan Support Vector Machine (SVM) dan Ellipsoid Region Search Strategy (ERSS) Arimoto Entropy berdasarkan Ciri Warna dan Tekstur Hakim, Lukman; Mutrofin, Siti; Ratnasari, Evy Kamilah
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 2, No 1 (2016): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v2i1.440

Abstract

Segmentasi citra merupakan suatu metode penting dalam pengolahan citra digital yang bertujuan membagi citra menjadi beberapa region yang homogen berdasarkan kriteria kemiripan tertentu. Salah satu syarat utama yang harus dimiliki suatu metode segmentasi citra yaitu menghasilkan citra boundary yang optimal.Untuk memenuhi syarat tersebut suatu metode segmentasi membutuhkan suatu klasifikasi piksel citra yang dapat memisahkan piksel secara linier dan non-linear. Pada penelitian ini, penulis mengusulkan metode segmentasi citra menggunakan SVM dan entropi Arimoto berbasis ERSS sehingga tahan terhadap derau dan mempunyai kompleksitas yang rendah untuk menghasilkan citra boundary yang optimal. Pertama, ekstraksi ciri warna dengan local homogeneity dan ciri tekstur dengan menggunakan Gray Level Co-occurrence Matrix (GLCM) yang menghasilkan beberapa fitur. Kedua, pelabelan dengan Arimoto berbasis ERSS yang digunakan sebagai kelas dalam klasifikasi. Ketiga, hasil ekstraksi fitur dan training kemudian diklasifikasi berdasarkan label dengan SVM yang telah di-training. Dari percobaan yang dilakukan menunjukkan hasil segmentasi kurang optimal dengan akurasi 69 %. Reduksi fitur perlu dilakukan untuk menghasilkan citra yang tersegmentasi dengan baik. Kata kunci: segmentasi citra, support vector machine, ERSS Arimoto Entropy, ekstraksi ciri. Abstract Image segmentation is an important tool in image processing that divides an image into homogeneous regions based on certain similarity criteria, which ideally should be meaning-full for a certain purpose. Optimal boundary is one of the main criteria that an image segmentation method should has. A classification method that can partitions pixel linearly or non-linearly is needed by an image segmentation method. We propose a color image segmentation using Support Vector Machine (SVM) classification and ERSS Arimoto entropy thresholding to get optimal boundary of segmented image that noise-free and low complexity. Firstly, the pixel-level color feature and texture feature of the image, which is used as input to SVM model (classifier), are extracted via the local homogeneity and Gray Level Co-Occurrence Matrix (GLCM). Then, determine class of classifier using Arimoto based ERSS thresholding. Finally, the color image is segmented with the trained SVM model (classifier). This image segmentation result less satisfied segmented image with 69 % accuracy. Feature reduction is needed to get an effective image segmentation. Key word: image segmentation, support vector machine, ERSS Arimoto Entropy, feature extraction.
Parsing struktur semantik soal cerita matematika berbahasa indonesia menggunakan recursive neural network Prasetya, Agung; Fatichah, Chastine; Yuhana, Umi Laili
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 5, No 2 (2019): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v5i2.1537

Abstract

Soal cerita berperan penting untuk kemajuan pengembangan kecerdasan buatan. Hal ini karena penyelesaian soal cerita melibatkan pengembangan sebuah sistem yang mampu memahami bahasa alami. Pembentukan sistem penyelesaian soal memerlukan mekanisme untuk mendekomposisikan teks soal ke segmen-segmen teks untuk diterjemahkan ke jenis operasi hitung. Segmen-segmen tersebut ditentukan melalui proses parsing semantik struktur soal agar menghasilkan segmen-segmen yang maknanya menunjuk operasi hitung. Sejumlah metode usulan saat ini sesuai untuk diterapkan pada soal cerita berbahasa Inggris dan belum diterapkan pada soal cerita berbahasa Indonesia. Dampaknya adalah segmen-segmen yang dihasilkan belum tentu menghasilkan urutan pengerjaan operasi yang sesuai makna cerita. Penelitian ini mengusulkan penggunaaan Recursive Neural Network (RNN) sebagai parser struktur semantik soal cerita berbahasa Indonesia. Pengujian parser struktur semantik soal dilakukan terhadap soal-soal yang berasal dari Buku Sekolah Elektronik (BSE) Sekolah Dasar (SD) dari Pusat Perbukuan Kementerian Pendidikan dan Kebudayaan. Hasil pengujian menunjukkan akurasi akhir sebesar 86,4%.  Math word problems play an important role for the development of artificial intelligent. This is because solving word problems involves the development of a system that can understand natural language.  Designing a system for solving math word problems requires a mechanism for decomposing a text into segments of text to be translated into math operation. The segments are categorized through the process of parsing the semantic structure of the word problems to obtain segments whose meanings refer to math operation. A number of current proposed methods are suitable to be applied to English math word problems and have never been applied to Indonesian math word problems. The impact is that the segments produced are not necessarily in line with the sequences of operations appropriate with the meaning of the story.  This study proposed the use of Recursive Neural Network (RNN) as a parser of semantic structure of Indonesian math word problems. The testing of the parser was carried out on the math word problems taken from the Elementary School’s Electronic School Book  (BSE) published by the Book Center of the Ministry of Education and Culture. The result of the testing showed that the final accuracy was 86.4%.
Multi-parent order crossover mechanism of genetic algorithm for minimizing violation of soft constraint on course timetabling problem Fajrin, Ahmad Miftah; Fatichah, Chastine
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 6, No 1 (2020): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v6i1.1663

Abstract

A crossover operator is one of the critical procedures in genetic algorithms. It creates a new chromosome from the mating result to an extensive search space. In the course timetabling problem, the quality of the solution is evaluated based on the hard and soft constraints. The hard constraints need to be satisfied without violation while the soft constraints allow violation. In this research, a multi-parent crossover mechanism is used to modify the classical crossover and minimize the violation of soft constraints, in order to produce the right solution. Multi-parent order crossover mechanism tends to produce better chromosome and also prevent the genetic algorithm from being trapped in a local optimum. The experiment with 21 datasets shows that the multi-parent order crossover mechanism provides a better performance and fitness value than the classical with a zero fitness value or no violation occurred. It is noteworthy that the proposed method is effective to produce available course timetabling.
Designing mobile farmer application using object oriented analysis and design Mufti, Abdul; Novianti, Desi; Anjani, Dewi
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 3, No 2 (2017): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v3i2.1100

Abstract

Sistem e-farmers merupakan sebuah sistem penjualan berbasis teknologi (e-commerce) yang dapat diakses melalui website, digunakan untuk membantu para petani menjual hasil pertanian berupa beras secara langsung ke konsumen. Namun dengan adanya kendala dalam hal kepemilikan perangkat komputer dan laptop, petani maupun konsumen yang merupakan pengakses website ladangku.id beralih menggunakan perangkat mobile. Dengan alasan ini, maka peneliti membuat sebuah sistem e-farmers yang awalnya berupa website dapat juga diakses melalui perangkat mobile dengan sistem operasi Android. Karena sistem berbasis website berbeda dengan sistem berbasis mobile, untuk itu dibutuhkan sebuah perancangan sistem e-farmer yang berbasis mobile yang akan terintegrasi dengan sistem berbasis website. Di mana metode yang digunakan adalah metode Research and Development (R&D), yang mana mengembangkan sistem yang sudah ada dan hasil akhirnya menghasilkan sebuah produk berupa rancangan sistem aplikasi e-farmers yang dapat berkerja di platform Android.  E-farmers system is a technology-based commerce system (e-commerce) that can be accessed via a website, used for assisting farmers in selling rice product directly to consumers. However, due to the constraint in the ownership of computer and laptop, farmers and consumers as the users of the website ladangku.id now use mobile devices instead. For this reason, the researcher developed an e-farmers system that was initially only accessible via the website but now can be accessed via mobile devices with the Android operating system. Because the website-based system and mobile-based system are different, it is necessary to have a mobile-based e-farmer system design that is integrated with the website-based system. The method used was Research and Development (R&D) method by developing the existing system, and the final product was in the form of a design of e-farmer application system that can work on Android platform.
TOPSIS for mobile based group and personal decision support system Dewi, Ratih Kartika; Jonemaro, Eriq Muhammad Adams; Kharisma, Agi Putra; Farah, Najla Alia; Dewantoro, Mury Fajar
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 7, No 1 (2021): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v7i1.2140

Abstract

Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is an algorithm that can be used for alternative design in a decision support system (DSS). TOPSIS provides recommendation so that users can get information that support their decision, for example a tourist wants to visit a tourist destination in Malang, then TOPSIS provides recommendations of tourist destinations in the form of ranking recommendation, with the highest rank is the most recommended recommendation. TOPSIS-based Mobile Decision Support System (DSS) has relatively low algorithm complexity. However, there are some cases that require development from personal DSS to group DSS, for example tourists rarely come alone, in which case most of them invite friends or family. For users who are more than 1 person, the TOPSIS algorithm can be combined with the BORDA algorithm. This study explains about the implementation & testing of TOPSIS and TOPSIS-BORDA as algorithms for personal and group DSS in mobile-based tourism recommendation system in Malang. Correlation testing was conducted to test the effectiveness of TOPSIS in mobile-based recommendation system. In previous study, correlation testing for personal DSS showed that there was a relationship between the recommendation and user choice, with correlation value of 0.770769231. In this study, correlation testing for group DSS showed there is a positive correlation of 0.88 between the recommendations of the group produced by TOPSIS-BORDA and personal recommendations for each user produced by TOPSIS.
Sistem Informasi Absensi Haul Berbasis Web di Pondok Pesantren Muhyiddin Surabaya Jannah, Erliyah Nurul; Arifin, Agus Zainal
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 1, No 1 (2015): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v1i1.405

Abstract

Teknologi informasi saat ini telah menjadi kebutuhan bagi hampir semua instansi, baik pemerintah maupun swasta. Tak terkecuali pondok pesantren, khususnya Pondok Pesantren Muhyiddin Surabaya. Berbagai permasalahan di pondok pesantren membutuhkan bantuan teknologi informasi dalam penyelesaiannya. Salah satunya adalah permasalahan pencatatan kehadiran peserta dalam suatu acara tertentu seperti acara Haul. Haul merupakan acara tahunan yang bertujuan untuk memperingati hari lahirnya Nabi Muhammad SAW. Acara Haul di PP. Muhyiddin mendatangkan lebih dari seribu peserta yang merupakan penghafal Quran. Panitia Haul harus mengabsen peserta satu persatu serta menempatkannya ke majelis-majelis berdasarkan urutan kedatangan dan kota asal. Sistem informasi absensi yang ada masih berbasis desktop dan hanya mampu digunakan untuk mengabsen peserta saja. Sistem tersebut belum mampu melakukan pembagian majelis peserta secara otomatis. Padahal proses pembagian majelis inilah yang menyebabkan proses absensi memakan waktu lama. Oleh sebab itu, dibuatlah sebuah Sistem Informasi Absensi Haul yang berbasis web. Sistem ini diharapkan mampu untuk membuat proses absensi pada acara Haul menjadi lebih efisien. Dari hasil pengujian sistem yang telah dilakukan, dalam satu menit sistem dapat digunakan untuk mengabsen sepuluh peserta, membagi peserta tersebut ke majelis-majelis, dan mencetak kartu peserta Haul.
Query Expansion menggunakan Word Embedding dan Pseudo Relevance Feedback Tanuwijaya, Evan; Adam, Safri; Anggris, Mohammad Fatoni; Arifin, Agus Zainal
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 5, No 1 (2019): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v5i1.1385

Abstract

Kata kunci merupakan hal terpenting dalam mencari sebuah informasi. Penggunaan kata kunci yang tepat menghasilkan informasi yang relevan. Saat penggunaannya sebagai query, pengguna menggunakan bahasa yang alami, sehingga terdapat kata di luar dokumen jawaban yang telah disiapkan oleh sistem. Sistem tidak dapat memproses bahasa alami secara langsung yang dimasukkan oleh pengguna, sehingga diperlukan proses untuk mengolah kata-kata tersebut dengan mengekspansi setiap kata yang dimasukkan pengguna yang dikenal dengan Query Expansion (QE). Metode QE pada penelitian ini menggunakan Word Embedding karena hasil dari Word Embedding dapat memberikan kata-kata yang sering muncul bersama dengan kata-kata dalam query. Hasil dari word embedding dipakai sebagai masukan pada pseudo relevance feedback untuk diperkaya berdasarkan dokumen jawaban yang telah ada. Metode QE diterapkan dan diuji coba pada aplikasi chatbot. Hasil dari uji coba metode QE yang diterapkan pada chatbot didapatkan nilai recall, precision, dan F-measure masing-masing 100%; 70% dan 82,35 %. Hasil tersebut meningkat 1,49% daripada chatbot tanpa menggunakan QE yang pernah dilakukan sebelumnya yang hanya meraih akurasi sebesar 68,51%. Berdasarkan hasil pengukuran tersebut, QE menggunakan word embedding dan pseudo relevance feedback pada chatbot dapat mengatasi query masukan dari pengguna yang ambigu dan alami, sehingga dapat memberikan jawaban yang relevan kepada pengguna.  Keywords are the most important words and phrases used to obtain relevant information on content. Although users make use of natural languages, keywords are processed as queries by the system due to its inability to process. The language directly entered by the user is known as query expansion (QE). The proposed QE in this research uses word embedding owing to its ability to provide words that often appear along with those in the query. The results are used as inputs to the pseudo relevance feedback to be enriched based on the existing documents. This method is also applied to the chatbot application and precision, and F-measure values of the results obtained were 100%, 70%, 82.35% respectively. The results are 1.49% better than chatbot without using QE with 68.51% accuracy. Based on the results of these measurements, QE using word embedding and pseudo which gave relevance feedback in chatbots can resolve ambiguous and natural user’s input queries thereby enabling the system retrieve relevant answers.
Fuzzy-AHP MOORA approach for vendor selection applications Al Khoiry, I’tishom; Gernowo, Rahmat; Surarso, Bayu
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 8, No 1 (2022): In progress (January)
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v8i1.2356

Abstract

Vendor selection is a critical activity in order to support the achievement of company success and competitiveness. Significantly, the company has some specific standards in the selection. Therefore, an evaluation is needed to see which vendors match the company's criteria. The purpose of this study is to evaluate and select the proposed vendor in a web-based decision support system (DSS) by using the fuzzy-AHP MOORA approach. The fuzzy-AHP method is used to determine the importance level of the criteria, while the MOORA method is used for alternative ranking. The results showed that vendor 4 has the highest score than other alternatives with a value of 0.2536. Sensitivity analysis showed that the proposed DSS fuzzy-AHP MOORA concept was already solid and suitable for this problem, with a low rate of change.
Segmentasi Pembuluh Darah Retina Pada Citra Fundus Menggunakan Gradient Based Adaptive Thresholding Dan Region Growing Sutaji, Deni; Fatichah, Chastine; Navastara, Dini Adni
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 2, No 2 (2016): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v2i2.553

Abstract

 Segmentasi pembuluh darah pada citra fundus retina menjadi hal yang substansial dalam dunia kedokteran, karena dapat digunakan untuk mendeteksi penyakit, seperti: diabetic retinopathy, hypertension, dan cardiovascular. Dokter membutuhkan waktu sekitar dua jam untuk mendeteksi pembuluh darah retina, sehingga diperlukan metode yang dapat membantu screening agar lebih cepat.Penelitian sebelumnya mampu melakukan segmentasi pembuluh darah yang sensitif terhadap variasi ukuran lebar pembuluh darah namun masih terjadi over-segmentasi pada area patologi. Oleh karena itu, penelitian ini bertujuan untuk mengembangkan metode segmentasi pembuluh darah pada citra fundus retina yang dapat mengurangi over-segmentasi pada area patologi menggunakan Gradient Based Adaptive Thresholding dan Region Growing.Metode yang diusulkan terdiri dari 3 tahap, yaitu segmentasi pembuluh darah utama, deteksi area patologi dan segmentasi pembuluh darah tipis. Tahap segmentasi pembuluh darah utama menggunakan high-pass filtering dan tophat reconstruction pada kanal hijau citra yang sudah diperbaiki kontrasnya sehingga lebih jelas perbedaan antara pembuluh darah dan background. Tahap deteksi area patologi menggunakan metode Gradient Based Adaptive Thresholding. Tahap segmentasi pembuluh darah tipis menggunakan Region Growing berdasarkan informasi label pembuluh darah utama dan label area patologi. Hasil segmentasi pembuluh darah utama dan pembuluh darah tipis kemudian digabungkan sehingga menjadi keluaran sistem berupa citra biner pembuluh darah. Berdasarkan hasil uji coba, metode ini mampu melakukan segmentasi pembuluh darah retina dengan baik pada citra fundus DRIVE, yaitu dengan akurasi rata-rata 95.25% dan nilai Area Under Curve (AUC) pada kurva Relative Operating Characteristic (ROC) sebesar 74.28%.                           Kata Kunci: citra fundus retina, gradient based adaptive thresholding, patologi, pembuluh darah retina, region growing, segmentasi.  Segmentation of blood vessels in the retina fundus image becomes substantial in the medical, because it can be used to detect diseases, such as diabetic retinopathy, hypertension, and cardiovascular. Doctor takes about two hours to detect the blood vessels of the retina, so screening methods are needed to make it faster. The previous methods are able to segment the blood vessels that are sensitive to variations in the size of the width of blood vessels, but there is over-segmentation in the area of pathology. Therefore, this study aims to develop a segmentation method of blood vessels in retinal fundus images which can reduce over-segmentation in the area of pathology using Gradient Based Adaptive Thresholding and Region Growing. The proposed method consists of three stages, namely the segmentation of the main blood vessels, detection area of pathology and segmentation thin blood vessels. Main blood vessels segmentation using high-pass filtering and tophat reconstruction on the green channel which adjusted of contras image that results the clearly between object and background. Detection area of pathology using Gradient Based Adaptive thresholding method. Thin blood vessels segmentation using Region Growing based on the information main blood vessel segmentation and detection of pathology area. Output of the main blood vessel segmentation and thin blood vessels are then combined to reconstruct an image of the blood vessels as output system.This method is able to segment the blood vessels in retinal fundus images DRIVE with an accuracy of 95.25% and the value of Area Under Curve (AUC) in the relative operating characteristic curve (ROC) of 74.28%.Keywords: Blood vessel, fundus retina image, gradient based adaptive thresholding, pathology, region growing, segmentation.

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