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Prediction of Employee Attendance Factors Using C4.5 Algorithm, Random Tree, Random Forest Fahlapi, Riza; Hermanto, Hermanto; Kuntoro, Antonius Yadi; Effendi, Lasman; Nitra, Ridatu Oca; Nurlela, Siti
Semesta Teknika Vol 23, No 1 (2020): MEI 2020
Publisher : Semesta Teknika

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Research on the performance of workers based on the determination of standard working hours for absences conducted by workers in a certain period. In disciplinary supervision, workers are expected to be able to provide the best performance in the implementation of work in accordance with predetermined working hours. The measurement of the level of discipline of admission hours for placement workers is carried out every working day, continuously and continuously. Attendance monitoring already uses online attendance by using data downloaded from the online attendance provider as the main data. In addition, data collection is done by filtering employee absentee data and supporting information on the categories that cause mismatches in meeting work schedules. Mobilization of workers according to location and working hours has been regulated in company regulations allowing the placement of workers in accordance with the residence so as not to affect the desired work results the company is still within reasonable limits and can be increased. The assessment of this study as a progression factor inhibiting the company in achieving company targets. From the results of the author's analysis of the prediction of employee delay factors using three algorithms, namely the C.45 algorithm accuracy = 79.37% and AUC value = 0.646, Random Forest Algorithm accuracy = 78.58% and AUC value = 0.807 while for the Random Tree algorithm accuracy = 76.26% and the AUC value = 0.610.

Prediction of Employee Attendance Factors Using C4.5 Algorithm, Random Tree, Random Forest Riza Fahlapi; Hermanto Hermanto; Antonius Yadi Kuntoro; Lasman Effendi; Ridatu Oca Nitra; Siti Nurlela
Semesta Teknika Vol 23, No 1 (2020): MEI 2020
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/st.v23i1.7984

Research on the performance of workers based on the determination of standard working hours for absences conducted by workers in a certain period. In disciplinary supervision, workers are expected to be able to provide the best performance in the implementation of work in accordance with predetermined working hours. The measurement of the level of discipline of admission hours for placement workers is carried out every working day, continuously and continuously. Attendance monitoring already uses online attendance by using data downloaded from the online attendance provider as the main data. In addition, data collection is done by filtering employee absentee data and supporting information on the categories that cause mismatches in meeting work schedules. Mobilization of workers according to location and working hours has been regulated in company regulations allowing the placement of workers in accordance with the residence so as not to affect the desired work results the company is still within reasonable limits and can be increased. The assessment of this study as a progression factor inhibiting the company in achieving company targets. From the results of the author's analysis of the prediction of employee delay factors using three algorithms, namely the C.45 algorithm accuracy = 79.37% and AUC value = 0.646, Random Forest Algorithm accuracy = 78.58% and AUC value = 0.807 while for the Random Tree algorithm accuracy = 76.26% and the AUC value = 0.610.

Implementasi Management QOS Bandwidth Untuk CCTV Menggunakan Metode Simple Queue Pada BSI Cibitung Lasman Effendi; Ridatu Oca Nitra; Muhammad Hilman Fakhriza
JURIKOM (Jurnal Riset Komputer) Vol 5, No 6 (2018): Desember 2018
Publisher : STMIK Budi Darma

The use of CCTV today is very important as a support for emergencies around the area of the company / building, and serves to assist officers in the building security room. In this case the function of CCTV only helps the officer to minimize the frequent crimes, not to reduce from the crime itself. CCTV itself only displays the image and save it in HDD to see the incident occurring in the hook. The more powerful the quality of CCTV itself is still many shortcomings that developed the resulting image quality, the area captured by the camera, therefore the supervisory function is still less effective and efficient for all things crime. In this research. By using remote monitoring using Pro Surveillance System application. To facilitate monitoring.

Prediction of PrivyID Application Comments Use as an Electronic Document (e-doc) using the Ensemble Vote method Riza Fahlapi; Hermanto Hermanto; Taufik Asra; Antonius Yadi Kuntoro; Ridatu Oca Nitra; Lasman Effendi
Jurnal Teknik Komputer AMIK BSI Vol 9, No 1 (2023): JTK Periode Januari 2023
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jtk.v9i1.14245

Indonesia is developing one of the more efficient and effective Financial Technology (Fintek) support services innovations by using electronic documents. The Electronic Document provider business that is used as a reference and utilized by fintech companies is PrivyID. In this study, how is the commentary aspect of using the PrivyID application for digital signature services to become a legal electronic document. Web-based application platforms and mobile applications in the community are indispensable for the use of Electronic Documents developed by PrivyID as a service provider in business and personal transactions that are needed by the community. More in-depth research regarding the Prediction of PrivyID Application Comments in Its Use as an Electronic Document (e-doc) taken from 818 data of PrivyID application users. The research was conducted by combining 3 (three) algorithms (k-Nearest Neighbor, Na¨ıve Bayes, and C4.5) in the Ensembles Vote method which resulted in the best Prediction Comment value with an accuracy of 86.80.

ANALISA SENTIMEN VAKSINASI COVID-19 DENGAN METODE SUPPORT VECTOR MACHINE DAN NAÏVE BAYES BERBASIS TEKNIK SMOTE Riza Fahlapi; Hermanto Hermanto; Taufik Asra; Antonius Yadi Kuntoro; Ridatu Ocanitra; Lasman Effendi; Ferry Syukmana
Jurnal Informatika Kaputama (JIK) Vol 6 No 1 (2022): Volume 6, Nomor 1, Januari 2022
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v6i1.136

Keadaan dan tantangan pandemi pada awal tahun 2021 dengan telah ditemukannya vaksin atas virus Covid-19 tentunya diperlukan percepatan dalam pemberian vaksin kepada seluruh umat manusia di seluruh dunia. Di Indonesia, Pemerintah menggalakan program vaksinasi masal kepada seluruh Warga Negara Indonesia dengan melakukan percepatan vaksinasi di seluruh wilayah Indonesia sampai dengan saat ini. Berdasarkan hal tersebut diatas dipandang perlu melakukan analisa sentimen. Media sosial twitter dipilih sebagai salah satu sarana dalam analisas sentiman ini. Terdapat 1013 komentar positif dan negatif para pengguna twitter dengan kata kunci “vaksin” yang didapatkan untuk diproses terkait tanggapan masyarakat atas pelaksanaan vaksinasi masal yang dilaksanakan di Indonesia. Dengan menggunakan Algoritma Support Vector Machine (SVM) dan Naïve Bayes berbasis SMOTE dilakukan perbandingan pengujian atas komentar positif dan negatif tersebut. Dari proses pengujian tersebut didapatkan hasil akurasi dari algoritma SVM menggunakan teknik SMOTE didapatkan nilai akurasi =70.51% dan nilai AUC =0.827, sedangkan proses pengujian menggunakan algoritma Naïve Bayes dengan teknik SMOTE didapatkan nilai akurasi = 64.36% dan nilai AUC = 0.423. dari proses diatas, penggunaan Support Vector Machine berbasis teknik SMOTE memiliki akurasi yang lebih tinggi sehingga dapat digunakan untuk memberikan solusi terhadap analisis sentimen vaksinasi Covid-19.

Pelatihan Aplikasi Microsoft Office Untuk Kelancaran Proses Pembuatan Proposal Pada Ikatan Remaja Islam Fathuzzaman (IREIFA) Minda Septiani; Ridatu Ocanitra; Cep Adiwiharja; Lasman Effendi
Nusantara: Jurnal Pengabdian kepada Masyarakat Vol. 3 No. 1 (2023): Februari : Jurnal Pengabdian Kepada Masyarakat
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/nusantara.v3i1.849

Perkembangan ilmu pengetahuan dan teknologi menyebabkan perubahan yang berarti bagi manusia dan beberapa teknologi informasi dapat dimanfaatkan sebagai media pembelajaran. Ikatan Remaja Islam Fathuzzaman (IREIFA) Jakarta Selatan belum sepenuhnya menerapkan Microsoft Office khususnya Microsoft Word pada kegiatan sehari-hari, dan hal tersebut menyebabkan tidak efisien dalam pembuatan proposal sebagai penunjang kegiatan yang telah diadakan. Berdasarkan alasan kegiatan masyarakat harus tetap berjalan selama pandemi maka Universitas Bina Sarana Informatika mengadakan Pelatihan Aplikasi Microsoft Office Untuk Kelancaran Proses Pembuatan Proposal Pada Ikatan Remaja Islam Fathuzzaman (IREIFA). Pelatihan ini bertujuan untuk lebih dapat menerapkan Microsoft Office khususnya Microsoft Word sebagai penunjang kegiatan sehari-hari di lingkungan IREIFA dan dapat memudahkan dalam membuat proposal kegiatan yang dibutuhkan IREIFA khususnya pengurus kelompok tersebut.

SENTIMENT ANALYSIS ON GOJEK AND GRAB USER REVIEWS USING SVM ALGORITHM BASED ON PARTICLE SWARM OPTIMIZATION Hermanto, Hermanto; Kuntoro, Antonius Yadi; Asra, Taufik; Nurajijah, Nurajijah; Effendi, Lasman; Ocanitra, Ridatu
Jurnal Pilar Nusa Mandiri Vol 16 No 1 (2020): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Users of the Gojek and Grab application can provide reviews or comments about the application on Google Play. Reviews in the form of giving opinions about their satisfaction or dissatisfaction with the services provided. So with the many opinions provided, making people selective in choosing an online motorcycle taxi service provider. The application with the best review will be chosen by the community. In previous studies regarding the classification of online ojek service review using the Naïve Bayes algorithm, C.45 and Random Forest produced an unsatisfactory accuracy of 69.18% at the highest value. This study aims to determine the extent of the analysis of Gojek and Grab application user reviews based on user comments by classifying negative and positive reviews with a higher level of accuracy than previous studies so that applications with the best reviews can be known for public consideration in using the application's services. The method used for data review classification is using the Support Vector Machine (SVM) based on Particle Swarm Optimization (PSO). The test results on the Grab application review get the highest accuracy results in the amount of 73.09% with AUC value = 0.804, while for the test results on the application review Gojek get an accuracy value of 65.59% and AUC value = 0.680

Penerapan Metode Algortima Apriori Untuk Menentukan Pola Pembelian Pada Toko Pakaian Sukajadi Busana Effendi, Lasman; Sopandi, Robi; Apriliah, Widya
Simpatik: Jurnal Sistem Informasi dan Informatika Vol. 5 No. 1 (2025): Juni 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/simpatik.v5i1.8888

Industri pakaian dan fashion merupakan salah satu subsektor dalam bidang ritel yang mengalami perkembangan pesat serta dinamis, seiring dengan perubahan tren, gaya hidup, dan preferensi konsumen. Meskipun digitalisasi telah mendorong banyak pelaku usaha beralih ke platform daring, toko pakaian berbasis luring tetap memiliki peranan yang signifikan dalam ekosistem ritel. Toko fisik masih menjadi pilihan utama bagi konsumen untuk merasakan langsung kualitas produk, melakukan pencocokan ukuran, serta memperoleh pengalaman berbelanja yang lebih personal dan interaktif. Namun demikian, Sukajadi Busana sebagai salah satu pelaku usaha di bidang ini menghadapi beberapa permasalahan operasional, di antaranya adalah keterbatasan stok dan variasi produk yang tersedia, serta sistem pencatatan inventaris yang belum optimal. Ketersediaan barang hanya diingat berdasarkan daya ingat pemilik, sehingga tidak seluruh produk tercatat secara sistematis. Untuk mengatasi permasalahan ini, penerapan algoritma Apriori dapat menjadi solusi yang efektif. Algoritma tersebut berfungsi untuk menganalisis pola pembelian konsumen dengan mengidentifikasi asosiasi antarproduk yang sering dibeli secara bersamaan. Hasil analisis tersebut dapat dimanfaatkan untuk menghasilkan rekomendasi produk yang relevan serta menyusun strategi pemasaran yang lebih efisien dan tepat sasaran. Dengan demikian, pemilik Sukajadi Busana dapat melakukan perencanaan stok yang lebih akurat dan merancang promosi terhadap produk-produk yang memiliki tingkat permintaan tinggi.

Pengukuran Kualitas Aplikasi PeduliLindungi Dengan Metode WebQual 4.0 Alfarisi, Tri Lukman; Khubaero, Ulfi; Effendi, Lasman
Jurnal Keilmuan Teknologi Informasi dan Ilmu Manajemen (Justifi) Vol 2 No 1 (2022): JURNAL JUSTIFI
Publisher : Jurnal Keilmuan Teknologi Informasi dan Ilmu Manajemen (Justifi)

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During the current Covid-19 pandemic, almost all activities have been shifted online to break the chain of transmission of the virus. To help the government detect the transmission of Covid-19, the Indonesian Ministry of SOEs together with the Indonesian Ministry of Communication and Information and Telkom Indonesia initiated the creation of the PeduliLindungi application. This application still has problems for its users. The purpose of this study was to determine the quality of the PeduliLindungi application. The method used is WebQual 4.0 by using 3 variables, namely usability, information quality and interaction quality, as well as descriptive analysis to determine the criteria for the data obtained. The results showed that the usability variable got very good criteria, then the information quality variable also got very good criteria and finally the interaction quality variable got good criteria.

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