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All Journal Pixel : Jurnal Ilmiah Komputer Grafis JURTEKSI Jurnal Review Pendidikan dan Pengajaran (JRPP) Jurnal Manajemen Informatika dan Sistem Informasi Jambura Journal of Electrical and Electronics Engineering JATI (Jurnal Mahasiswa Teknik Informatika) JISA (Jurnal Informatika dan Sains) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal IPTEK Bagi Masyarakat Jurnal ABDIMAS Budi Darma Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer (JURITEK) Ilmu Komputer untuk Masyarakat Jurnal Informatika Teknologi dan Sains (Jinteks) SainsTech Innovation Journal Internet of Things and Artificial Intelligence Journal Journal of Artificial Intelligence and Digital Business ETIK (Jurnal Elektronika Terapan dan Ilmu Komputer) Jurnal Pengabdian Bersama Masyarakat Indonesia

Saikin

STMIK Lombok

Author-ID : 2968286

Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

Published : 26 Documents Claim Missing Document

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MODEL DATA MINING UNTUK KAREKTERISTIK DATA TRAVELLER PADA PERUSAHAAN TOUR AND TRAVEL Saikin Saikin; Kusrini Kusrini
Jurnal Manajemen Informatika dan Sistem Informasi Vol. 2 No. 2 (2019): MISI Juni 2019
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/misi.v2i2.105

Bagi perusahaan yang bergerak dibidang sektor jasa, seperti perusahaan tour and travel pengolahan data sangatlah penting untuk mengetahui karakteristik atau minat wisatawan dalam berwisata. Sulitnya memprediksi kebutuhan atau minat wisatawan, merupakan kendala yang dihadapi perusahaan tour and travel sehingga manajemen harus dapat mengambil keputusan yang tepat dan cepat, guna memberikan pelayanan yang baik serta kepuasan kepada customer. Keputusan yang diambil harus mempertimbangkan dengan baik berdasarkan data-data yang dimiliki terutama yang berkaitan erat dengan karakteristik data traveller. Analisis data untuk mencari pola karakteristik data dari traveler memutuhkan metode yang baik dan hasil yang akurat , sehingga hasil dari analisis tersebut dapat menemukan informasi yang berguna bagi perusahaan. Metode pengeolahan data yang sering digunakan ialah data mining. K-Nearest Neighbour (K-NN) merupakan salah satu algoritma data mining yang cara kerjanya menerapkan pembelajaran pada data. Tujuan dari penelitian ini akan melakukan analisis data travellers atau wisatawan pada perusahaan tour and travel dengan menggunakan algoritma K-NN untuk mencari minat atau karakteristik wisatawan dalam memilih objek wisata. Pada hasil kualifikasi metode K-NN dan pengujian dengan metode confusion matrix nilai akurasi yang didapat 84%, nilai presisi 88%, nilai recall 85 dan nilai f1-score 85%. Pada hasil kualifikasi menunjukan bahwa objek wisata yang cenderung dominan menjadi minat wisatawan ada pada objek wisata pantai.Berdasarkan hasil analisis dengan menggunakan kedua metode tersebut bahwa karakteristik wisatawan cendrung memilih paket nomor 3 yakni Reguler Tour Lombok Packagage, dan objek wisata yang dominan minat wisatawan yakni objek wisata pantai dan disusul oleh objek wisata gili.

PENERAPAN DATA MINING UNTUK MEMPREDIKSI PENJUALAN KAIN TENUN MNGGUNAKAN REGRESI LINEAR Firda Widia; Wafiah Murniati; Saikin
Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer Vol 2 No 1 (2022): Maret, Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer
Publisher : Sekolah Tinggi Ilmu Ekonomi Trianandra

Abstract Weaving craft is one of the handicrafts located in Lombok, West Nusa Tenggara. Weaving is one of the MSMEs that is very close to the tourism industry and has good economic potential because it absorbs a lot of labor, opens up business fields, and increases the country's foreign exchange. The problem that is often faced by entrepreneurs of woven fabrics is the difficulty in estimating customer demand, so that some of the products requested by customers are not available. It is necessary for sales analysis of woven fabric products to be able to predict customer demand, by means of analyzing past sales data to predict future sales. The research that will be carried out is to predict sales of woven fabric products by processing sales data in the past by modeling the Linear Regression method, and for testing the algorithm is by Mean Square Error (MSE), Mean Square Error (MSE) and Root Mean Square Error. (RMSE). From the results of linear regression modeling the score obtained is 0.8041320270845731. and the test results mean Mean Square Error (MSE) the error value obtained is too high, namely 47,377, and the Root Mean Square Error (RMSE) value is 6.883125, while the MAE score is 3.373572.

Pembuatan Vidio Profil Sebagai Penunjang Informasi Dan Promosi Cagar Budaya Di Lombok Tengah Suhaini Suhaini; Sofiansyah Fadli; Maemun Saleh; Lalu Mutawalli; Hairul Fahmi; Maulana Ashari; Saikin Saikin
Jurnal ABDIMAS Budi Darma Vol 2, No 2 (2022): Februari 2022
Publisher : STMIK Budi Darma

Indonesia is one of the countries with the most favorite tourist objects in the world. There are many cultures, customs and natural beauty that are still preserved. One type of tourism that is closely related to history and ancestral heritage is cultural heritage. Cultural heritage has a high historical value and witnesses the civilization of life on earth. One of the districts in West Nusa Tenggara, namely Central Lombok Regency, has 150 cultural heritages spread across various sub-districts. 7 of these cultural heritages have been recorded at the national and even international levels. However, due to limited sources of information and access to cultural heritage sites, tourists and local people do not know the locations and history of the cultural heritage sites. So that research is carried out with the aim of obtaining valid data and information to be promoted in the form of videos that can be watched by anyone, anywhere and anytime via YouTube and can be used as a medium of learning about the life history of the ancestors of the Sasak tribe in Central Lombok Regency.In the research conducted, the researchers collected data and information by means of literature study, observation and direct interviews to cultural heritage locations and the Tourism Office of Central Lombok Regency. Method of analysis with SWOT (Strengths, Weaknesses, Opportunities, Threats). The design method uses the multimedia production process flow method with Adobe Audition software as audio editing and Adobe Premiere Pro 2020 as video editing. And the questionnaire test is used to obtain responses from the respondents by calculating the Likert scale

Implementation of Data Mining on Tourist Visits Patterns on Lombok Island Tourism Objects Sofiansyah Fadli; Saikin Saikin; Maulana Ashari
JISA(Jurnal Informatika dan Sains) Vol 5, No 1 (2022): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v5i1.1062

Foreign tourists entering Indonesia in 2017 and 2018 have increased. From the data obtained on the website of the Ministry of Tourism (Kemenpar) the number of foreign tourists in 2017 was 14,039,799, while in 2018 there were 15,806.1, with a comparison of the number of tourists from the two years, the percentage increase in tourists was 12.58%. The data analysis approach using a classification model is a data analysis approach by studying the data and making predictions with the new data. in the classification model, there are many algorithms that can be applied in data analysis, one of which is the Decision Tree algorithm. This study aims to analyze the pattern of tourist visits based on the objects visited by the number of tourists visiting certain tourist objects. From the modeling using the Decesion Tree C4.5 Algorithm and the scenario of splitting the data into three parts, the highest accuracy value was obtained for splitting data of 80:20 for train and testing data and max depth 7, which obtained an accuracy of 94% for train data and 92% for data. testing. Modeling with the Boostrap Aggregating Method, the accuracy score obtained on training data is 93% and testing data is 92. percent. 3 accuracy results from using bagging reduce the accuracy of the C4.5 algorithm on the data training side from 94% to 93 percent, while the accuracy of testing data is still the same, namely 92%.

Optimization of Support Vector Machine Method Using Feature Selection to Improve Classification Results Saikin Saikin; Sofiansyah Fadli; Maulana Ashari
JISA(Jurnal Informatika dan Sains) Vol 4, No 1 (2021): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v4i1.881

The performance of the organizations or companiesare based on the qualities possessed by their employee. Both of good or bad employee performance will have an impact on productivity and the impact of profits obtained by the company. Support Vector Machine (SVM) is a machine learning method based on statistical learning theory and can solve high non-linearity, regression, etc. In machine learning, the optimization model is a part for improving the accuracy of the model for data learning. Several techniques are used, one of which is feature selection, namely reducing data dimensions so that it can reduce computation in data modeling. This study aims to apply the method of machine learning to the employee data of the Bank Rakyat Indonesia (BRI) company. The method used is SVM method by increasing the accuracy of learning data by using a feature selection technique using a wrapper algorithm. From the results of the classification test, the average accuracy obtained is 72 percent with a precision value of 71 and the recall value is rounded off to 72 percent, with a combination of SVM and cross-validation. Data obtained from Kaggle data, which consists of training data and testing data. each consisting of 30 columns and 22005 rows in the training data and testing data consisting of 29 col-umns and 6000 rows. The results of this study get a classification score of 82 percent. The precision value obtained is rounded off to 82 percent, a recall of 86 percent and an f1-score of 81 percent.

SISTEM PENDUKUNG KEPUTUSAN PENERIMAAN MURID BARU MENGGUNAKAN METODE AHP DAN SAW Maulana Ashari; Siti Halimatun Jannah; Sofiansyah Fadli; Saikin
Pixel :Jurnal Ilmiah Komputer Grafis Vol 14 No 2 (2021): Jurnal Ilmiah Komputer Grafis
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/pixel.v14i2.592

The decision support system as a tool for decision making, has now begun to be widely applied in various fields of life, not least in making a decision for the process of accepting new students at the MA Sabilurrasyad NW Barabaliused. With the decision support system (SPK) can help schools in the selection of new students. The method used in building a decision support system in this research is the Analytical Hierarchy Process (AHP). The method used to select new students is the Analytical Hierarchy Process (AHP) which functions to calculate the final score of each student in the school and the Simple Additive Weighting (SAW) serves to rank each student.The result of this study is that the combination of the AHP (Analytical Hierarchy Process) and SAW (Simple Additive Weighting) methods in determining new student admissions at the MA Sabilurrasyad NW Barabali School can be used. SPK (Decision Making System) can display information according to what the user inputs correctly.

Sistem Pendukung Keputusan Penentuan Keluarga Miskin Menggunakan Metode Fuzzy Tsukamoto Sofiansyah Fadli; Maulana Ashari; Saikin Saikin
Journal of Information System Research (JOSH) Vol 4 No 1 (2022): October 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

The government, in this case the ministry of national development planning the Republic of Indonesia/national development planning agency has tried to reduce poverty in each region. With articulated the various poverty alleviation programmes, including the presence of cluster I, cluster II, cluster III and cluster IV. Social assistance programs launched by the Government, in particular the first Cluster program got more attention from the citizens of society. There are 14 poverty criteria, which became the reference of criteria for Badan Pusat Statistik (BPS) in determining the poor families that eligible to receive aid from the Government. Poor and not poor membership has a value of 0 and 1, were in fact, poverty has different levels. Determination of the poverty program at this time there is a problem in terms of decision-taking which there are to many subjectivity, for example which is not poor is said to be poor in the data recording/logging. In this paper, a computerized system for determining of a poor family. The method used in this studyis developed Fuzzy Tsukamoto. Tsukamoto Fuzzy method used in the process of selection by holding against 14 criteria. Output of the system can facilitate the Management of the village in taking decisions to determine the recipients of the aid programs initiated by the Governmen. The results based on the accuracy test that has been carried out using a data sample of 7 RUTA, the results obtained are 0.568 (very poor), 0.684 (poor), 0.506 (very poor), 0.697 (poor), 0.577 (very poor), 0.609 (poor). ), and 0.625 (poor). The poverty rate (Fuzzy Results) with Recommendations (Expert Validation) show the same results or results so that the Fuzzy Tsukamoto method can be applied well in poor families in Darmaji Village.

MODEL FORMAL UNTUK MEMPREDIKSI FAKTOR KEBERHASILAN UMKM DI MASA PANDEMI Lalu Mutawalli; Saikin; Gilang Restu Imam Wahyudi
Jurnal Informatika Teknologi dan Sains Vol 4 No 4 (2022): EDISI 14
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

MSMEs are one of the supports of the Indonesian economy, the impact of Covid 19 affects the decline in MSMEs in all regions of Indonesia including in Lombok. Since Pandemic Indonesia has implemented a policy of restrictions on various sectors including tourism. Restrictions impact the lack of tourist visits in Lombok it affects the growth of MSMEs in Lombok. However, some MSMEs have managed to survive even though the conditions of tourism in Lombok are still not normal. The study of the success of MSMEs that succeeded in surviving the Pandemic was needed to gain knowledge about strategies that could strengthen MSMEs. This study uses a FCA as a methodology to make an analysis. The analysis results show discounts and save money in banks, sales on medsos have the highest support of 93%, teamwork and extent capital sources of 87%, PCS, from PC, reciprocity to customers, business development training, Sales with Facebook, also business liquidity is considered sufficient at the same extent point, namely 80%, source of personal capital, product prices with market prices, CS is considered good at the same extent point, which is 73%, there is only one intent Has an extent 67% following training from the government.

Web Edukasi Untuk Pencegahan Pernikahan Dini Menggunakan Metode Waterfall Di Desa Beraim Haekal Fawaid; Saikin; Ahmad S. Pardiansyah; Yuan Sa'adati
SainsTech Innovation Journal Vol. 6 No. 1 (2023): SIJ Volume 6 Nomor 1 Mei 2023
Publisher : LPPM Universitas Qamarul Huda Badaruddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37824/sij.v6i1.2023.389

Pada penelitian ini kami mengembangkan sebuah media edukasi berbentuk website untuk pencegahan pernikahan dini. Metode pengembangan untuk sistem yang kami gunakan adalah metode waterfall. Alasan pemilihan metode ini karena intensnya komunikasi antara pengembang dan pengguna aplikasi, sehingga aplikasi yang dibangun dapat diperbaiki secara berkelanjutan (maintenace). Terdapat beberapa kanal yang kami sediakan dalam rangka memberikan informasi seputar pencegahan pernikahan dini, pernikahan, keluarga, dan kanal latihan soal yang kami tujukan sebagai sarana Tanya jawab dengan pakar di bidang kesehatan keluarga. Berdasarkan hasil pengujian menggunakan metode pengujian blackbox didapatkan hasil yang sesuai untuk semua fitur yang ada dalam aplikasi. Penelitian selanjutnya akan dilakukan pengembangan, perbaikan maupun penambahan fitur berdasarkan hasil masukan dan evaluasi dari pengguna aplikasi. Pernikahan merupakan salah satu fase dalam kehidupan yang mana mayoritas manusia dewasa akan mengalaminya.

EVALUASI USABILITY SISENSI MOBILE MENGGUNAKAN METODE ISO/IEC 9126 DAN NIELSEN MODEL Ayu Lestari; Wafiah Murniati; Saikin; Hasyim Asyari
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 6 No 2 (2024): EDISI 20
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v6i2.4123

The Mobile Attendance and Presence Information System (SISENSI) is an online attendance application that has problems or shortcomings, such as requiring a long time to be absent and lacking a leave permit feature so that users have difficulty applying for leave permission. Therefore, the aim of this research is to test the SISENSI mobile application to determine the quality and shortcomings of the application. The usability evaluation methods that will be used are ISO/IEC 9126 and Nielsen Model. The results of combining ISO/IEC 9126 and the Nielsen Model obtained eight SISENSI Mobile testing factors in the usability field, namely understandability, learnability, operability, attractiveness, memorability, efficiency, errors, and user satisfactions. Respondents in this study were 164 people. The results of this research obtained values for each sub-characteristic namely: understandability 84%, learnability 80%, operability 80%, attractiveness 69%, efficiency 82%, memorability 67%, errors 75% and user satisfactions 65%. Meanwhile, the average value is 75%, so overall SISENSI Mobile is in good condition.

Co-Authors Ahmad S. Pardiansyah Akbar, Jihadul Amrina Rosada, Amrina Apriati, Yati Ayu Lestari Cahyanti, Riska Indah Didik Sudyana Didik Sudyana Fadli, Sofiansyah Fahmi , Hairul Fahmi, Hairul Fauzi Zulkarnain, Mohammad Febrian, Melyana Firda Widia Gilang Restu Imam Wahyudi Haekal Fawaid Hairul Fahmi Handayani, Yudiana Tutik Hasyim Asyari Husnul Khotimah Ichwan Purwata Indah Cahyanti, Riska Kusrini Kusrini Lalu Mutawalli Maemun Saleh Maulana Ashari Mohammad Taufan Asri Zaen Muliana, Muliana Musofa, Aolia Pirmansyah Pirmansyah Riska Indah Cahyanti Saeful Hamdi Sari, Kadek Dwijayanti Komala Septiani, Ria Siti Halimatun Jannah Sofiansyah Fadli Suhaini Suhaini Tantoni, Ahmad Wafiah Murniati Wahyu Hadi, Wahyu Wire Bagye Yuan Sa'adati

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