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All Journal International Journal of Electrical and Computer Engineering Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Techno.Com: Jurnal Teknologi Informasi Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Prosiding SNATIF Jurnal Edukasi dan Penelitian Informatika (JEPIN) International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics Journal of Information Systems Engineering and Business Intelligence JAIS (Journal of Applied Intelligent System) Register: Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Teknologi dan Sistem Komputer Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Prosiding SAKTI (Seminar Ilmu Komputer dan Teknologi Informasi) JISKa (Jurnal Informatika Sunan Kalijaga) APTIKOM Journal on Computer Science and Information Technologies (CSIT) Innovation in Research of Informatics (INNOVATICS) Journal of Soft Computing Exploration Unnes Journal of Mathematics Journal of Student Research Exploration Journal of Information System Exploration and Research Nusantara Journal of Computers and its Applications Jurnal Informatika: Jurnal Pengembangan IT Scientific Journal of Informatics
Much Aziz Muslim
Unknown Affiliation
Aerospace Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Other

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Information Retrieval System for Determining The Title of Journal Trends in Indonesian Language Using TF-IDF and Na?ve Bayes Classifier Trihanto, Wandha Budhi; Arifudin, Riza; Muslim, Much Aziz
Scientific Journal of Informatics Vol 4, No 2 (2017): November 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v4i2.11876

Abstract

The journal is known as one of the relevant serial literature that can support a researcher in doing his research. In its development journal has two formats that can be accessed by library users namely: printed format and digital format. Then from the number of published journals, not accompanied by the growing amount of information and knowledge that can be retrieved from these documents. The TF-IDF method is one of the fastest and most efficient text mining methods to extract useful words as the value of information from a document. This method combines two concepts of weight calculation that is the frequency of word appearance on a particular document and the inverse frequency of documents containing the word. Furthermore, data analysis of journal title is done by Nave Bayes Classifier method. The purpose of the research is to build a website-based information retrieval system that can help to classify and define trends from Indonesian journal titles. This research produces a system that can be used to classify journal titles in Indonesian language, with system accuracy in determining the classification of 90,6% and 9,4% error rate. The highest percentage result that became the trend of title classification was decision support system category which was 24.7%.
Forecasting Inflation Rate Using Support Vector Regression (SVR) Based Weight Attribute Particle Swarm Optimization (WAPSO) Priliani, Erlin Mega; Putra, Anggyi Trisnawan; Muslim, Much Aziz
Scientific Journal of Informatics Vol 5, No 2 (2018): November 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i2.14613

Abstract

Data mining is the process of finding patterns or interesting information in selected data by using a particular technique or method. Utilization of data mining one of which is forecasting. Various forecasting methods have progressed along with technological developments. Support Vector Regression (SVR) is one of the forecasting methods that can be used to predict inflation. The level of accuracy of forecasting is determined by the precision of parameter selection for SVR. Determination of these parameters can be done by optimization, to obtain optimal forecasting of SVR method. The optimization technique used is Weight Attribute Particle Swarm Optimization (WAPSO). The use of WAPSO can find optimal SVR parameters, so as to improve the accuracy of forecasting. The purpose of this research is to implement SVR and SVR-WAPSO to predict the inflation rate based on Consumer Price Index (CPI) and to know the level of accuracy. The data used in this study is CPI Semarang City period January 2010-February 2018. Implementation experiments using Netbeans 8.2 gives results, SVR method has an accuracy of 94.654%. SVR-WAPSO method has an accuracy of 97.459%. Thus, the SVR-WAPSO method can increase the accuracy of 2,805% of a single SVR method for inflation rate forecasting. This research can be used as a reference for the next researcher can make improvements in determining the range of SVR parameters to get the value of each parameter more effective and efficient to get more optimal accuracy.
PEMBUATAN SISTEM INFORMASI GARDU INDUK PT. PLN (Persero) APP SEMARANG SE-KOTA SEMARANG DENGAN JAVA ANDROID Muslim, Much Aziz
Prosiding SAKTI (Seminar Ilmu Komputer dan Teknologi Informasi) Vol 2, No 1 (2017): Vol 2, No 1 (2017): Prosiding Seminar Nasional Ilmu Komputer dan Teknologi Infor
Publisher : Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (797.667 KB)

Abstract

Perusahaan Listrik Negara (PLN) atau PT. PLN (Persero) adalah sebuah BUMN (Badan Usaha Milik Negara) yang bertugas melaksanakan operasi dan pemeliharaan semua aspek kelistrikan yang ada di Indonesia. PT. PLN (Persero) APP Semarang merupakan pusat pengaturan beban Jawa Tengah dan Daerah Istimewa Yogyakarta yang berlokasi di Ungaran, selain mengatur pada lokasi di Jateng-DIY, PT. PLN (Persero) APP Semarang juga memonitoring semua unit gardu induknya melalui server utama di PT. PLN (Persero) APP Semarang. Memonitoring gardu induk dapat dilakukan dengan mudah bila disajikan dalam smartphone yang dapat dengan mudah diakses. Tujuan pembuatan sistem informasi ini yaitu agar penyajian data yang mudah disajikan melalui smartphone android yang dapat diakses oleh semua pegawai PT. PLN (Persero) APP Semarang.
Penyajian Data Komoditi Batik Kabupaten Sukoharjo Dengan Google Earth Larasati, Ukhti Ikhsani; Muslim, Much Aziz
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 2, No 2 (2016): Volume 2 No 2
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (557.789 KB) | DOI: 10.26418/jp.v2i2.17454

Abstract

Kabupaten Sukoharjo memiliki banyak potensi daerah yang merupakan komoditi unggulan kabupaten yaitu komoditi mebel kayu, mebel rotan, batik, tekstil dan produk tekstil, kaca grafir, kerajinan kulit/tatah sungging (wayang), kerajinan gitar, kerajinan gamelan, shuttlecock, jamu tradisional, emping mlinjo, sarung goyor, beras, dan alkohol. Dinas Perindustrian dan Perdagangan kabupaten Sukoharjo adalah salah satu pelaksana urusan Pemerintah Daerah kabupaten Sukoharjo di bidang perindustrian dan perdagangan. Metode pengumpulan data yang digunakan adalah metode observasi dan studi pustaka. Observasi dilakukan dengan mengamati langsung bagaimana data-data komoditi unggulan kabupaten Sukoharjo disajikan di Dinas Perindustrian dan Perdagangan kabupaten Sukoharjo. Setelah mengetahui sistem penyajian data yang diterapkan yaitu secara manual, kemudian muncul gagasan menggunakan aplikasi Google Earth yang digunakan untuk menyajikan data komoditi unggulan khususnya komoditi unggulan batik. Dengan adanya perubahan sistem penyajian data ini Dinas Perindustrian dan Perdagangan kabupaten Sukoharjo lebih terbantu dalam menemukan lokasi-lokasi produksi batik di kabupaten Sukoharjo. Sehingga Dinas Perindustrian dan Perdagangan kabupaten Sukoharjo dapat dengan mudah dalam memantau perkembangan produsen komoditi unggulan. Ada sebanyak 36 data komoditi batik yang berhasil disajikan ke dalam Google Earth dari 36 data komoditi batik kabupaten Sukoharjo.   Kata kunci— GIS, Google Earth, Komoditi Batik
Bayes Theorem and Forward Chaining Method On Expert System for Determine Hypercholesterolemia Drugs Perbawawati, Anna Adi; Sugiharti, Endang; Muslim, Much Aziz
Scientific Journal of Informatics Vol 6, No 1 (2019): Mei 2019
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v6i1.14149

Abstract

The development of technology capable to imitating the process of human thinking  and led to a new branch of computer science named the expert system. One of the problem that can be solved by an expert system is selecting hypercholesterolemia drugs.  Drug selection starts from find the symptoms and then determine the best drug for the patient. This is consist with the mechanism of forward chaining which starts from searching for information about the symptoms, and then try to illustrate the conclusions. To accommodate the missing fact, expert systems can be complemented with the Bayes theorem that provides a simple rule for calculating the conditional probability so the accuracy of the method approaches the accuracy of the experts. This reseacrh uses 30 training data and 76 testing data of medical record that use hypercholesterolemia drugs from Tugurejo Hospital of Semarang. The variable are common symptoms and some hypercholesterolemia drugs. This research obtained a selection of hypercholesterolemia drugs system with 96.05% accuracy
Improve the Accuracy of Support Vector Machine Using Chi Square Statistic and Term Frequency Inverse Document Frequency on Movie Review Sentiment Analysis Larasati, Ukhti Ikhsani; Muslim, Much Aziz; Arifudin, Riza; Alamsyah, Alamsyah
Scientific Journal of Informatics Vol 6, No 1 (2019): Mei 2019
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v6i1.14244

Abstract

Data processing can be done with text mining techniques. To process large text data is required a machine to explore opinions, including positive or negative opinions. Sentiment analysis is a process that applies text mining methods. Sentiment analysis is a process that aims to determine the content of the dataset in the form of text is positive or negative. Support vector machine is one of the classification algorithms that can be used for sentiment analysis. However, support vector machine works less well on the large-sized data. In addition, in the text mining process there are constraints one is number of attributes used. With many attributes it will reduce the performance of the classifier so as to provide a low level of accuracy. The purpose of this research is to increase the support vector machine accuracy with implementation of feature selection and feature weighting. Feature selection will reduce a large number of irrelevant attributes. In this study the feature is selected based on the top value of K = 500. Once selected the relevant attributes are then performed feature weighting to calculate the weight of each attribute selected. The feature selection method used is chi square statistic and feature weighting using Term Frequency Inverse Document Frequency (TFIDF). Result of experiment using Matlab R2017b is integration of support vector machine with chi square statistic and TFIDF that uses 10 fold cross validation gives an increase of accuracy of 11.5% with the following explanation, the accuracy of the support vector machine without applying chi square statistic and TFIDF resulted in an accuracy of 68.7% and the accuracy of the support vector machine by applying chi square statistic and TFIDF resulted in an accuracy of 80.2%.
The Implementation of The Neuro Fuzzy Method Using Information Gain for Improving Accuracy in Determination of Landslide Prone Areas Astuti, Winda Try; Muslim, Much Aziz; Sugiharti, Endang
Scientific Journal of Informatics Vol 6, No 1 (2019): Mei 2019
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v6i1.16648

Abstract

The accuracy of information is increasing rapidly as technological development. For the example, the information in determination of disaster severity. The disasters that can be determined is landslide. This determination can be conducted using the fuzzy method. One of method is neuro fuzzy. Neuro fuzzy is a combined method of two systems, fuzzy logic and artificial neural network. The accuracy of neuro fuzzy method can be increased by applying the information gain. The purpose of this study is to implement and to know the accuracy of the implementation of information gain as the selection of landslide data features. It conducted to the neuro fuzzy method in determining landslide prone areas. The distribution of training data and testing data was using 20 k-fold cross validation. The implementation of the neuro fuzzy method on landslide data was obtained an accuracy of 81.9231%. In the implementation of the neuro fuzzy method with information gain was conducted in classification process. The process will stop when the accuracy has decreased. The highest accuracy result was obtained of 88.489% by removing an attribute. So, it can be concluded the accuracy increase of 6.5659% in the implementation of the neuro fuzzy method and information gain in determination of landslide prone areas.
Implementasi Logika Fuzzy Mamdani untuk Mendeteksi Kerentanan Daerah Banjir di Semarang Utara Arifin, Saiful; Muslim, Much Aziz; Sugiman, Sugiman
Scientific Journal of Informatics Vol 2, No 2 (2015): November 2015
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v2i2.5086

Abstract

Kerentanan (Vuinerability) adalah keadaan atau kondisi yang dapat mengurangi kemampuan masyarakat untuk mempersiapkan diri menghadapi bahaya atau ancaman bencana. Logika Fuzzy adalah cara untuk memetakan suatu ke dalam suatu ruang output. Salah satu aplikasi logika Fuzzy adalah untuk menentukan kerentanan daerah banjir di Semarang Utara. Pengujian dilakukan dengan metode Mamdani Fuzzy Inference System. secara manual dan program menggunakan 5 defuzifikasi, yaitu Centroid, SOM (Smallest Of Maximum), LOM (Large Of Maximum), MOM (Mean Of Maximum), Bisector. Dari 2 contoh kasus diperoleh hasil pengujian dengan kesimpulan yang sama.
Implementasi Cloud Computing Menggunakan Metode Pengembangan Sistem Agile Muslim, Much Aziz; Retno, Nur Astri
Scientific Journal of Informatics Vol 1, No 1 (2014): May 2014
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v1i1.3639

Abstract

Cloud computing merupakan sebuah teknologi yang menyediakan layanan terhadap sumber daya komputasi melalui sebuah jaringan. Sumber daya yang di sediakan di dalam cloud computing meliputi mesin, media penyimpanan data, sistem operasi dan program aplikasi. Fitur dari cloud computing dipercaya akan jauh lebih hemat dan memuaskan. Masalah yang muncul adalah bagaimana mengimplementasi Cloud Computing dengan menggunakan Windows Azure Pack dan bagaimana provisioning Windows Azure Pack SQL Database. Fokus pada penelitian ini adalah pada proses deploying dan provisioning SQL Database Server. Pengimplementasian cloud computing menggunakan metode pengembangan sistem agile dengan langkah-langkah meliputi perencanaan, implementasi, pengujian (test), dokumentasi, deployment dan pemeliharaan. Untuk menjalankan proses tersebut kebutuhan perangkat yang dipersiapkan meliputi perangkat keras seperti PC Server Cisco UCS C240 M3S2, Hardisk 8753 GB, 256 GB RAM, bandwith minimal 1 Mbps dan kebutuhan perangkat lunak meliputi Windows Server 2012 R2, VMM, Windows Azure Pack, IIS, SQL Server 2012 dan Web Patform Installer. Hasil dari implementasi cloud computing menggunakan metode pengembangan sistem agile adalah terbentuknya sebuah sistem cloud hosting provider dengan menggunakan Windows Azure Pack dan SQL Server 2012 sebagai sistem utama dan pengelolaan database menggunakan Microsoft SQL Server Management
Penyajian Data Pelanggan pada Lima Area PT. Telekomunikasi Indonesia, Tbk. Kandatel Pekalongan Menggunakan Google Earth Muslim, Much Aziz; Pramesti, Atikah Ari
Scientific Journal of Informatics Vol 1, No 2 (2014): November 2014
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v1i2.4026

Abstract

Prosedur sistem penyajian data pelanggan di PT. Telekomunikasi Indonesia, Tbk. Kandatel Pekalongan khususnya bidang Divisi Business Services masih menggunakan cara manual, hanya menggunakan media Micorsoft Excel. Dalam hal ini peneliti ingin menerapkannya dalam bentuk aplikasi Google Earth untuk membuat penyajian data pelanggan, karena Google Earth dapat memetakan bumi dari superimposisi gambar yang dikumpulkan dari pemetaan satelit, fotografi udara dan globe GIS tiga dimensi sehingga akan menghasilkan data yang akurat. Penyajian data dengan menggunakan Google Earth dilakukan dengan memanfaatkan bahasa markup HTML. Dengan cara ini, Divisi Business Service akan menjadi lebih mudah ketika menyajikan data-data para pelanggan Telkom yang mencakup lima area yaitu Batang, Pekalongan, Pemalang, Tegal dan Brebes.
Co-Authors Afifah Ratna Safitri Agus Harjoko Ahmad, Kamilah Alabid, Noralhuda N. Alamsyah - Aldi Nurzahputra Aldi Nurzahputra, Aldi Alfatah, Abdul Muis Alfatah, Abdul Muis Ali, Muazam Amanah Febrian Indriani Aminuyati Anggyi Trisnawan Putra Annegrat, Ahmed Mohamed Astuti, Winda Try Astuti, Winda Try Atikah Ari Pramesti, Atikah Ari Budi Prasetiyo Budi Prasetiyo, Budi Darmawan, Aditya Yoga Dewi Handayani Untari Ningsih Dinova, Dony Benaya Djuniharto Djun Doni Aprilianto Dullah, Ahmad Ubai Eka Listiana Endang Sugiharti, Endang Fadhilah, Muhammad Syafiq Fadli Dony Pradana Falasari, Anisa Farih, Habib al Florentina Yuni Arini, Florentina Yuni Hadiq, Hadiq Hakim, M. Faris Al Hakim, Roshan Aland Hendi Susanto Imam Ahmad Ashari, Imam Ahmad Irfan, Mohammad Syarif Jeffry Nur Rifa’i Jumanto , Jumanto Jumanto Jumanto, Jumanto Jumanto Unjung Khan, Atta Ullah Larasati, Ukhti Ikhsani Larasati, Ukhti Ikhsani Lestari, Apri Dwi Listiana, Eka Listiana, Eka Maulana, Muhamad Irvan Miranita Khusniati moh minhajul mubarok Muhamad Anbiya Nur Islam Mustaqim, Amirul Muzayanah, Rini Nikmah, Tiara Lailatul Nina Fitriani, Nina Ningsih, Maylinna Rahayu Nugraha, Faizal Widya Nur Astri Retno, Nur Astri Nurdin, Alya Aulia Nurriski, Yopi Julia Perbawawati, Anna Adi Perbawawati, Anna Adi Pertiwi, Dwika Ananda Agustina Priliani, Erlin Mega Priliani, Erlin Mega Purnawan, Dedy Putri Utami, Putri Putri, Salma Aprilia Huda Putriaji Hendikawati Putro, Ari Nugroho Qohar, Bagus Al Raharjo, Bagus Purbo Rahman, Raihan Muhammad Rizki Rahmanda, Primana Oky Rahmanda, Primana Oky Riza Arifudin Rofik Rofik, Rofik Roni Kurniawan Rukmana, Siti Hardiyanti Ryo Pambudi S.Pd. M Kes I Ketut Sudiana . Safri, Yofi Firdan Safri, Yofi Firdan Saiful Arifin Salahudin, Shahrul Nizam Sanjani, Fathimah Az Zahra Seivany, Ravenia Simanjuntak, Robert Panca R. Solehatin, Solehatin Sugiman Sugiman Sulistiana Syarifah, Aulia Tanga , Yulizchia Malica Pinkan Tanga, Yulizchia Malica Pinkan Tanzilal Mustaqim Trihanto, Wandha Budhi Trihanto, Wandha Budhi Triyana Fadila Varindya Ditta Iswari Vedayoko, Lucky Gagah Vedayoko, Lucky Gagah Wibowo, Kevyn Alifian Hernanda Yosza Dasril Yosza Dasril