Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

1.288

P-Index

This Author published in this journals

All Journal Jurnal Informatika Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Jurnal Teknik ITS IPTEK Journal of Proceedings Series IPTEK The Journal for Technology and Science Majalah Ilmiah Matematika Komputer Jurnal Buana Informatika JUTI: Jurnal Ilmiah Teknologi Informasi International Journal of Advances in Intelligent Informatics Jurnal Teknobisnis INFORMAL: Informatics Journal Register: Jurnal Ilmiah Teknologi Sistem Informasi EMITTER International Journal of Engineering Technology Journal of ICSAR Math Didactic: Jurnal Pendidikan Matematika Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Eksplora Informatika SISFO International Journal of Supply Chain Management CCIT (Creative Communication and Innovative Technology) Journal Indonesian Journal of Electrical Engineering and Computer Science Makara Journal of Technology Sewagati JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)

Buliali, Joko Lianto

Departemen Teknik Informatika, Institut Teknologi Sepuluh Nopember, Kampus ITS, Keputih, Sukolilo, Surabaya 60111

Author-ID : 244737

Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences Transportation Other

Published : 45 Documents Claim Missing Document

Claim Missing Document

Articles

1 2 3 4 5

PERANGKAT LUNAK PENDUKUNG PROCUREMENT PADA B2B BILATERAL MENGGUNAKAN MICROSOFT.NET Buliali, Joko Lianto; Lili, Suhadi; Hartono, Hartono
Majalah Ilmiah Matematika Komputer 2006: MAJALAH MATEMATIKA KOMPUTER EDISI APRIL
Publisher : Majalah Ilmiah Matematika Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (8447.282 KB)

E-commerce memberikan wama baru dalam pengelolaan bisnis sekaligus menawarkan peluang bisnisbaru. Sistem e-commerce B2B yang ada selama ini banyak melibatkan pihak ketiga (broker) dalamtransaksi dan pengelolaan data. Dalam penelitian ini disajikan sebuah teknologi procurement B2Bbilateral menggunakan Microsoft .NET yang menjamin privacy anggota selama melakukan transaksidengan cara memberikan hak pengelolaan data kepada masing-masing buyer. Pengelola komunitashanya mengelola data keanggotaan dan katalog barang. Dalam penelitian ini, ASP.NET, VB.NET danXML Web Service dalam Micorsoft .NET Framework digunakan dalam proses pengembangansistem, Aplikasi web site dibuat dengan ASP.NET dengan VB.NETsebagai bahasa pemrogramannya.Komunikasi antar server menggunakan XML Web Service. Untuk memfungsikan web servicedilakukan dengan cara menempatkan file web service dalam sebuah virtual directory. Untukmembangun komunikasi dengan aplikasi dengan web service dibutuhkan sebuah proxy object class.Dengan melakukan reference pada lokasi web service, aplikasi yang dibuat dapat menjalankanmethod-method yang berada pada web service tersebut. Uji coba transaksi antara supplier-buyerdalam komunitas bisnis B2B bilateral menunjukkan buyer telah dapat melakukan pemesanan barangke satu atau lebih supplier yang menjadi rekanannya, supplier dapat langsung merespon dataperrnintaan dari buyer, dan buyerdapat memilih penawaran yang diajukan oleh para supplier.

Computation of Reliability, Average Reliability, and Maintainability of Service Demand Fulfilment Dynamically using System Dynamics Mudjahidin, Mudjahidin; Buliali, Joko Lianto; Yuniarto, Muhammad Nur; Suryani, Erma
International Journal of Supply Chain Management Vol 8, No 3 (2019): International Journal of Supply Chain Management (IJSCM)
Publisher : International Journal of Supply Chain Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (13.163 KB)

An enterprise not only need information about the time-based service performance (reliability and maintenance of services) but also need to know the effect of time variables on service performance and demand dynamically so as to determine the right service time to providing the services level. This article proposes system dynamics approach to simulate the reliability, average reliability and maintainability of services and enterprise based on service time of demand fulfillment. The model created is a dynamic model that forms a closed system containing negative feedbacks that can be used to simulate. Generally, in a dynamic model with negative feedback, the decrease of time variable causes the increase of reliability of service. However, the simulation scenarios of the dynamic model with negative feedbacks in this article show the decrease of time variables (service time of demand fulfillment and its meantime, meantime of reliability function) can cause either decrease, increase or no change to the total of demand as well as number and average of demand reliability, average reliability, and maintainability in the enterprise.

SISTEM REKOMENDASI INDEKS WEB DENGAN METODE FREQUENT TERMS BERBASIS MULTI INSTANCE LEARNING Herumurti, Darlis; Buliali, Joko Lianto; Andriana, Ria
Jurnal Informatika Vol 8, No 1 (2007): MAY 2007
Publisher : Institute of Research and Community Outreach - Petra Christian University

Web index page is well known as page that arranges information by giving the title and short explanation about the information, where the complete information will be presented in other page. However since the amount of information become accumulate, the existence of a lot of index page exactly cause difficulty on getting information because it is possible to direct users into a mount of irrelevant information. Without a system which can help user navigation, the process of seeking the expected information is equal to a trial and error processing. In this paper, web index recommendation system is investigated which involved the activity of user on accessing the index page. This system will arrange the frequent term in index page and then implement Multi Instance Learning to give recommendation of the new index page automatically. The algorithm is citation kNN that will be adapted into fretCit kNN by implementing the minimal Hausdorff distance in measuring the distance. The experiments show that from the several test of users, the system give performance in average recommendation until 82,41% accuracy with 66,71% recall. Abstract in Bahasa Indonesia : Halaman indeks dikenal sebagai halaman yang mengelompokkan informasi-informasi, dengan memberikan judul serta penjelasan singkat tentang suatu informasi, dimana informasi lengkap akan dipresentasikan pada halaman-halaman lain. Namun dengan ketersediaan informasi yang menjadi semakin menumpuk, keberadaan halaman indeks yang semakin banyak justru menyebabkan kesulitan dalam mendapatkan informasi karena mungkin akan mengarahkan pada banyak informasi yang tidak relevan. Tanpa adanya sebuah sistem yang dapat membantu navigasi user, untuk mencari informasi yang diinginkan sama saja dengan sebuah kegiatan trial dan error. Dalam penelitian ini, dirancang sebuah sistem rekomendasi indeks web yang melibatkan aktifitas user dalam mengakses halaman indeks. Sistem ini mengelompokkan frequent terms pada halaman indeks dan kemudian mengimplementasikan metode Multi Instance Learning untuk memberikan rekomendasi secara otomatis dari halaman-halaman indeks baru. Algoritma yang digunakan adalah algoritma Citation kNN yang diadaptasi menjadi fretCit-kNN dengan mengaplikasikan minimal Hausdorff distance dalam pengukuran jaraknya. Dalam hasil proses dan analisis disimpulkan bahwa dengan beberapa macam uji coba data dari beberapa user sistem menampilkan performa hingga rata-rata 82,41% akurasi dan nilai kembalian sebesar 66,71%. Kata kunci: halaman indeks, sistem rekomendasi, multi instance learning, citation kNN, hausdorff distance.

PENJUALAN MOBIL BERBASIS WEB DAN MANAJEMEN DATA PEMBAYARAN DI SHOWROOM MOBIL XYZ Buliali, Joko Lianto; Handojo, Andreas; Wiharjo, Frica Salim
Jurnal Informatika Vol 6, No 1 (2005): MAY 2005
Publisher : Institute of Research and Community Outreach - Petra Christian University

The purpose of this research is to build a virtual showroom for a car showroom company which allows company to do marketing, selling, and providing payment information through Web. The system is developed based on the requirements of the users and current selling procedure in the showroom. From the investigation result, analysis, design, and implementation are carried out. Testing on the system shows that the system has fulfilled all the requirements needed by the users of the of the system Abstract in Bahasa Indonesia : Penelitian ini bertujuan untuk mengembangkan suatu sistem showroom virtual pada suatu showroom mobil sehingga dapat dilakukan pemasaran dan penjualan mobil disertai dengan informasi pembayaran customernya melalui Web. Sistem dikembangkan berdasarkan kebutuhan pengguna terhadap sistem dan prosedur penjualan pada showroom tersebut saat ini. Dari hasil tersebut, dilakukan analisis, desain, dan implementasi sistem yang dibutuhkan. Uji coba terhadap sistem yang dibuat menunjukkan bahwa sistem yang dibuat sudah memiliki seluruh fasilitas yang dibutuhkan pengguna sistem. Kata kunci: showroom virtual, pemasaran, penjualan mobil.

ITIL v3 and Van Grembergen Framework for System Transition Process Wulandari, Desi; Buliali, Joko Lianto
IPTEK Journal of Proceedings Series No 5 (2019): The 1st International Conference on Business and Management of Technology (IConBMT)
Publisher : Institut Teknologi Sepuluh Nopember

Recently, PT XYZ replaced their old ERP system into the Microsoft Dynamics AX 365. PT XYZ has twenty branch offices. The system transition process uses direct conversion and pilot conversion models. This study reports on how ITIL v3 and Van Grembergen Framework can work together in developing guidelines for system transition processes. This study was conducted by mapping the organizational structure, processes, and relational mechanisms in accordance with the Van Grembergen framework. The results obtained from this mapping will be used as material for consideration for the preparation of governance using the ITIL v3 framework. This research will only use the Service Transition domain on ITIL. The questionnaire was taken in part from the template issued by UCISA. As a result of the study, we present that ITIL v3 and Van Grembergen are able to be used to rebuild structures, processes, and relational mechanisms after the system transition process is done. And also to improve how to do the next transition process in another branch offices. Organizations must adapt and adapt to changes that means, Organizations cannot only carry out practices that have been done and hoped for get success like what happened in the past, because the practices in the past that have been done may not be valid now because the environment has changed. Therefore, in this case if organizations wants to achieve and gain a competitive advantage, it must focus and make changes to the goal strategic, having a far-sighted future

FRIEND RELATIONSHIP WEIGHTING FOR ACADEMIC PERFORMANCE PREDICTION ON UNIVERSITY DELEGATION AT FOLLOWING COMPETITION Bisono, Eva Firdayanti; Fahrudin, Tora; Buliali, Joko Lianto
IPTEK The Journal for Technology and Science Vol 30, No 2 (2019)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Academic performance is an important key to student success or failure. Therefore, academic performance prediction become a popular research on education. In general, several researches used GPA to predicting academic performance. However, there are some aspect that also plays a role in student academic performance, like friend relationship. So, this paper will analyze the correlation between academic performance and friend relationship. Friendship will be seen from communication frequency between students when become University delegation. Each students friend will have weight to show their closeness. In this paper, proposed method gives friendship weight based on communication frequency proportion between student among all student in one faculty. Indeed, close friends have a higher weight than other friends. So, the friendship weight sorted into descending order to get the closest friend. Then, their GPA convert into academic label, i.e. cumlaude, excellent, very good, or drop out. Furthermore, label will be compared to obtaining validation of our hypotheses that friendship plays a role in academic performance achievement. We use scholar student delegation dataset in competition from year 2015 in 7 study programme with 160 scholar students. Experimental results showed that the proposed method can predict academic performance 43% from the total data sample.

Prediction of Biochemical Oxygen Demand Using Radial Basis Function Network Noor, Muhammad; Buliali, Joko Lianto
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 5, No. 1, February 2020
Publisher : Universitas Muhammadiyah Malang

Biochemical oxygen demand shows the amount of oxygen needed by microorganisms to decompose dissolved organic substances suspended in water. This variable determines water quality. The higher value indicates lower water quality. Obtaining this value requires a lengthy procedure of five days in typical laboratories. This paper proposes to predict biochemical oxygen demand using a radial basis function network with improvement relational fuzzy c-means clustering to set centroid by using 11 parameters that come from water quality records. The dataset used in testing consisting of weekly parameters between 2014-2019. Testing results show performance measurement of mean absolute error, mean square error, root mean square error, mean absolute percentage error, and accuracy using centroid with improvement relational fuzzy c-means 0.15016, 0.3677, 0.19082, 21.64490 and 78.35510 comparing with centroid from fuzzy c-means 0.16002, 0.04021, 0.19963, 22.83184, and 77.16816.

METODE HIBRIDA K-MEANS DAN GENERALIZED REGRESSION NEURAL NETWORK UNTUK PREDIKSI ARUS LALU LINTAS Mamase, Saprina; Buliali, Joko Lianto
Jurnal Buana Informatika Vol 7, No 3 (2016): Jurnal Buana Informatika Volume 7 Nomor 3 Juli 2016
Publisher : Universitas Atma Jaya Yogyakarta

Abstract. Traffic flow forecasting is a popular research topic in the development of Intelligent Transportation System. There have been many forecasting methods used for traffic flow forecasting, such as Generalized Regression Neural Network (GRNN) which has a fairly good accuracy. One of the GRNN?s characteristics is that the number of neurons in pattern layer increases as the number of training samples raise and this can cause overfitting problem. In this research, a hybrid method to predict traffic flow is proposed, that is K-means and GRNN algorithm. K-means method aims to solve overfitting problem in GRNN model by choosing training samples based on their similar characteristics. Leave One Out Cross Validation (LOOCV) is used to select an appropriate smoothing factor parameter at each GRNN?s model. Mean Absolute Percentage Error (MAPE) is used as the evaluation criterion in the testing process. The results show that the proposed method could improve the accuracy of predictions by reducing the value of MAPE by 0.82-3.81%.Keywords: Traffic flow forecasting, K-means, Generalized Regression Neural Network, Leave One Out Cross ValidationAbstrak. Prediksi arus lalu lintas telah menjadi tren topik penelitian untuk pengembangan sistem transportasi cerdas. Telah banyak metode yang digunakan terkait prediksi arus lalu lintas, diantaranya yaitu Generalized Regression Neural Network (GRNN) yang memiliki akurasi yang cukup baik. Salah satu karakteristik GRNN adalah jumlah neuron pada pattern layer akan bertambah seiring meningkatnya jumlah data latih yang akan mengakibatkan masalah overfitting. Dalam penelitian ini diusulkan metode hibrida K-means dan GRNN untuk prediksi arus lalu lintas. Metode K-means bertujuan untuk mengatasi masalah overfitting pada model GRNN dengan memilih data latih berdasarkan kemiripan karateristiknya. Algoritma Leave One Out Cross Validation (LOOCV) digunakan untuk memilih parameter smoothing factor terbaik pada setiap model GRNN. Mean Absolute Percentage Error (MAPE) digunakan sebagai kriteria evaluasi model prediksi. Hasil menunjukkan bahwa metode yang diusulkan dapat meningkatkan akurasi prediksi dengan penurunan nilai MAPE sebesar 0,82-3,81%.Kata Kunci: Prediksi arus lalu lintas, K-means, Generalized Regression Neural Network, Leave One Out Cross Validation

Penanganan imbalance class data laboratorium kesehatan dengan Majority Weighted Minority Oversampling Technique Untoro, Meida Cahyo; Buliali, Joko Lianto
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 4, No 1 (2018): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v4i1.1184

Diagnosis suatu penyakit akan menjadi tepat jika didukung dengan berbagai proses mulai pengecekan awal (amannesa) sampai pengecekan laboratorium. Hasil dari proses laboratorium mempunyai informasi berbagai penyakit, akan tetapi beberapa jenis penyakit memiliki prevalensi rendah. Penyakit bervalensi rendah memiliki pengaruh dalam penanganan pasien lebih lanjut. Dengan rasio yang tidak seimbang data laboratorium akan menyebabkan nilai akurasi menjadi rendah dalam pengklasifikasian dan penanganan penyakit. Majority Weighted Minority Oversampling Technique (MWMOTE) adalah saalah satu cara untuk menyelesaikan imbalanced. Penelitian ini bertujuan menangani permasalahan ketidakseimbangan data laboratorium kesehatan sehingga diperoleh hasil pengklasifikasian penyakit dengan tingkat akurasi lebih tinggi. Hasil pada penelitian ini menunjukkan bahwa MWMOTE dapat meningkatkan akurasi untuk permasalahan ketidakseimbangan data sebesar 3,13%.Â Â Â Diagnosis of a disease will be appropriate if supported by various processes ranging from initial checks (amannesa) to laboratory checks. Results from the laboratory process have information on various diseases, but some types of diseases have a low prevalence. Low-valvature disease has an effect in the treatment of the patient further. With an unbalanced ratio the laboratory data will cause the accuracy value to be low in the classification and handling of the disease. Majority Weighted Minority Oversampling Technique (MWMOTE) is one way to complete imbalanced. This study aims to address the problem of imbalance of health laboratory data to obtain the results of the classification of disease with a higher degree of accuracy. The results of this study indicate that MWMOTE can improve accuracy for data imbalance problems by 3.13%.

Performance Study Of Uncertainty Based Feature Selection Method On Detection Of Chronic Kidney Disease With SVM Classification Qolby, Lailly Syifa'ul; Buliali, Joko Lianto; Saikhu, Ahmad
IPTEK The Journal for Technology and Science Vol 32, No 2 (2021)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v32i2.10483

Chronic Kidney Disease (CKD) is a disorder that impairs kidney function. Early signs of CKD patients are very difficult until they lose 25% of their kidney function. Therefore, early detection and effective treatment are needed to reduce the mortality rate of CKD sufferers. In this study, the authors diagnose the CKD dataset using the Support Vector Machine (SVM) classification method to obtain accurate diagnostic results. The authors propose a comparison of the result on applying the feature selec- tion method to get the best feature candidates in improving the classification result. The testing process compares the Symmetrical Uncertainty (SU) and Multivariate Symmetrical Uncertainty (MSU) feature selection method and the SVM method as a classification method. Several experimental scenarios were carried out using the SU and MSU feature selection methods using the CKD dataset. From the results of the tests carried out, it shows that using the MSU feature selection method with 80%: 20% data split produces nine important features with an accuracy value of 0.9, sensi- tivity 0.84, specification 1.0, and when viewed on the ROC graph, the MSU method graph shows the true positive value is higher than the false positive value. So the classification using the MSU feature selection method is better than the SU feature selection method by 90% accuracy

Co-Authors A.A. Ketut Agung Cahyawan W Achmad Saidul Agri Kridanto Agri Kridanto, Agri Ahmad Saikhu Ahmad Saikhu Alvin Lazaro Andreas Handojo Andreast Wahyu Sugiyarta Andrew Andrew Andriyani Andriyani Andriyani Andriyani Andriyani Arlianti, Irma Arya Yudhi Wijaya Arya Yudi Wijaya Bilqis Amaliah Bisono, Eva Firdayanti Cempaka A. Swastyastu Choirul Mahfud Darlis Herumurti Diagnosa Fenomena Diana Purwitasari Dwi Sunaryono Erma Suryani Fadilah Fahrul Hardiansyah Fadilah Fahrul Hardiansyah, Fadilah Fahrul Fenky Sugiarto Frica Salim Wiharjo Ginardi, Raden Venantius Hari Giri Wiriapradja Hadi Siswidiastono Harseno, Ahmad Rieskha Hartono Hartono Heru Tri Ahmanto Isye Arieshanti Jingga, Azharine Purwa Juniastuti, Susi Kartika Nuswantara Mohammad Yazdi Pusadan Muhammad Faris Musthafa Muhammad Noor Muhammad Zuber Myrna ermawati Pradana, Muhamad Hilmil Muchtar Aditya Prayogo, Reza Prasetya Prayuda, Janandra Aji Qolby, Lailly Syifa'ul Ratna Rintaningrum, Ratna Ria Andriana Riyanarto Sarno Saifulloh, Mohamad Saprina Mamase Savitri, Eka Dian Siti Maimunah Suhadi Lili Suhadi Lili Tora Fahrudin Tsabbit Aqdami Mukhtar, Tsabbit Aqdami Umi Trisyanti, Umi Untoro, Meida Cahyo Victor Hariadi Wahyudi Agustiono Waskitho Wibisino Waskitho Wibisono Wijaya, Arya Yudi Wulandari, Desi Yanuar Risah Prayogi Yudhi Purwananto Yudhiakto Pramudya Yuhana, Umi Laili Yuniarto, Muhammad Nur

Title

Found 45 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 45 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 45 Documents
Search