The presence of women in Indonesian politics remains underrepresented whereas cultural and societal aspects pose critical influence in determining voter behavior toward female candidates. The aim of this article is to examine voter behavior regarding female candidates and the probability for them to be elected as members of parliament. We apply quantitative method by developing three models representing three combinations of predictor variables, (i) socio-demography, (ii) gender- equality concern, and (iii) political attitude towards female candidates as determinants towards female candidate electability. The study took place in Pelalawan Regency in Riau Province, by analyzing 400 respondents with equal numbers of men and women from various socio-economic backgrounds through clustered random sampling method. We tested these hypotheses and our three models by utilizing logistic regression analysis. The result shows that political attitude toward female candidates (Model 3) are the strongest coefficient and most significant determinant for female candidate electability. The study also revealed that female candidate’s electability in Pelalawan Regency is lower than male candidate’s electability among male respondents. On the other hand, female candidate’s electability is higher than male candidate’s electability among female respondents. Moreover, we also found that education determines female candidate’s electability where the more educated an individual is, the more he/she tends to vote for female candidates.

AbstrakPenelitian ini mengeksplorasi bagaimana peran Aksi Cepat Tanggap (ACT) Indonesia dan Global Qurban sebagai salah satu program unggulannya di tingkat global. ACT adalah organisasi nirlaba profesional yang memfokuskan kerja-kerja kemanusiaan akibat bencana alam dan konflik kemanusiaan. Wilayah kerja ACT di skala global diawali dengan kiprah dalam setiap tragedi kemanusiaan di berbagai belahan dunia seperti bencana alam, kelaparan dan kekeringan, konflik dan peperangan, termasuk penindasan terhadap kelompok minoritas berbagai negara. Penelitian ini menggunakan pendekatan kualitatif. Jenis penelitian ini tergolong dalam penelitian Fenomenologis yang mencari makna dari sebuah realitas sosial dari sudut pandang manusia di dalamnya-Aksi Cepat Tanggap. Penelitian ini menggunakan enam pendekatan konseptual untuk mengeksplorasi temuantemuan penelitian diantaranya Global Qurban Aksi Cepat Tanggap dari sudut pandang (i) gerakan sosial, (ii) masyarakat internasional, (iii) pembangunan dan pengembangan, (iv) rezim dan kebijakan, (v) pemanfaatan media sosial, dan dari sudut pandang (vi) kajian jaringan advokasi transnasional. Hasil dari penelitian ini menunjukkan bahwa bantuan kemanusiaan-dan juga isu-isu kemanusiaan-masih menjadi tren utama dalam dinamika organisasi transnasional. Selain itu, pemanfaatan media sosial dinilai cukup menentukan perkembangan dan kemajuan dari sebuah jaringan advokasi transnasional. AbstractThe research explores how the role of Aksi Cepat Tanggap (ACT) Indonesia and Global Qurban as one of its flagship programs at the global level. ACT is a professional non-profit organization that focuses on humanitarian work due to natural disasters and humanitarian conflicts. ACT's working area on a global scale begins with gait in every humanitarian tragedy in various parts of the world such as natural disasters, hunger and drought, conflict and war, including the suppression of minority groups of various countries. This study applies qualitative approach. This type of research is classified into Phenomenological research which seeks meaning from a social reality from a human point of view within it-Aksi Cepat Tanggap. This study applies six conceptual approaches on exploring the research

Machine learning is one of the areas of research that has received great attention in various fields of science. One of the most important applications of machine learning is its ability to perform data analysis. Machine learning plays an important role in finding patterns from data and providing predictions based on existing data. This research aims to apply the concept of machine learning to analyze the arms trade for the Southeast Asia region, which is currently rarely discussed. The research tries to make a prediction system for the arms dynamics based on the political and economic strength of a country. There are three main data sources in this study, namely wordbank.org for the economic strength variable, polity5 for political variable and sipri.org for the arms dynamics variable. The algorithm chosen is the K-NN algorithm which is proven to be one of the best and simplest algorithms in handling data classification. Based on the research that has been carried out, it can be concluded that this study succeeded in developing a data classification system that can be used to predict arms trade with a fairly high degree of accuracy.

Kinerja pelayanan publik menjadi hal yang penting dalam memberikan pelayanan kepada pengguna jasa. salah satu hal yang dapat mempengaruhi tingkat pendidikan pegawai sebagai sumber daya manusia. Penelitian ini mengungkapkan sejauh mana tingkat pendidikan (x) pegawai berpengaruh terhadap kinerja pegawai (y) dalam melayani masyarakat di kantor kecamatan Kampar Kiri Hulu. Penelitian ini menggunakan pendekatan kuantitatif dengan menggunakan survei lapangan. 40 orang secara sukarela sebagai responden dengan tingkat respon 80%. Hasil uji regresi yang diperoleh adalah tingkat pendidikan berpengaruh terhadap kinerja pegawai sebesar 38%. Dalam penelitian ini juga digunakan beberapa variabel pemoderasi seperti pangkat atau jabatan pegawai, masa kerja, dan pengalaman pelatihan sehingga mempengaruhi hasil yang diperoleh.

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