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Perbandingan Akurasi Klasifikasi Citra Kayu Jati Menggunakan Metode Naive Bayes dan k-Nearest Neighbor (k-NN) Waliyansyah, Rahmat Robi; Fitriyah, Citra
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 5, No 2 (2019): Volume 5 No 2
Publisher : Program Studi Informatika

Indonesia saat ini merupakan salah satu produsen terbesar produk yang terbuat dari kayu. Kayu-kayu tersebut tidak semuanya memiliki nilai jual. Kayu jati merupakan salah satu kayu yang memiliki nilai jual yang tinggi, baik skala nasional maupun internasional. Pengelompokkan jenis kayu jati menggunakan beberapa parameter yaitu tekstur, berat, warna dan lain sebagainya. Pengelompokkan jenis kayu jati biasanya memiliki subjektifitas yaitu ketergantungan dari mata manusia (ahli/pakar). Oleh karena itu diterapkanlah teknologi untuk membantu dalam menganalisis suatu tekstur kayu jati agar bisa diklasifikasikan ke dalam kelompok-kelompok tertentu. Pada penelitian ini jenis kayu jati yang digunakan ada 3 : semarangan, blora dan sulawesi. Proses klasifikasi jati menggunakan pengolahan citra digital dengan Metode Naive Bayes dan k-Nearest Neighbor (k-NN). Analisis yang digunakan adalah tekstur dengan Metode Gray Level Co-occurrence Matrix (GLCM) dan jarak spasial adalah 1 piksel. Berdasarkan hasil pengujian dan analisis, Metode k-NN secara umum baik dalam mengklasifikasikan 3 jenis kayu jati yaitu semarangan, blora dan sulawesi dengan tingkat akurasi di atas 70%. Akan tetapi klasifikasi paling baik untuk jenis kayu jati sulawesi dengan Metode Naive Bayes, tingkat akurasinya sebesar 82,7%.

PENGELOLAAN LIMBAH DAN OPTIMALISASI SOSIAL MEDIA SEBAGAI PEMASARAN ONLINE DI DESA JAWISARI, KECAMATAN LIMBANGAN, KABUPATEN KENDAL PROVINSI JAWA TENGAH Robi Waliyansyah, Rahmat; Wibowo, Setyoningsih; Budirahardjo, Slamet
Join Vol. 1 No. 2 (2020): September 2020
Publisher : Program Studi Informatika Fakultas Teknik dan Informatika

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Desa jawisari memiliki beberapa pelaku usaha umkm pengolahan keripik kimpul Permasalahan yang dihadapi adalah belum maksimal dalam pengelolaan limbah dan pemasaran. Masyarakat desa dan pelaku umkm memiliki keinginan untuk menambah pengetahuan dan ketrampilan dalam pengelolaan limbah dan pengembangan pemasaran online. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk pemberdayaan masyarakat desa dan pelaku umkm di Desa Jawisari, Kecamatan Limbangan, Kabupaten Kendal melalui kegiatan pengabdian masyarakat dalam pengelolaan limbah agar terbebas dari bahaya limbah dan lingkungan semakin sehat serta pemanfaatan social media sebagai pemasaran online yang dapat memperluas pemasaran. Luaran yang dihasilkan dari pengabdian ini antara lain pengelolaan limbah agar tidak berkonotasi negarif namun dapat dimanfaatkan dan optimalisasi penggunaan smartphone dengan memanfaatkan social media (whatsapp, instagram dan facebook) sebagai pemasaran online. Kegiatan ini dilakukan melalui tahapan sosialisasi, pelatihan dan yang terakhir diadakan evaluasi. Pemahaman tentang pengelolaan limbah mengalami peningkatan 61.61%, sedangkan untuk pemanfaatan social media sebagai pemasaran online 60.63%.

Sistem Pakar Pembagian Harta Waris Menurut Hukum Islam Aksin, Nur; Waliyansyah, Rahmat Robi; Saputro, Nugroho Dwi
Walisongo Journal of Information Technology Vol 2, No 2 (2020): Walisongo Journal of Information Technology
Publisher : Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/wjit.2020.2.2.5984

In general, Muslims regarding the distribution of inheritance and calculation procedures lack understanding and the difficulty of also getting experts in the field of inheritance distribution according to Islamic law (faraidh), this is an issue for the Muslim community, especially for heirs who want to divide inheritance according to law Islam. The author uses backward chaining methods in designing expert systems. The result of this research is the design of an expert system for dividing inheritance that can be used by the general public to help Islam solve the problem of calculation inheritance.

Driving Factors Affecting Lecturers and Employees Performance During the Covid-19 Pandemic Qristin violinda; Suwarno Widodo; Mahmud Yunus; Istiyaningsih Istiyaningsih; Rahmat Robi Waliyansyah
JPBM (Jurnal Pendidikan Bisnis dan Manajemen) Vol 7, No 2: SEPTEMBER 2021
Publisher : JPBM (Jurnal Pendidikan Bisnis dan Manajemen)

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The Covid-19 pandemic has enhanced business competition at both public and private universities. As a consequence, the competition encourages universities to promote a creative strategy. To deal with this issue, this study examines the driving factors affecting lecturers and employees at PGRI University Semarang during the Covid-19 Pandemic. The sample was selected using simple random sampling with a total of 206 respondents consisting of 81 employees and 125 lecturers. The measurement of the study adopted a Likert scale, and the data obtained were processed using Partial Least Square (PLS). The results of the study indicate that there is a direct influence of employee management on organizational culture. Additionally, this study remarks that a robust correlation between organizational learning and organizational culture as well as organizational culture can promote the performance of lecturers and employees. Lastly, there is no direct influence of employee arrangement on the performance of lecturers and employees. The largest total effect on the performance of lecturers and employees is organizational learning, which includes a direct effect of 39.3 percent and an indirect effect through the organizational culture of 21.9 percent. Keywords: Staffing Practices, Organizational Learning, organizational culture, employee performance

Diseminasi Teknologi Pengelolaan Pam Desa “SIPAMDES” Berbasis Website di Desa Kaligading Mega Novita; Rahmat Robi Waliyansyah; Nugroho Dwi Saputro; Bambang Agus Herlambang
COMVICE: Journal Of Community Service Vol. 6 No. 1 (2022): April (2022)
Publisher : STIE PGRI Dewantara Jombang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26533/comvice.v6i1.860

Desa Kaligading yang terletak di Kecamatan Boja, Kabupaten Kendal, Provinsi Jawa Tengah, memiliki usaha pengadaaan air bersih yang diperoleh dari sumur bor yang dikelola oleh 6 titik wilayah. Seluruh saluran mulai dari mata air hingga siap pakai oleh konsumen didukung dengan ketersediaan Perusahaan Air Minum (PAM). Sayangnya, pengelolaan PAM di Desa Kaligading masih belum baik, karena masih menggunakan metode manual yaitu pencatatan oleh petugas tiap bulan berdasarkan catatan petugas. Kegiatan pengabdian kepada masyarakat ini dilakukan oleh tim penulis berupa diseminasi teknologi pengelolaan dan pencatatan penggunaan air yang disebut SIPAMDES. Kegiatan ini dapat diselesaikan dengan baik dan membawa manfaat yaitu: 1) membatu pengurus PAM Desa dalam mengola data, 2) melayani proses pembayaran dan informasi dengan lebih cepat, lengkap dan akurat, 3) pelanggan dapat mengetahui informasi tagihan atau tunggakan yang belum dibayar, 4) pelanggan dapat menyampaikan pengaduan.

Program Kemitraan Masyarakat BUDISDAMBER (Budidaya Ikan dan Sayur Dalam Ember) RT 08 RW X Kelurahan Kembangarum Kecamatan Semarang Barat Slamet Budirahardjo; Setyoningsih Wibowo; Rahmat Robi Waliyansyah; Bagus Priyatno
Indonesian Journal of Community Services Vol 3, No 1 (2021): May 2021
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/ijocs.3.1.47-55

Secara umum warga RT 08 RW X Kelurahan Kembangarum Kecamatan Semarang Barat Kota Semarang berjumlah 40 (empat puluh) Kepala Keluarga. Sebagian besar warga bermata pencaharian sebagai buruh. Dimasa pandemi seperi ini perekonomian warga menjadi sangat memprihatinkan, banyak pabrik-pabrik/industri/tempat bekerja warga mengalami kerugian yang akibatnya beberapa warga kena PHK. Sementara kebutuhan pangan setiap hari untuk keluarga harus terpenuhi. Kegiatan pendampingan warga dimasa pandemic seperti ini sangatlah dibutuhkan dan sangat membantu warga. Pendampingan merupakan salah satu pemberdayaan masyarakat dengan kata lain kegiatan yang mengikutsertakan warga dalam mengembangkan potensi yang ada di lingkungan warga, selain itu bertujuan untuk meningkatkan pengetahuan warga dan meningkatkan kesejahteraan warga. Dalam pendampingan ini kami bertugas sebagai pembimbing, perencana, pemotivasi, sumber informasi, penghubung, fasilitator sekaligus sebagai evaluator. Metode pendampingan ini melalui beberapa tahap, yaitu sosialisasi program, pemaparan materi tentang ketahanan pangan, materi tentang system Budisdamber dan diakhiri dengan evaluasi. Target dari kegiatan ini adalah terciptanya ketahanan pangan secara mandiri, bertambahnya pengetahuan tentang sistem Budisdamber yaitu budidaya ikan dan sayur dalam ember yang dapat dilakukan di lahan yang sempit. Dari hasil post test yang telah diisi oleh bapak/ibu peserta yang mendapatkan amanah untuk memelihara ikan dan sayur, tingkat pemahaman tentang ketahanan pangan sebesar 68.13% dan tingkat pemahaman tentang system budidaya ikan dan sayur dalam ember sebesar 57.50%. kesimpulan yang diambil bahwa warga sudah dapat mengaplikasikan pengetahuan ini sebagai bekal ketahanan pangan dengan memanfaatkan lahan sempitnya.In general, the residents of RT. 08 RW. X Kembangarum Village, West Semarang District, Semarang City, totaling 40 (forty) heads of families. Most of the residents work as laborers. During a pandemic like this, the economy of the people is very worrying, many factories / industries / workplaces of residents suffer losses, as a result some residents are laid off. Meanwhile, the daily food needs for the family must be fulfilled. Community assistance activities during a pandemic like this are very much needed and very helpful for residents. Assistance is one of community empowerment in other words, an activity that involves residents in developing the potential that exists in the community, besides that it aims to increase citizen knowledge and improve the welfare of residents. In this assistance, we serve as mentors, planners, motivators, sources of information, liaisons, facilitators as well as evaluators. This mentoring method takes several stages, namely program socialization, presentation of material on food security, material on the Budisdamber system and ending with an evaluation. The target of this activity is the creation of independent food security, increased knowledge of the Budisdamber system, namely the cultivation of fish and vegetables in buckets that can be done in a narrow area. From the results of the post tests that have been filled in by the participating fathers / mothers who received the mandate to raise fish and vegetables, the level of understanding of food security was 68.13% and the level of understanding of the fish and vegetable cultivation system in buckets was 57.50%. The conclusion was drawn that the residents were able to apply this knowledge as a provision for food security by utilizing their narrow land.

Identifikasi Jenis Biji Kedelai (Glycine Max L) Menggunakan Gray Level Coocurance Matrix (GLCM) dan K-Means Clustering Rahmat Robi Waliyansyah
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7, No 1: Februari 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

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Kacang kedelai merupakan tanaman pangan yang dapat diolah dalam berbagai olahan, seperti tempe & tahu. Indonesia mempunyai banyak varietas kedelai, varietas lokal atau impor. Meningkatnya konsumsi kedelai tersebut sangat dipengaruhi oleh pemilihan varietas dari kedelai tersebut. Tetapi hanya beberapa varietas saja yang dapat diolah dalam industri pengolahan kedelai, khususnya industri tahu & tempe. Untuk itu perlu adanya aplikasi identifikasi kedelai yang dapat membedakan varietas biji kedelai. Aplikasi untuk identifikasi jenis biji kedelai menggunakan pengolahan citra digital, dalam proses segmentasinya menggunakan Citra L*a*b dan K-Means Clustering. Ekstraksi ciri yang digunakan ada dua yaitu tekstur dan morfologi. Ekstraksi ciri tekstur menggunakan Metode Gray Level Coocurrence Matrix (GLCM) dengan jarak spasial 2 pixel. Parameter yang digunakan ada 4 yaitu energy, contrast, homogeneity & correlation.. Ekstraksi ciri morfologi menggunakan 2 parameter yaitu Metric dan Eccentricity. Ada pun varietas biji kedelai yang digunakan adalah : Anjasmoro, Burangrang, Dering-1, Dena-1, Demas-1 dan Grobogan untuk jenis varietas kedelai emas serta Detam-1, Detam-3, Detam-4 untuk jenis varietas kedelai hitam. Berdasarkan hasil pengujian, didapatkan tingkat akurasi sebesar 47% dari total 198 sampel citra uji biji kedelai dan 0% pada pengujian biji-bijian yang lain (kacang hijau) yang secara tekstur, bentuk dan warna mirip dengan kedelai (hitam). Hasil pengujian yang kurang baik ini disebabkan oleh belum maksimalnya data yang digunakan, karena sampel biji kedelai tidak selalu tersedia dan juga tiap jenis kedelai yang dipanen memiliki ukuran yang berbeda. AbstractSoybeans are food crops that can be processed in various preparations, such as tempeh & tofu. Indonesia has many varieties of soybeans, both local and imported varieties. Increased consumption of soybeans is strongly affected by the selection of varieties of soybeans. But only a few varieties that can be processed in soybean processing industry, in particular the tofu & tempe industry. Applications made using digital image processing, while the segmentation used is the Image L * a * b and K-Means Clustering. The feature extraction used is two, i.e. texture and morphology. The extraction of Texture feature was using the Gray Level Co-occurrence Matrix Method (GLCM) with a spatial distance of 2 pixels. The parameters used were 4, i.e. energy, contrast, homogeneity & correlation. Morphological feature extraction used 2 parameters, Metric and Eccentricity. There were also soybean seed varieties that were used: Anjasmoro, Burangrang, Dering-1, Dena-1, Demas-1 and Grobogan which are grouped into the types of golden soybean varieties, and Detam-1, Detam-3, Detam-4 for black soybean varieties. Based on the test results, an accuracy rate of 47% was obtained from a total of 198 samples of soybean seed test images. This unfavorable test result is caused by the lack of data used because soybean seed samples are not always available and also each type of soybean that grows has a different size.

Driving Factors Affecting Lecturers and Employees Performance During the Covid-19 Pandemic Qristin violinda; Suwarno Widodo; Mahmud Yunus; Istiyaningsih Istiyaningsih; Rahmat Robi Waliyansyah
JPBM (Jurnal Pendidikan Bisnis dan Manajemen) Vol 7, No 2: SEPTEMBER 2021
Publisher : JPBM (Jurnal Pendidikan Bisnis dan Manajemen)

Show Abstract | Download Original | Original Source | Check in Google Scholar

The Covid-19 pandemic has enhanced business competition at both public and private universities. As a consequence, the competition encourages universities to promote a creative strategy. To deal with this issue, this study examines the driving factors affecting lecturers and employees at PGRI University Semarang during the Covid-19 Pandemic. The sample was selected using simple random sampling with a total of 206 respondents consisting of 81 employees and 125 lecturers. The measurement of the study adopted a Likert scale, and the data obtained were processed using Partial Least Square (PLS). The results of the study indicate that there is a direct influence of employee management on organizational culture. Additionally, this study remarks that a robust correlation between organizational learning and organizational culture as well as organizational culture can promote the performance of lecturers and employees. Lastly, there is no direct influence of employee arrangement on the performance of lecturers and employees. The largest total effect on the performance of lecturers and employees is organizational learning, which includes a direct effect of 39.3 percent and an indirect effect through the organizational culture of 21.9 percent. Keywords: Staffing Practices, Organizational Learning, organizational culture, employee performance

Forecasting New Student Candidates Using the Random Forest Method Rahmat Robi Waliyansyah; Nugroho Dwi Saputro
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol 11 No 1 (2020): Vol. 11, No. 1 April 2020
Publisher : Institute for Research and Community Services, Udayana University

College education institutions regularly hold new student admissions activities, and the number of new students can increase and can also decrease. University of PGRI Semarang (UPGRIS) on the development of new student admissions for the 2014/2015 academic year up to 2018/2019 with so many admissions selection stages. To meet the minimum comparison requirements between the number of students with the development of human resources, facilities, and infrastructure, it is necessary to predict how much the number of students increases each year. To make a prediction system or forecasting, the number of prospective new students required a good forecasting method and sufficiently precise calculations to predict the number of prospective students who register. In this study, the method to be taken is the Random Forest method. For the evaluation of forecasting models used Random Sampling and Cross-validation. The parameter used is Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Coefficient of Determination (R2). The results of this study obtained the five highest and lowest study programs in the admission of new students. Therefore, UPGRIS will make a new strategy for the five lowest study programs so that the desired number of new students is achieved

Comparison of Tree Method, Support Vector Machine, Naïve Bayes, and Logistic Regression on Coffee Bean Image Rahmat Robi Waliyansyah; Umar Hafidz Asy'ari Hasbullah
EMITTER International Journal of Engineering Technology Vol 9 No 1 (2021)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v9i1.536

Coffee is one of the many favorite drinks of Indonesians. In Indonesia there are 2 types of coffee, namely Arabica & Robusta. The classification of coffee beans is usually done in a traditional way & depends on the human senses. However, the human senses are often inconsistent, because it depends on the mental or physical condition in question at that time, and only qualitative measures can be determined. In this study, to classify coffee beans is done by digital image processing. The parameters used are texture analysis using the Gray Level Coocurrence Matrix (GLCM) method with 4 features, namely Energy, Correlation, Homogeneity & Contrast. For feature extraction using a classification algorithm, namely Naïve Bayes, Tree, Support Vector Machine (SVM) and Logistic Regression. The evaluation of the coffee bean classification model uses the following parameters: AUC, F1, CA, precision & recall. The dataset used is 29 images of Arabica coffee beans and 29 images of Robusta beans. To test the accuracy of the model using Cross Validation. The results obtained will be evaluated using the confusion Matrix. Based on the results of testing and evaluation of the model, it is obtained that the SVM method is the best with the value of AUC = 1, CA = 0.983, F1 = 0.983, Precision = 0.983 and Recall = 0.983.

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