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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Proceeding of the Electrical Engineering Computer Science and Informatics Fountain of Informatics Journal Faktor Exacta Jukung (Jurnal Teknik Lingkungan) CogITo Smart Journal Pendas : Jurnah Ilmiah Pendidikan Dasar KACANEGARA Jurnal Pengabdian pada Masyarakat Informatik : Jurnal Ilmu Komputer Jurnal Riset Informatika Jurnal Pengabdian Masyarakat Multidisiplin SKANIKA: Sistem Komputer dan Teknik Informatika Jurnal Teknik Informatika (JUTIF) Jurnal PkM (Pengabdian kepada Masyarakat) Jurnal EduHealth Kresna: Jurnal Riset dan Pengabdian Masyarakat Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Telematika MKOM Jurnal Ticom: Technology of Information and Communication
Painem, Painem
Universitas Budi Luhur
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Optimization of Gradient Boosting Method for Predicting Narcissistic Personality Disorder (NPD) in Employees Solichin, Achmad; Pramudita, Bagas; Painem, Painem; Pradiptha, Anindya Putri
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 19, No 2 (2025): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.103551

Abstract

Narcissistic Personality Disorder (NPD) is a serious challenge in modern workplace environments; however, early detection and appropriate intervention remain unmet needs. This research aims to address the issue by proposing an intelligent system model based on machine learning, utilizing the Gradient Boosting method to predict NPD. The Gradient Boosting method was chosen for its ability to handle complex data and gradually improve prediction performance. This model is integrated with employee data, including a range of psychological, behavioral, and demographic variables relevant to NPD. The primary contribution of this research is the development of a predictive model that can assist organizations in identifying and providing early intervention to employees at risk of developing NPD. In doing so, it is expected to reduce the negative impact of NPD on the workplace, such as interpersonal conflicts and decreased productivity. The study shows significant results in the model's classification performance after applying Recursive Feature Elimination (RFE) to optimize the Gradient Boosting method. The accuracy rate reached 82%, an improvement from the previous 79% achieved using the Gradient Boosting Classifier. This indicates that the RFE-Gradient Boosting model has greater potential in classifying employees who genuinely have narcissistic personality disorder versus those who do not.
Analysis of Factors Influencing Mothers' Interest in Using IUD Contraception at PKM Kemuningsari Kidul Painem, Painem; Safitri, Rani
Jurnal EduHealth Vol. 16 No. 03 (2025): Jurnal EduHealt, Edition July - September , 2025
Publisher : Sean Institute

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

Abstract

The issue of low use of long-term contraception such as IUD is still a challenge in the program for Family Planning (KB) in Indonesia. This study's goal is to investigate the impact of knowledge, attitudes, and husband's support on mothers' interest in using IUD contraception at work ​​Kemuningsari Kidul Health Center. This study used a using a cross-sectional design and a quantitative descriptive analytical method and involved 30 fertile mothers selected through purposive sampling techniques. The tool that was employed was a closed survey that underwent validity and reliability testing. Data analysis was carried out using SPSS version 27, including normality, homogeneity, multicollinearity, heteroscedasticity, testing for hypotheses and multiple linear regression. The results showed that attitudes and knowledge had a significant effect on mothers' interest in using IUDs (p <0.05), while husband's support had no significant effect (p>0.05). These findings indicate the importance of increasing education and correct information to encourage mothers' interest in choosing IUD contraception as a long-term family planning method.
Analisis Sentimen Ulasan Pengguna Aplikasi Threads pada Google Play Store Menggunakan Multinomial Naive Bayes dan Support Vector Machine Java, Muhammad Arya; Mohammad Syafrullah; Windarto, Windarto; Painem, Painem
Jurnal Ticom: Technology of Information and Communication Vol 12 No 2 (2024): Jurnal Ticom-Januari 2024
Publisher : Asosiasi Pendidikan Tinggi Informatika dan Komputer Provinsi DKI Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70309/ticom.v12i2.112

Abstract

Analisis sentimen pada ulasan pengguna aplikasi menjadi topik yang menarik untuk dipelajari karena memberikan wawasan tentang bagaimana pengguna merespons dan mempersepsikan sebuah aplikasi. Penelitian ini bertujuan untuk melakukan analisis sentimen pada ulasan aplikasi Threads di Google Play Store dengan menggunakan metode Multinomial Naive Bayes dan Support Vector Machine. Latar belakang penelitian ini didasarkan pada penggunaan aplikasi jejaring sosial yang semakin populer dan banyaknya ulasan pengguna yang perlu dianalisis secara efisien. Masalah yang dihadapi adalah volume besar ulasan yang sulit untuk dianalisis secara manual. Metode yang digunakan mencakup persiapan data, penanganan ketidakseimbangan kelas dengan penerapan SMOTE, dan ekstraksi fitur dengan TF-IDF. Evaluasi model dilakukan dengan mengukur accuracy, precision, recall, dan F1-score untuk mengklasifikasikan sentimen ulasan menjadi positif atau negatif. Dari hasil pengujian menunjukkan kedua algoritma memiliki performa hampir seimbang dengan akurasi sekitar 81% model-model ini mampu mengklasifikasikan sentimen ulasan dengan baik, memiliki precision dan recall yang tinggi untuk kedua kelas. Kesimpulan penelitian ini adalah metode Machine Learning berhasil memberikan solusi efisien dan akurat untuk analisis sentimen pada ulasan aplikasi Threads di Google Play Store, namun batasan data Bahasa Indonesia menjadi perhatian untuk penelitian selanjutnya
The Relationship between Mother's Knowledge and Attitudes and Giving Early Complementary Breastfeeding at UPTD Boronadu Health Center South Nias Regency in 2022 Fau, Yentiria; Painem, Painem; Purba, Edy Marjuang; Sari, Febriana; Situmorang, Tetti Seriati; Nainggolan, Anna Waris; Sinaga, Rosmani
Jurnal EduHealth Vol. 13 No. 02 (2022): Jurnal eduHealth, Periode Oktober - December, 2022
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (213.901 KB)

Abstract

Giving complementary breastfeeding too early is one of the inhibiting factors for exclusive breastfeeding. The results of a preliminary survey conducted at the UPTD Health center Boronadu South Nias Regency where interviews were conducted with mothers and it was found that 8 mothers did not know that babies should only be given breast milk until they were 6 months old and they agreed that babies less than 6 months old were given additional food other than breast milk such as bananas, tea, formula milk and other foods. This study aims to determine the relationship between knowledge and attitudes of mothers regarding early complementary breastfeeding at the UPTD Health center Boronadu South Nias Regency in 2022. This study was an analytic observational study with a cross sectional design. The population is all mothers having babies more than 6 months at the UPTD Health center Boronadu South Nias Regency, namely 118. The number of samples based on the sample formula is 48 people. There is a significant relationship between the knowledge (p=0.022) and attitudes (p=0.006) of postpartum mothers and the provision of early complementary breastfeeding in the UPTD Work Area of the Boronadu Health Center in 2022. It is also hoped that health workers at the UPTD Boronadu Health Center will be able to further increase public knowledge regarding complementary breastfeeding and increasing its role in efforts to achieve exclusive breastfeeding through counseling, which can be carried out at village meetings, posyandu and counseling during pregnancy checks.
Enhancing Prediction of Treatment Duration in New Tuberculosis Cases: A Comprehensive Approach with Ensemble Methods and Medication Adherence Rusdah, Rusdah; Painem, Painem; Kusumaningsih, Dewi
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 2 (2025): JUTIF Volume 6, Number 2, April 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.2.4263

Abstract

Tuberculosis (TB) remains a significant global health problem, with treatment duration varying among patients. TB patients have difficulty following a long-term treatment regimen. After the final diagnosis is determined, it is necessary to know the predicted duration of treatment for a patient. By increasing patient compliance with taking medication, the percentage of TB patients will increase, and this can reduce cases of multi-drug resistant patients and dropouts. This study aims to build a prediction model for the duration of treatment for new cases of Pulmonary TB patients by adding medication compliance parameters using the ensemble method. The research methodology uses CRISP-DM. This study begins with identifying problems and objectives, collecting data, preprocessing and analyzing data, modeling, evaluating, and validating models. The results showed that adding medication compliance parameters can improve model performance. However, the results of model exploration with feature selection techniques and various ensemble methods have not shown good performance. The medication adherence parameters used in this study are the number of medications swallowed in Phase I and Anti-Tuberculosis drug compliance in Phase I. These parameters had never been used in previous studies. The prediction model can be used as an early warning for a patient. If a patient is predicted to have a treatment duration of more than six months, then the patient will receive stricter drug intake supervision. Thus, this proposed model is expected to help achieve the target of eliminating Tuberculosis in 2030 to reduce the death rate by 90% compared to 2019.
Peningkatan kompetensi algoritma dan pemrograman C/C++ bagi siswa dan siswi SMK YADIKA 4 Painem, Painem; Soetanto, Hari; Kristanto, Dwi; Solichin, Achmad; Rusdah, Rusdah
KACANEGARA Jurnal Pengabdian pada Masyarakat Vol 6, No 4 (2023): November
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/kacanegara.v6i4.1689

Abstract

Salah satu bentuk tridharma perguruan tinggi adalah pengabdian kepada masyarakat. Selain menyelenggarakan pendidikan dan penelitian, perguruan tinggi juga memiliki tanggung jawab untuk memberikan kontribusi yang nyata bagi masyarakat di sekitar mereka. Pelatihan pemrograman bahasa C pada SMK Yadika 4 merupakan salah satu kontribusi nyata perguruan tinggi bagi masyarakat sekitar. Pelatihan pemrograman C/C++ dan kompetensi algoritma menjadi hal yang penting bagi siswa/siswi SMK Yadika 4. Hal ini bertujuan untuk meningkatkan kualitas pendidikan dan kesiapan siswa/siswi dalam memasuki dunia kerja yang membutuhkan kemampuan pemrogramanPelatihan pemrograman C/C++ dan kompetensi algoritma menjadi hal yang penting bagi siswa/siswi SMK Yadika 4 serta membekali siswa/siswi dengan pengetahuan dan keterampilan dasar pemrograman C/C++ sehingga mereka dapat mengembangkan aplikasi sederhana. Selain itu, pelatihan ini akan meningkatkan kompetensi algoritma siswa/siswi dalam memecahkan masalah dan merancang solusi yang tepat menggunakan algoritma yang efektif. Hal ini bertujuan untuk meningkatkan kualitas pendidikan dan kesiapan siswa/siswi dalam memasuki dunia kerja yang membutuhkan kemampuan pemrograman. Dalam pelatihan ini, siswa/siswi akan diberikan pemahaman dan latihan tentang konsep dasar pemrograman C/C++ dan kompetensi algoritma. Pelatihan ini akan meliputi pembelajaran teori dan juga praktek pengembangan program, di mana siswa/siswi akan belajar mengenai sintaks dasar, variabel, tipe data, operator, penggunaan loop dan kondisi, fungsi, dan lain sebagainya. Dengan meningkatnya kompetensi siswa/siswi dalam pemrograman C/C++ dan algoritma, diharapkan SMK Yadika 4 dapat melahirkan lulusan-lulusan yang siap dan mampu berkontribusi dalam industri teknologi informasi di masa depan.
Somatic, Auditory, Visual, dan Intellectual (SAVI) : Solusi Cerdas untuk Mengoptimalkan Capaian Belajar Peserta didik pada Mata Pelajaran Pendidikan Pancasila Umay, SITI; Rahman, MS Khabibur; Painem, Painem
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 10 No. 02 (2025): Volume 10 No. 02 Juni 2025 In Build
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v10i02.25252

Abstract

In the context of education, learning outcomes are the main target as well as an indicator of the effectiveness of the learning process. Basically, learning outcomes reflect the accumulation of various learning activities carried out by students. This research shows that the Somatic, Auditory, Visual, and Intellectual (SAVI) learning model has a significant positive impact on improving students' learning outcomes. The SAVI learning model emphasises the active participation of learners in the learning process through the use of all five senses so that the learning process becomes more comprehensive and meaningful. The research method used was Classroom Action Research (PTK) with two cycles. The results of the analysis in cycle I obtained the average score of students which was 63.5 with the predicate ‘Very Less and Less’. After the application of the SAVI learning model, there was an increase in cycle II to 80 with the majority of students (70%) in the predicate ‘Very Good’ and the absence of the predicate ‘Very Poor’. This SAVI learning model can be implemented by teachers as an alternative in learning activities to encourage students to be more enthusiastic and active in learning during the learning process.
Pengamanan File Gambar pada Media Video dengan Kriptografi Algoritma RSA dan Steganografi Algoritma End of File (EOF) Malvi, Afif; Painem, Painem
Informatik : Jurnal Ilmu Komputer Vol 16 No 2 (2020): Agustus 2020
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v16i2.1860

Abstract

Keamanan data merupakan suatu hal penting, karena berkaitan dengan privasi, integritas, otentikasi dan kerahasiaan. Apabila suatu data hilang atau diubah oleh pihak yang tidak bertanggung jawab, maka dapat merugikan bagi pemilik data. Keamanan data digital sangat penting pada perkembangan teknologi saat ini, termasuk di bidang percetakan. Pada bidang percetakan cover majalah dan pengeditan gambar dibutuhkan aplikasi pengamanan data untuk mencegah terjadinya pemalsuan data dan manipulasi data yang dilakukan oleh orang-orang yang tidak bertanggung jawab. Pada penelitian ini dikembangkan sebuah aplikasi yang berfungsi untuk mengamankan file gambar pada PT. Segoro Arto Sejati. Aplikasi yang dikembangkan menggunakan algoritma kriptografi RSA dan dipadukan dengan steganografi algoritma End of File (EOF). Proses pengamanan file terdiri dari dua tahap, yaitu proses enkripsi file menggunakan metode RSA yang menghasilkan file terenkripsi (encrypted file), diikuti dengan tahap penyisipan file terenkripsi ke dalam media penampung menggunakan metode EOF. Berdasarkan hasil pengujian proses pengamanan file diperoleh tingkat keberhasilan aplikasi mencapai 100% dengan rata-rata waktu proses pengamanan file (embedding) sebesar 5,651 detik dan waktu proses ekstraksi file sebesar 17,533 detik.
Penerapan Algoritma Naïve Bayes untuk Analisis Pandangan Masyarakat terhadap Pemindahan Ibu Kota Indonesia Painem, Painem; Prayogo, Aditya Izhar Eka
Informatik : Jurnal Ilmu Komputer Vol 18 No 3 (2022): Desember 2022
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v18i3.5050

Abstract

Pemerintah sudah lama mengumumkan rencana untuk memindahkan ibu kota negara, tetapi masih terdapat kontroversi di antara masyarakat yang setuju dan tidak setuju dengan rencana tersebut. Masyarakat memiliki alasan dan pandangan yang berbeda-beda tentang rencana ini. Untuk mendapatkan gambaran umum tentang respon masyarakat terhadap rencana pemindahan ibu kota, perlu melihat berbagai reaksi yang berbeda. Dengan era teknologi yang sangat canggih seperti sekarang ini, membuat penilaian sentimen publik terhadap berbagai isu menjadi mudah dan cepat. Hal ini disebabkan oleh maraknya penggunaan media sosial oleh masyarakat. Media sosial saat ini dapat digunakan sebagai media hiburan, tetapi juga sebagai media untuk menyatakan pendapat dan pandangan tentang berbagai topik. Begitu juga dengan topik pemindahan ibu kota negara, dimana masyarakat banyak mengekspresikan reaksinya melalui berbagai media, termasuk media sosial seperti Twitter. Twitter adalah salah satu media sosial yang banyak digunakan oleh masyarakat Indonesia untuk menyatakan pendapatnya. Pendapat tentang pemindahan ibu kota yang diperoleh dari Twitter perlu dianalisis. Pada penelitian ini, metode analisis sentimen yang digunakan untuk menganalisa topik pemindahan ibu kota dari media sosial twitter adalah metode Naive Bayes Classifier (NBC).  Hasil analisis berdasarkan 1.272 tweet menunjukan bahwa sentimen positif sebesar 86.95 % dan sentimen negatif sebesar 13.05 % pada periode 10 May 2022 hingga 1 Juni 2022, sementara hasil pengujian yang diperoleh adalah nilai akurasi sebesar 93 %, presisi sebesar 87 % dan recall sebesar 100 %.
Co-Authors Abdullah &#039;Alim Achmad Solichin Akbar Maulana Putra Andiono, Endro Anidnya Putri Pradiptha Anindya Putri Pradiptha Anna Waris Nainggolan Denny Eka Erlianto Derian Rabbani Destriyani Destriyani Dwi Kristanto Fau, Yentiria Febriana Sari, Febriana Gabriel Yoda Gustiegan Hari Soetanto Heri Soetanto Indra Indra Ismoyo, Maret Java, Muhammad Arya Joko Christian Chandra Kaishananda Dwi Takanwiedi Kusumaningsih, Dewi Malvi, Afif Mohammad Syafrullah MS Khabibur Rahman Muhammad Sadli Pradiptha, Anindya Putri Pramudita, Bagas Prayogo, Aditya Izhar Eka Purba, Edy Marjuang Purwanto Purwanto Rifky Aditia Hamdan Riyan Sugiharto Rusdah Rusdah Safitri, Rani SINAGA, ROSMANI situmorang, tetti seriati Syafrullah, Mohammad Tomi Hartanto Umay, SITI Utomo Budiyanto Wahyuawaludin, Nizam Windarto, Windarto Yusup Supriyadi Zahrul Basim